From a1bc9ec0c27ab615460b145e59d7e7b8fdea8406 Mon Sep 17 00:00:00 2001 From: hugocasa Date: Mon, 26 Oct 2026 19:22:45 +0100 Subject: [PATCH] feat: tool approval and a question tool for ai agent steps (#11826) * feat(ai-agent): built-in approval tool that parks the agent An AI agent step can now be given a built-in "Request approval" tool. The model calls `request_approval` with a message; the agent stores its conversation in the new `ai_agent_checkpoint` table, releases its worker by parking its own queue row like a workflow-as-code parent, and resumes with the answer (approved, approver, comment) or a timeout once someone answers from the run page. Co-Authored-By: Claude Opus 5.5 * fix(ai-agent): tie approval answers to their request and hold the turn - A turn that asks for approval runs none of its other calls; they are refused so the model repeats them after the answer. - The run page sends the request's call id. An answer naming another request is ignored and the agent parks again for the time left; `suspend` is zeroed when the answer is read, so answers sent while the agent runs are refused. - The checkpoint is read whatever the current roster holds, the answer's outcome is written by position, and a cancel that beats the park completes the job as cancelled. Co-Authored-By: Claude Opus 5.5 * fix(ai-agent): say why calls beside an invalid approval request were refused Co-Authored-By: Claude Opus 5.5 * fix(ai-agent): one approval form per request, none on a finished run Co-Authored-By: Claude Opus 5.5 * feat(ai-agent): answer approval requests from a flow's chat Co-Authored-By: Claude Opus 5.5 * fix(ai-agent): show chat approvals for agents that do not stream Co-Authored-By: Claude Opus 5.5 * feat(ai-agent): approval as a per-tool setting, built-in tool asks a question Co-Authored-By: Claude Opus 5.5 * fix(ai-agent): say when a nested agent leaves out tools that require approval Co-Authored-By: Claude Opus 5.5 * feat(ai-agent): show chat approvals and questions on the tool's own card Co-Authored-By: Claude Opus 5.5 * feat(ai-agent): question choices, and approval buttons shared with approval steps Co-Authored-By: Claude Opus 5.5 * feat(ai-agent): show a waiting agent as suspended, and refused calls as not run Co-Authored-By: Claude Opus 5.5 * fix(ai-agent): each added chat card shows its own call, answered marker keyed by job Co-Authored-By: Claude Opus 5.5 * test(ai-agent): approve and reject a held call through resume_suspended Co-Authored-By: Claude Opus 5.5 * feat(ai-agent): require approval in a tool settings tab, plain descriptions on built-in tool panes Co-Authored-By: Claude Opus 5.5 * fix(ai-agent): sentence case for the web search tool label Co-Authored-By: Claude Opus 5.5 * feat(ai-agent): built-in tool drawers explain themselves in the header subtitle Co-Authored-By: Claude Opus 5.5 * fix(ai-agent): clearer question tool subtitle Co-Authored-By: Claude Opus 5.5 * fix(ai-agent): badge the tool settings tab like run settings Co-Authored-By: Claude Opus 5.5 * chore(ai-agent): regenerate system prompts and MCP session files Co-Authored-By: Claude Opus 5.5 --------- Co-authored-by: Claude Opus 5.5 --- ...0261016162101_ai_agent_checkpoint.down.sql | 1 + .../20261016162101_ai_agent_checkpoint.up.sql | 9 + backend/src/monitor.rs | 19 + backend/summarized_schema.txt | 1 + backend/tests/ai_agent_approval.rs | 154 +++++++ backend/windmill-ai/src/types.rs | 5 + .../src/mcp/session/gen/instructions.json | 2 +- backend/windmill-types/src/flow_status.rs | 25 ++ backend/windmill-types/src/flows.rs | 23 +- backend/windmill-worker/src/ai/compaction.rs | 63 +++ backend/windmill-worker/src/ai/mod.rs | 1 + backend/windmill-worker/src/ai/pause.rs | 377 ++++++++++++++++++ .../src/ai/stream_event_processor.rs | 8 +- backend/windmill-worker/src/ai/tools.rs | 236 ++++++++++- backend/windmill-worker/src/ai/utils.rs | 36 ++ backend/windmill-worker/src/ai_executor.rs | 302 ++++++++++++-- chat-sdk/README.md | 1 + chat-sdk/src/chat.ts | 2 + chat-sdk/src/types.ts | 2 + cli/src/commands/lint/flow_semantics.ts | 16 +- cli/src/guidance/skills.gen.ts | 13 +- docs/reusable-ai-agents.md | 45 +++ .../components/AgentApprovalRequest.svelte | 122 ++++++ .../components/FlowStatusViewerInner.svelte | 26 ++ .../FlowStatusWaitingForEvents.svelte | 80 ++-- frontend/src/lib/components/JobStatus.svelte | 3 +- frontend/src/lib/components/agentRequest.ts | 60 +++ frontend/src/lib/components/agentTrace.ts | 9 + .../approvals/ApprovalActions.svelte | 76 ++++ .../copilot/chat/flow/openFlow.json | 2 +- .../copilot/chat/flow/openFlowZod.gen.ts | 8 +- .../components/flows/FlowProgressBar.svelte | 9 +- .../lib/components/flows/agentDraft.svelte.ts | 10 +- .../src/lib/components/flows/agentToolTree.ts | 7 +- .../components/flows/agentToolUtils.test.ts | 7 + .../lib/components/flows/agentToolUtils.ts | 41 +- .../flows/content/AgentConfigModal.svelte | 10 +- .../flows/content/AgentToolRoster.svelte | 18 +- .../flows/content/AgentToolWrapper.svelte | 6 + .../flows/content/FlowModuleComponent.svelte | 38 +- .../flows/content/McpToolEditor.svelte | 14 + .../flows/content/QuestionToolDisplay.svelte | 32 ++ .../flows/content/WebsearchToolDisplay.svelte | 15 +- .../conversations/FlowChatInterface.svelte | 52 ++- .../conversations/flowChatViewHost.svelte.ts | 128 +++++- .../conversations/flowChatViewHost.test.ts | 45 +++ .../components/flows/flowStateUtils.svelte.ts | 4 + .../flows/map/InsertModuleInner.svelte | 12 +- .../flows/pickers/TopLevelNode.svelte | 4 +- .../components/graph/graphBuilder.svelte.ts | 1 + .../graph/renderers/nodes/AIToolNode.svelte | 55 ++- .../graph/renderers/nodes/ModuleNode.svelte | 9 +- .../renderers/nodes/NewAIToolNode.svelte | 8 + .../runs/FlowExecutionStatus.svelte | 15 +- .../lib/components/runs/JobStatusIcon.svelte | 3 +- openflow.openapi.yaml | 72 +++- system_prompts/auto-generated/flow.md | 13 +- system_prompts/auto-generated/prompts.ts | 13 +- .../auto-generated/skills/write-flow/SKILL.md | 13 +- system_prompts/base/flow-base.md | 11 +- 60 files changed, 2193 insertions(+), 199 deletions(-) create mode 100644 backend/migrations/20261016162101_ai_agent_checkpoint.down.sql create mode 100644 backend/migrations/20261016162101_ai_agent_checkpoint.up.sql create mode 100644 backend/tests/ai_agent_approval.rs create mode 100644 backend/windmill-worker/src/ai/pause.rs create mode 100644 frontend/src/lib/components/AgentApprovalRequest.svelte create mode 100644 frontend/src/lib/components/agentRequest.ts create mode 100644 frontend/src/lib/components/approvals/ApprovalActions.svelte create mode 100644 frontend/src/lib/components/flows/content/QuestionToolDisplay.svelte diff --git a/backend/migrations/20261016162101_ai_agent_checkpoint.down.sql b/backend/migrations/20261016162101_ai_agent_checkpoint.down.sql new file mode 100644 index 0000000000..002ce5d21d --- /dev/null +++ b/backend/migrations/20261016162101_ai_agent_checkpoint.down.sql @@ -0,0 +1 @@ +DROP TABLE IF EXISTS ai_agent_checkpoint; diff --git a/backend/migrations/20261016162101_ai_agent_checkpoint.up.sql b/backend/migrations/20261016162101_ai_agent_checkpoint.up.sql new file mode 100644 index 0000000000..a4407190b0 --- /dev/null +++ b/backend/migrations/20261016162101_ai_agent_checkpoint.up.sql @@ -0,0 +1,9 @@ +-- The conversation of an AI agent step parked on its approval tool, read back when the job is +-- pulled again. No foreign key to v2_job_queue: one would lock that table on every write here. +-- The monitor deletes rows whose job left the queue. +CREATE TABLE IF NOT EXISTS ai_agent_checkpoint ( + job_id UUID PRIMARY KEY, + workspace_id VARCHAR(50) NOT NULL, + checkpoint JSONB NOT NULL, + created_at TIMESTAMPTZ NOT NULL DEFAULT now() +); diff --git a/backend/src/monitor.rs b/backend/src/monitor.rs index 868e558f8d..a27f9d2055 100644 --- a/backend/src/monitor.rs +++ b/backend/src/monitor.rs @@ -4172,6 +4172,9 @@ pub async fn monitor_db( if let Err(e) = cleanup_flow_iterator_data_orphaned_jobs(&db).await { tracing::error!("Error cleaning up flow_iterator_data: {:?}", e); } + if let Err(e) = cleanup_ai_agent_checkpoint_orphaned_jobs(&db).await { + tracing::error!("Error cleaning up ai_agent_checkpoint: {:?}", e); + } } } }; @@ -7729,6 +7732,22 @@ async fn cleanup_job_result_stream_orphaned_jobs(db: &DB) -> error::Result<()> { Ok(()) } +/// A parked agent cancelled from outside, or a worker that died mid-segment, never deletes its +/// checkpoint itself. +async fn cleanup_ai_agent_checkpoint_orphaned_jobs(db: &DB) -> error::Result<()> { + let deleted = sqlx::query( + "DELETE FROM ai_agent_checkpoint c + WHERE NOT EXISTS (SELECT 1 FROM v2_job_queue q WHERE q.id = c.job_id)", + ) + .execute(db) + .await? + .rows_affected(); + if deleted > 0 { + tracing::info!("Cleaned up {deleted} orphaned ai_agent_checkpoint rows"); + } + Ok(()) +} + async fn cleanup_flow_iterator_data_orphaned_jobs(db: &DB) -> error::Result<()> { let result = sqlx::query!( " diff --git a/backend/summarized_schema.txt b/backend/summarized_schema.txt index 418108cd30..9b89ad2561 100644 --- a/backend/summarized_schema.txt +++ b/backend/summarized_schema.txt @@ -37,6 +37,7 @@ _sqlx_migrations: version(bigint), description(text), installed_on(ts), success( account: workspace_id(char), id(int), expires_at(ts), refresh_token(char), client(char), refresh_error(text), grant_type(char), cc_client_id(char), cc_client_secret(char), cc_token_url(char), mcp_server_url(text), scopes(text[]) FK: (workspace_id) -> workspace(id) agent_token_blacklist: token(char), expires_at(ts), blacklisted_at(ts), blacklisted_by(char) +ai_agent_checkpoint: job_id(uuid), workspace_id(char), checkpoint(jsonb), created_at(ts) ai_agent_memory: workspace_id(char), conversation_id(uuid), step_id(char), messages(jsonb), created_at(ts), updated_at(ts) ai_free_token_daily_usage: day(date), cost_nanos(bigint), updated_at(ts) ai_free_token_usage: email(char), cost_nanos(bigint), updated_at(ts) diff --git a/backend/tests/ai_agent_approval.rs b/backend/tests/ai_agent_approval.rs new file mode 100644 index 0000000000..9c5c00a7f7 --- /dev/null +++ b/backend/tests/ai_agent_approval.rs @@ -0,0 +1,154 @@ +use axum::{routing::post, Json, Router}; +use serde_json::{json, Value}; +use sqlx::{types::Uuid, Pool, Postgres}; +use std::time::Duration; +use windmill_common::{flows::FlowValue, jobs::JobPayload}; +use windmill_test_utils::{ + completed_job, in_test_worker, listen_for_completed_jobs, ApiServer, RunJob, StreamFind, +}; + +async fn model(Json(body): Json) -> ([(&'static str, &'static str); 1], String) { + let answered = body["messages"] + .as_array() + .unwrap() + .iter() + .any(|m| m["role"] == "tool"); + let delta = if answered { + json!({"role":"assistant", "content":"done"}) + } else { + json!({"role":"assistant", "tool_calls":[{ + "index":0, "id":"call_0", "type":"function", + "function":{"name":"delete_database", "arguments":"{}"} + }]}) + }; + let event = json!({"choices":[{"index":0, "delta":delta, "finish_reason":null}]}); + let end = json!({"choices":[{"index":0, "delta":{}, "finish_reason":if answered {"stop"} else {"tool_calls"}}]}); + ( + [("content-type", "text/event-stream")], + format!("data: {event}\n\ndata: {end}\n\ndata: [DONE]\n\n"), + ) +} + +/// The agent parks on a call that requires approval, is answered through the endpoint the run +/// page and the chat use, and resumes: an approved call runs, a rejected one never does. +async fn answer(db: Pool, approved: bool) -> anyhow::Result { + std::env::set_var("ALLOW_PRIVATE_AI_BASE_URLS", "true"); + let server = ApiServer::start(db.clone()).await?; + let port = server.addr.port(); + let listener = tokio::net::TcpListener::bind("127.0.0.1:0").await?; + let base = format!("http://{}", listener.local_addr()?); + let stub = tokio::spawn(async move { + axum::serve( + listener, + Router::new().route("/v1/chat/completions", post(model)), + ) + .await + .unwrap(); + }); + let flow: FlowValue = serde_json::from_value(json!({"modules":[{"id":"agent","value":{ + "type":"aiagent", + "tools":[{"id":"t0", "summary":"delete_database", "requires_approval":true, "value":{ + "type":"rawscript", "language":"bun", "input_transforms":{}, + "content":"export async function main() { return 'ran' }" + }}], + "input_transforms":{ + "provider":{"type":"static","value":{"kind":"customai","model":"approval-test","resource":{"base_url":format!("{base}/v1")}}}, + "user_message":{"type":"static","value":"delete it"}, + "max_iterations":{"type":"static","value":3} + } + }}]}))?; + let id = RunJob::from(JobPayload::RawFlow { + value: flow, + path: Some("u/test/agent_approval".into()), + restarted_from: None, + }) + .push(&db) + .await; + let notifications = listen_for_completed_jobs(&db).await; + let db_ = db.clone(); + let answered = async move { + let agent = loop { + let parked: Option = sqlx::query_scalar( + "SELECT q.id FROM v2_job_queue q JOIN v2_job j USING (id) + JOIN ai_agent_checkpoint c ON c.job_id = q.id + WHERE j.parent_job = $1 AND q.suspend > 0", + ) + .bind(id) + .fetch_optional(&db_) + .await + .unwrap(); + if let Some(agent) = parked { + break agent; + } + tokio::time::sleep(Duration::from_millis(200)).await; + }; + let token = windmill_common::auth::create_token_for_owner( + &db_, + "test-workspace", + "u/test-user", + "approval-test", + 100, + "test@windmill.dev", + &Uuid::nil(), + None, + None, + ) + .await + .unwrap(); + let response = reqwest::Client::new() + .post(format!( + "http://localhost:{port}/api/w/test-workspace/jobs_u/flow/resume_suspended/{agent}" + )) + .bearer_auth(token) + .json(&json!({"approved":approved, "payload":{"call_id":"call_0", "comment":"not today"}})) + .send() + .await + .unwrap(); + assert!( + response.status().is_success(), + "{}", + response.text().await.unwrap() + ); + notifications.find(&id).await; + }; + tokio::time::timeout(Duration::from_secs(60), in_test_worker(&db, answered, port)).await?; + + let result = completed_job(id, &db).await; + assert!(result.success, "{:?}", result.result); + let tool_jobs: i64 = sqlx::query_scalar( + "SELECT count(*) FROM v2_job WHERE parent_job IN (SELECT id FROM v2_job WHERE parent_job = $1)", + ) + .bind(id) + .fetch_one(&db) + .await?; + assert_eq!(tool_jobs, approved as i64, "only an approved call runs"); + stub.abort(); + server.close().await?; + let result = result.json_result().expect("agent result"); + Ok(result["messages"] + .as_array() + .unwrap() + .iter() + .find(|m| m["role"] == "tool") + .expect("the call's answer")["content"] + .clone()) +} + +#[sqlx::test(fixtures("base"))] +#[serial_test::serial] +async fn approved_call_runs_after_the_agent_resumes(db: Pool) -> anyhow::Result<()> { + assert_eq!(answer(db, true).await?, "\"ran\""); + Ok(()) +} + +#[sqlx::test(fixtures("base"))] +#[serial_test::serial] +async fn rejected_call_reaches_the_model_as_not_run(db: Pool) -> anyhow::Result<()> { + let content = answer(db, false).await?; + let content = content.as_str().unwrap(); + assert!( + content.starts_with("Not run") && content.contains("not today"), + "{content}" + ); + Ok(()) +} diff --git a/backend/windmill-ai/src/types.rs b/backend/windmill-ai/src/types.rs index 3950576aed..267e16c6eb 100644 --- a/backend/windmill-ai/src/types.rs +++ b/backend/windmill-ai/src/types.rs @@ -60,6 +60,11 @@ pub struct Tool { pub module: Option, pub def: ToolDef, pub mcp_source: Option, + /// Each call waits for a person to approve it, without the agent holding a worker. + pub requires_approval: bool, + /// Set on the built-in question tool, which the worker answers by parking the agent until + /// someone answers or this many seconds pass. + pub question_timeout_secs: Option, } #[derive(Deserialize, Serialize, Debug, Clone, PartialEq)] diff --git a/backend/windmill-api/src/mcp/session/gen/instructions.json b/backend/windmill-api/src/mcp/session/gen/instructions.json index 9cdb920c99..4f366ea992 100644 --- a/backend/windmill-api/src/mcp/session/gen/instructions.json +++ b/backend/windmill-api/src/mcp/session/gen/instructions.json @@ -224,7 +224,7 @@ "script.duckdb": "# Global draft script instructions\n\n- Global mode writes complete draft payloads only; it does not save, deploy, run, or generate metadata.\n- A script draft is a workspace item: `{ type: 'script', path, summary?, language, value, isDraft }` where `value` is the source code string.\n- Paths follow the conventions in the system prompt: default to `u//` when the user gave a bare name; only use `f//` when the folder is known to exist. Preserve the current path/language when modifying unless the user asked to change them.\n- Use `edit_script` for small localized changes (provide `old_string`/`new_string`); use `write_script` for full rewrites.\n\n# Windmill script authoring reference (duckdb)\n\n# Windmill Script Writing Guide\n\n## General Principles\n\n- A script's inputs are its parameters. Credentials and configuration come in as resource-typed parameters, never hard-coded or read from the environment; the language section below shows how that language declares parameters\n- When no resource type exists for a service, still take its connection as one resource-typed parameter, of a custom type holding the connection fields (base URL, account identifiers, credentials), its secret in a variable the resource references. A custom type is named `c_`, which keeps it apart from a hub type synced later: the parameter takes `RT.C` in TypeScript, a `c_` TypedDict in Python. A plain string parameter or a variable read inside the code only when the user asks for it: the resource keeps a connection's fields together, lets whoever runs the script pick an existing connection, and keeps the secret out of the arguments a run records. If the instance is reported as not having synced the Windmill Hub's resource types, mention that a superadmin can sync them, since the hub has types for most services. Otherwise, or when the user prefers it to syncing, propose the resource type and ask before creating it\n- A Windmill Hub script takes a resource type the hub publishes, so on an instance that has not synced the hub's types that type is missing: say so, and that a superadmin can sync them, before asking for a resource of it. Hub scripts often declare the type inline (`type Stripe = { token: string }`), which is still the `stripe` resource type; in code you write, name it the way the language section shows (`RT.Stripe` in TypeScript) rather than copying the inline declaration\n- Libraries are installed automatically - do not show installation instructions\n- In a language with an entrypoint function (TypeScript, Python, Go, Rust, PHP, R, …), name it `main` (`Main` in C#) and do not call it; in TypeScript it must be async. SQL, GraphQL, Bash, PowerShell and Ansible scripts have no `main`: their language section shows how they take arguments\n- Where the language has a Windmill client (`wmill`), use it to interact with the platform\n- A script's input schema may carry a top-level `prompt_for_ai` string: its author's instructions to an AI choosing the inputs. Follow it when you pick arguments to run that script, and keep it when you rewrite the schema\n\n## Return Values\n\n- A script can return any JSON-serializable value; a SQL script returns the rows its query produces\n- Return values become available to subsequent flow steps via `results.step_id`\n\n## Preprocessor Scripts\n\nPreprocessor scripts process raw trigger data from various sources (webhook, custom HTTP route, SQS, WebSocket, Kafka, NATS, MQTT, AMQP, Postgres, GCP Pub/Sub, Azure, or email) before passing it to the flow. This separates the trigger logic from the flow logic and keeps the auto-generated UI clean.\n\nA preprocessor is written in TypeScript or Python: its function is named `preprocessor` instead of `main`, and it receives a single parameter called `event` (the language section gives its type).\n\nThe returned object determines the parameter values passed to the flow.\ne.g., `{ b: 1, a: 2 }` calls the flow with `a = 2` and `b = 1`, assuming the flow has two inputs called `a` and `b`.\n\n\n# DuckDB\n\nArguments are defined with comments and used with `$name` syntax:\n\n```sql\n-- $name (text) = default\n-- $age (integer)\nSELECT * FROM users WHERE name = $name AND age > $age;\n```\n\n## Ducklake Integration\n\nAttach Ducklake for data lake operations:\n\n```sql\n-- Main ducklake\nATTACH 'ducklake' AS dl;\n\n-- Named ducklake\nATTACH 'ducklake://my_lake' AS dl;\n\n-- Then query\nSELECT * FROM dl.schema.table;\n```\n\n## External Database Connections\n\nConnect to external databases using resources:\n\n```sql\nATTACH '$res:path/to/resource' AS db (TYPE postgres);\nSELECT * FROM db.schema.table;\n```\n\n## S3 File Operations\n\nRead files from S3 storage:\n\n```sql\n-- Default storage\nSELECT * FROM read_csv('s3:///path/to/file.csv');\n\n-- Named storage\nSELECT * FROM read_csv('s3://storage_name/path/to/file.csv');\n\n-- Parquet files\nSELECT * FROM read_parquet('s3:///path/to/file.parquet');\n\n-- JSON files\nSELECT * FROM read_json('s3:///path/to/file.json');\n```\n\n### Receiving an S3Object as a script parameter\n\nDeclare the arg with type `(s3object)`. Windmill renders an S3 file picker for it\nand binds the arg as the bare `s3://storage/key` URI, which DuckDB's reader\nfunctions consume directly:\n\n```sql\n-- $file (s3object)\nSELECT * FROM read_parquet($file);\n```\n\nWorks with any DuckDB reader: `read_csv($file)`, `read_json($file)`, etc.\n\n### Writing query results to S3\n\nDuckDB writes to S3 natively via `COPY ... TO`:\n\n```sql\nCOPY (SELECT * FROM users) TO 's3:///exports/users.parquet' (FORMAT PARQUET);\n```\n\nUse this instead of the `-- s3` streaming directive supported by the other SQL\ndialects — that directive is not available in DuckDB.\n", "script.bunnative": "# Global draft script instructions\n\n- Global mode writes complete draft payloads only; it does not save, deploy, run, or generate metadata.\n- A script draft is a workspace item: `{ type: 'script', path, summary?, language, value, isDraft }` where `value` is the source code string.\n- Paths follow the conventions in the system prompt: default to `u//` when the user gave a bare name; only use `f//` when the folder is known to exist. Preserve the current path/language when modifying unless the user asked to change them.\n- Use `edit_script` for small localized changes (provide `old_string`/`new_string`); use `write_script` for full rewrites.\n\n# Windmill script authoring reference (bunnative)\n\n# Windmill Script Writing Guide\n\n## General Principles\n\n- A script's inputs are its parameters. Credentials and configuration come in as resource-typed parameters, never hard-coded or read from the environment; the language section below shows how that language declares parameters\n- When no resource type exists for a service, still take its connection as one resource-typed parameter, of a custom type holding the connection fields (base URL, account identifiers, credentials), its secret in a variable the resource references. A custom type is named `c_`, which keeps it apart from a hub type synced later: the parameter takes `RT.C` in TypeScript, a `c_` TypedDict in Python. A plain string parameter or a variable read inside the code only when the user asks for it: the resource keeps a connection's fields together, lets whoever runs the script pick an existing connection, and keeps the secret out of the arguments a run records. If the instance is reported as not having synced the Windmill Hub's resource types, mention that a superadmin can sync them, since the hub has types for most services. Otherwise, or when the user prefers it to syncing, propose the resource type and ask before creating it\n- A Windmill Hub script takes a resource type the hub publishes, so on an instance that has not synced the hub's types that type is missing: say so, and that a superadmin can sync them, before asking for a resource of it. Hub scripts often declare the type inline (`type Stripe = { token: string }`), which is still the `stripe` resource type; in code you write, name it the way the language section shows (`RT.Stripe` in TypeScript) rather than copying the inline declaration\n- Libraries are installed automatically - do not show installation instructions\n- In a language with an entrypoint function (TypeScript, Python, Go, Rust, PHP, R, …), name it `main` (`Main` in C#) and do not call it; in TypeScript it must be async. SQL, GraphQL, Bash, PowerShell and Ansible scripts have no `main`: their language section shows how they take arguments\n- Where the language has a Windmill client (`wmill`), use it to interact with the platform\n- A script's input schema may carry a top-level `prompt_for_ai` string: its author's instructions to an AI choosing the inputs. Follow it when you pick arguments to run that script, and keep it when you rewrite the schema\n\n## Return Values\n\n- A script can return any JSON-serializable value; a SQL script returns the rows its query produces\n- Return values become available to subsequent flow steps via `results.step_id`\n\n## Preprocessor Scripts\n\nPreprocessor scripts process raw trigger data from various sources (webhook, custom HTTP route, SQS, WebSocket, Kafka, NATS, MQTT, AMQP, Postgres, GCP Pub/Sub, Azure, or email) before passing it to the flow. This separates the trigger logic from the flow logic and keeps the auto-generated UI clean.\n\nA preprocessor is written in TypeScript or Python: its function is named `preprocessor` instead of `main`, and it receives a single parameter called `event` (the language section gives its type).\n\nThe returned object determines the parameter values passed to the flow.\ne.g., `{ b: 1, a: 2 }` calls the flow with `a = 2` and `b = 1`, assuming the flow has two inputs called `a` and `b`.\n\n\n# TypeScript (Bun Native)\n\nNative TypeScript execution. Native scripts are Bun scripts that run on the native worker — a lightweight V8 isolate that exposes `fetch` and the JavaScript standard library — and can be heavily parallelized. Every script MUST start with `//native` on its first line so Windmill routes it to the native worker; without it the exact same script runs on the regular Bun worker. You may import npm packages and other Windmill scripts (e.g. `./helper.ts`) — imports are resolved and bundled just like a regular Bun script — as long as everything (your code and its dependencies) relies only on `fetch` and the standard library. Libraries that need Node/Bun runtime APIs (filesystem, `node:*` modules, child processes, native addons) will not work on the native worker; use the regular `bun` language for those.\n\n## Structure\n\nExport a single **async** function called `main`:\n\n```typescript\n//native\nexport async function main(param1: string, param2: number) {\n // Your code here\n return { result: param1, count: param2 };\n}\n```\n\nDo not call the main function.\n\n## Resource Types\n\nOn Windmill, credentials and configuration are stored in resources and passed as parameters to main.\n\nUse the `RT` namespace for resource types:\n\n```typescript\n//native\nexport async function main(stripe: RT.Stripe) {\n // stripe contains API key and config from the resource\n}\n```\n\nOnly use resource types if you need them to satisfy the instructions. Always use the RT namespace.\n\n## Imports\n\n**The constraint is the runtime, not the import list.** You may import npm packages and relative Windmill scripts; they are resolved and bundled exactly like a regular Bun script. But the native worker only provides `fetch` and the JavaScript standard library, so any imported code must work using only those. Anything requiring Node/Bun built-ins (`node:fs`, `child_process`, the `Bun` API, native modules) belongs in a regular `bun` script instead. Use the globally available `fetch` for HTTP:\n\n```typescript\n//native\nexport async function main(url: string) {\n const response = await fetch(url);\n return await response.json();\n}\n```\n\n## Pure computation: `//no_network`\n\nA native script that only transforms its inputs can declare `//no_network` in its leading comment block (right after `//native`). The runtime then refuses every connection the script attempts: `fetch` to any host, the Windmill API (so `windmill-client` calls fail too), raw sockets and unix sockets, and `WM_TOKEN` is not set. Without `//native` it means something else: the script must run in an nsjail sandbox (`//sandbox`, or instance-wide sandboxing), which then loses its network, and it fails to run otherwise. Use it only when the script needs no external data beyond its arguments:\n\n```typescript\n//native\n//no_network\nexport async function main(items: { price: number; qty: number }[]) {\n return items.reduce((sum, i) => sum + i.price * i.qty, 0);\n}\n```\n\n## Windmill Client\n\n`windmill-client` works on the native worker (its calls go over `fetch`), so use it as the **preferred way to talk to Windmill** — reading resources/variables/states, running scripts and flows, and the S3 helpers below (`loadS3File`, `loadS3FileStream`, `writeS3File`, `S3Object`). It handles auth, the workspace, and the base URL for you. Reserve raw `fetch` for calling *external* HTTP APIs that aren't Windmill.\n\nThe full `windmill-client` API reference (every exported function and its signature) is included below — consult it for the exact method instead of hand-rolling a `fetch` against the Windmill API.\n\n## Preprocessor Scripts\n\nFor preprocessor scripts, the function should be named `preprocessor` and receives an `event` parameter:\n\n```typescript\n//native\ntype Event = {\n kind:\n | \"webhook\"\n | \"http\"\n | \"websocket\"\n | \"kafka\"\n | \"email\"\n | \"nats\"\n | \"postgres\"\n | \"sqs\"\n | \"mqtt\"\n | \"amqp\"\n | \"gcp\"\n | \"azure\";\n body: any;\n headers: Record;\n query: Record;\n};\n\nexport async function preprocessor(event: Event) {\n return {\n param1: event.body.field1,\n param2: event.query.id,\n };\n}\n```\n\n## S3 Object Operations\n\nWindmill provides built-in support for S3-compatible storage operations. The `wmill.S3Object` type covers both the `s3://storage/key` URI form (`s3:///key` for the workspace default storage) and the `{ s3, storage? }` record form — always use it instead of redefining your own.\n\n### Receiving an S3Object as a script parameter\n\n```typescript\n//native\nimport * as wmill from \"windmill-client\";\n\nexport async function main(file: wmill.S3Object) {\n const content = await wmill.loadS3File(file);\n // ...\n}\n```\n\n### S3 operations\n\n```typescript\n//native\nimport * as wmill from \"windmill-client\";\n\n// Load file content from S3\nconst content: Uint8Array = await wmill.loadS3File(s3object);\n\n// Load file as stream\nconst blob: Blob = await wmill.loadS3FileStream(s3object);\n\n// Write file to S3\nconst result: wmill.S3Object = await wmill.writeS3File(\n s3object, // Target path (or undefined to auto-generate)\n fileContent, // string or Blob\n s3ResourcePath // Optional: specific S3 resource to use\n);\n```\n\n\n# TypeScript SDK (windmill-client)\n\nImport: import * as wmill from 'windmill-client'\n\nThe client configures itself from the job's environment — base URL, token and credentials mode\nare all set before your code runs, so there is nothing to initialize and no reason to read\nWM_TOKEN or BASE_INTERNAL_URL and build an API URL yourself. Reconstructing that by hand only\nreintroduces details the client already handles. Call the SDK for anything Windmill, and use raw\nHTTP for third-party APIs.\n\nThe helpers below are the surface to prefer. For an endpoint none of them covers, import the\ngenerated service classes (JobService, ScriptService, ...) from 'windmill-client' — they are not\nlisted here but they do exist. What does not exist is a helper name you guessed at: if it is\nneither listed below nor a service method, do not call it.\n\nTo know who is running the script, read the contextual variables rather than calling the API:\n`process.env.WM_END_USER_EMAIL || process.env.WM_EMAIL`. WM_END_USER_EMAIL is the app viewer when\nthe run was triggered from an app and empty otherwise (both variables are always defined), WM_EMAIL\nis the user the job is permissioned as. WM_USERNAME is the matching username.\n\nworkerHasInternalServer(): boolean\n\n/**\n * Initialize the Windmill client with authentication token and base URL\n * @param token - Authentication token (defaults to WM_TOKEN env variable)\n * @param baseUrl - API base URL (defaults to BASE_INTERNAL_URL or BASE_URL env variable)\n */\nsetClient(token?: string, baseUrl?: string): void\n\n/**\n * Create a client configuration from env variables\n * @returns client configuration\n */\ngetWorkspace(): string\n\n/**\n * Get a resource value by path\n * @param path path of the resource, default to internal state path\n * @param undefinedIfEmpty if the resource does not exist, return undefined instead of throwing an error\n * @returns resource value\n */\nasync getResource(path?: string, undefinedIfEmpty?: boolean): Promise\n\n/**\n * Get the true root job id\n * @param jobId job id to get the root job id from (default to current job)\n * @returns root job id\n */\nasync getRootJobId(jobId?: string): Promise\n\n/**\n * Run a script synchronously by its path and wait for the result\n * @param path - Script path in Windmill\n * @param args - Arguments to pass to the script\n * @param verbose - Enable verbose logging\n * @param tag - Override the worker tag the job runs on\n * @returns Script execution result\n */\nasync runScriptByPath(path: string, args: Record | null = null, verbose: boolean = false, tag: string | null = null): Promise\n\n/**\n * Run a script synchronously by its hash and wait for the result\n * @param hash_ - Script hash in Windmill\n * @param args - Arguments to pass to the script\n * @param verbose - Enable verbose logging\n * @param tag - Override the worker tag the job runs on\n * @returns Script execution result\n */\nasync runScriptByHash(hash_: string, args: Record | null = null, verbose: boolean = false, tag: string | null = null): Promise\n\n/**\n * Append a text to the result stream\n * @param text text to append to the result stream\n */\nappendToResultStream(text: string): void\n\n/**\n * Stream to the result stream\n * @param stream stream to stream to the result stream\n */\nasync streamResult(stream: AsyncIterable): Promise\n\n/**\n * Run a flow synchronously by its path and wait for the result\n * @param path - Flow path in Windmill\n * @param args - Arguments to pass to the flow\n * @param verbose - Enable verbose logging\n * @param tag - Override the worker tag the job runs on\n * @returns Flow execution result\n */\nasync runFlow(path: string | null = null, args: Record | null = null, verbose: boolean = false, tag: string | null = null): Promise\n\n/**\n * Wait for a job to complete and return its result\n * @param jobId - ID of the job to wait for\n * @param verbose - Enable verbose logging\n * @returns Job result when completed\n */\nasync waitJob(jobId: string, verbose: boolean = false): Promise\n\n/**\n * Get the result of a completed job\n * @param jobId - ID of the completed job\n * @returns Job result\n */\nasync getResult(jobId: string): Promise\n\n/**\n * Get the result of a job if completed, or its current status\n * @param jobId - ID of the job\n * @returns Object with started, completed, success, and result properties\n */\nasync getResultMaybe(jobId: string): Promise\n\n/**\n * Cancel a queued or running job by ID.\n * @param jobId - UUID of the job to cancel\n * @param reason - Optional reason for cancellation\n * @returns Response message from the cancel endpoint\n */\nasync cancelJob(jobId: string, reason: string | undefined = undefined): Promise\n\n/**\n * Run a script asynchronously by its path\n * @param path - Script path in Windmill\n * @param args - Arguments to pass to the script\n * @param scheduledInSeconds - Schedule execution for a future time (in seconds), or {@link RunScriptAsyncOptions}\n * `{ scheduledInSeconds?, tag?, retry? }`, e.g. `{ retry: { constant: { attempts: 3, seconds: 10 } } }`\n * @param tag - Override the worker tag the job runs on\n * @returns Job ID of the created job\n */\nasync runScriptByPathAsync(path: string, args: Record | null = null, scheduledInSeconds: number | null | RunScriptAsyncOptions = null, tag: string | null = null): Promise\n\n/**\n * Run a script asynchronously by its hash\n * @param hash_ - Script hash in Windmill\n * @param args - Arguments to pass to the script\n * @param scheduledInSeconds - Schedule execution for a future time (in seconds), or {@link RunScriptAsyncOptions}\n * `{ scheduledInSeconds?, tag?, retry? }`, e.g. `{ retry: { constant: { attempts: 3, seconds: 10 } } }`\n * @param tag - Override the worker tag the job runs on\n * @returns Job ID of the created job\n */\nasync runScriptByHashAsync(hash_: string, args: Record | null = null, scheduledInSeconds: number | null | RunScriptAsyncOptions = null, tag: string | null = null): Promise\n\n/**\n * Run a flow asynchronously by its path\n * @param path - Flow path in Windmill\n * @param args - Arguments to pass to the flow\n * @param scheduledInSeconds - Schedule execution for a future time (in seconds)\n * @param doNotTrackInParent - If false, tracks state in parent job (only use when fully awaiting the job)\n * @param tag - Override the worker tag the job runs on\n * @returns Job ID of the created job\n */\nasync runFlowAsync(path: string | null, args: Record | null, scheduledInSeconds: number | null = null, // can only be set to false if this the job will be fully await and not concurrent with any other job // as otherwise the child flow and its own child will store their state in the parent job which will // lead to incorrectness and failures doNotTrackInParent: boolean = true, tag: string | null = null): Promise\n\n/**\n * Resolve a resource value in case the default value was picked because the input payload was undefined\n * @param obj resource value or path of the resource under the format `$res:path`\n * @returns resource value\n */\nasync resolveDefaultResource(obj: any): Promise\n\n/**\n * Get the state file path from environment variables\n * @returns State path string\n */\ngetStatePath(): string\n\n/**\n * Set a resource value by path\n * @param path path of the resource to set, default to state path\n * @param value new value of the resource to set\n * @param initializeToTypeIfNotExist if the resource does not exist, initialize it with this type\n */\nasync setResource(value: any, path?: string, initializeToTypeIfNotExist?: string): Promise\n\n/**\n * Set the state\n * @param state state to set\n * @param path Optional state resource path override. Defaults to `getStatePath()`.\n */\nasync setState(state: any, path?: string): Promise\n\n/**\n * Set the progress\n * Progress cannot go back and limited to 0% to 99% range\n * @param percent Progress to set in %\n * @param jobId? Job to set progress for\n */\nasync setProgress(percent: number, jobId?: any): Promise\n\n/**\n * Get the progress\n * @param jobId? Job to get progress from\n * @returns Optional clamped between 0 and 100 progress value\n */\nasync getProgress(jobId?: any): Promise\n\n/**\n * Whether the worker running this job has received its shutdown signal.\n * A draining worker waits for its current job to finish before exiting, so a\n * long-running script can poll this and return early to let the worker be replaced.\n * @param jobId? Job to check, defaults to the current job\n */\nasync workerIsDraining(jobId?: string): Promise\n\n/**\n * Set a flow user state\n * @param key key of the state\n * @param value value of the state\n */\nasync setFlowUserState(key: string, value: any, errorIfNotPossible?: boolean): Promise\n\n/**\n * Get a flow user state\n * @param path path of the variable\n */\nasync getFlowUserState(key: string, errorIfNotPossible?: boolean): Promise\n\n/**\n * Get the state shared across executions\n * @param path Optional state resource path override. Defaults to `getStatePath()`.\n */\nasync getState(path?: string): Promise\n\n/**\n * Get a variable by path\n * @param path path of the variable\n * @returns variable value\n */\nasync getVariable(path: string): Promise\n\n/**\n * Set a variable by path, create if not exist\n * @param path path of the variable\n * @param value value of the variable\n * @param isSecretIfNotExist if the variable does not exist, create it as secret or not (default: false)\n * @param descriptionIfNotExist if the variable does not exist, create it with this description (default: \"\")\n */\nasync setVariable(path: string, value: string, isSecretIfNotExist?: boolean, descriptionIfNotExist?: string): Promise\n\n/**\n * Build a PostgreSQL connection URL from a database resource\n * @param path - Path to the database resource\n * @returns PostgreSQL connection URL string\n */\nasync databaseUrlFromResource(path: string): Promise\n\nasync polarsConnectionSettings(s3_resource_path: string | undefined): Promise\n\nasync duckdbConnectionSettings(s3_resource_path: string | undefined): Promise\n\n/**\n * Get S3 client settings from a resource or workspace default\n * @param s3_resource_path - Path to S3 resource (uses workspace default if undefined)\n * @param workspace - Workspace to read from (defaults to the `WM_WORKSPACE` env var)\n * @returns S3 client configuration settings\n */\nasync denoS3LightClientSettings(s3_resource_path: string | undefined, workspace: string | undefined = undefined): Promise\n\n/**\n * Load the content of a file stored in S3. If the s3ResourcePath is undefined, it will default to the workspace S3 resource.\n * \n * ```typescript\n * let fileContent = await wmill.loadS3FileContent(inputFile)\n * // if the file is a raw text file, it can be decoded and printed directly:\n * const text = new TextDecoder().decode(fileContentStream)\n * console.log(text);\n * ```\n * \n * @param workspace - Workspace to read from (defaults to the `WM_WORKSPACE` env var)\n */\nasync loadS3File(s3object: S3Object, s3ResourcePath: string | undefined = undefined, workspace: string | undefined = undefined): Promise\n\n/**\n * Load the content of a file stored in S3 as a stream. If the s3ResourcePath is undefined, it will default to the workspace S3 resource.\n * \n * ```typescript\n * let fileContentBlob = await wmill.loadS3FileStream(inputFile)\n * // if the content is plain text, the blob can be read directly:\n * console.log(await fileContentBlob.text());\n * ```\n * \n * @param workspace - Workspace to read from (defaults to the `WM_WORKSPACE` env var)\n */\nasync loadS3FileStream(s3object: S3Object, s3ResourcePath: string | undefined = undefined, workspace: string | undefined = undefined): Promise\n\n/**\n * Persist a file to the S3 bucket. If the s3ResourcePath is undefined, it will default to the workspace S3 resource.\n * \n * ```typescript\n * const s3object = await writeS3File(s3Object, \"Hello Windmill!\")\n * const fileContentAsUtf8Str = (await s3object.toArray()).toString('utf-8')\n * console.log(fileContentAsUtf8Str)\n * ```\n * \n * @param workspace - Workspace to write to (defaults to the `WM_WORKSPACE` env var)\n */\nasync writeS3File(s3object: S3Object | undefined, fileContent: string | Blob, s3ResourcePath: string | undefined = undefined, contentType: string | undefined = undefined, contentDisposition: string | undefined = undefined, workspace: string | undefined = undefined): Promise\n\n/**\n * Permanently delete a file from S3 by key.\n * \n * ```typescript\n * await wmill.deleteS3File({ s3: \"path/to/file.txt\" })\n * ```\n * \n * @param s3object - S3 object identifying the file to delete (must have `s3` set)\n * @param workspace - Workspace to delete from (defaults to the `WM_WORKSPACE` env var)\n */\nasync deleteS3File(s3object: S3Object, workspace: string | undefined = undefined): Promise\n\n/**\n * Sign S3 objects to be used by anonymous users in public apps\n * @param s3objects s3 objects to sign\n * @param expirySecs how long the signature stays valid, in seconds (default 43200 = 12h, clamped to [60, 604800])\n * @returns signed s3 objects\n */\nasync signS3Objects(s3objects: S3Object[], { expirySecs }: { expirySecs?: number } = {}): Promise\n\n/**\n * Sign S3 object to be used by anonymous users in public apps\n * @param s3object s3 object to sign\n * @param expirySecs how long the signature stays valid, in seconds (default 43200 = 12h, clamped to [60, 604800])\n * @returns signed s3 object\n */\nasync signS3Object(s3object: S3Object, { expirySecs }: { expirySecs?: number } = {}): Promise\n\n/**\n * Generate a presigned public URL for an array of S3 objects.\n * If an S3 object is not signed yet, it will be signed first.\n * @param s3Objects s3 objects to sign\n * @param expirySecs how long the signature stays valid, in seconds (default 43200 = 12h, clamped to [60, 604800])\n * @returns list of signed public URLs\n */\nasync getPresignedS3PublicUrls(s3Objects: S3Object[], { baseUrl, expirySecs }: { baseUrl?: string; expirySecs?: number } = {}): Promise\n\n/**\n * Generate a presigned public URL for an S3 object. If the S3 object is not signed yet, it will be signed first.\n * @param s3Object s3 object to sign\n * @param expirySecs how long the signature stays valid, in seconds (default 43200 = 12h, clamped to [60, 604800])\n * @returns signed public URL\n */\nasync getPresignedS3PublicUrl(s3Objects: S3Object, { baseUrl, expirySecs }: { baseUrl?: string; expirySecs?: number } = {}): Promise\n\n/**\n * Get URLs needed for resuming a flow after this step\n * @param approver approver name\n * @param flowLevel if true, generate resume URLs for the parent flow instead of the specific step.\n * This allows pre-approvals that can be consumed by any later suspend step in the same flow.\n * @returns approval page UI URL, resume and cancel API URLs for resuming the flow\n */\nasync getResumeUrls(approver?: string, flowLevel?: boolean): Promise<{\n approvalPage: string;\n resume: string;\n cancel: string;\n}>\n\n/**\n * Get an OIDC jwt token for auth to external services (e.g: Vault, AWS) (ee only)\n * @param audience audience of the token\n * @param expiresIn Optional number of seconds until the token expires\n * @returns jwt token\n */\nasync getIdToken(audience: string, expiresIn?: number): Promise\n\n/**\n * Convert a base64-encoded string to Uint8Array\n * @param data - Base64-encoded string\n * @returns Decoded Uint8Array\n */\nbase64ToUint8Array(data: string): Uint8Array\n\n/**\n * Convert a Uint8Array to base64-encoded string\n * @param arrayBuffer - Uint8Array to encode\n * @returns Base64-encoded string\n */\nuint8ArrayToBase64(arrayBuffer: Uint8Array): string\n\n/**\n * Sends an interactive approval request via Slack, allowing optional customization of the message, approver, and form fields.\n * \n * **[Enterprise Edition Only]** To include form fields in the Slack approval request, go to **Advanced -> Suspend -> Form**\n * and define a form. Learn more at [Windmill Documentation](https://www.windmill.dev/docs/flows/flow_approval#form).\n * \n * @param {Object} options - The configuration options for the Slack approval request.\n * @param {string} options.slackResourcePath - The path to the Slack resource in Windmill.\n * @param {string} options.channelId - The Slack channel ID where the approval request will be sent.\n * @param {string} [options.message] - Optional custom message to include in the Slack approval request.\n * @param {string} [options.approver] - Optional user ID or name of the approver for the request.\n * @param {DefaultArgs} [options.defaultArgsJson] - Optional object defining or overriding the default arguments to a form field.\n * @param {Enums} [options.dynamicEnumsJson] - Optional object overriding the enum default values of an enum form field.\n * @param {string} [options.resumeButtonText] - Optional text for the resume button.\n * @param {string} [options.cancelButtonText] - Optional text for the cancel button.\n * \n * @returns {Promise} Resolves when the Slack approval request is successfully sent.\n * \n * @throws {Error} If the function is not called within a flow or flow preview.\n * @throws {Error} If the `JobService.getSlackApprovalPayload` call fails.\n * \n * **Usage Example:**\n * ```typescript\n * await requestInteractiveSlackApproval({\n * slackResourcePath: \"/u/alex/my_slack_resource\",\n * channelId: \"admins-slack-channel\",\n * message: \"Please approve this request\",\n * approver: \"approver123\",\n * defaultArgsJson: { key1: \"value1\", key2: 42 },\n * dynamicEnumsJson: { foo: [\"choice1\", \"choice2\"], bar: [\"optionA\", \"optionB\"] },\n * resumeButtonText: \"Resume\",\n * cancelButtonText: \"Cancel\",\n * });\n * ```\n * \n * **Note:** This function requires execution within a Windmill flow or flow preview.\n */\nasync requestInteractiveSlackApproval({ slackResourcePath, channelId, message, approver, defaultArgsJson, dynamicEnumsJson, resumeButtonText, cancelButtonText, }: SlackApprovalOptions): Promise\n\n/**\n * Sends an interactive approval request via Teams, allowing optional customization of the message, approver, and form fields.\n * \n * **[Enterprise Edition Only]** To include form fields in the Teams approval request, go to **Advanced -> Suspend -> Form**\n * and define a form. Learn more at [Windmill Documentation](https://www.windmill.dev/docs/flows/flow_approval#form).\n * \n * @param {Object} options - The configuration options for the Teams approval request.\n * @param {string} options.teamName - The Teams team name where the approval request will be sent.\n * @param {string} options.channelName - The Teams channel name where the approval request will be sent.\n * @param {string} [options.message] - Optional custom message to include in the Teams approval request.\n * @param {string} [options.approver] - Optional user ID or name of the approver for the request.\n * @param {DefaultArgs} [options.defaultArgsJson] - Optional object defining or overriding the default arguments to a form field.\n * @param {Enums} [options.dynamicEnumsJson] - Optional object overriding the enum default values of an enum form field.\n * \n * @returns {Promise} Resolves when the Teams approval request is successfully sent.\n * \n * @throws {Error} If the function is not called within a flow or flow preview.\n * @throws {Error} If the `JobService.getTeamsApprovalPayload` call fails.\n * \n * **Usage Example:**\n * ```typescript\n * await requestInteractiveTeamsApproval({\n * teamName: \"admins-teams\",\n * channelName: \"admins-teams-channel\",\n * message: \"Please approve this request\",\n * approver: \"approver123\",\n * defaultArgsJson: { key1: \"value1\", key2: 42 },\n * dynamicEnumsJson: { foo: [\"choice1\", \"choice2\"], bar: [\"optionA\", \"optionB\"] },\n * });\n * ```\n * \n * **Note:** This function requires execution within a Windmill flow or flow preview.\n */\nasync requestInteractiveTeamsApproval({ teamName, channelName, message, approver, defaultArgsJson, dynamicEnumsJson, }: TeamsApprovalOptions): Promise\n\nsetWorkflowCtx(ctx: WorkflowCtx | null): void\n\nasync sleep(seconds: number): Promise\n\n/**\n * Execute `fn` inline and checkpoint the result. On replay the cached value is\n * returned without re-executing `fn`.\n * \n * `fn`'s result is encoded as JSON and decoded back before it is returned, so\n * the round that runs the body sees the same types every replay sees: a `Date`\n * comes back as a string, a `Map` as `{}`. {@link Jsonified} is that shape.\n * \n * Called from inside a task body, `fn` runs in place and nothing is\n * checkpointed: a task is a single job and is never replayed.\n */\nasync step(name: string, fn: () => T | Promise,): Promise>>\n\n/**\n * Create a task that dispatches to a separate Windmill script.\n * \n * @example\n * const extract = taskScript(\"f/data/extract\");\n * // inside workflow: await extract({ url: \"https://...\" })\n */\ntaskScript(path: string, options?: TaskOptions): (...args: any[]) => PromiseLike\n\n/**\n * Create a task that dispatches to a separate Windmill flow.\n * \n * @example\n * const pipeline = taskFlow(\"f/etl/pipeline\");\n * // inside workflow: await pipeline({ input: data })\n */\ntaskFlow(path: string, options?: TaskOptions): (...args: any[]) => PromiseLike\n\n/**\n * Mark an async function as a workflow-as-code entry point.\n * \n * The function must be **deterministic**: given the same inputs it must call\n * tasks in the same order on every replay. Branching on task results is fine\n * (results are replayed from checkpoint), but branching on external state\n * (current time, random values, external API calls) must use `step()` to\n * checkpoint the value so replays see the same result.\n */\nworkflow(fn: (...args: any[]) => Promise): void\n\n/**\n * Suspend the workflow and wait for an external approval.\n * \n * Pass `key` to name the step, then `getApprovalUrls(key)` yields the URLs that\n * resume exactly this approval — route them through your own channel. Without a\n * key the steps are named `approval`, `approval_2`, ...\n * \n * `skin: \"minimal\"` shows approvers only the request (form and approve/reject)\n * instead of the detailed page with the workflow's details. `description` is\n * shown above the form: a string, or a rich value such as `{ markdown: \"...\" }`.\n * \n * @example\n * const urls = await step(\"urls\", () => getApprovalUrls(\"manager\"));\n * await step(\"notify\", () => sendEmail(urls.resume, urls.cancel));\n * const { value, approver } = await waitForApproval({ key: \"manager\", timeout: 3600 });\n */\nwaitForApproval(options?: { timeout?: number; form?: object; selfApproval?: boolean; key?: string; skin?: \"detailed\" | \"minimal\"; description?: string | object; }): PromiseLike<{ value: any; approver: string; approved: boolean }>\n\n/**\n * Resume/cancel/approval-page URLs bound to one `waitForApproval` step.\n * \n * Unlike `getResumeUrls()`, which signs a random nonce, these address the very\n * `resume_job` record the step's built-in approval buttons use, so they are\n * stable across replays and safe to embed in a custom notification.\n * \n * `stepKey` must match the `key` given to `waitForApproval`. Keys must be unique\n * within a workflow; reusing one throws rather than silently renaming it. The URL\n * only resumes while that step is awaiting approval; used at any other moment it is\n * rejected rather than banking a row a different approval would consume. Send it\n * ahead of time — approvers just cannot act before the workflow reaches the step.\n * \n * `resume` and `cancel` are step-bound; `approvalPage` is not — it opens the job's\n * approval page, which acts on whichever approval is pending when it is used.\n * \n * @example\n * const urls = await step(\"urls\", () => getApprovalUrls(\"manager\"));\n * await step(\"notify\", () => sendEmail(urls.resume, urls.cancel));\n * await waitForApproval({ key: \"manager\" });\n */\nasync getApprovalUrls(stepKey: string = \"approval\", approver?: string): Promise<{\n approvalPage: string;\n resume: string;\n cancel: string;\n}>\n\n/**\n * Process items in parallel with optional concurrency control.\n * \n * Each item is processed by calling `fn(item)`, which should be a task().\n * Items are dispatched in batches of `concurrency` (default: all at once).\n * \n * @example\n * const process = task(async (item: string) => { ... });\n * const results = await parallel(items, process, { concurrency: 5 });\n */\nasync parallel(items: T[], fn: (item: T) => PromiseLike | R, options?: { concurrency?: number },): Promise\n\n/**\n * Commit Kafka offsets for a trigger with auto_commit disabled.\n * @param triggerPath - Path to the Kafka trigger (from event.wm_trigger.trigger_path)\n * @param topic - Kafka topic name (from event.topic)\n * @param partition - Partition number (from event.partition)\n * @param offset - Message offset to commit (from event.offset)\n */\nasync commitKafkaOffsets(triggerPath: string, topic: string, partition: number, offset: number,): Promise\n\n/**\n * Parse an S3 object from URI string or record format\n * @param s3Object - S3 object as URI string (`s3://storage/key`, `s3:///key`\n * for the default storage) or record. Any other string throws rather than\n * falling back to an auto-generated key: an auto key is requested by\n * omitting the object, and a fallback would silently misplace the upload\n * on any typo.\n * @returns S3 object record with storage and s3 key\n */\nparseS3Object(s3Object: S3Object): S3ObjectRecord\n\n/**\n * Create a SQL template function for PostgreSQL/datatable queries\n * @param name - Database/datatable name (default: \"main\")\n * @param opts.role - Connect as this data table role instead of the data table's default one.\n * Only meaningful on a data table under roles, and only for a role you are a tenant of.\n * @returns SQL template function for building parameterized queries\n * @example\n * let sql = wmill.datatable()\n * let name = 'Robin'\n * let age = 21\n * await sql`\n * SELECT * FROM friends\n * WHERE name = ${name} AND age = ${age}::int\n * `.fetch()\n * @example\n * // Read through a restricted role\n * let sql = wmill.datatable(\"main\", { role: \"analytics\" })\n */\ndatatable(name: string = \"main\", opts?: DatatableOptions): DatatableSqlTemplateFunction\n\n/**\n * Create a SQL template function for DuckDB/ducklake queries\n * @param name - DuckDB database name, optionally with a schema as `name:schema` (default: \"main\")\n * @returns SQL template function for building parameterized queries\n * @example\n * let sql = wmill.ducklake()\n * let name = 'Robin'\n * let age = 21\n * await sql`\n * SELECT * FROM friends\n * WHERE name = ${name} AND age = ${age}\n * `.fetch()\n * @example\n * // Target a specific schema within the ducklake\n * let sql = wmill.ducklake(\"my_lake:analytics\")\n */\nducklake(name: string = \"main\"): SqlTemplateFunction\n\n/**\n * Idempotently materialize `selectSql` into a ducklake table for one\n * partition (or the whole table when `partition` is omitted) — the client-side\n * equivalent of the `// materialize` engine.\n * With `uniqueKey` it upserts the slice (delete-by-key + insert); otherwise it\n * replaces it (whole table → `CREATE OR REPLACE`; partition → delete + insert).\n * Safe to re-run for the same partition (backfill / failure-recovery).\n * \n * Returns a lazy statement — call `.execute()` to run it:\n * `await wmill.upsertPartition({ table, selectSql, partition }).execute()`.\n */\nupsertPartition(opts: DucklakeMaterializeOptions): SqlStatement\n\n/**\n * INSERT-only materialization (no dedup/replace) for append-only tables.\n * Re-running the same partition duplicates rows — use only for immutable\n * event-log sources.\n * \n * Returns a lazy statement — call `.execute()` to run it:\n * `await wmill.appendPartition({ table, selectSql, partition }).execute()`.\n */\nappendPartition(opts: Omit,): SqlStatement\n", "script.dbt": "# Global draft script instructions\n\n- Global mode writes complete draft payloads only; it does not save, deploy, run, or generate metadata.\n- A script draft is a workspace item: `{ type: 'script', path, summary?, language, value, isDraft }` where `value` is the source code string.\n- Paths follow the conventions in the system prompt: default to `u//` when the user gave a bare name; only use `f//` when the folder is known to exist. Preserve the current path/language when modifying unless the user asked to change them.\n- Use `edit_script` for small localized changes (provide `old_string`/`new_string`); use `write_script` for full rewrites.\n\n# Windmill script authoring reference (dbt)\n\n# Windmill Script Writing Guide\n\n## General Principles\n\n- A script's inputs are its parameters. Credentials and configuration come in as resource-typed parameters, never hard-coded or read from the environment; the language section below shows how that language declares parameters\n- When no resource type exists for a service, still take its connection as one resource-typed parameter, of a custom type holding the connection fields (base URL, account identifiers, credentials), its secret in a variable the resource references. A custom type is named `c_`, which keeps it apart from a hub type synced later: the parameter takes `RT.C` in TypeScript, a `c_` TypedDict in Python. A plain string parameter or a variable read inside the code only when the user asks for it: the resource keeps a connection's fields together, lets whoever runs the script pick an existing connection, and keeps the secret out of the arguments a run records. If the instance is reported as not having synced the Windmill Hub's resource types, mention that a superadmin can sync them, since the hub has types for most services. Otherwise, or when the user prefers it to syncing, propose the resource type and ask before creating it\n- A Windmill Hub script takes a resource type the hub publishes, so on an instance that has not synced the hub's types that type is missing: say so, and that a superadmin can sync them, before asking for a resource of it. Hub scripts often declare the type inline (`type Stripe = { token: string }`), which is still the `stripe` resource type; in code you write, name it the way the language section shows (`RT.Stripe` in TypeScript) rather than copying the inline declaration\n- Libraries are installed automatically - do not show installation instructions\n- In a language with an entrypoint function (TypeScript, Python, Go, Rust, PHP, R, …), name it `main` (`Main` in C#) and do not call it; in TypeScript it must be async. SQL, GraphQL, Bash, PowerShell and Ansible scripts have no `main`: their language section shows how they take arguments\n- Where the language has a Windmill client (`wmill`), use it to interact with the platform\n- A script's input schema may carry a top-level `prompt_for_ai` string: its author's instructions to an AI choosing the inputs. Follow it when you pick arguments to run that script, and keep it when you rewrite the schema\n\n## Return Values\n\n- A script can return any JSON-serializable value; a SQL script returns the rows its query produces\n- Return values become available to subsequent flow steps via `results.step_id`\n\n## Preprocessor Scripts\n\nPreprocessor scripts process raw trigger data from various sources (webhook, custom HTTP route, SQS, WebSocket, Kafka, NATS, MQTT, AMQP, Postgres, GCP Pub/Sub, Azure, or email) before passing it to the flow. This separates the trigger logic from the flow logic and keeps the auto-generated UI clean.\n\nA preprocessor is written in TypeScript or Python: its function is named `preprocessor` instead of `main`, and it receives a single parameter called `event` (the language section gives its type).\n\nThe returned object determines the parameter values passed to the flow.\ne.g., `{ b: 1, a: 2 }` calls the flow with `a = 2` and `b = 1`, assuming the flow has two inputs called `a` and `b`.\n", - "flow": "# Global draft flow instructions\n\n- Global mode writes complete draft payloads only; it does not save, deploy, run, scaffold local files, or generate metadata.\n- Paths follow the conventions in the system prompt: default to `u//` when the user gave a bare name; only use `f//` when the folder is known to exist. Never invent a folder.\n- `write_flow` mirrors flow mode's `set_flow_json`: pass `path`, optional `summary`, optional `description`, required `modules`, and optional `schema`, `preprocessor_module`, `failure_module`, `groups`, and `notes`. `summary` and `description` are top-level flow metadata (not part of the compact value `patch_flow_json` edits); the flow-structure arguments are JSON strings, matching the tool schema descriptions. When overwriting an existing flow, top-level flow settings (see below) are preserved from the current flow — use `patch_flow_json` to change them.\n- `read_workspace_item` returns a compact flow `value` object with `modules`, `schema`, `preprocessor_module`, `failure_module`, `groups`, `notes`, and any top-level flow settings that are set.\n- Top-level flow settings appear as top-level keys of the compact flow value and can be added, edited, or removed with `patch_flow_json`: same_worker, preserve_step_tags, concurrent_limit, concurrency_key, concurrency_time_window_s, debounce_delay_s, debounce_key, debounce_args_to_accumulate, max_total_debouncing_time, max_total_debounces_amount, skip_expr, cache_ttl, cache_ignore_s3_path, delete_after_secs, flow_env, priority, early_return, chat_input_enabled. For example, `chat_input_enabled: true` marks a flow as chat-style (flow-as-chat); keep it intact when restructuring such a flow.\n- `modules` contains normal sequential modules. Use top-level `preprocessor_module` and `failure_module` for special modules; do not put `preprocessor` or `failure` in `modules`.\n- Every module needs a stable unique `id` and a useful `summary` when the schema supports it.\n- Prefer path/script/flow modules when composing existing workspace logic. Use rawscript modules only when new inline code is needed.\n- When writing rawscript module code, call `get_instructions` with `subject: \"script\"` and the rawscript language first.\n\n## Groups and notes\n\n- Add `groups` to any non-trivial flow without being asked; \"Organizing Flows: Groups and Notes\" in the reference below gives the fields and the rules the editor enforces. Pass `null` to `write_flow` to clear them, and the same for `notes`.\n- With `patch_flow_json`, edit `groups` and `notes` the same way as any other field — they appear as top-level keys in the compact flow value.\n\n## Compact view: how rawscript bodies surface in tool I/O\n\n- `read_workspace_item` and `patch_flow_json` operate on a **compact view** of the flow: every rawscript module's `value.content` is replaced with the placeholder `\"inline_script.\"` so inline script bodies don't bloat tool I/O. Schema, groups, notes, preprocessor_module and failure_module are all shown in this view.\n- Inline rawscript content is **not** part of the JSON `patch_flow_json` sees. Edits to inline bodies happen via dedicated tools:\n - `read_flow_module_code(path, module_id)` — returns the raw inline script content for one module.\n - `set_flow_module_code(path, module_id, code)` — overwrites that module's inline script content; saves to the draft.\n- Use `patch_flow_json` for *structural* edits: module ids, paths, input_transforms, branch arrangement, summaries, preprocessor/failure swaps, schema/groups/notes. Use `set_flow_module_code` for changes inside a specific rawscript body.\n- When **adding a new rawscript module** with `patch_flow_json`, set its `content` to the placeholder `\"inline_script.\"` (matching the compact view) — never real code — then **immediately fill the body** with `set_flow_module_code(path, module_id, code)`. The module is saved with an empty body until you do; the tool result lists the module ids still awaiting code. A placeholder that names anything other than the module's own id or an existing rawscript module is rejected.\n- `write_flow` is for full overwrites / create-from-scratch. Its `modules`, `preprocessor_module`, and `failure_module` arguments are **non-compact** flow modules: inline each rawscript body directly in `content` by default. But if a body is long or quote/backslash-heavy enough that escaping it into the JSON string is error-prone — or if a `write_flow` call comes back with a JSON parse error — create that module with **empty content** (`\"content\": \"\"`) and fill it with `set_flow_module_code(path, module_id, code)`, whose `code` is a plain argument with no nested escaping. `write_flow` reports which modules still have empty bodies so you know what to fill.\n - When overwriting an **existing** flow, set `\"content\": \"inline_script.\"` on any rawscript module whose code you are not changing — the placeholder resolves to that module's current body, so you never re-send (or re-read) unchanged code. Placeholders that match no existing rawscript module and are not the module's own id are rejected.\n\n\n# Windmill flow authoring reference\n\n# Windmill Flow Building Guide\n\n## OpenFlow Schema\n\nThe OpenFlow schema (openflow.openapi.yaml) is the source of truth for flow structure. Refer to OPENFLOW_SCHEMA for the complete type definitions.\n\n## Reserved Module IDs\n\n- `failure` - Reserved for failure handler module\n- `preprocessor` - Reserved for preprocessor module\n- `Input` - Reserved for flow input reference\n\n## Hard Structural Rules\n\nThese are strict Windmill schema rules. Follow them exactly.\n\n- `value.modules` is only for normal sequential steps\n- `value.preprocessor_module` and `value.failure_module` are special top-level fields inside `value`, not entries in `value.modules`\n- If a flow needs a preprocessor, create `value.preprocessor_module` with `id: preprocessor`\n- If a flow needs a failure handler, create `value.failure_module` with `id: failure`\n- Do NOT create regular modules inside `value.modules` named `preprocessor` or `failure`\n- `preprocessor_module` and `failure_module` only support `script` or `rawscript`\n- `preprocessor_module` runs before normal modules and cannot reference `results.*`\n- `failure_module` can use the `error` object with `error.message`, `error.step_id`, `error.name`, and `error.stack`\n- A flow whose `failure_module` runs still ends as failed, unless the handler returns an object with `recover: true`: the flow then ends as a success. This also holds when the failing step is inside a loop, a branch or a subflow. `recover` never changes which steps run; whether a loop or branch carries on past a failure is still decided by its own settings (`skip_failures`, `continue_on_error`)\n\nCorrect shape:\n\n```yaml\nvalue:\n preprocessor_module:\n id: preprocessor\n value:\n type: rawscript\n ...\n failure_module:\n id: failure\n value:\n type: rawscript\n ...\n modules:\n - id: process_event\n value:\n type: rawscript\n ...\n```\n\nIncorrect shape:\n\n```yaml\nvalue:\n modules:\n - id: preprocessor\n ...\n - id: process_event\n ...\n - id: failure\n ...\n```\n\n## Module ID Rules\n\n- Must be unique across the entire flow\n- Use underscores, not spaces (e.g., `fetch_data` not `fetch data`)\n- Use descriptive names that reflect the step's purpose\n\n## AI Agent Modules\n\nAn `aiagent` module runs an LLM that can call tools. Each entry of `value.tools` is a module-shaped\nobject with an extra `value.tool_type`: `flowmodule` for a script/flow tool, `mcp` for an MCP server\ntool, `websearch` for web search.\n\n```json\n{\n \"id\": \"support_agent\",\n \"summary\": \"AI agent for customer support\",\n \"value\": {\n \"type\": \"aiagent\",\n \"input_transforms\": {\n \"provider\": {\n \"type\": \"static\",\n \"value\": { \"kind\": \"openai\", \"resource\": \"$res:f/ai_providers/openai\", \"model\": \"gpt-4o\" }\n },\n \"output_type\": { \"type\": \"static\", \"value\": \"text\" },\n \"user_message\": { \"type\": \"javascript\", \"expr\": \"flow_input.query\" },\n \"system_prompt\": { \"type\": \"static\", \"value\": \"You are a helpful assistant.\" }\n },\n \"tools\": [\n {\n \"id\": \"search_docs\",\n \"summary\": \"search_documentation\",\n \"description\": \"Search the product documentation. Use it whenever the user asks how a feature works.\",\n \"value\": {\n \"tool_type\": \"flowmodule\",\n \"type\": \"rawscript\",\n \"language\": \"bun\",\n \"content\": \"export async function main(query: string) { return ['doc1', 'doc2']; }\",\n \"input_transforms\": { \"query\": { \"type\": \"static\", \"value\": \"\" } }\n }\n }\n ]\n }\n}\n```\n\n- `provider` is an object, not a bare resource string: `{ \"kind\": ,\n \"resource\": \"$res:\", \"model\": }`. Required unless the module links to a saved\n agent through `value.agent`. Static is right for a flow run from a form; a chat flow wires its\n fields to flow inputs instead — see below\n\n### Chat-Mode Flows\n\nA flow with `value.chat_input_enabled: true` is run from a chat instead of a form: the composer\nsends one message per turn and renders the conversation. It needs a required `user_message` string\ninput, read by the agent. Any other flow input the composer does not edit itself is asked for\nunder Configure inputs.\n\n**A static `provider` gives a chat that cannot change its model.** Feed it from flow inputs\ninstead, either way round: one input carrying the whole object (`\"expr\": \"flow_input.model_config\"`)\nmakes every field editable, or wire it field by field to fix some and expose others. A field the\nchat can write becomes a control in the composer — a provider picker, a model list, a thinking\ncontrol — and a field left static is fixed, with no control drawn for it. `kind` is the one\nexception: the composer writes it only together with `resource`, since a provider is picked as a\npair, so a `kind` input wired on its own stays askable under Configure inputs and nothing the run\nneeds becomes unreachable.\n\n```json\n{\n \"id\": \"chat_agent\",\n \"value\": {\n \"type\": \"aiagent\",\n \"input_transforms\": {\n \"provider\": {\n \"type\": \"javascript\",\n \"expr\": \"({ kind: 'anthropic', resource: '$res:f/ai/claude', model: flow_input.model, reasoning_effort: flow_input.thinking })\"\n },\n \"user_message\": { \"type\": \"javascript\", \"expr\": \"flow_input.user_message\" },\n \"user_attachments\": { \"type\": \"javascript\", \"expr\": \"flow_input.files\" },\n \"memory\": { \"type\": \"static\", \"value\": { \"kind\": \"compaction\" } },\n \"streaming\": { \"type\": \"static\", \"value\": true },\n \"output_type\": { \"type\": \"static\", \"value\": \"text\" }\n },\n \"tools\": []\n }\n}\n```\n\n- Wiring field by field means one object literal whose values are literals or bare `flow_input.x`\n references. A spread, a call or a computed key leaves the composer unable to tell which input\n feeds which field, so it offers no control at all — a bare `flow_input.x` for the whole object\n is read instead as that one input carrying every field\n- A step linked to a saved agent (`agent` set) has no `provider` of its own. It exposes the same\n two controls through its `model` and `reasoning_effort` inputs, which replace what the agent\n saved: `\"model\": { \"type\": \"javascript\", \"expr\": \"flow_input.model\" }`. An empty model keeps the\n saved one, an empty effort sends none, and the provider resource always stays the agent's\n- `memory` is what lets the agent see earlier turns; without it every message starts from nothing\n- `streaming` on makes the answer and its thinking appear token by token instead of all at once\n- `user_attachments` points at a flow input typed as an array of s3 objects\n (`{ \"type\": \"array\", \"items\": { \"type\": \"object\", \"resourceType\": \"s3object\" } }`), so files\n sent with a message reach the agent\n- Running one needs a `memory_id` **query parameter** — not a flow argument — naming the\n conversation the turn belongs to: a fresh UUID starts one, reusing a UUID continues it. The chat\n supplies it itself; a run driven any other way has to pass it or the server refuses the job\n\n### Tool Naming Rules\n\nThese rules cover `flowmodule` tools, the ones the agent calls by name. A `websearch` tool's\n`summary` is a plain label (`Web Search`), and an `mcp` tool exposes the MCP server's own tool\nnames, so neither is name-checked at all — leave those summaries as they are.\n\n- A flowmodule tool's `summary` is the **name the agent calls it by**, not a human label. Put the\n human-readable explanation in `description`\n- `summary` must match `^[a-zA-Z0-9_]+$`: letters, numbers and underscores only. No spaces, dashes,\n dots or accents — `search_documentation`, never `Search documentation`\n- Always set `summary`. It must be unique among that agent's tools, and must not be one of the\n reserved ids (`do`, `bg`, `ctx`, `state`, `if`, `else`, `for`, `delete`, `while`, `new`, `in`,\n `failure`, `preprocessor`, `as`, `Input`, `Result`, `Trigger`)\n- A tool name outside that character set fails any run that offers the tool to the agent, with `Invalid tool name`.\n The flow write tools refuse such a name.\n- Tool `id` follows the same rules as any module ID — unique across the flow, underscores not spaces\n- `description` is optional free text telling the agent when and how to call the tool. Set it\n whenever the name alone does not make that obvious; it overrides the description derived from the\n underlying script\n\n## AI Decision Modules\n\nAn `aidecision` module asks a decision model (TypeSafe's Jev, Cloudflare's Clef or OpenAI's Decisions API) typed questions about a `state` and\nanswers each with calibrated probabilities instead of text. Prefer it over an `aiagent` when the step\nis a judgment (classify, route, score or a yes/no check) that needs no tools and no free text: it\nis faster, cheaper, and its answers have a fixed shape.\n\n```json\n{\n \"id\": \"triage\",\n \"summary\": \"Classify the ticket\",\n \"value\": {\n \"type\": \"aidecision\",\n \"input_transforms\": {\n \"provider\": {\n \"type\": \"static\",\n \"value\": { \"kind\": \"typesafe\", \"resource\": \"$res:f/ai/typesafe\", \"model\": \"jev-latest\" }\n },\n \"state\": { \"type\": \"javascript\", \"expr\": \"flow_input.message\" },\n \"questions\": {\n \"type\": \"static\",\n \"value\": {\n \"intent\": {\n \"type\": \"choice\",\n \"instructions\": \"What does the customer want?\",\n \"criteria\": { \"refund\": \"Money back\", \"bug\": \"Something is broken\", \"other\": \"Anything else\" }\n },\n \"urgency\": {\n \"type\": \"score\",\n \"instructions\": \"How urgent is the ticket?\",\n \"criteria\": [\"Can wait\", \"This week\", \"Today\", \"Right now\"]\n },\n \"angry\": { \"type\": \"noul\", \"instructions\": \"Is the customer angry?\" }\n }\n }\n }\n }\n}\n```\n\n- `provider.kind` is `typesafe` (`model` `jev-latest` unless a version is pinned), `cloudflare`\n (`model` `clef`, or `clef-flash` for faster answers) or `openai` (`model` `gpt-6-luna`, never a\n chat model); the resource is of that same type\n- `state` is the content to evaluate: usually a text, such as the message to classify. To combine\n several values, pass an object with descriptive keys holding only what the questions need\n (`({ message: flow_input.message, plan: results.get_account.plan })`); an array of strings also works\n- `questions` maps each question name to `{ type, instructions, criteria }`:\n - `choice`: `criteria` maps each option to its description (up to 255 options). The answer has\n `choice`, `probabilities` and `confidence`\n - `score`: `criteria` is an ordered array of 2 to 10 level descriptions. The answer has `score`,\n `legend`, `probabilities` and `confidence`\n - `noul`: yes/no, `criteria` optionally `{ \"true\": ..., \"false\": ... }` descriptions. The answer has\n `noul`, the probability of yes from 0 to 1\n- The result is `{ output, model, usage }` with `output` keyed by question name, so a later step\n reads `results.triage.output.intent.choice`, `results.triage.output.urgency.score` or\n `results.triage.output.angry.noul > 0.7`\n- On `openai` the same `questions` are translated for its Decisions API and the answers read the\n same way (`choice`, `score`, `noul`), except that `probabilities` is a list of\n `{ value, probability }` (plus `label` on a score) and a score has no `legend`. A question OpenAI\n refuses to answer fails the step. A `state` that is\n an array of user messages (`[{ role: \"user\", content: [{ type: \"input_text\", text }, { type: \"input_image\", image_url: \"data:image/png;base64,...\" }] }]`)\n is sent as is, which is how an image is evaluated; any other object or array is sent as JSON text\n\n### Branching on the Answers\n\nTo route on the answers, put a `branchone` right after the decision, one branch per option, with\neach `expr` reading the decision by id:\n\n```json\n{\n \"id\": \"route\",\n \"value\": {\n \"type\": \"branchone\",\n \"branches\": [\n { \"summary\": \"refund\", \"expr\": \"results.triage.output.intent.choice === 'refund'\", \"modules\": [...] },\n { \"summary\": \"bug\", \"expr\": \"results.triage.output.intent.choice === 'bug'\", \"modules\": [...] }\n ],\n \"default\": [...]\n }\n}\n```\n\nFor a yes/no question, one branch with `\"expr\": \"results.triage.output.angry.noul >= 0.5\"` (tune the\nthreshold as needed) and the `default` as the \"no\" path.\n\n### As an Agent Tool\n\nAn `aidecision` can be a `flowmodule` tool of an `aiagent` (`\"tool_type\": \"flowmodule\", \"type\":\n\"aidecision\"`): set `state` to `{ \"type\": \"ai\" }` so the calling model supplies it, and only `output`\ngoes back to the model. The Tool Naming Rules apply to its `summary`. Only a flow's own agent step\ncan call one, not an agent used as a tool.\n\n## Common Mistakes to Avoid\n\n- Missing `input_transforms` - Rawscript parameters won't receive values without them\n- Referencing future steps - `results.step_id` only works for steps that execute before the current one\n- Duplicate module IDs - Each module ID must be unique in the flow\n- AI agent flowmodule tool names with spaces - `summary` is the tool name and only accepts letters, numbers and underscores\n\n## Data Flow Between Steps\n\n- `flow_input.property` - Access flow input parameters\n- `results.step_id` - Access output from a previous step only when that step result is in scope\n- `results.step_id.property` - Access specific property from a previous step output only when that step result is in scope\n- `flow_input.iter.value` - Current iteration value inside a `forloopflow`; in a `whileloopflow` it is just the iteration index (a plain number, same as `flow_input.iter.index`)\n- `flow_input.iter.index` - Current loop index when inside a loop (`forloopflow` or `whileloopflow`)\n- After a suspend step (approval), the next step's javascript expressions also get:\n - `resume` - the last resume payload (the resume form values); with `continue_on_disapprove_timeout`, a disapproval or timeout yields `{ error: { name: \"SuspendedDisapproved\" | \"SuspendedTimedOut\", message } }` instead\n - `resumes` - every resume payload, in arrival order\n - `approvers` - a plain array of strings, one per resume: for a resume through the `resume`/`cancel` URL from `getResumeUrls(approver)`, the `approver` passed there if any; otherwise (including the `approvalPage` link) the resuming user's username, else `\"anonymous\"`, e.g. `approvers[0]`. It is NOT the `{ resume_id, approver }` objects stored in the flow status, so `approvers[0].approver` is always undefined\n\n## Loop Structure Rules\n\n- A `forloopflow` runs its `modules` once per element of `iterator`, a javascript expression returning an array (e.g. `results.get_items`); `parallel: true` runs the iterations concurrently, and `skip_failures: true` carries on past a failed iteration\n- For `whileloopflow`, break the loop with a module-level `stop_after_if`: on the loop module itself, or on an inner step (required when that step carries state via its own `results` — see below)\n- `stop_after_if` is always a sibling of `id` and `value` on a flow module — never a direct key of the loop's `value` object\n- `stop_after_all_iters_if` is for checks after the whole loop finishes, not the normal per-iteration break condition\n- `stop_after_if` is evaluated after each iteration: on the loop module, `result` is that iteration's result (what its last step returned); on an inner step, it is that step's result\n- `flow_input.iter.value` in a `whileloopflow` is just the iteration index (same number as `flow_input.iter.index`) — it never carries state, so `flow_input.iter.value.` is always undefined and a loop whose stop condition depends on it never terminates\n- To carry state across iterations, a step reads its own previous-iteration result via `results.` with a first-iteration fallback (e.g. `results.b ?? flow_input.start`) — but then the loop's `stop_after_if` MUST sit on that inner step, not on the loop module: a body that is exactly one plain step with the stop condition on the loop module runs on a fast path where `results.` is null on every iteration and the loop never terminates (bodies with 2+ steps, or whose single step has its own `stop_after_if`, retry or similar, resolve `results` across iterations regardless of stop placement)\n- For state that is just a counter, derive it from the index instead (e.g. `flow_input.iter.index + 1`) — that works in every configuration, including with `stop_after_if` on the loop module\n- If the user asks for a final scalar/object after a loop, add a normal step after the loop that extracts the final value from the loop result instead of returning the whole loop result array\n\nCorrect `whileloopflow` shape:\n\n```yaml\n- id: loop_until_done\n stop_after_if:\n expr: result.done === true\n skip_if_stopped: false\n value:\n type: whileloopflow\n skip_failures: false\n modules:\n - id: advance_state\n value:\n type: rawscript\n input_transforms:\n count:\n type: javascript\n expr: flow_input.iter.index + 1\n- id: return_final_state\n value:\n type: rawscript\n input_transforms:\n final_state:\n type: javascript\n expr: results.loop_until_done[results.loop_until_done.length - 1]\n```\n\nCorrect `whileloopflow` shape carrying state via `results` (stop condition on the inner step):\n\n```yaml\n- id: loop_until_done\n value:\n type: whileloopflow\n skip_failures: false\n modules:\n - id: advance_state\n stop_after_if:\n expr: result.done === true\n skip_if_stopped: false\n value:\n type: rawscript\n input_transforms:\n state:\n type: javascript\n expr: results.advance_state ?? flow_input.initial_state\n```\n\nIncorrect `whileloopflow` patterns:\n\n```yaml\n- id: loop_until_done\n value:\n type: whileloopflow\n stop_after_if:\n expr: result.done === true\n```\n\n```yaml\ninput_transforms:\n state:\n type: javascript\n # iter.value is a number (the iteration index); there is no previous-iteration state\n expr: flow_input.iter.value.count\n```\n\n```yaml\ninput_transforms:\n final_state:\n type: javascript\n expr: results.loop_until_done\n```\n\n## Approval / Suspend Structure\n\nAn approval step is a normal **script** step (`type: rawscript` or `type: script`) that is turned into an approval by adding a module-level `suspend`. Its script calls `wmill.getResumeUrls(approver)` to generate the secret resume/cancel URLs and returns them so they can be sent to the approver(s) (Slack, email, etc.) or approved from the run page.\n\n- `suspend` belongs on the flow module object itself, as a sibling of `id` and `value`\n- Never put `suspend` inside `value`\n- Do NOT use `type: identity` for an approval step. An identity step suspends but never produces the resume URLs, so approvers have no link to act on — it is not a functional approval.\n\nCorrect shape:\n\n```yaml\n- id: request_approval\n suspend:\n required_events: 1\n resume_form:\n schema:\n type: object\n properties:\n comment:\n type: string\n required: [comment]\n value:\n type: rawscript\n language: bun\n input_transforms:\n approver:\n type: static\n value: ''\n content: |\n import * as wmill from \"windmill-client\"\n\n export async function main(approver?: string) {\n const urls = await wmill.getResumeUrls(approver)\n // send urls.resume / urls.cancel to the approver(s), e.g. via Slack or email\n return urls\n }\n```\n\nIncorrect shape (suspend misplaced inside `value`):\n\n```yaml\n- id: request_approval\n value:\n type: rawscript\n suspend:\n required_events: 1\n```\n\nIncorrect shape (identity has no resume URLs — not a real approval):\n\n```yaml\n- id: request_approval\n suspend:\n required_events: 1\n value:\n type: identity\n```\n\n## Branch Result Scope Rules\n\n- A `branchone` runs the first of its `branches` whose `expr` is true, in order, and its `default` modules when none is; a `branchall` runs every branch (concurrently with `parallel: true`)\n- Inside a branch, you may reference earlier outer steps and earlier steps in the same branch\n- Outside a `branchone`, do NOT reference ids of steps that only exist inside its branches or default branch. Use `results.` instead\n- Outside a `branchall`, do NOT reference ids of steps inside its branches. Use `results.` instead\n- If downstream steps need a stable shape after a branch, make each branch return the same fields\n- When needed, add a normalization step immediately after the branch and consume `results.` there\n\nCorrect after `branchone`:\n\n```yaml\n- id: route_order\n value:\n type: branchone\n ...\n- id: send_confirmation\n value:\n input_transforms:\n routed:\n type: javascript\n expr: results.route_order\n```\n\nIncorrect after `branchone`:\n\n```yaml\nexpr: results.create_shipment\nexpr: results.create_backorder\n```\n\nCorrect after `branchall`:\n\n```yaml\n- id: enrich_parallel\n value:\n type: branchall\n parallel: true\n ...\n- id: combine_data\n value:\n input_transforms:\n enrichments:\n type: javascript\n expr: results.enrich_parallel\n```\n\n## Input Transforms\n\nEvery rawscript module needs `input_transforms` to map function parameters to values:\n\nStatic transform (fixed value):\n{\"param_name\": {\"type\": \"static\", \"value\": \"fixed_string\"}}\n\nJavaScript transform (dynamic expression):\n{\"param_name\": {\"type\": \"javascript\", \"expr\": \"results.previous_step.data\"}}\n\n## Resource References\n\n- For flow inputs: Use type `\"object\"` with format `\"resource-{type}\"` (e.g., `\"resource-postgresql\"`)\n- For step inputs: Use static value `\"$res:path/to/resource\"`\n\n## Reusing Existing Scripts and Flows\n\nUnless the user asked for new code, look for a workspace script or flow that already does a step's job before writing it, and reuse it by path instead of copying its logic into a rawscript:\n\n- a workspace script: `type: script` with `path` (e.g. `f/folder/send_email`)\n- a workspace flow, run as a subflow: `type: flow` with `path`\n- a Hub script: `type: script` with a `hub///` path\n\nThe step's `input_transforms` must cover the reused item's inputs, so read its input schema first.\n\n## Additional Prompt for AI\n\nA flow's input schema may carry a top-level `prompt_for_ai` string, as a script's can: its author's instructions to an AI choosing the inputs. Follow it when you pick arguments to run that flow, and keep it when you rewrite the schema.\n\n## Organizing Flows: Groups and Notes\n\nGroups and notes shape how a flow reads in the editor; neither changes what it does.\n\n**Segment every non-trivial flow into groups without waiting to be asked.** Whenever a flow has more than a couple of steps, or consecutive steps form a stage (\"fetch\", \"transform\", \"notify\"), put them in a group, and aim for every meaningful step to belong to one. Use notes sparingly, for flow-wide information that belongs to no span of steps: the flow's purpose, key assumptions, warnings, TODOs. One note is usually enough; never label a run of steps with a note, which is what a group is for.\n\n`value.groups` lists the groups, each spanning the steps from `start_id` to `end_id`:\n\n- `start_id`, `end_id` (required): ids of the group's first and last step; the same id for both makes a one-step group\n- `summary`: the group's title\n- `note`: markdown shown under the title\n- `color`: one of `yellow`, `blue`, `green`, `purple`, `pink`, `orange`, `red`, `cyan`, `lime`, `gray`, never a hex code or CSS color; leave it out and the editor picks one\n- `autocollapse`: `true` shows the group collapsed by default\n\nThe editor refuses to draw a flow whose groups break any of these rules:\n\n- `start_id` and `end_id` are steps of the same list: both top-level, or both in the same loop body or branch. A group can hold a loop or branch step whole, but cannot start outside one and end inside it\n- `start_id` does not come after `end_id` in that list\n- groups nest (one entirely inside another) but never partly overlap, and no two groups share both `start_id` and `end_id`\n- groups hold ordinary steps only: never `preprocessor`, `failure`, `Input`, `Result`, `Trigger`, or an AI agent's tools\n\n`value.notes` lists sticky notes, each with a unique `id`, markdown `text`, a `color` from the same list, and `type: free`. The `group` note type is deprecated; use `value.groups` instead.\nLeave a note's `position` and `size` out and they are filled in for you.\n\n## Final Structural Self-Check\n\nBefore finalizing a flow, verify:\n\n- any preprocessor is in `value.preprocessor_module`\n- any failure handler is in `value.failure_module`\n- any approval step has module-level `suspend`\n- no downstream step references inner branch step ids from outside the branch\n- every AI agent flowmodule tool has a unique `summary` made only of letters, numbers and underscores\n- every group starts and ends on steps of the same list, start before end, nesting without partial overlap\n\n## S3 Object Operations\n\nWindmill provides built-in support for S3-compatible storage operations.\n\nTo accept an S3 object as flow input:\n\n```json\n{\n \"type\": \"object\",\n \"properties\": {\n \"file\": {\n \"type\": \"object\",\n \"format\": \"resource-s3_object\",\n \"description\": \"File to process\"\n }\n }\n}\n```\n\n## Using Resources in Flows\n\nOn Windmill, credentials and configuration are stored in resources. Resource types define the format of the resource.\n\n### As Flow Input\n\nIn the flow schema, set the property type to `\"object\"` with format `\"resource-{type}\"`:\n\n```json\n{\n \"type\": \"object\",\n \"properties\": {\n \"database\": {\n \"type\": \"object\",\n \"format\": \"resource-postgresql\",\n \"description\": \"Database connection\"\n }\n }\n}\n```\n\n### When No Resource Type Fits\n\nA connection still comes in as one resource input, not as separate string inputs (a URL, a token) or a variable read inside a step: type the input `resource-c_` with a custom resource type holding the service's connection fields, its secret in a variable the resource references. The `c_` prefix of custom types keeps one apart from a hub type synced later under the same name.\n\n- If the instance is reported as not having synced the Windmill Hub's resource types, mention that a superadmin can sync them, since the hub has types for most services.\n- Otherwise, or when the user prefers it to syncing, propose the resource type and ask before creating it.\n- A plain variable is fine when the user asks for it.\n\n### As Step Input (Static Reference)\n\nReference a specific resource using `$res:` prefix:\n\n```json\n{\n \"database\": {\n \"type\": \"static\",\n \"value\": \"$res:f/folder/my_database\"\n }\n}\n```\n\n\n## OpenFlow Schema\n\n{\"OpenFlow\":{\"type\":\"object\",\"description\":\"Top-level flow definition containing metadata, configuration, and the flow structure\",\"properties\":{\"summary\":{\"type\":\"string\",\"description\":\"Short description of what this flow does\"},\"description\":{\"type\":\"string\",\"description\":\"Detailed documentation for this flow\"},\"value\":{\"$ref\":\"#/components/schemas/FlowValue\"},\"schema\":{\"type\":\"object\",\"description\":\"JSON Schema for flow inputs. Use this to define input parameters, their types, defaults, and validation. For resource inputs, set type to 'object' and format to 'resource-' (e.g., 'resource-stripe')\"},\"on_behalf_of_email\":{\"type\":\"string\",\"description\":\"Address of the account the flow runs on behalf of. Derived from on_behalf_of on read; accepted on write, where it is resolved to the account it names.\"},\"on_behalf_of\":{\"type\":\"string\",\"description\":\"The flow runs with the permissions of this identity: u/{username}, g/{group}, or a bare email when the username is itself email-shaped. The only stored half of the identity; on_behalf_of_email is derived from it. Omit it when writing and it is resolved from that address instead.\"}},\"required\":[\"summary\",\"value\"]},\"FlowValue\":{\"type\":\"object\",\"description\":\"The flow structure containing modules and optional preprocessor/failure handlers\",\"properties\":{\"modules\":{\"type\":\"array\",\"description\":\"Array of steps that execute in sequence. Each step can be a script, subflow, loop, or branch\",\"items\":{\"$ref\":\"#/components/schemas/FlowModule\"}},\"failure_module\":{\"description\":\"Special module that executes when the flow fails. Receives error object with message, name, stack, and step_id. Must have id 'failure'. Only supports script/rawscript types\",\"$ref\":\"#/components/schemas/FlowModule\"},\"preprocessor_module\":{\"description\":\"Special module that runs before the first step on external triggers. Must have id 'preprocessor'. Only supports script/rawscript types. Cannot reference other step results\",\"$ref\":\"#/components/schemas/FlowModule\"},\"same_worker\":{\"type\":\"boolean\",\"description\":\"If true, all steps run on the same worker for better performance\"},\"preserve_step_tags\":{\"type\":\"boolean\",\"description\":\"If true and the flow runs on a custom worker tag, steps that declare their own non-empty tag run on it instead of inheriting the flow tag. Steps without their own tag still inherit the flow tag.\"},\"concurrent_limit\":{\"type\":\"number\",\"description\":\"Maximum number of concurrent executions of this flow\"},\"concurrency_key\":{\"type\":\"string\",\"description\":\"Expression to group concurrent executions (e.g., by user ID)\"},\"concurrency_time_window_s\":{\"type\":\"number\",\"description\":\"Time window in seconds for concurrent_limit\"},\"debounce_delay_s\":{\"type\":\"integer\",\"description\":\"Delay in seconds to debounce flow executions\"},\"debounce_key\":{\"type\":\"string\",\"description\":\"Expression to group debounced executions\"},\"debounce_args_to_accumulate\":{\"type\":\"array\",\"description\":\"Arguments to accumulate across debounced executions\",\"items\":{\"type\":\"string\"}},\"max_total_debouncing_time\":{\"type\":\"integer\",\"description\":\"Maximum total time in seconds that a job can be debounced\"},\"max_total_debounces_amount\":{\"type\":\"integer\",\"description\":\"Maximum number of times a job can be debounced\"},\"skip_expr\":{\"type\":\"string\",\"description\":\"JavaScript expression to conditionally skip the entire flow\"},\"cache_ttl\":{\"type\":\"number\",\"description\":\"Cache duration in seconds for flow results\"},\"cache_ignore_s3_path\":{\"type\":\"boolean\"},\"delete_after_secs\":{\"type\":\"integer\",\"description\":\"If set, delete the flow job's args, result and logs after this many seconds following job completion\"},\"flow_env\":{\"type\":\"object\",\"description\":\"Environment variables available to all steps. Values can be strings, JSON values, or special references: '$var:path' (workspace variable) or '$res:path' (resource).\",\"additionalProperties\":{}},\"priority\":{\"type\":\"number\",\"description\":\"Execution priority (higher numbers run first)\"},\"early_return\":{\"type\":\"string\",\"description\":\"Id of the step whose result a sync webhook returns as soon as that step completes, while the rest of the flow keeps running. When the step does not run, or fails while the flow has a failure module, the flow's final result is returned instead.\"},\"chat_input_enabled\":{\"type\":\"boolean\",\"description\":\"Whether this flow accepts chat-style input\"},\"notes\":{\"type\":\"array\",\"description\":\"Sticky notes attached to the flow\",\"items\":{\"$ref\":\"#/components/schemas/FlowNote\"}},\"groups\":{\"type\":\"array\",\"description\":\"Semantic groups of modules for organizational purposes\",\"items\":{\"$ref\":\"#/components/schemas/FlowGroup\"}}},\"required\":[\"modules\"]},\"Retry\":{\"type\":\"object\",\"description\":\"Retry configuration for failed module executions\",\"properties\":{\"constant\":{\"type\":\"object\",\"description\":\"Retry with constant delay between attempts\",\"properties\":{\"attempts\":{\"type\":\"integer\",\"description\":\"Number of retry attempts\"},\"seconds\":{\"type\":\"integer\",\"description\":\"Seconds to wait between retries\"}}},\"exponential\":{\"type\":\"object\",\"description\":\"Retry with exponential backoff: the n-th retry waits multiplier \\u00d7 seconds^n\",\"properties\":{\"attempts\":{\"type\":\"integer\",\"description\":\"Number of retry attempts\"},\"multiplier\":{\"type\":\"integer\",\"description\":\"Multiplier for exponential backoff\"},\"seconds\":{\"type\":\"integer\",\"minimum\":1,\"description\":\"Base of the exponential (seconds); the n-th retry waits multiplier \\u00d7 seconds^n, where n counts constant retries too\"},\"random_factor\":{\"type\":\"integer\",\"minimum\":0,\"maximum\":100,\"description\":\"Random jitter percentage (0-100) to avoid thundering herd\"}}},\"retry_if\":{\"$ref\":\"#/components/schemas/RetryIf\"}}},\"FlowNote\":{\"type\":\"object\",\"description\":\"A sticky note attached to a flow for documentation and annotation\",\"properties\":{\"id\":{\"type\":\"string\",\"description\":\"Unique identifier for the note\"},\"text\":{\"type\":\"string\",\"description\":\"Content of the note\"},\"position\":{\"type\":\"object\",\"description\":\"Position of the note in the flow editor\",\"properties\":{\"x\":{\"type\":\"number\",\"description\":\"X coordinate\"},\"y\":{\"type\":\"number\",\"description\":\"Y coordinate\"}},\"required\":[\"x\",\"y\"]},\"size\":{\"type\":\"object\",\"description\":\"Size of the note in the flow editor\",\"properties\":{\"width\":{\"type\":\"number\",\"description\":\"Width in pixels\"},\"height\":{\"type\":\"number\",\"description\":\"Height in pixels\"}},\"required\":[\"width\",\"height\"]},\"color\":{\"type\":\"string\",\"description\":\"Color of the note, one of: yellow, blue, green, purple, pink, orange, red, cyan, lime, gray. Any other value renders unstyled.\"},\"type\":{\"type\":\"string\",\"enum\":[\"free\",\"group\"],\"description\":\"Type of note - 'free' for standalone notes. 'group' notes are deprecated; segment a flow with FlowValue.groups instead.\"},\"locked\":{\"type\":\"boolean\",\"default\":false,\"description\":\"Whether the note is locked and cannot be edited or moved\"},\"contained_node_ids\":{\"type\":\"array\",\"items\":{\"type\":\"string\"},\"description\":\"For group notes, the IDs of nodes contained within this group\"}},\"required\":[\"id\",\"text\",\"color\",\"type\"]},\"FlowGroup\":{\"type\":\"object\",\"description\":\"A semantic group of flow modules for organizational purposes. Does not affect execution \\u2014 modules remain in their original position in the flow. Groups provide naming and collapsibility in the editor. Members are computed dynamically from all nodes on paths between start_id and end_id.\",\"properties\":{\"summary\":{\"type\":\"string\",\"description\":\"Display name for this group\"},\"note\":{\"type\":\"string\",\"description\":\"Markdown note shown below the group header\"},\"autocollapse\":{\"type\":\"boolean\",\"default\":false,\"description\":\"If true, this group is collapsed by default in the flow editor. UI hint only.\"},\"start_id\":{\"type\":\"string\",\"description\":\"ID of the first flow module in this group (topological entry point)\"},\"end_id\":{\"type\":\"string\",\"description\":\"ID of the last flow module in this group (topological exit point)\"},\"color\":{\"type\":\"string\",\"description\":\"Color for the group in the flow editor, one of: yellow, blue, green, purple, pink, orange, red, cyan, lime, gray. Omit it to let the editor pick one.\"}},\"required\":[\"start_id\",\"end_id\"]},\"RetryIf\":{\"type\":\"object\",\"description\":\"Conditional retry based on error or result\",\"properties\":{\"expr\":{\"type\":\"string\",\"description\":\"JavaScript expression that returns true to retry. Has access to 'result' and 'error' variables\"}},\"required\":[\"expr\"]},\"StopAfterIf\":{\"type\":\"object\",\"description\":\"Early termination condition for a module\",\"properties\":{\"skip_if_stopped\":{\"type\":\"boolean\",\"description\":\"If true, following steps are skipped when this condition triggers\"},\"expr\":{\"type\":\"string\",\"description\":\"JavaScript expression evaluated after the module runs. Can use 'result' (step's result) or 'flow_input'. Return true to stop\"},\"error_message\":{\"type\":\"string\",\"nullable\":true,\"description\":\"Custom error message when stopping with an error. Mutually exclusive with skip_if_stopped. If set to a non-empty string, the flow stops with this error. If empty string, a default error message is used. If null or omitted, no error is raised.\"},\"error_include_result\":{\"type\":\"boolean\",\"description\":\"When stopping with an error (error_message set), embed the stopping step's own result inside the raised error object (as error.result) instead of discarding it. The top-level result stays { error }. Defaults to false.\"}},\"required\":[\"expr\"]},\"FlowModule\":{\"type\":\"object\",\"description\":\"A single step in a flow. Can be a script, subflow, loop, or branch\",\"properties\":{\"id\":{\"type\":\"string\",\"description\":\"Unique identifier for this step. Used to reference results via 'results.step_id'. Must be a valid identifier (alphanumeric, underscore, hyphen)\"},\"value\":{\"$ref\":\"#/components/schemas/FlowModuleValue\"},\"stop_after_if\":{\"description\":\"Early termination condition evaluated after this step completes\",\"$ref\":\"#/components/schemas/StopAfterIf\"},\"stop_after_all_iters_if\":{\"description\":\"For loops only - early termination condition evaluated after all iterations complete\",\"$ref\":\"#/components/schemas/StopAfterIf\"},\"skip_if\":{\"type\":\"object\",\"description\":\"Conditionally skip this step based on previous results or flow inputs\",\"properties\":{\"expr\":{\"type\":\"string\",\"description\":\"JavaScript expression that returns true to skip. Can use 'flow_input' or 'results.'\"}},\"required\":[\"expr\"]},\"sleep\":{\"description\":\"Delay before executing this step (in seconds or as expression)\",\"$ref\":\"#/components/schemas/InputTransform\"},\"cache_ttl\":{\"type\":\"number\",\"description\":\"Cache duration in seconds for this step's results\"},\"cache_ignore_s3_path\":{\"type\":\"boolean\"},\"timeout\":{\"description\":\"Maximum execution time in seconds (static value or expression)\",\"$ref\":\"#/components/schemas/InputTransform\"},\"delete_after_secs\":{\"type\":\"integer\",\"description\":\"If set, delete the step's args, result and logs after this many seconds following job completion\"},\"summary\":{\"type\":\"string\",\"description\":\"Short description of what this step does\"},\"mock\":{\"type\":\"object\",\"description\":\"Mock configuration for testing without executing the actual step\",\"properties\":{\"enabled\":{\"type\":\"boolean\",\"description\":\"If true, return mock value instead of executing\"},\"return_value\":{\"description\":\"Value to return when mocked\"}}},\"suspend\":{\"type\":\"object\",\"description\":\"Configuration for approval/resume steps that wait for user input\",\"properties\":{\"required_events\":{\"type\":\"integer\",\"description\":\"Number of approvals required before continuing\"},\"timeout\":{\"type\":\"integer\",\"description\":\"Timeout in seconds before auto-continuing or canceling\"},\"resume_form\":{\"type\":\"object\",\"description\":\"Form schema for collecting input when resuming\",\"properties\":{\"schema\":{\"type\":\"object\",\"description\":\"JSON Schema for the resume form\"}}},\"user_auth_required\":{\"type\":\"boolean\",\"description\":\"If true, only authenticated users can approve\"},\"user_groups_required\":{\"description\":\"Expression or list of groups that can approve\",\"$ref\":\"#/components/schemas/InputTransform\"},\"self_approval_disabled\":{\"type\":\"boolean\",\"description\":\"If true, the user who started the flow cannot approve\"},\"hide_cancel\":{\"type\":\"boolean\",\"description\":\"If true, hide the cancel button on the approval form\"},\"continue_on_disapprove_timeout\":{\"type\":\"boolean\",\"description\":\"If true, continue flow on timeout instead of canceling\"},\"skin\":{\"type\":\"string\",\"enum\":[\"detailed\",\"minimal\"],\"description\":\"How the approval request is presented, on the approval page and in Slack/Teams approval messages. 'detailed' (used when unset) shows the flow details (arguments, graph, approvers); 'minimal' shows only the request: the step description, form and approve/reject actions\"}}},\"priority\":{\"type\":\"number\",\"description\":\"Execution priority for this step (higher numbers run first)\"},\"continue_on_error\":{\"type\":\"boolean\",\"description\":\"If true, flow continues even if this step fails\"},\"job_token_scopes\":{\"type\":\"array\",\"nullable\":true,\"items\":{\"type\":\"string\"},\"description\":\"Scopes the token of this step's jobs is restricted to (domain:action[:resource], e.g. oidc:write), on top of the flow's own restriction: a step can only narrow it. Applies to everything the step runs (loop and branch bodies, AI agent tools).\"},\"retry\":{\"description\":\"Retry configuration if this step fails\",\"$ref\":\"#/components/schemas/Retry\"},\"debouncing\":{\"description\":\"Debounce configuration for this step (EE only)\",\"type\":\"object\",\"properties\":{\"debounce_delay_s\":{\"type\":\"integer\",\"description\":\"Delay in seconds to debounce this step's executions across flow runs\"},\"debounce_key\":{\"type\":\"string\",\"description\":\"Expression to group debounced executions. Supports $workspace and $args[name]. Default: $workspace/flow/-\"},\"debounce_args_to_accumulate\":{\"type\":\"array\",\"description\":\"Array-type arguments to accumulate across debounced executions\",\"items\":{\"type\":\"string\"}},\"max_total_debouncing_time\":{\"type\":\"integer\",\"description\":\"Maximum total time in seconds before forced execution\"},\"max_total_debounces_amount\":{\"type\":\"integer\",\"description\":\"Maximum number of debounces before forced execution\"}}}},\"required\":[\"value\",\"id\"]},\"InputTransform\":{\"description\":\"Maps input parameters for a step. Can be a static value or a JavaScript expression that references previous results or flow inputs\",\"oneOf\":[{\"$ref\":\"#/components/schemas/StaticTransform\"},{\"$ref\":\"#/components/schemas/JavascriptTransform\"},{\"$ref\":\"#/components/schemas/AiTransform\"}],\"discriminator\":{\"propertyName\":\"type\",\"mapping\":{\"static\":\"#/components/schemas/StaticTransform\",\"javascript\":\"#/components/schemas/JavascriptTransform\",\"ai\":\"#/components/schemas/AiTransform\"}}},\"StaticTransform\":{\"type\":\"object\",\"description\":\"Static value passed directly to the step. Use for hardcoded values or resource references like '$res:path/to/resource'\",\"properties\":{\"value\":{\"description\":\"The static value. For resources, use format '$res:path/to/resource'\"},\"type\":{\"type\":\"string\",\"enum\":[\"static\"]}},\"required\":[\"type\"]},\"JavascriptTransform\":{\"type\":\"object\",\"description\":\"JavaScript expression evaluated at runtime. Can reference previous step results via 'results.step_id' or flow inputs via 'flow_input.property'. Inside for loops, use 'flow_input.iter.value' for the current iteration value (in while loops it equals 'flow_input.iter.index')\",\"properties\":{\"expr\":{\"type\":\"string\",\"description\":\"JavaScript expression returning the value. Available variables - results (object with all previous step results), flow_input (flow inputs), flow_input.iter (in loops)\"},\"type\":{\"type\":\"string\",\"enum\":[\"javascript\"]}},\"required\":[\"expr\",\"type\"]},\"AiTransform\":{\"type\":\"object\",\"description\":\"Value resolved by the AI runtime for this input. The AI engine decides how to satisfy the parameter.\",\"properties\":{\"type\":{\"type\":\"string\",\"enum\":[\"ai\"]}},\"required\":[\"type\"]},\"AIProviderKind\":{\"type\":\"string\",\"description\":\"Supported AI provider types\",\"enum\":[\"openai\",\"azure_openai\",\"azure_foundry\",\"anthropic\",\"mistral\",\"deepseek\",\"googleai\",\"groq\",\"openrouter\",\"togetherai\",\"customai\",\"aws_bedrock\",\"typesafe\",\"cloudflare\"]},\"ProviderConfig\":{\"type\":\"object\",\"description\":\"Complete AI provider configuration with resource reference and model selection\",\"properties\":{\"kind\":{\"$ref\":\"#/components/schemas/AIProviderKind\"},\"resource\":{\"type\":\"string\",\"description\":\"Resource reference in format '$res:{resource_path}' pointing to provider credentials\"},\"model\":{\"type\":\"string\",\"description\":\"Model identifier (e.g., 'gpt-4', 'claude-3-opus-20240229', 'gemini-pro')\"},\"reasoning_effort\":{\"type\":\"string\",\"description\":\"Provider-native reasoning effort token (e.g. 'low', 'high', 'none') for models that support extended thinking. Optional; unset leaves the provider default.\"}},\"required\":[\"kind\",\"resource\",\"model\"]},\"StaticProviderTransform\":{\"type\":\"object\",\"description\":\"Static provider configuration passed directly to the AI agent\",\"properties\":{\"value\":{\"$ref\":\"#/components/schemas/ProviderConfig\"},\"type\":{\"type\":\"string\",\"enum\":[\"static\"]}},\"required\":[\"type\",\"value\"]},\"ProviderTransform\":{\"description\":\"Provider configuration - can be static (ProviderConfig), JavaScript expression, or AI-determined\",\"oneOf\":[{\"$ref\":\"#/components/schemas/StaticProviderTransform\"},{\"$ref\":\"#/components/schemas/JavascriptTransform\"},{\"$ref\":\"#/components/schemas/AiTransform\"}],\"discriminator\":{\"propertyName\":\"type\",\"mapping\":{\"static\":\"#/components/schemas/StaticProviderTransform\",\"javascript\":\"#/components/schemas/JavascriptTransform\",\"ai\":\"#/components/schemas/AiTransform\"}}},\"MemoryOff\":{\"type\":\"object\",\"description\":\"No conversation memory/context\",\"properties\":{\"kind\":{\"type\":\"string\",\"enum\":[\"off\"]}},\"required\":[\"kind\"]},\"MemoryWindow\":{\"type\":\"object\",\"description\":\"Keeps the most recent messages of the memory named by the run's memory id (or the step's\\n`memory_id`). Without a memory id the agent runs without memory.\\n\",\"properties\":{\"kind\":{\"type\":\"string\",\"enum\":[\"window\"]},\"context_length\":{\"type\":\"integer\",\"description\":\"Number of most recent messages to load and store. 0 turns memory off.\"}},\"required\":[\"kind\",\"context_length\"]},\"MemoryAuto\":{\"type\":\"object\",\"deprecated\":true,\"description\":\"Deprecated, still read as it was written: the run's memory id, else the `memory_id` here.\\nThe step's own `memory_id` is not read while this kind is set; switch the kind to `window`\\nto use it. Without a `context_length`, or with 0, it is `off` and reads `previous_messages`.\\n\",\"properties\":{\"kind\":{\"type\":\"string\",\"enum\":[\"auto\"]},\"context_length\":{\"type\":\"integer\",\"description\":\"Maximum number of messages to retain in context\"},\"memory_id\":{\"type\":\"string\",\"description\":\"Identifier for persistent memory across agent invocations\"}},\"required\":[\"kind\"]},\"MemoryCompaction\":{\"type\":\"object\",\"description\":\"Keeps the whole memory named by the run's memory id (or the step's `memory_id`), replacing\\nits older part with a summary as the conversation approaches the model's context window.\\nWithout a memory id the agent runs without memory, and compaction bounds the run's own loop.\\n\",\"properties\":{\"kind\":{\"type\":\"string\",\"enum\":[\"compaction\"]},\"context_window\":{\"type\":\"integer\",\"description\":\"Overrides the context window looked up from the model, in tokens. Only a model\\nWindmill does not know needs one; those fall back to 128000.\\n\"}},\"required\":[\"kind\"]},\"MemoryMessage\":{\"type\":\"object\",\"description\":\"A single message in conversation history\",\"properties\":{\"role\":{\"type\":\"string\",\"enum\":[\"user\",\"assistant\",\"system\"]},\"content\":{\"type\":\"string\"}},\"required\":[\"role\",\"content\"]},\"MemoryManual\":{\"type\":\"object\",\"deprecated\":true,\"description\":\"Deprecated, still read as it was written. Move the step to `off` with `previous_messages` instead.\",\"properties\":{\"kind\":{\"type\":\"string\",\"enum\":[\"manual\"]},\"messages\":{\"type\":\"array\",\"items\":{\"$ref\":\"#/components/schemas/MemoryMessage\"}}},\"required\":[\"kind\",\"messages\"]},\"MemoryConfig\":{\"description\":\"Managed memory, stored by Windmill and replayed with each request. The memory is named by a memory id, see `memory_id`. While it is off, a step can supply its history in `previous_messages`.\",\"oneOf\":[{\"$ref\":\"#/components/schemas/MemoryOff\"},{\"$ref\":\"#/components/schemas/MemoryWindow\"},{\"$ref\":\"#/components/schemas/MemoryCompaction\"},{\"$ref\":\"#/components/schemas/MemoryAuto\"},{\"$ref\":\"#/components/schemas/MemoryManual\"}],\"discriminator\":{\"propertyName\":\"kind\",\"mapping\":{\"off\":\"#/components/schemas/MemoryOff\",\"window\":\"#/components/schemas/MemoryWindow\",\"compaction\":\"#/components/schemas/MemoryCompaction\",\"auto\":\"#/components/schemas/MemoryAuto\",\"manual\":\"#/components/schemas/MemoryManual\"}}},\"StaticMemoryTransform\":{\"type\":\"object\",\"description\":\"Static memory configuration passed directly to the AI agent\",\"properties\":{\"value\":{\"$ref\":\"#/components/schemas/MemoryConfig\"},\"type\":{\"type\":\"string\",\"enum\":[\"static\"]}},\"required\":[\"type\",\"value\"]},\"MemoryTransform\":{\"description\":\"Memory configuration - can be static (MemoryConfig), JavaScript expression, or AI-determined\",\"oneOf\":[{\"$ref\":\"#/components/schemas/StaticMemoryTransform\"},{\"$ref\":\"#/components/schemas/JavascriptTransform\"},{\"$ref\":\"#/components/schemas/AiTransform\"}],\"discriminator\":{\"propertyName\":\"type\",\"mapping\":{\"static\":\"#/components/schemas/StaticMemoryTransform\",\"javascript\":\"#/components/schemas/JavascriptTransform\",\"ai\":\"#/components/schemas/AiTransform\"}}},\"FlowModuleValue\":{\"description\":\"The actual implementation of a flow step. Can be a script (inline or referenced), subflow, loop, branch, or special module type\",\"oneOf\":[{\"$ref\":\"#/components/schemas/RawScript\"},{\"$ref\":\"#/components/schemas/PathScript\"},{\"$ref\":\"#/components/schemas/PathFlow\"},{\"$ref\":\"#/components/schemas/ForloopFlow\"},{\"$ref\":\"#/components/schemas/WhileloopFlow\"},{\"$ref\":\"#/components/schemas/BranchOne\"},{\"$ref\":\"#/components/schemas/BranchAll\"},{\"$ref\":\"#/components/schemas/Identity\"},{\"$ref\":\"#/components/schemas/AiAgent\"},{\"$ref\":\"#/components/schemas/AiDecision\"}],\"discriminator\":{\"propertyName\":\"type\",\"mapping\":{\"rawscript\":\"#/components/schemas/RawScript\",\"script\":\"#/components/schemas/PathScript\",\"flow\":\"#/components/schemas/PathFlow\",\"forloopflow\":\"#/components/schemas/ForloopFlow\",\"whileloopflow\":\"#/components/schemas/WhileloopFlow\",\"branchone\":\"#/components/schemas/BranchOne\",\"branchall\":\"#/components/schemas/BranchAll\",\"identity\":\"#/components/schemas/Identity\",\"aiagent\":\"#/components/schemas/AiAgent\",\"aidecision\":\"#/components/schemas/AiDecision\"}}},\"RawScript\":{\"type\":\"object\",\"description\":\"Inline script with code defined directly in the flow. Use 'bun' as default language if unspecified. The script receives arguments from input_transforms\",\"properties\":{\"input_transforms\":{\"type\":\"object\",\"description\":\"Map of parameter names to their values (static or JavaScript expressions). These become the script's input arguments\",\"additionalProperties\":{\"$ref\":\"#/components/schemas/InputTransform\"}},\"content\":{\"type\":\"string\",\"description\":\"The script source code. Should export a 'main' function\"},\"language\":{\"type\":\"string\",\"description\":\"Programming language for this script\",\"enum\":[\"deno\",\"bun\",\"bunnative\",\"python3\",\"go\",\"bash\",\"powershell\",\"postgresql\",\"mysql\",\"bigquery\",\"snowflake\",\"mssql\",\"oracledb\",\"graphql\",\"nativets\",\"php\",\"rust\",\"ansible\",\"csharp\",\"nu\",\"java\",\"ruby\",\"rlang\",\"duckdb\"]},\"path\":{\"type\":\"string\",\"description\":\"Optional path for saving this script\"},\"lock\":{\"type\":\"string\",\"description\":\"Lock file content for dependencies\"},\"type\":{\"type\":\"string\",\"enum\":[\"rawscript\"]},\"tag\":{\"type\":\"string\",\"description\":\"Worker group tag for execution routing\"},\"concurrent_limit\":{\"type\":\"number\",\"description\":\"Maximum concurrent executions of this script\"},\"concurrency_time_window_s\":{\"type\":\"number\",\"description\":\"Time window for concurrent_limit\"},\"custom_concurrency_key\":{\"type\":\"string\",\"description\":\"Custom key for grouping concurrent executions\"},\"is_trigger\":{\"type\":\"boolean\",\"description\":\"If true, this script is a trigger that can start the flow\"},\"assets\":{\"type\":\"array\",\"description\":\"External resources this script accesses (S3 objects, resources, etc.)\",\"items\":{\"type\":\"object\",\"required\":[\"path\",\"kind\"],\"properties\":{\"path\":{\"type\":\"string\",\"description\":\"Path to the asset\"},\"kind\":{\"type\":\"string\",\"description\":\"Type of asset\",\"enum\":[\"s3object\",\"resource\",\"ducklake\",\"datatable\",\"volume\",\"dbt\"]},\"access_type\":{\"type\":\"string\",\"nullable\":true,\"description\":\"Access level for this asset\",\"enum\":[\"r\",\"w\",\"rw\"]},\"alt_access_type\":{\"type\":\"string\",\"nullable\":true,\"description\":\"Alternative access level\",\"enum\":[\"r\",\"w\",\"rw\"]}}}}},\"required\":[\"type\",\"content\",\"language\",\"input_transforms\"]},\"PathScript\":{\"type\":\"object\",\"description\":\"Reference to an existing script by path. Use this when calling a previously saved script instead of writing inline code\",\"properties\":{\"input_transforms\":{\"type\":\"object\",\"description\":\"Map of parameter names to their values (static or JavaScript expressions). These become the script's input arguments\",\"additionalProperties\":{\"$ref\":\"#/components/schemas/InputTransform\"}},\"path\":{\"type\":\"string\",\"description\":\"Path to the script in the workspace (e.g., 'f/scripts/send_email')\"},\"hash\":{\"type\":\"string\",\"description\":\"Optional specific version hash of the script to use\"},\"type\":{\"type\":\"string\",\"enum\":[\"script\"]},\"tag_override\":{\"type\":\"string\",\"description\":\"Override the script's default worker group tag\"},\"is_trigger\":{\"type\":\"boolean\",\"description\":\"If true, this script is a trigger that can start the flow\"}},\"required\":[\"type\",\"path\",\"input_transforms\"]},\"PathFlow\":{\"type\":\"object\",\"description\":\"Reference to an existing flow by path. Use this to call another flow as a subflow\",\"properties\":{\"input_transforms\":{\"type\":\"object\",\"description\":\"Map of parameter names to their values (static or JavaScript expressions). These become the subflow's input arguments\",\"additionalProperties\":{\"$ref\":\"#/components/schemas/InputTransform\"}},\"path\":{\"type\":\"string\",\"description\":\"Path to the flow in the workspace (e.g., 'f/flows/process_user')\"},\"type\":{\"type\":\"string\",\"enum\":[\"flow\"]}},\"required\":[\"type\",\"path\",\"input_transforms\"]},\"ForloopFlow\":{\"type\":\"object\",\"description\":\"Executes nested modules in a loop over an iterator. Inside the loop, use 'flow_input.iter.value' to access the current iteration value, and 'flow_input.iter.index' for the index. Supports parallel execution for better performance on I/O-bound operations\",\"properties\":{\"modules\":{\"type\":\"array\",\"description\":\"Steps to execute for each iteration. These can reference the iteration value via 'flow_input.iter.value'\",\"items\":{\"$ref\":\"#/components/schemas/FlowModule\"}},\"iterator\":{\"description\":\"JavaScript expression that returns an array to iterate over. Can reference 'results.step_id' or 'flow_input'\",\"$ref\":\"#/components/schemas/InputTransform\"},\"skip_failures\":{\"type\":\"boolean\",\"description\":\"If true, iteration failures don't stop the loop. Failed iterations return null\"},\"type\":{\"type\":\"string\",\"enum\":[\"forloopflow\"]},\"parallel\":{\"type\":\"boolean\",\"description\":\"If true, iterations run concurrently (faster for I/O-bound operations). Use with parallelism to control concurrency\"},\"parallelism\":{\"description\":\"Maximum number of concurrent iterations when parallel=true. Limits resource usage. Can be static number or expression\",\"$ref\":\"#/components/schemas/InputTransform\"},\"squash\":{\"type\":\"boolean\"}},\"required\":[\"modules\",\"iterator\",\"skip_failures\",\"type\"]},\"WhileloopFlow\":{\"type\":\"object\",\"description\":\"Executes nested modules repeatedly until stopped. The implicit iterator is the iteration counter, so 'flow_input.iter.value' equals 'flow_input.iter.index' (0, 1, 2, ...) and never carries state. To carry state across iterations, a step reads its own previous-iteration result via 'results.' with a first-iteration fallback - the loop's stop_after_if must then be on that inner step (a plain single-step body with stop_after_if on the loop module does not resolve 'results' across iterations and never terminates); plain counters can instead be derived from 'flow_input.iter.index', which works in every configuration. stop_after_if is evaluated after each iteration - on the loop module 'result' is the last iteration's result\",\"properties\":{\"modules\":{\"type\":\"array\",\"description\":\"Steps to execute in each iteration\",\"items\":{\"$ref\":\"#/components/schemas/FlowModule\"}},\"skip_failures\":{\"type\":\"boolean\",\"description\":\"If true, iteration failures don't stop the loop. Failed iterations return null\"},\"type\":{\"type\":\"string\",\"enum\":[\"whileloopflow\"]},\"parallel\":{\"type\":\"boolean\",\"description\":\"If true, iterations run concurrently (use with caution in while loops)\"},\"parallelism\":{\"description\":\"Maximum number of concurrent iterations when parallel=true\",\"$ref\":\"#/components/schemas/InputTransform\"},\"squash\":{\"type\":\"boolean\"}},\"required\":[\"modules\",\"skip_failures\",\"type\"]},\"BranchOne\":{\"type\":\"object\",\"description\":\"Conditional branching where only the first matching branch executes. Branches are evaluated in order, and the first one with a true expression runs. If no branches match, the default branch executes\",\"properties\":{\"branches\":{\"type\":\"array\",\"description\":\"Array of branches to evaluate in order. The first branch with expr evaluating to true executes\",\"items\":{\"type\":\"object\",\"properties\":{\"summary\":{\"type\":\"string\",\"description\":\"Short description of this branch condition\"},\"expr\":{\"type\":\"string\",\"description\":\"JavaScript expression that returns boolean. Can use 'results.step_id' or 'flow_input'. First true expr wins\"},\"modules\":{\"type\":\"array\",\"description\":\"Steps to execute if this branch's expr is true\",\"items\":{\"$ref\":\"#/components/schemas/FlowModule\"}}},\"required\":[\"modules\",\"expr\"]}},\"default\":{\"type\":\"array\",\"description\":\"Steps to execute if no branch expressions match\",\"items\":{\"$ref\":\"#/components/schemas/FlowModule\"}},\"type\":{\"type\":\"string\",\"enum\":[\"branchone\"]}},\"required\":[\"branches\",\"default\",\"type\"]},\"BranchAll\":{\"type\":\"object\",\"description\":\"Parallel branching where all branches execute simultaneously. Unlike BranchOne, all branches run regardless of conditions. Useful for executing independent tasks concurrently\",\"properties\":{\"branches\":{\"type\":\"array\",\"description\":\"Array of branches that all execute (either in parallel or sequentially)\",\"items\":{\"type\":\"object\",\"properties\":{\"summary\":{\"type\":\"string\",\"description\":\"Short description of this branch's purpose\"},\"skip_failure\":{\"type\":\"boolean\",\"description\":\"If true, failure in this branch doesn't fail the entire flow\"},\"modules\":{\"type\":\"array\",\"description\":\"Steps to execute in this branch\",\"items\":{\"$ref\":\"#/components/schemas/FlowModule\"}}},\"required\":[\"modules\"]}},\"type\":{\"type\":\"string\",\"enum\":[\"branchall\"]},\"parallel\":{\"type\":\"boolean\",\"description\":\"If true, all branches execute concurrently. If false, they execute sequentially\"}},\"required\":[\"branches\",\"type\"]},\"AgentTool\":{\"type\":\"object\",\"description\":\"A tool available to an AI agent. Can be a flow module or an external MCP (Model Context Protocol) tool\",\"properties\":{\"id\":{\"type\":\"string\",\"description\":\"Unique identifier for this tool. Cannot contain spaces - use underscores instead (e.g., 'get_user_data' not 'get user data')\"},\"summary\":{\"type\":\"string\",\"description\":\"The name the AI agent calls this tool by, not a human label. On a flowmodule tool it must match ^[a-zA-Z0-9_]+$ - letters, numbers and underscores only (e.g. 'search_documentation', not 'Search documentation') - and always be set; on an mcp or websearch tool it is a plain label. Put the human-readable explanation in 'description'.\"},\"description\":{\"type\":\"string\",\"description\":\"Free-text description of the tool given to the AI to decide when and how to call it. Overrides the description auto-derived from the underlying script.\"},\"job_token_scopes\":{\"type\":\"array\",\"nullable\":true,\"items\":{\"type\":\"string\"},\"description\":\"Scopes the token of this tool's jobs is restricted to, on top of the agent step's own restriction: a tool can only narrow it.\"},\"value\":{\"$ref\":\"#/components/schemas/ToolValue\"}},\"required\":[\"id\",\"value\"]},\"ToolValue\":{\"description\":\"The implementation of a tool. Can be a flow module (script/flow) or an MCP tool reference\",\"oneOf\":[{\"$ref\":\"#/components/schemas/FlowModuleTool\"},{\"$ref\":\"#/components/schemas/McpToolValue\"},{\"$ref\":\"#/components/schemas/WebsearchToolValue\"}],\"discriminator\":{\"propertyName\":\"tool_type\",\"mapping\":{\"flowmodule\":\"#/components/schemas/FlowModuleTool\",\"mcp\":\"#/components/schemas/McpToolValue\",\"websearch\":\"#/components/schemas/WebsearchToolValue\"}}},\"FlowModuleTool\":{\"description\":\"A tool implemented as a flow module (script, flow, etc.). The AI can call this like any other flow module\",\"allOf\":[{\"type\":\"object\",\"properties\":{\"tool_type\":{\"type\":\"string\",\"enum\":[\"flowmodule\"]}},\"required\":[\"tool_type\"]},{\"$ref\":\"#/components/schemas/FlowModuleValue\"}]},\"WebsearchToolValue\":{\"type\":\"object\",\"description\":\"A tool implemented as a websearch tool. The AI can call this like any other websearch tool\",\"properties\":{\"tool_type\":{\"type\":\"string\",\"enum\":[\"websearch\"]}},\"required\":[\"tool_type\"]},\"McpToolValue\":{\"type\":\"object\",\"description\":\"Reference to an external MCP (Model Context Protocol) tool. The AI can call tools from MCP servers\",\"properties\":{\"tool_type\":{\"type\":\"string\",\"enum\":[\"mcp\"]},\"resource_path\":{\"type\":\"string\",\"description\":\"Path to the MCP resource/server configuration\"},\"include_tools\":{\"type\":\"array\",\"description\":\"Whitelist of specific tools to include from this MCP server\",\"items\":{\"type\":\"string\"}},\"exclude_tools\":{\"type\":\"array\",\"description\":\"Blacklist of tools to exclude from this MCP server\",\"items\":{\"type\":\"string\"}}},\"required\":[\"tool_type\",\"resource_path\"]},\"AiAgent\":{\"type\":\"object\",\"description\":\"AI agent step that can use tools to accomplish tasks. The agent receives inputs and can call any of its configured tools to complete the task\",\"properties\":{\"input_transforms\":{\"type\":\"object\",\"description\":\"Input parameters for the AI agent mapped to their values\",\"properties\":{\"provider\":{\"$ref\":\"#/components/schemas/ProviderTransform\"},\"output_type\":{\"allOf\":[{\"$ref\":\"#/components/schemas/InputTransform\"}],\"description\":\"Output format type.\\nValid values: 'text' (default) - plain text response, 'image' - image generation\\n\"},\"user_message\":{\"allOf\":[{\"$ref\":\"#/components/schemas/InputTransform\"}],\"description\":\"The user's prompt/message to the AI agent. Supports variable interpolation with\\nflow.input syntax. Required unless memory is off and `previous_messages` supplies\\nthe prompt; image output always needs it.\\n\"},\"system_prompt\":{\"allOf\":[{\"$ref\":\"#/components/schemas/InputTransform\"}],\"description\":\"System instructions that guide the AI's behavior, persona, and response style. Optional.\"},\"streaming\":{\"allOf\":[{\"$ref\":\"#/components/schemas/InputTransform\"}],\"description\":\"Boolean. If true, stream the AI response incrementally.\\nStreaming events include: token_delta, reasoning_token_delta, tool_call, tool_call_arguments, tool_execution, tool_result\\n\"},\"memory\":{\"$ref\":\"#/components/schemas/MemoryTransform\"},\"memory_id\":{\"allOf\":[{\"$ref\":\"#/components/schemas/InputTransform\"}],\"description\":\"String. Names the memory this step reads and writes, overriding the memory id the run\\nwas started with (the chat conversation, an app chat session or the `memory_id` run\\nparameter). Leave unset to use the run's memory id. A fixed value shares one memory\\nacross every run; an expression such as `flow_input.customer_id` keeps one memory per\\nkey. When it evaluates to an empty value the agent runs without memory. Read only\\nwhile `memory` is `window` or `compaction`: it is ignored when memory is off, and an\\nolder `auto` or `manual` memory reads neither history input.\\n\"},\"previous_messages\":{\"allOf\":[{\"$ref\":\"#/components/schemas/InputTransform\"}],\"description\":\"Array of MemoryMessage. History supplied by the flow, sent between the system prompt\\nand the user message. Read only while `memory` is off or absent: managed memory\\nignores it, and an older `auto` or `manual` memory reads neither history input.\\n\"},\"output_schema\":{\"allOf\":[{\"$ref\":\"#/components/schemas/InputTransform\"}],\"description\":\"JSON Schema object defining structured output format. Used when you need the AI to return data in a specific shape.\\nSupports standard JSON Schema properties: type, properties, required, items, enum, pattern, minLength, maxLength, minimum, maximum, etc.\\nExample: { type: 'object', properties: { name: { type: 'string' }, age: { type: 'integer' } }, required: ['name'] }\\n\"},\"user_attachments\":{\"allOf\":[{\"$ref\":\"#/components/schemas/InputTransform\"}],\"description\":\"Array of file references (images or PDFs) for the AI agent.\\nFormat: Array<{ bucket: string, key: string }> - S3 object references\\nExample: [{ bucket: 'my-bucket', key: 'documents/report.pdf' }]\\n\"},\"enabled_tools\":{\"allOf\":[{\"$ref\":\"#/components/schemas/InputTransform\"}],\"description\":\"Array of strings naming which of the tools configured in `tools` the agent may call\\nthis run. Leaving it unset carries every one of them; an empty array carries none.\\nA tool is named as the model is shown it. An entry the model is shown nothing of is\\nnamed by what identifies it instead: an MCP server by its resource path, carrying\\nevery tool it exposes (which of them stays that entry's include_tools/exclude_tools),\\nand a websearch entry by the reserved name '__wm_web_search', whatever summary it carries\\n(no tool may take that name).\\nExample: ['get_user', 'u/admin/github_mcp', '__wm_web_search']\\n\"},\"max_completion_tokens\":{\"allOf\":[{\"$ref\":\"#/components/schemas/InputTransform\"}],\"description\":\"Integer. Maximum number of tokens the AI will generate in its response.\\nRange: 1 to 4,294,967,295. Typical values: 256-4096 for most use cases.\\n\"},\"temperature\":{\"allOf\":[{\"$ref\":\"#/components/schemas/InputTransform\"}],\"description\":\"Float. Controls randomness/creativity of responses.\\nRange: 0.0 to 2.0 (provider-dependent)\\n- 0.0 = deterministic, focused responses\\n- 0.7 = balanced (common default)\\n- 1.0+ = more creative/random\\n\"},\"max_iterations\":{\"allOf\":[{\"$ref\":\"#/components/schemas/InputTransform\"}],\"description\":\"Number. Limits how many times the agent can loop through reasoning and tool use.\\nRange: 1-1000.\\n\"},\"model\":{\"allOf\":[{\"$ref\":\"#/components/schemas/InputTransform\"}],\"description\":\"String. Only on a step linked to a saved agent (see `agent`): replaces the model\\nsaved on the agent for this step's runs, on the agent's own provider resource. An\\nempty value keeps the saved model. Set it to an expression such as\\n`flow_input.model` to choose the model per run.\\n\"},\"reasoning_effort\":{\"allOf\":[{\"$ref\":\"#/components/schemas/InputTransform\"}],\"description\":\"String. Only on a step linked to a saved agent (see `agent`): replaces the reasoning\\neffort saved on the agent for this step's runs, as a provider-native token (e.g.\\n'low', 'high', 'none'). An empty value sends no effort, so the model runs at its\\ndefault. Leave the input out to keep the saved effort, which holds only while the\\nstep runs the saved model. A step that is not linked sets both inside `provider`.\\n\"}}},\"tools\":{\"type\":\"array\",\"description\":\"Array of tools the agent can use. The agent decides which tools to call based on the task\",\"items\":{\"$ref\":\"#/components/schemas/AgentTool\"}},\"type\":{\"type\":\"string\",\"enum\":[\"aiagent\"]},\"tag\":{\"type\":\"string\",\"description\":\"Worker group tag for execution routing. If not set, the AI agent step runs on the flow's tag (default `flow`)\"},\"omit_output_from_conversation\":{\"type\":\"boolean\",\"default\":false,\"description\":\"If true, this AI agent step does not persist its assistant or tool messages to the flow conversation when chat mode is enabled.\"},\"agent\":{\"type\":\"string\",\"description\":\"Path of a reusable `ai_agent` resource (hybrid linking). When set, the agent brain\\nconfig (provider/model/system prompt/etc.) and tool set are resolved at runtime from\\nthat resource; the module's input_transforms then only carry the flow-local inputs\\n(user_message, user_attachments, enabled_tools and the history inputs memory_id and previous_messages)\\nand, optionally, the `model` and `reasoning_effort` overrides of what the agent saved.\\n\"},\"tool_inputs\":{\"type\":\"object\",\"description\":\"Host-local wiring for an agent's tool inputs, keyed by tool id then input key. Binds the\\nreferenced agent's tools to this flow's context (flow_input/results) without mutating the\\nshared resource; overlaid onto the tools' input_transforms at runtime \\u2014 including when\\n`agent` is unset, since a step forked for editing keeps these overrides until it is saved\\nback or unlinked.\\n\",\"additionalProperties\":{\"type\":\"object\",\"additionalProperties\":{\"$ref\":\"#/components/schemas/InputTransform\"}}},\"parallel\":{\"type\":\"boolean\",\"description\":\"If true, the agent can execute multiple tool calls in parallel\"}},\"required\":[\"type\",\"input_transforms\"]},\"AiDecision\":{\"type\":\"object\",\"description\":\"AI decision step: one call to a decision model (TypeSafe's Jev, Cloudflare's\\nJev-compatible Clef, or OpenAI's Decisions API) that answers typed questions about a\\nstate with calibrated probabilities, instead of generating text.\\nPrefer it over an AI agent to classify, route, score or check something: it is fast,\\ncheap and its answers are structured. Its result is { output: { : answer },\\nmodel, usage }, so a later step reads e.g. results..output.intent.choice. To route on\\nthe answers, follow it with a branchone whose branch exprs read\\nresults..output..choice. Usable as an AI agent tool, where the calling agent\\nsupplies the state.\\n\",\"properties\":{\"input_transforms\":{\"type\":\"object\",\"description\":\"Input parameters for the decision mapped to their values\",\"properties\":{\"provider\":{\"$ref\":\"#/components/schemas/ProviderTransform\"},\"state\":{\"allOf\":[{\"$ref\":\"#/components/schemas/InputTransform\"}],\"description\":\"What the questions are asked about: a string, an object or an array of strings.\\nAn object with descriptive keys holding only what the questions need works best.\\nExample: { message: flow_input.message, plan: results.a.plan }\\n\"},\"questions\":{\"allOf\":[{\"$ref\":\"#/components/schemas/InputTransform\"}],\"description\":\"Object mapping each question name to { type, instructions, criteria }, where type is:\\n- 'choice': criteria maps each option to its description (up to 255); the answer\\n has choice, probabilities and confidence\\n- 'score': criteria is an ordered array of 2 to 10 level descriptions; the answer\\n has score, legend, probabilities and confidence\\n- 'noul': yes/no, criteria optionally { true, false } descriptions; the answer has\\n noul, the probability of yes (0 to 1)\\nExample: { intent: { type: 'choice', instructions: 'What does the customer want?',\\ncriteria: { refund: 'Money back', bug: 'Something is broken' } } }\\n\"}},\"required\":[\"provider\",\"state\",\"questions\"]},\"type\":{\"type\":\"string\",\"enum\":[\"aidecision\"]},\"tag\":{\"type\":\"string\",\"description\":\"Worker group tag for execution routing. If not set, the step runs on the flow's tag (default `flow`)\"}},\"required\":[\"type\",\"input_transforms\"]},\"Identity\":{\"type\":\"object\",\"description\":\"Pass-through module that returns its input unchanged. Useful for flow structure or as a placeholder\",\"properties\":{\"type\":{\"type\":\"string\",\"enum\":[\"identity\"]},\"flow\":{\"type\":\"boolean\",\"description\":\"If true, marks this as a flow identity (special handling)\"}},\"required\":[\"type\"]},\"FlowStatus\":{\"type\":\"object\",\"properties\":{\"step\":{\"type\":\"integer\"},\"modules\":{\"type\":\"array\",\"items\":{\"$ref\":\"#/components/schemas/FlowStatusModule\"}},\"user_states\":{\"additionalProperties\":true},\"preprocessor_module\":{\"allOf\":[{\"$ref\":\"#/components/schemas/FlowStatusModule\"}]},\"failure_module\":{\"allOf\":[{\"$ref\":\"#/components/schemas/FlowStatusModule\"},{\"type\":\"object\",\"properties\":{\"parent_module\":{\"type\":\"string\"}}}]},\"retry\":{\"type\":\"object\",\"properties\":{\"fail_count\":{\"type\":\"integer\"},\"failed_jobs\":{\"type\":\"array\",\"items\":{\"type\":\"string\",\"format\":\"uuid\"}}}}},\"required\":[\"step\",\"modules\",\"failure_module\"]},\"FlowStatusModule\":{\"type\":\"object\",\"properties\":{\"type\":{\"type\":\"string\",\"enum\":[\"WaitingForPriorSteps\",\"WaitingForEvents\",\"WaitingForExecutor\",\"InProgress\",\"Success\",\"Failure\"]},\"id\":{\"type\":\"string\"},\"job\":{\"type\":\"string\",\"format\":\"uuid\"},\"count\":{\"type\":\"integer\"},\"progress\":{\"type\":\"integer\"},\"iterator\":{\"type\":\"object\",\"properties\":{\"index\":{\"type\":\"integer\"},\"itered\":{\"type\":\"array\",\"items\":{}},\"itered_len\":{\"type\":\"integer\"},\"args\":{}}},\"flow_jobs\":{\"type\":\"array\",\"items\":{\"type\":\"string\"}},\"flow_jobs_success\":{\"type\":\"array\",\"items\":{\"type\":\"boolean\"}},\"flow_jobs_duration\":{\"type\":\"object\",\"properties\":{\"started_at\":{\"type\":\"array\",\"items\":{\"type\":\"string\"}},\"duration_ms\":{\"type\":\"array\",\"items\":{\"type\":\"integer\"}}}},\"branch_chosen\":{\"type\":\"object\",\"properties\":{\"type\":{\"type\":\"string\",\"enum\":[\"branch\",\"default\"]},\"branch\":{\"type\":\"integer\"}},\"required\":[\"type\"]},\"branchall\":{\"type\":\"object\",\"properties\":{\"branch\":{\"type\":\"integer\"},\"len\":{\"type\":\"integer\"}},\"required\":[\"branch\",\"len\"]},\"approvers\":{\"type\":\"array\",\"items\":{\"type\":\"object\",\"properties\":{\"resume_id\":{\"type\":\"integer\"},\"approver\":{\"type\":\"string\"}},\"required\":[\"resume_id\",\"approver\"]}},\"failed_retries\":{\"type\":\"array\",\"items\":{\"type\":\"string\",\"format\":\"uuid\"}},\"skipped\":{\"type\":\"boolean\"},\"agent_actions\":{\"type\":\"array\",\"items\":{\"type\":\"object\",\"oneOf\":[{\"type\":\"object\",\"properties\":{\"job_id\":{\"type\":\"string\",\"format\":\"uuid\"},\"function_name\":{\"type\":\"string\"},\"type\":{\"type\":\"string\",\"enum\":[\"tool_call\"]},\"module_id\":{\"type\":\"string\"}},\"required\":[\"job_id\",\"function_name\",\"type\",\"module_id\"]},{\"type\":\"object\",\"properties\":{\"call_id\":{\"type\":\"string\",\"format\":\"uuid\"},\"function_name\":{\"type\":\"string\"},\"resource_path\":{\"type\":\"string\"},\"type\":{\"type\":\"string\",\"enum\":[\"mcp_tool_call\"]},\"arguments\":{\"type\":\"object\"}},\"required\":[\"call_id\",\"function_name\",\"resource_path\",\"type\"]},{\"type\":\"object\",\"properties\":{\"type\":{\"type\":\"string\",\"enum\":[\"web_search\"]}},\"required\":[\"type\"]},{\"type\":\"object\",\"properties\":{\"type\":{\"type\":\"string\",\"enum\":[\"message\"]}},\"required\":[\"content\",\"type\"]}]}},\"agent_actions_success\":{\"type\":\"array\",\"items\":{\"type\":\"boolean\"}}},\"required\":[\"type\"]}}", + "flow": "# Global draft flow instructions\n\n- Global mode writes complete draft payloads only; it does not save, deploy, run, scaffold local files, or generate metadata.\n- Paths follow the conventions in the system prompt: default to `u//` when the user gave a bare name; only use `f//` when the folder is known to exist. Never invent a folder.\n- `write_flow` mirrors flow mode's `set_flow_json`: pass `path`, optional `summary`, optional `description`, required `modules`, and optional `schema`, `preprocessor_module`, `failure_module`, `groups`, and `notes`. `summary` and `description` are top-level flow metadata (not part of the compact value `patch_flow_json` edits); the flow-structure arguments are JSON strings, matching the tool schema descriptions. When overwriting an existing flow, top-level flow settings (see below) are preserved from the current flow — use `patch_flow_json` to change them.\n- `read_workspace_item` returns a compact flow `value` object with `modules`, `schema`, `preprocessor_module`, `failure_module`, `groups`, `notes`, and any top-level flow settings that are set.\n- Top-level flow settings appear as top-level keys of the compact flow value and can be added, edited, or removed with `patch_flow_json`: same_worker, preserve_step_tags, concurrent_limit, concurrency_key, concurrency_time_window_s, debounce_delay_s, debounce_key, debounce_args_to_accumulate, max_total_debouncing_time, max_total_debounces_amount, skip_expr, cache_ttl, cache_ignore_s3_path, delete_after_secs, flow_env, priority, early_return, chat_input_enabled. For example, `chat_input_enabled: true` marks a flow as chat-style (flow-as-chat); keep it intact when restructuring such a flow.\n- `modules` contains normal sequential modules. Use top-level `preprocessor_module` and `failure_module` for special modules; do not put `preprocessor` or `failure` in `modules`.\n- Every module needs a stable unique `id` and a useful `summary` when the schema supports it.\n- Prefer path/script/flow modules when composing existing workspace logic. Use rawscript modules only when new inline code is needed.\n- When writing rawscript module code, call `get_instructions` with `subject: \"script\"` and the rawscript language first.\n\n## Groups and notes\n\n- Add `groups` to any non-trivial flow without being asked; \"Organizing Flows: Groups and Notes\" in the reference below gives the fields and the rules the editor enforces. Pass `null` to `write_flow` to clear them, and the same for `notes`.\n- With `patch_flow_json`, edit `groups` and `notes` the same way as any other field — they appear as top-level keys in the compact flow value.\n\n## Compact view: how rawscript bodies surface in tool I/O\n\n- `read_workspace_item` and `patch_flow_json` operate on a **compact view** of the flow: every rawscript module's `value.content` is replaced with the placeholder `\"inline_script.\"` so inline script bodies don't bloat tool I/O. Schema, groups, notes, preprocessor_module and failure_module are all shown in this view.\n- Inline rawscript content is **not** part of the JSON `patch_flow_json` sees. Edits to inline bodies happen via dedicated tools:\n - `read_flow_module_code(path, module_id)` — returns the raw inline script content for one module.\n - `set_flow_module_code(path, module_id, code)` — overwrites that module's inline script content; saves to the draft.\n- Use `patch_flow_json` for *structural* edits: module ids, paths, input_transforms, branch arrangement, summaries, preprocessor/failure swaps, schema/groups/notes. Use `set_flow_module_code` for changes inside a specific rawscript body.\n- When **adding a new rawscript module** with `patch_flow_json`, set its `content` to the placeholder `\"inline_script.\"` (matching the compact view) — never real code — then **immediately fill the body** with `set_flow_module_code(path, module_id, code)`. The module is saved with an empty body until you do; the tool result lists the module ids still awaiting code. A placeholder that names anything other than the module's own id or an existing rawscript module is rejected.\n- `write_flow` is for full overwrites / create-from-scratch. Its `modules`, `preprocessor_module`, and `failure_module` arguments are **non-compact** flow modules: inline each rawscript body directly in `content` by default. But if a body is long or quote/backslash-heavy enough that escaping it into the JSON string is error-prone — or if a `write_flow` call comes back with a JSON parse error — create that module with **empty content** (`\"content\": \"\"`) and fill it with `set_flow_module_code(path, module_id, code)`, whose `code` is a plain argument with no nested escaping. `write_flow` reports which modules still have empty bodies so you know what to fill.\n - When overwriting an **existing** flow, set `\"content\": \"inline_script.\"` on any rawscript module whose code you are not changing — the placeholder resolves to that module's current body, so you never re-send (or re-read) unchanged code. Placeholders that match no existing rawscript module and are not the module's own id are rejected.\n\n\n# Windmill flow authoring reference\n\n# Windmill Flow Building Guide\n\n## OpenFlow Schema\n\nThe OpenFlow schema (openflow.openapi.yaml) is the source of truth for flow structure. Refer to OPENFLOW_SCHEMA for the complete type definitions.\n\n## Reserved Module IDs\n\n- `failure` - Reserved for failure handler module\n- `preprocessor` - Reserved for preprocessor module\n- `Input` - Reserved for flow input reference\n\n## Hard Structural Rules\n\nThese are strict Windmill schema rules. Follow them exactly.\n\n- `value.modules` is only for normal sequential steps\n- `value.preprocessor_module` and `value.failure_module` are special top-level fields inside `value`, not entries in `value.modules`\n- If a flow needs a preprocessor, create `value.preprocessor_module` with `id: preprocessor`\n- If a flow needs a failure handler, create `value.failure_module` with `id: failure`\n- Do NOT create regular modules inside `value.modules` named `preprocessor` or `failure`\n- `preprocessor_module` and `failure_module` only support `script` or `rawscript`\n- `preprocessor_module` runs before normal modules and cannot reference `results.*`\n- `failure_module` can use the `error` object with `error.message`, `error.step_id`, `error.name`, and `error.stack`\n- A flow whose `failure_module` runs still ends as failed, unless the handler returns an object with `recover: true`: the flow then ends as a success. This also holds when the failing step is inside a loop, a branch or a subflow. `recover` never changes which steps run; whether a loop or branch carries on past a failure is still decided by its own settings (`skip_failures`, `continue_on_error`)\n\nCorrect shape:\n\n```yaml\nvalue:\n preprocessor_module:\n id: preprocessor\n value:\n type: rawscript\n ...\n failure_module:\n id: failure\n value:\n type: rawscript\n ...\n modules:\n - id: process_event\n value:\n type: rawscript\n ...\n```\n\nIncorrect shape:\n\n```yaml\nvalue:\n modules:\n - id: preprocessor\n ...\n - id: process_event\n ...\n - id: failure\n ...\n```\n\n## Module ID Rules\n\n- Must be unique across the entire flow\n- Use underscores, not spaces (e.g., `fetch_data` not `fetch data`)\n- Use descriptive names that reflect the step's purpose\n\n## AI Agent Modules\n\nAn `aiagent` module runs an LLM that can call tools. Each entry of `value.tools` is a module-shaped\nobject with an extra `value.tool_type`: `flowmodule` for a script/flow tool, `mcp` for an MCP server\ntool, `websearch` for web search, `question` for a built-in `ask_question` tool (the agent stops,\nwithout holding a worker, until someone answers from the run page or the chat; optional\n`value.timeout` in seconds, default 1800). Set `requires_approval: true` on a `flowmodule` or `mcp`\ntool to have a person approve or reject each of its calls before it runs.\n\n```json\n{\n \"id\": \"support_agent\",\n \"summary\": \"AI agent for customer support\",\n \"value\": {\n \"type\": \"aiagent\",\n \"input_transforms\": {\n \"provider\": {\n \"type\": \"static\",\n \"value\": { \"kind\": \"openai\", \"resource\": \"$res:f/ai_providers/openai\", \"model\": \"gpt-4o\" }\n },\n \"output_type\": { \"type\": \"static\", \"value\": \"text\" },\n \"user_message\": { \"type\": \"javascript\", \"expr\": \"flow_input.query\" },\n \"system_prompt\": { \"type\": \"static\", \"value\": \"You are a helpful assistant.\" }\n },\n \"tools\": [\n {\n \"id\": \"search_docs\",\n \"summary\": \"search_documentation\",\n \"description\": \"Search the product documentation. Use it whenever the user asks how a feature works.\",\n \"value\": {\n \"tool_type\": \"flowmodule\",\n \"type\": \"rawscript\",\n \"language\": \"bun\",\n \"content\": \"export async function main(query: string) { return ['doc1', 'doc2']; }\",\n \"input_transforms\": { \"query\": { \"type\": \"static\", \"value\": \"\" } }\n }\n }\n ]\n }\n}\n```\n\n- `provider` is an object, not a bare resource string: `{ \"kind\": ,\n \"resource\": \"$res:\", \"model\": }`. Required unless the module links to a saved\n agent through `value.agent`. Static is right for a flow run from a form; a chat flow wires its\n fields to flow inputs instead — see below\n\n### Chat-Mode Flows\n\nA flow with `value.chat_input_enabled: true` is run from a chat instead of a form: the composer\nsends one message per turn and renders the conversation. It needs a required `user_message` string\ninput, read by the agent. Any other flow input the composer does not edit itself is asked for\nunder Configure inputs.\n\n**A static `provider` gives a chat that cannot change its model.** Feed it from flow inputs\ninstead, either way round: one input carrying the whole object (`\"expr\": \"flow_input.model_config\"`)\nmakes every field editable, or wire it field by field to fix some and expose others. A field the\nchat can write becomes a control in the composer — a provider picker, a model list, a thinking\ncontrol — and a field left static is fixed, with no control drawn for it. `kind` is the one\nexception: the composer writes it only together with `resource`, since a provider is picked as a\npair, so a `kind` input wired on its own stays askable under Configure inputs and nothing the run\nneeds becomes unreachable.\n\n```json\n{\n \"id\": \"chat_agent\",\n \"value\": {\n \"type\": \"aiagent\",\n \"input_transforms\": {\n \"provider\": {\n \"type\": \"javascript\",\n \"expr\": \"({ kind: 'anthropic', resource: '$res:f/ai/claude', model: flow_input.model, reasoning_effort: flow_input.thinking })\"\n },\n \"user_message\": { \"type\": \"javascript\", \"expr\": \"flow_input.user_message\" },\n \"user_attachments\": { \"type\": \"javascript\", \"expr\": \"flow_input.files\" },\n \"memory\": { \"type\": \"static\", \"value\": { \"kind\": \"compaction\" } },\n \"streaming\": { \"type\": \"static\", \"value\": true },\n \"output_type\": { \"type\": \"static\", \"value\": \"text\" }\n },\n \"tools\": []\n }\n}\n```\n\n- Wiring field by field means one object literal whose values are literals or bare `flow_input.x`\n references. A spread, a call or a computed key leaves the composer unable to tell which input\n feeds which field, so it offers no control at all — a bare `flow_input.x` for the whole object\n is read instead as that one input carrying every field\n- A step linked to a saved agent (`agent` set) has no `provider` of its own. It exposes the same\n two controls through its `model` and `reasoning_effort` inputs, which replace what the agent\n saved: `\"model\": { \"type\": \"javascript\", \"expr\": \"flow_input.model\" }`. An empty model keeps the\n saved one, an empty effort sends none, and the provider resource always stays the agent's\n- `memory` is what lets the agent see earlier turns; without it every message starts from nothing\n- `streaming` on makes the answer and its thinking appear token by token instead of all at once\n- `user_attachments` points at a flow input typed as an array of s3 objects\n (`{ \"type\": \"array\", \"items\": { \"type\": \"object\", \"resourceType\": \"s3object\" } }`), so files\n sent with a message reach the agent\n- Running one needs a `memory_id` **query parameter** — not a flow argument — naming the\n conversation the turn belongs to: a fresh UUID starts one, reusing a UUID continues it. The chat\n supplies it itself; a run driven any other way has to pass it or the server refuses the job\n\n### Tool Naming Rules\n\nThese rules cover `flowmodule` tools, the ones the agent calls by name. A `websearch` or `question`\ntool's `summary` is a plain label (`Web Search`), and an `mcp` tool exposes the MCP\nserver's own tool names, so none is name-checked at all — leave those summaries as they are.\n\n- A flowmodule tool's `summary` is the **name the agent calls it by**, not a human label. Put the\n human-readable explanation in `description`\n- `summary` must match `^[a-zA-Z0-9_]+$`: letters, numbers and underscores only. No spaces, dashes,\n dots or accents — `search_documentation`, never `Search documentation`\n- Always set `summary`. It must be unique among that agent's tools, and must not be one of the\n reserved ids (`do`, `bg`, `ctx`, `state`, `if`, `else`, `for`, `delete`, `while`, `new`, `in`,\n `failure`, `preprocessor`, `as`, `Input`, `Result`, `Trigger`)\n- A tool name outside that character set fails any run that offers the tool to the agent, with `Invalid tool name`.\n The flow write tools refuse such a name.\n- Tool `id` follows the same rules as any module ID — unique across the flow, underscores not spaces\n- `description` is optional free text telling the agent when and how to call the tool. Set it\n whenever the name alone does not make that obvious; it overrides the description derived from the\n underlying script\n\n## AI Decision Modules\n\nAn `aidecision` module asks a decision model (TypeSafe's Jev, Cloudflare's Clef or OpenAI's Decisions API) typed questions about a `state` and\nanswers each with calibrated probabilities instead of text. Prefer it over an `aiagent` when the step\nis a judgment (classify, route, score or a yes/no check) that needs no tools and no free text: it\nis faster, cheaper, and its answers have a fixed shape.\n\n```json\n{\n \"id\": \"triage\",\n \"summary\": \"Classify the ticket\",\n \"value\": {\n \"type\": \"aidecision\",\n \"input_transforms\": {\n \"provider\": {\n \"type\": \"static\",\n \"value\": { \"kind\": \"typesafe\", \"resource\": \"$res:f/ai/typesafe\", \"model\": \"jev-latest\" }\n },\n \"state\": { \"type\": \"javascript\", \"expr\": \"flow_input.message\" },\n \"questions\": {\n \"type\": \"static\",\n \"value\": {\n \"intent\": {\n \"type\": \"choice\",\n \"instructions\": \"What does the customer want?\",\n \"criteria\": { \"refund\": \"Money back\", \"bug\": \"Something is broken\", \"other\": \"Anything else\" }\n },\n \"urgency\": {\n \"type\": \"score\",\n \"instructions\": \"How urgent is the ticket?\",\n \"criteria\": [\"Can wait\", \"This week\", \"Today\", \"Right now\"]\n },\n \"angry\": { \"type\": \"noul\", \"instructions\": \"Is the customer angry?\" }\n }\n }\n }\n }\n}\n```\n\n- `provider.kind` is `typesafe` (`model` `jev-latest` unless a version is pinned), `cloudflare`\n (`model` `clef`, or `clef-flash` for faster answers) or `openai` (`model` `gpt-6-luna`, never a\n chat model); the resource is of that same type\n- `state` is the content to evaluate: usually a text, such as the message to classify. To combine\n several values, pass an object with descriptive keys holding only what the questions need\n (`({ message: flow_input.message, plan: results.get_account.plan })`); an array of strings also works\n- `questions` maps each question name to `{ type, instructions, criteria }`:\n - `choice`: `criteria` maps each option to its description (up to 255 options). The answer has\n `choice`, `probabilities` and `confidence`\n - `score`: `criteria` is an ordered array of 2 to 10 level descriptions. The answer has `score`,\n `legend`, `probabilities` and `confidence`\n - `noul`: yes/no, `criteria` optionally `{ \"true\": ..., \"false\": ... }` descriptions. The answer has\n `noul`, the probability of yes from 0 to 1\n- The result is `{ output, model, usage }` with `output` keyed by question name, so a later step\n reads `results.triage.output.intent.choice`, `results.triage.output.urgency.score` or\n `results.triage.output.angry.noul > 0.7`\n- On `openai` the same `questions` are translated for its Decisions API and the answers read the\n same way (`choice`, `score`, `noul`), except that `probabilities` is a list of\n `{ value, probability }` (plus `label` on a score) and a score has no `legend`. A question OpenAI\n refuses to answer fails the step. A `state` that is\n an array of user messages (`[{ role: \"user\", content: [{ type: \"input_text\", text }, { type: \"input_image\", image_url: \"data:image/png;base64,...\" }] }]`)\n is sent as is, which is how an image is evaluated; any other object or array is sent as JSON text\n\n### Branching on the Answers\n\nTo route on the answers, put a `branchone` right after the decision, one branch per option, with\neach `expr` reading the decision by id:\n\n```json\n{\n \"id\": \"route\",\n \"value\": {\n \"type\": \"branchone\",\n \"branches\": [\n { \"summary\": \"refund\", \"expr\": \"results.triage.output.intent.choice === 'refund'\", \"modules\": [...] },\n { \"summary\": \"bug\", \"expr\": \"results.triage.output.intent.choice === 'bug'\", \"modules\": [...] }\n ],\n \"default\": [...]\n }\n}\n```\n\nFor a yes/no question, one branch with `\"expr\": \"results.triage.output.angry.noul >= 0.5\"` (tune the\nthreshold as needed) and the `default` as the \"no\" path.\n\n### As an Agent Tool\n\nAn `aidecision` can be a `flowmodule` tool of an `aiagent` (`\"tool_type\": \"flowmodule\", \"type\":\n\"aidecision\"`): set `state` to `{ \"type\": \"ai\" }` so the calling model supplies it, and only `output`\ngoes back to the model. The Tool Naming Rules apply to its `summary`. Only a flow's own agent step\ncan call one, not an agent used as a tool.\n\n## Common Mistakes to Avoid\n\n- Missing `input_transforms` - Rawscript parameters won't receive values without them\n- Referencing future steps - `results.step_id` only works for steps that execute before the current one\n- Duplicate module IDs - Each module ID must be unique in the flow\n- AI agent flowmodule tool names with spaces - `summary` is the tool name and only accepts letters, numbers and underscores\n\n## Data Flow Between Steps\n\n- `flow_input.property` - Access flow input parameters\n- `results.step_id` - Access output from a previous step only when that step result is in scope\n- `results.step_id.property` - Access specific property from a previous step output only when that step result is in scope\n- `flow_input.iter.value` - Current iteration value inside a `forloopflow`; in a `whileloopflow` it is just the iteration index (a plain number, same as `flow_input.iter.index`)\n- `flow_input.iter.index` - Current loop index when inside a loop (`forloopflow` or `whileloopflow`)\n- After a suspend step (approval), the next step's javascript expressions also get:\n - `resume` - the last resume payload (the resume form values); with `continue_on_disapprove_timeout`, a disapproval or timeout yields `{ error: { name: \"SuspendedDisapproved\" | \"SuspendedTimedOut\", message } }` instead\n - `resumes` - every resume payload, in arrival order\n - `approvers` - a plain array of strings, one per resume: for a resume through the `resume`/`cancel` URL from `getResumeUrls(approver)`, the `approver` passed there if any; otherwise (including the `approvalPage` link) the resuming user's username, else `\"anonymous\"`, e.g. `approvers[0]`. It is NOT the `{ resume_id, approver }` objects stored in the flow status, so `approvers[0].approver` is always undefined\n\n## Loop Structure Rules\n\n- A `forloopflow` runs its `modules` once per element of `iterator`, a javascript expression returning an array (e.g. `results.get_items`); `parallel: true` runs the iterations concurrently, and `skip_failures: true` carries on past a failed iteration\n- For `whileloopflow`, break the loop with a module-level `stop_after_if`: on the loop module itself, or on an inner step (required when that step carries state via its own `results` — see below)\n- `stop_after_if` is always a sibling of `id` and `value` on a flow module — never a direct key of the loop's `value` object\n- `stop_after_all_iters_if` is for checks after the whole loop finishes, not the normal per-iteration break condition\n- `stop_after_if` is evaluated after each iteration: on the loop module, `result` is that iteration's result (what its last step returned); on an inner step, it is that step's result\n- `flow_input.iter.value` in a `whileloopflow` is just the iteration index (same number as `flow_input.iter.index`) — it never carries state, so `flow_input.iter.value.` is always undefined and a loop whose stop condition depends on it never terminates\n- To carry state across iterations, a step reads its own previous-iteration result via `results.` with a first-iteration fallback (e.g. `results.b ?? flow_input.start`) — but then the loop's `stop_after_if` MUST sit on that inner step, not on the loop module: a body that is exactly one plain step with the stop condition on the loop module runs on a fast path where `results.` is null on every iteration and the loop never terminates (bodies with 2+ steps, or whose single step has its own `stop_after_if`, retry or similar, resolve `results` across iterations regardless of stop placement)\n- For state that is just a counter, derive it from the index instead (e.g. `flow_input.iter.index + 1`) — that works in every configuration, including with `stop_after_if` on the loop module\n- If the user asks for a final scalar/object after a loop, add a normal step after the loop that extracts the final value from the loop result instead of returning the whole loop result array\n\nCorrect `whileloopflow` shape:\n\n```yaml\n- id: loop_until_done\n stop_after_if:\n expr: result.done === true\n skip_if_stopped: false\n value:\n type: whileloopflow\n skip_failures: false\n modules:\n - id: advance_state\n value:\n type: rawscript\n input_transforms:\n count:\n type: javascript\n expr: flow_input.iter.index + 1\n- id: return_final_state\n value:\n type: rawscript\n input_transforms:\n final_state:\n type: javascript\n expr: results.loop_until_done[results.loop_until_done.length - 1]\n```\n\nCorrect `whileloopflow` shape carrying state via `results` (stop condition on the inner step):\n\n```yaml\n- id: loop_until_done\n value:\n type: whileloopflow\n skip_failures: false\n modules:\n - id: advance_state\n stop_after_if:\n expr: result.done === true\n skip_if_stopped: false\n value:\n type: rawscript\n input_transforms:\n state:\n type: javascript\n expr: results.advance_state ?? flow_input.initial_state\n```\n\nIncorrect `whileloopflow` patterns:\n\n```yaml\n- id: loop_until_done\n value:\n type: whileloopflow\n stop_after_if:\n expr: result.done === true\n```\n\n```yaml\ninput_transforms:\n state:\n type: javascript\n # iter.value is a number (the iteration index); there is no previous-iteration state\n expr: flow_input.iter.value.count\n```\n\n```yaml\ninput_transforms:\n final_state:\n type: javascript\n expr: results.loop_until_done\n```\n\n## Approval / Suspend Structure\n\nAn approval step is a normal **script** step (`type: rawscript` or `type: script`) that is turned into an approval by adding a module-level `suspend`. Its script calls `wmill.getResumeUrls(approver)` to generate the secret resume/cancel URLs and returns them so they can be sent to the approver(s) (Slack, email, etc.) or approved from the run page.\n\n- `suspend` belongs on the flow module object itself, as a sibling of `id` and `value`\n- Never put `suspend` inside `value`\n- Do NOT use `type: identity` for an approval step. An identity step suspends but never produces the resume URLs, so approvers have no link to act on — it is not a functional approval.\n\nCorrect shape:\n\n```yaml\n- id: request_approval\n suspend:\n required_events: 1\n resume_form:\n schema:\n type: object\n properties:\n comment:\n type: string\n required: [comment]\n value:\n type: rawscript\n language: bun\n input_transforms:\n approver:\n type: static\n value: ''\n content: |\n import * as wmill from \"windmill-client\"\n\n export async function main(approver?: string) {\n const urls = await wmill.getResumeUrls(approver)\n // send urls.resume / urls.cancel to the approver(s), e.g. via Slack or email\n return urls\n }\n```\n\nIncorrect shape (suspend misplaced inside `value`):\n\n```yaml\n- id: request_approval\n value:\n type: rawscript\n suspend:\n required_events: 1\n```\n\nIncorrect shape (identity has no resume URLs — not a real approval):\n\n```yaml\n- id: request_approval\n suspend:\n required_events: 1\n value:\n type: identity\n```\n\n## Branch Result Scope Rules\n\n- A `branchone` runs the first of its `branches` whose `expr` is true, in order, and its `default` modules when none is; a `branchall` runs every branch (concurrently with `parallel: true`)\n- Inside a branch, you may reference earlier outer steps and earlier steps in the same branch\n- Outside a `branchone`, do NOT reference ids of steps that only exist inside its branches or default branch. Use `results.` instead\n- Outside a `branchall`, do NOT reference ids of steps inside its branches. Use `results.` instead\n- If downstream steps need a stable shape after a branch, make each branch return the same fields\n- When needed, add a normalization step immediately after the branch and consume `results.` there\n\nCorrect after `branchone`:\n\n```yaml\n- id: route_order\n value:\n type: branchone\n ...\n- id: send_confirmation\n value:\n input_transforms:\n routed:\n type: javascript\n expr: results.route_order\n```\n\nIncorrect after `branchone`:\n\n```yaml\nexpr: results.create_shipment\nexpr: results.create_backorder\n```\n\nCorrect after `branchall`:\n\n```yaml\n- id: enrich_parallel\n value:\n type: branchall\n parallel: true\n ...\n- id: combine_data\n value:\n input_transforms:\n enrichments:\n type: javascript\n expr: results.enrich_parallel\n```\n\n## Input Transforms\n\nEvery rawscript module needs `input_transforms` to map function parameters to values:\n\nStatic transform (fixed value):\n{\"param_name\": {\"type\": \"static\", \"value\": \"fixed_string\"}}\n\nJavaScript transform (dynamic expression):\n{\"param_name\": {\"type\": \"javascript\", \"expr\": \"results.previous_step.data\"}}\n\n## Resource References\n\n- For flow inputs: Use type `\"object\"` with format `\"resource-{type}\"` (e.g., `\"resource-postgresql\"`)\n- For step inputs: Use static value `\"$res:path/to/resource\"`\n\n## Reusing Existing Scripts and Flows\n\nUnless the user asked for new code, look for a workspace script or flow that already does a step's job before writing it, and reuse it by path instead of copying its logic into a rawscript:\n\n- a workspace script: `type: script` with `path` (e.g. `f/folder/send_email`)\n- a workspace flow, run as a subflow: `type: flow` with `path`\n- a Hub script: `type: script` with a `hub///` path\n\nThe step's `input_transforms` must cover the reused item's inputs, so read its input schema first.\n\n## Additional Prompt for AI\n\nA flow's input schema may carry a top-level `prompt_for_ai` string, as a script's can: its author's instructions to an AI choosing the inputs. Follow it when you pick arguments to run that flow, and keep it when you rewrite the schema.\n\n## Organizing Flows: Groups and Notes\n\nGroups and notes shape how a flow reads in the editor; neither changes what it does.\n\n**Segment every non-trivial flow into groups without waiting to be asked.** Whenever a flow has more than a couple of steps, or consecutive steps form a stage (\"fetch\", \"transform\", \"notify\"), put them in a group, and aim for every meaningful step to belong to one. Use notes sparingly, for flow-wide information that belongs to no span of steps: the flow's purpose, key assumptions, warnings, TODOs. One note is usually enough; never label a run of steps with a note, which is what a group is for.\n\n`value.groups` lists the groups, each spanning the steps from `start_id` to `end_id`:\n\n- `start_id`, `end_id` (required): ids of the group's first and last step; the same id for both makes a one-step group\n- `summary`: the group's title\n- `note`: markdown shown under the title\n- `color`: one of `yellow`, `blue`, `green`, `purple`, `pink`, `orange`, `red`, `cyan`, `lime`, `gray`, never a hex code or CSS color; leave it out and the editor picks one\n- `autocollapse`: `true` shows the group collapsed by default\n\nThe editor refuses to draw a flow whose groups break any of these rules:\n\n- `start_id` and `end_id` are steps of the same list: both top-level, or both in the same loop body or branch. A group can hold a loop or branch step whole, but cannot start outside one and end inside it\n- `start_id` does not come after `end_id` in that list\n- groups nest (one entirely inside another) but never partly overlap, and no two groups share both `start_id` and `end_id`\n- groups hold ordinary steps only: never `preprocessor`, `failure`, `Input`, `Result`, `Trigger`, or an AI agent's tools\n\n`value.notes` lists sticky notes, each with a unique `id`, markdown `text`, a `color` from the same list, and `type: free`. The `group` note type is deprecated; use `value.groups` instead.\nLeave a note's `position` and `size` out and they are filled in for you.\n\n## Final Structural Self-Check\n\nBefore finalizing a flow, verify:\n\n- any preprocessor is in `value.preprocessor_module`\n- any failure handler is in `value.failure_module`\n- any approval step has module-level `suspend`\n- no downstream step references inner branch step ids from outside the branch\n- every AI agent flowmodule tool has a unique `summary` made only of letters, numbers and underscores\n- every group starts and ends on steps of the same list, start before end, nesting without partial overlap\n\n## S3 Object Operations\n\nWindmill provides built-in support for S3-compatible storage operations.\n\nTo accept an S3 object as flow input:\n\n```json\n{\n \"type\": \"object\",\n \"properties\": {\n \"file\": {\n \"type\": \"object\",\n \"format\": \"resource-s3_object\",\n \"description\": \"File to process\"\n }\n }\n}\n```\n\n## Using Resources in Flows\n\nOn Windmill, credentials and configuration are stored in resources. Resource types define the format of the resource.\n\n### As Flow Input\n\nIn the flow schema, set the property type to `\"object\"` with format `\"resource-{type}\"`:\n\n```json\n{\n \"type\": \"object\",\n \"properties\": {\n \"database\": {\n \"type\": \"object\",\n \"format\": \"resource-postgresql\",\n \"description\": \"Database connection\"\n }\n }\n}\n```\n\n### When No Resource Type Fits\n\nA connection still comes in as one resource input, not as separate string inputs (a URL, a token) or a variable read inside a step: type the input `resource-c_` with a custom resource type holding the service's connection fields, its secret in a variable the resource references. The `c_` prefix of custom types keeps one apart from a hub type synced later under the same name.\n\n- If the instance is reported as not having synced the Windmill Hub's resource types, mention that a superadmin can sync them, since the hub has types for most services.\n- Otherwise, or when the user prefers it to syncing, propose the resource type and ask before creating it.\n- A plain variable is fine when the user asks for it.\n\n### As Step Input (Static Reference)\n\nReference a specific resource using `$res:` prefix:\n\n```json\n{\n \"database\": {\n \"type\": \"static\",\n \"value\": \"$res:f/folder/my_database\"\n }\n}\n```\n\n\n## OpenFlow Schema\n\n{\"OpenFlow\":{\"type\":\"object\",\"description\":\"Top-level flow definition containing metadata, configuration, and the flow structure\",\"properties\":{\"summary\":{\"type\":\"string\",\"description\":\"Short description of what this flow does\"},\"description\":{\"type\":\"string\",\"description\":\"Detailed documentation for this flow\"},\"value\":{\"$ref\":\"#/components/schemas/FlowValue\"},\"schema\":{\"type\":\"object\",\"description\":\"JSON Schema for flow inputs. Use this to define input parameters, their types, defaults, and validation. For resource inputs, set type to 'object' and format to 'resource-' (e.g., 'resource-stripe')\"},\"on_behalf_of_email\":{\"type\":\"string\",\"description\":\"Address of the account the flow runs on behalf of. Derived from on_behalf_of on read; accepted on write, where it is resolved to the account it names.\"},\"on_behalf_of\":{\"type\":\"string\",\"description\":\"The flow runs with the permissions of this identity: u/{username}, g/{group}, or a bare email when the username is itself email-shaped. The only stored half of the identity; on_behalf_of_email is derived from it. Omit it when writing and it is resolved from that address instead.\"}},\"required\":[\"summary\",\"value\"]},\"FlowValue\":{\"type\":\"object\",\"description\":\"The flow structure containing modules and optional preprocessor/failure handlers\",\"properties\":{\"modules\":{\"type\":\"array\",\"description\":\"Array of steps that execute in sequence. Each step can be a script, subflow, loop, or branch\",\"items\":{\"$ref\":\"#/components/schemas/FlowModule\"}},\"failure_module\":{\"description\":\"Special module that executes when the flow fails. Receives error object with message, name, stack, and step_id. Must have id 'failure'. Only supports script/rawscript types\",\"$ref\":\"#/components/schemas/FlowModule\"},\"preprocessor_module\":{\"description\":\"Special module that runs before the first step on external triggers. Must have id 'preprocessor'. Only supports script/rawscript types. Cannot reference other step results\",\"$ref\":\"#/components/schemas/FlowModule\"},\"same_worker\":{\"type\":\"boolean\",\"description\":\"If true, all steps run on the same worker for better performance\"},\"preserve_step_tags\":{\"type\":\"boolean\",\"description\":\"If true and the flow runs on a custom worker tag, steps that declare their own non-empty tag run on it instead of inheriting the flow tag. Steps without their own tag still inherit the flow tag.\"},\"concurrent_limit\":{\"type\":\"number\",\"description\":\"Maximum number of concurrent executions of this flow\"},\"concurrency_key\":{\"type\":\"string\",\"description\":\"Expression to group concurrent executions (e.g., by user ID)\"},\"concurrency_time_window_s\":{\"type\":\"number\",\"description\":\"Time window in seconds for concurrent_limit\"},\"debounce_delay_s\":{\"type\":\"integer\",\"description\":\"Delay in seconds to debounce flow executions\"},\"debounce_key\":{\"type\":\"string\",\"description\":\"Expression to group debounced executions\"},\"debounce_args_to_accumulate\":{\"type\":\"array\",\"description\":\"Arguments to accumulate across debounced executions\",\"items\":{\"type\":\"string\"}},\"max_total_debouncing_time\":{\"type\":\"integer\",\"description\":\"Maximum total time in seconds that a job can be debounced\"},\"max_total_debounces_amount\":{\"type\":\"integer\",\"description\":\"Maximum number of times a job can be debounced\"},\"skip_expr\":{\"type\":\"string\",\"description\":\"JavaScript expression to conditionally skip the entire flow\"},\"cache_ttl\":{\"type\":\"number\",\"description\":\"Cache duration in seconds for flow results\"},\"cache_ignore_s3_path\":{\"type\":\"boolean\"},\"delete_after_secs\":{\"type\":\"integer\",\"description\":\"If set, delete the flow job's args, result and logs after this many seconds following job completion\"},\"flow_env\":{\"type\":\"object\",\"description\":\"Environment variables available to all steps. Values can be strings, JSON values, or special references: '$var:path' (workspace variable) or '$res:path' (resource).\",\"additionalProperties\":{}},\"priority\":{\"type\":\"number\",\"description\":\"Execution priority (higher numbers run first)\"},\"early_return\":{\"type\":\"string\",\"description\":\"Id of the step whose result a sync webhook returns as soon as that step completes, while the rest of the flow keeps running. When the step does not run, or fails while the flow has a failure module, the flow's final result is returned instead.\"},\"chat_input_enabled\":{\"type\":\"boolean\",\"description\":\"Whether this flow accepts chat-style input\"},\"notes\":{\"type\":\"array\",\"description\":\"Sticky notes attached to the flow\",\"items\":{\"$ref\":\"#/components/schemas/FlowNote\"}},\"groups\":{\"type\":\"array\",\"description\":\"Semantic groups of modules for organizational purposes\",\"items\":{\"$ref\":\"#/components/schemas/FlowGroup\"}}},\"required\":[\"modules\"]},\"Retry\":{\"type\":\"object\",\"description\":\"Retry configuration for failed module executions\",\"properties\":{\"constant\":{\"type\":\"object\",\"description\":\"Retry with constant delay between attempts\",\"properties\":{\"attempts\":{\"type\":\"integer\",\"description\":\"Number of retry attempts\"},\"seconds\":{\"type\":\"integer\",\"description\":\"Seconds to wait between retries\"}}},\"exponential\":{\"type\":\"object\",\"description\":\"Retry with exponential backoff: the n-th retry waits multiplier \\u00d7 seconds^n\",\"properties\":{\"attempts\":{\"type\":\"integer\",\"description\":\"Number of retry attempts\"},\"multiplier\":{\"type\":\"integer\",\"description\":\"Multiplier for exponential backoff\"},\"seconds\":{\"type\":\"integer\",\"minimum\":1,\"description\":\"Base of the exponential (seconds); the n-th retry waits multiplier \\u00d7 seconds^n, where n counts constant retries too\"},\"random_factor\":{\"type\":\"integer\",\"minimum\":0,\"maximum\":100,\"description\":\"Random jitter percentage (0-100) to avoid thundering herd\"}}},\"retry_if\":{\"$ref\":\"#/components/schemas/RetryIf\"}}},\"FlowNote\":{\"type\":\"object\",\"description\":\"A sticky note attached to a flow for documentation and annotation\",\"properties\":{\"id\":{\"type\":\"string\",\"description\":\"Unique identifier for the note\"},\"text\":{\"type\":\"string\",\"description\":\"Content of the note\"},\"position\":{\"type\":\"object\",\"description\":\"Position of the note in the flow editor\",\"properties\":{\"x\":{\"type\":\"number\",\"description\":\"X coordinate\"},\"y\":{\"type\":\"number\",\"description\":\"Y coordinate\"}},\"required\":[\"x\",\"y\"]},\"size\":{\"type\":\"object\",\"description\":\"Size of the note in the flow editor\",\"properties\":{\"width\":{\"type\":\"number\",\"description\":\"Width in pixels\"},\"height\":{\"type\":\"number\",\"description\":\"Height in pixels\"}},\"required\":[\"width\",\"height\"]},\"color\":{\"type\":\"string\",\"description\":\"Color of the note, one of: yellow, blue, green, purple, pink, orange, red, cyan, lime, gray. Any other value renders unstyled.\"},\"type\":{\"type\":\"string\",\"enum\":[\"free\",\"group\"],\"description\":\"Type of note - 'free' for standalone notes. 'group' notes are deprecated; segment a flow with FlowValue.groups instead.\"},\"locked\":{\"type\":\"boolean\",\"default\":false,\"description\":\"Whether the note is locked and cannot be edited or moved\"},\"contained_node_ids\":{\"type\":\"array\",\"items\":{\"type\":\"string\"},\"description\":\"For group notes, the IDs of nodes contained within this group\"}},\"required\":[\"id\",\"text\",\"color\",\"type\"]},\"FlowGroup\":{\"type\":\"object\",\"description\":\"A semantic group of flow modules for organizational purposes. Does not affect execution \\u2014 modules remain in their original position in the flow. Groups provide naming and collapsibility in the editor. Members are computed dynamically from all nodes on paths between start_id and end_id.\",\"properties\":{\"summary\":{\"type\":\"string\",\"description\":\"Display name for this group\"},\"note\":{\"type\":\"string\",\"description\":\"Markdown note shown below the group header\"},\"autocollapse\":{\"type\":\"boolean\",\"default\":false,\"description\":\"If true, this group is collapsed by default in the flow editor. UI hint only.\"},\"start_id\":{\"type\":\"string\",\"description\":\"ID of the first flow module in this group (topological entry point)\"},\"end_id\":{\"type\":\"string\",\"description\":\"ID of the last flow module in this group (topological exit point)\"},\"color\":{\"type\":\"string\",\"description\":\"Color for the group in the flow editor, one of: yellow, blue, green, purple, pink, orange, red, cyan, lime, gray. Omit it to let the editor pick one.\"}},\"required\":[\"start_id\",\"end_id\"]},\"RetryIf\":{\"type\":\"object\",\"description\":\"Conditional retry based on error or result\",\"properties\":{\"expr\":{\"type\":\"string\",\"description\":\"JavaScript expression that returns true to retry. Has access to 'result' and 'error' variables\"}},\"required\":[\"expr\"]},\"StopAfterIf\":{\"type\":\"object\",\"description\":\"Early termination condition for a module\",\"properties\":{\"skip_if_stopped\":{\"type\":\"boolean\",\"description\":\"If true, following steps are skipped when this condition triggers\"},\"expr\":{\"type\":\"string\",\"description\":\"JavaScript expression evaluated after the module runs. Can use 'result' (step's result) or 'flow_input'. Return true to stop\"},\"error_message\":{\"type\":\"string\",\"nullable\":true,\"description\":\"Custom error message when stopping with an error. Mutually exclusive with skip_if_stopped. If set to a non-empty string, the flow stops with this error. If empty string, a default error message is used. If null or omitted, no error is raised.\"},\"error_include_result\":{\"type\":\"boolean\",\"description\":\"When stopping with an error (error_message set), embed the stopping step's own result inside the raised error object (as error.result) instead of discarding it. The top-level result stays { error }. Defaults to false.\"}},\"required\":[\"expr\"]},\"FlowModule\":{\"type\":\"object\",\"description\":\"A single step in a flow. Can be a script, subflow, loop, or branch\",\"properties\":{\"id\":{\"type\":\"string\",\"description\":\"Unique identifier for this step. Used to reference results via 'results.step_id'. Must be a valid identifier (alphanumeric, underscore, hyphen)\"},\"value\":{\"$ref\":\"#/components/schemas/FlowModuleValue\"},\"stop_after_if\":{\"description\":\"Early termination condition evaluated after this step completes\",\"$ref\":\"#/components/schemas/StopAfterIf\"},\"stop_after_all_iters_if\":{\"description\":\"For loops only - early termination condition evaluated after all iterations complete\",\"$ref\":\"#/components/schemas/StopAfterIf\"},\"skip_if\":{\"type\":\"object\",\"description\":\"Conditionally skip this step based on previous results or flow inputs\",\"properties\":{\"expr\":{\"type\":\"string\",\"description\":\"JavaScript expression that returns true to skip. Can use 'flow_input' or 'results.'\"}},\"required\":[\"expr\"]},\"sleep\":{\"description\":\"Delay before executing this step (in seconds or as expression)\",\"$ref\":\"#/components/schemas/InputTransform\"},\"cache_ttl\":{\"type\":\"number\",\"description\":\"Cache duration in seconds for this step's results\"},\"cache_ignore_s3_path\":{\"type\":\"boolean\"},\"timeout\":{\"description\":\"Maximum execution time in seconds (static value or expression)\",\"$ref\":\"#/components/schemas/InputTransform\"},\"delete_after_secs\":{\"type\":\"integer\",\"description\":\"If set, delete the step's args, result and logs after this many seconds following job completion\"},\"summary\":{\"type\":\"string\",\"description\":\"Short description of what this step does\"},\"mock\":{\"type\":\"object\",\"description\":\"Mock configuration for testing without executing the actual step\",\"properties\":{\"enabled\":{\"type\":\"boolean\",\"description\":\"If true, return mock value instead of executing\"},\"return_value\":{\"description\":\"Value to return when mocked\"}}},\"suspend\":{\"type\":\"object\",\"description\":\"Configuration for approval/resume steps that wait for user input\",\"properties\":{\"required_events\":{\"type\":\"integer\",\"description\":\"Number of approvals required before continuing\"},\"timeout\":{\"type\":\"integer\",\"description\":\"Timeout in seconds before auto-continuing or canceling\"},\"resume_form\":{\"type\":\"object\",\"description\":\"Form schema for collecting input when resuming\",\"properties\":{\"schema\":{\"type\":\"object\",\"description\":\"JSON Schema for the resume form\"}}},\"user_auth_required\":{\"type\":\"boolean\",\"description\":\"If true, only authenticated users can approve\"},\"user_groups_required\":{\"description\":\"Expression or list of groups that can approve\",\"$ref\":\"#/components/schemas/InputTransform\"},\"self_approval_disabled\":{\"type\":\"boolean\",\"description\":\"If true, the user who started the flow cannot approve\"},\"hide_cancel\":{\"type\":\"boolean\",\"description\":\"If true, hide the cancel button on the approval form\"},\"continue_on_disapprove_timeout\":{\"type\":\"boolean\",\"description\":\"If true, continue flow on timeout instead of canceling\"},\"skin\":{\"type\":\"string\",\"enum\":[\"detailed\",\"minimal\"],\"description\":\"How the approval request is presented, on the approval page and in Slack/Teams approval messages. 'detailed' (used when unset) shows the flow details (arguments, graph, approvers); 'minimal' shows only the request: the step description, form and approve/reject actions\"}}},\"priority\":{\"type\":\"number\",\"description\":\"Execution priority for this step (higher numbers run first)\"},\"continue_on_error\":{\"type\":\"boolean\",\"description\":\"If true, flow continues even if this step fails\"},\"job_token_scopes\":{\"type\":\"array\",\"nullable\":true,\"items\":{\"type\":\"string\"},\"description\":\"Scopes the token of this step's jobs is restricted to (domain:action[:resource], e.g. oidc:write), on top of the flow's own restriction: a step can only narrow it. Applies to everything the step runs (loop and branch bodies, AI agent tools).\"},\"retry\":{\"description\":\"Retry configuration if this step fails\",\"$ref\":\"#/components/schemas/Retry\"},\"debouncing\":{\"description\":\"Debounce configuration for this step (EE only)\",\"type\":\"object\",\"properties\":{\"debounce_delay_s\":{\"type\":\"integer\",\"description\":\"Delay in seconds to debounce this step's executions across flow runs\"},\"debounce_key\":{\"type\":\"string\",\"description\":\"Expression to group debounced executions. Supports $workspace and $args[name]. Default: $workspace/flow/-\"},\"debounce_args_to_accumulate\":{\"type\":\"array\",\"description\":\"Array-type arguments to accumulate across debounced executions\",\"items\":{\"type\":\"string\"}},\"max_total_debouncing_time\":{\"type\":\"integer\",\"description\":\"Maximum total time in seconds before forced execution\"},\"max_total_debounces_amount\":{\"type\":\"integer\",\"description\":\"Maximum number of debounces before forced execution\"}}}},\"required\":[\"value\",\"id\"]},\"InputTransform\":{\"description\":\"Maps input parameters for a step. Can be a static value or a JavaScript expression that references previous results or flow inputs\",\"oneOf\":[{\"$ref\":\"#/components/schemas/StaticTransform\"},{\"$ref\":\"#/components/schemas/JavascriptTransform\"},{\"$ref\":\"#/components/schemas/AiTransform\"}],\"discriminator\":{\"propertyName\":\"type\",\"mapping\":{\"static\":\"#/components/schemas/StaticTransform\",\"javascript\":\"#/components/schemas/JavascriptTransform\",\"ai\":\"#/components/schemas/AiTransform\"}}},\"StaticTransform\":{\"type\":\"object\",\"description\":\"Static value passed directly to the step. Use for hardcoded values or resource references like '$res:path/to/resource'\",\"properties\":{\"value\":{\"description\":\"The static value. For resources, use format '$res:path/to/resource'\"},\"type\":{\"type\":\"string\",\"enum\":[\"static\"]}},\"required\":[\"type\"]},\"JavascriptTransform\":{\"type\":\"object\",\"description\":\"JavaScript expression evaluated at runtime. Can reference previous step results via 'results.step_id' or flow inputs via 'flow_input.property'. Inside for loops, use 'flow_input.iter.value' for the current iteration value (in while loops it equals 'flow_input.iter.index')\",\"properties\":{\"expr\":{\"type\":\"string\",\"description\":\"JavaScript expression returning the value. Available variables - results (object with all previous step results), flow_input (flow inputs), flow_input.iter (in loops)\"},\"type\":{\"type\":\"string\",\"enum\":[\"javascript\"]}},\"required\":[\"expr\",\"type\"]},\"AiTransform\":{\"type\":\"object\",\"description\":\"Value resolved by the AI runtime for this input. The AI engine decides how to satisfy the parameter.\",\"properties\":{\"type\":{\"type\":\"string\",\"enum\":[\"ai\"]}},\"required\":[\"type\"]},\"AIProviderKind\":{\"type\":\"string\",\"description\":\"Supported AI provider types\",\"enum\":[\"openai\",\"azure_openai\",\"azure_foundry\",\"anthropic\",\"mistral\",\"deepseek\",\"googleai\",\"groq\",\"openrouter\",\"togetherai\",\"customai\",\"aws_bedrock\",\"typesafe\",\"cloudflare\"]},\"ProviderConfig\":{\"type\":\"object\",\"description\":\"Complete AI provider configuration with resource reference and model selection\",\"properties\":{\"kind\":{\"$ref\":\"#/components/schemas/AIProviderKind\"},\"resource\":{\"type\":\"string\",\"description\":\"Resource reference in format '$res:{resource_path}' pointing to provider credentials\"},\"model\":{\"type\":\"string\",\"description\":\"Model identifier (e.g., 'gpt-4', 'claude-3-opus-20240229', 'gemini-pro')\"},\"reasoning_effort\":{\"type\":\"string\",\"description\":\"Provider-native reasoning effort token (e.g. 'low', 'high', 'none') for models that support extended thinking. Optional; unset leaves the provider default.\"}},\"required\":[\"kind\",\"resource\",\"model\"]},\"StaticProviderTransform\":{\"type\":\"object\",\"description\":\"Static provider configuration passed directly to the AI agent\",\"properties\":{\"value\":{\"$ref\":\"#/components/schemas/ProviderConfig\"},\"type\":{\"type\":\"string\",\"enum\":[\"static\"]}},\"required\":[\"type\",\"value\"]},\"ProviderTransform\":{\"description\":\"Provider configuration - can be static (ProviderConfig), JavaScript expression, or AI-determined\",\"oneOf\":[{\"$ref\":\"#/components/schemas/StaticProviderTransform\"},{\"$ref\":\"#/components/schemas/JavascriptTransform\"},{\"$ref\":\"#/components/schemas/AiTransform\"}],\"discriminator\":{\"propertyName\":\"type\",\"mapping\":{\"static\":\"#/components/schemas/StaticProviderTransform\",\"javascript\":\"#/components/schemas/JavascriptTransform\",\"ai\":\"#/components/schemas/AiTransform\"}}},\"MemoryOff\":{\"type\":\"object\",\"description\":\"No conversation memory/context\",\"properties\":{\"kind\":{\"type\":\"string\",\"enum\":[\"off\"]}},\"required\":[\"kind\"]},\"MemoryWindow\":{\"type\":\"object\",\"description\":\"Keeps the most recent messages of the memory named by the run's memory id (or the step's\\n`memory_id`). Without a memory id the agent runs without memory.\\n\",\"properties\":{\"kind\":{\"type\":\"string\",\"enum\":[\"window\"]},\"context_length\":{\"type\":\"integer\",\"description\":\"Number of most recent messages to load and store. 0 turns memory off.\"}},\"required\":[\"kind\",\"context_length\"]},\"MemoryAuto\":{\"type\":\"object\",\"deprecated\":true,\"description\":\"Deprecated, still read as it was written: the run's memory id, else the `memory_id` here.\\nThe step's own `memory_id` is not read while this kind is set; switch the kind to `window`\\nto use it. Without a `context_length`, or with 0, it is `off` and reads `previous_messages`.\\n\",\"properties\":{\"kind\":{\"type\":\"string\",\"enum\":[\"auto\"]},\"context_length\":{\"type\":\"integer\",\"description\":\"Maximum number of messages to retain in context\"},\"memory_id\":{\"type\":\"string\",\"description\":\"Identifier for persistent memory across agent invocations\"}},\"required\":[\"kind\"]},\"MemoryCompaction\":{\"type\":\"object\",\"description\":\"Keeps the whole memory named by the run's memory id (or the step's `memory_id`), replacing\\nits older part with a summary as the conversation approaches the model's context window.\\nWithout a memory id the agent runs without memory, and compaction bounds the run's own loop.\\n\",\"properties\":{\"kind\":{\"type\":\"string\",\"enum\":[\"compaction\"]},\"context_window\":{\"type\":\"integer\",\"description\":\"Overrides the context window looked up from the model, in tokens. Only a model\\nWindmill does not know needs one; those fall back to 128000.\\n\"}},\"required\":[\"kind\"]},\"MemoryMessage\":{\"type\":\"object\",\"description\":\"A single message in conversation history\",\"properties\":{\"role\":{\"type\":\"string\",\"enum\":[\"user\",\"assistant\",\"system\"]},\"content\":{\"type\":\"string\"}},\"required\":[\"role\",\"content\"]},\"MemoryManual\":{\"type\":\"object\",\"deprecated\":true,\"description\":\"Deprecated, still read as it was written. Move the step to `off` with `previous_messages` instead.\",\"properties\":{\"kind\":{\"type\":\"string\",\"enum\":[\"manual\"]},\"messages\":{\"type\":\"array\",\"items\":{\"$ref\":\"#/components/schemas/MemoryMessage\"}}},\"required\":[\"kind\",\"messages\"]},\"MemoryConfig\":{\"description\":\"Managed memory, stored by Windmill and replayed with each request. The memory is named by a memory id, see `memory_id`. While it is off, a step can supply its history in `previous_messages`.\",\"oneOf\":[{\"$ref\":\"#/components/schemas/MemoryOff\"},{\"$ref\":\"#/components/schemas/MemoryWindow\"},{\"$ref\":\"#/components/schemas/MemoryCompaction\"},{\"$ref\":\"#/components/schemas/MemoryAuto\"},{\"$ref\":\"#/components/schemas/MemoryManual\"}],\"discriminator\":{\"propertyName\":\"kind\",\"mapping\":{\"off\":\"#/components/schemas/MemoryOff\",\"window\":\"#/components/schemas/MemoryWindow\",\"compaction\":\"#/components/schemas/MemoryCompaction\",\"auto\":\"#/components/schemas/MemoryAuto\",\"manual\":\"#/components/schemas/MemoryManual\"}}},\"StaticMemoryTransform\":{\"type\":\"object\",\"description\":\"Static memory configuration passed directly to the AI agent\",\"properties\":{\"value\":{\"$ref\":\"#/components/schemas/MemoryConfig\"},\"type\":{\"type\":\"string\",\"enum\":[\"static\"]}},\"required\":[\"type\",\"value\"]},\"MemoryTransform\":{\"description\":\"Memory configuration - can be static (MemoryConfig), JavaScript expression, or AI-determined\",\"oneOf\":[{\"$ref\":\"#/components/schemas/StaticMemoryTransform\"},{\"$ref\":\"#/components/schemas/JavascriptTransform\"},{\"$ref\":\"#/components/schemas/AiTransform\"}],\"discriminator\":{\"propertyName\":\"type\",\"mapping\":{\"static\":\"#/components/schemas/StaticMemoryTransform\",\"javascript\":\"#/components/schemas/JavascriptTransform\",\"ai\":\"#/components/schemas/AiTransform\"}}},\"FlowModuleValue\":{\"description\":\"The actual implementation of a flow step. Can be a script (inline or referenced), subflow, loop, branch, or special module type\",\"oneOf\":[{\"$ref\":\"#/components/schemas/RawScript\"},{\"$ref\":\"#/components/schemas/PathScript\"},{\"$ref\":\"#/components/schemas/PathFlow\"},{\"$ref\":\"#/components/schemas/ForloopFlow\"},{\"$ref\":\"#/components/schemas/WhileloopFlow\"},{\"$ref\":\"#/components/schemas/BranchOne\"},{\"$ref\":\"#/components/schemas/BranchAll\"},{\"$ref\":\"#/components/schemas/Identity\"},{\"$ref\":\"#/components/schemas/AiAgent\"},{\"$ref\":\"#/components/schemas/AiDecision\"}],\"discriminator\":{\"propertyName\":\"type\",\"mapping\":{\"rawscript\":\"#/components/schemas/RawScript\",\"script\":\"#/components/schemas/PathScript\",\"flow\":\"#/components/schemas/PathFlow\",\"forloopflow\":\"#/components/schemas/ForloopFlow\",\"whileloopflow\":\"#/components/schemas/WhileloopFlow\",\"branchone\":\"#/components/schemas/BranchOne\",\"branchall\":\"#/components/schemas/BranchAll\",\"identity\":\"#/components/schemas/Identity\",\"aiagent\":\"#/components/schemas/AiAgent\",\"aidecision\":\"#/components/schemas/AiDecision\"}}},\"RawScript\":{\"type\":\"object\",\"description\":\"Inline script with code defined directly in the flow. Use 'bun' as default language if unspecified. The script receives arguments from input_transforms\",\"properties\":{\"input_transforms\":{\"type\":\"object\",\"description\":\"Map of parameter names to their values (static or JavaScript expressions). These become the script's input arguments\",\"additionalProperties\":{\"$ref\":\"#/components/schemas/InputTransform\"}},\"content\":{\"type\":\"string\",\"description\":\"The script source code. Should export a 'main' function\"},\"language\":{\"type\":\"string\",\"description\":\"Programming language for this script\",\"enum\":[\"deno\",\"bun\",\"bunnative\",\"python3\",\"go\",\"bash\",\"powershell\",\"postgresql\",\"mysql\",\"bigquery\",\"snowflake\",\"mssql\",\"oracledb\",\"graphql\",\"nativets\",\"php\",\"rust\",\"ansible\",\"csharp\",\"nu\",\"java\",\"ruby\",\"rlang\",\"duckdb\"]},\"path\":{\"type\":\"string\",\"description\":\"Optional path for saving this script\"},\"lock\":{\"type\":\"string\",\"description\":\"Lock file content for dependencies\"},\"type\":{\"type\":\"string\",\"enum\":[\"rawscript\"]},\"tag\":{\"type\":\"string\",\"description\":\"Worker group tag for execution routing\"},\"concurrent_limit\":{\"type\":\"number\",\"description\":\"Maximum concurrent executions of this script\"},\"concurrency_time_window_s\":{\"type\":\"number\",\"description\":\"Time window for concurrent_limit\"},\"custom_concurrency_key\":{\"type\":\"string\",\"description\":\"Custom key for grouping concurrent executions\"},\"is_trigger\":{\"type\":\"boolean\",\"description\":\"If true, this script is a trigger that can start the flow\"},\"assets\":{\"type\":\"array\",\"description\":\"External resources this script accesses (S3 objects, resources, etc.)\",\"items\":{\"type\":\"object\",\"required\":[\"path\",\"kind\"],\"properties\":{\"path\":{\"type\":\"string\",\"description\":\"Path to the asset\"},\"kind\":{\"type\":\"string\",\"description\":\"Type of asset\",\"enum\":[\"s3object\",\"resource\",\"ducklake\",\"datatable\",\"volume\",\"dbt\"]},\"access_type\":{\"type\":\"string\",\"nullable\":true,\"description\":\"Access level for this asset\",\"enum\":[\"r\",\"w\",\"rw\"]},\"alt_access_type\":{\"type\":\"string\",\"nullable\":true,\"description\":\"Alternative access level\",\"enum\":[\"r\",\"w\",\"rw\"]}}}}},\"required\":[\"type\",\"content\",\"language\",\"input_transforms\"]},\"PathScript\":{\"type\":\"object\",\"description\":\"Reference to an existing script by path. Use this when calling a previously saved script instead of writing inline code\",\"properties\":{\"input_transforms\":{\"type\":\"object\",\"description\":\"Map of parameter names to their values (static or JavaScript expressions). These become the script's input arguments\",\"additionalProperties\":{\"$ref\":\"#/components/schemas/InputTransform\"}},\"path\":{\"type\":\"string\",\"description\":\"Path to the script in the workspace (e.g., 'f/scripts/send_email')\"},\"hash\":{\"type\":\"string\",\"description\":\"Optional specific version hash of the script to use\"},\"type\":{\"type\":\"string\",\"enum\":[\"script\"]},\"tag_override\":{\"type\":\"string\",\"description\":\"Override the script's default worker group tag\"},\"is_trigger\":{\"type\":\"boolean\",\"description\":\"If true, this script is a trigger that can start the flow\"}},\"required\":[\"type\",\"path\",\"input_transforms\"]},\"PathFlow\":{\"type\":\"object\",\"description\":\"Reference to an existing flow by path. Use this to call another flow as a subflow\",\"properties\":{\"input_transforms\":{\"type\":\"object\",\"description\":\"Map of parameter names to their values (static or JavaScript expressions). These become the subflow's input arguments\",\"additionalProperties\":{\"$ref\":\"#/components/schemas/InputTransform\"}},\"path\":{\"type\":\"string\",\"description\":\"Path to the flow in the workspace (e.g., 'f/flows/process_user')\"},\"type\":{\"type\":\"string\",\"enum\":[\"flow\"]}},\"required\":[\"type\",\"path\",\"input_transforms\"]},\"ForloopFlow\":{\"type\":\"object\",\"description\":\"Executes nested modules in a loop over an iterator. Inside the loop, use 'flow_input.iter.value' to access the current iteration value, and 'flow_input.iter.index' for the index. Supports parallel execution for better performance on I/O-bound operations\",\"properties\":{\"modules\":{\"type\":\"array\",\"description\":\"Steps to execute for each iteration. These can reference the iteration value via 'flow_input.iter.value'\",\"items\":{\"$ref\":\"#/components/schemas/FlowModule\"}},\"iterator\":{\"description\":\"JavaScript expression that returns an array to iterate over. Can reference 'results.step_id' or 'flow_input'\",\"$ref\":\"#/components/schemas/InputTransform\"},\"skip_failures\":{\"type\":\"boolean\",\"description\":\"If true, iteration failures don't stop the loop. Failed iterations return null\"},\"type\":{\"type\":\"string\",\"enum\":[\"forloopflow\"]},\"parallel\":{\"type\":\"boolean\",\"description\":\"If true, iterations run concurrently (faster for I/O-bound operations). Use with parallelism to control concurrency\"},\"parallelism\":{\"description\":\"Maximum number of concurrent iterations when parallel=true. Limits resource usage. Can be static number or expression\",\"$ref\":\"#/components/schemas/InputTransform\"},\"squash\":{\"type\":\"boolean\"}},\"required\":[\"modules\",\"iterator\",\"skip_failures\",\"type\"]},\"WhileloopFlow\":{\"type\":\"object\",\"description\":\"Executes nested modules repeatedly until stopped. The implicit iterator is the iteration counter, so 'flow_input.iter.value' equals 'flow_input.iter.index' (0, 1, 2, ...) and never carries state. To carry state across iterations, a step reads its own previous-iteration result via 'results.' with a first-iteration fallback - the loop's stop_after_if must then be on that inner step (a plain single-step body with stop_after_if on the loop module does not resolve 'results' across iterations and never terminates); plain counters can instead be derived from 'flow_input.iter.index', which works in every configuration. stop_after_if is evaluated after each iteration - on the loop module 'result' is the last iteration's result\",\"properties\":{\"modules\":{\"type\":\"array\",\"description\":\"Steps to execute in each iteration\",\"items\":{\"$ref\":\"#/components/schemas/FlowModule\"}},\"skip_failures\":{\"type\":\"boolean\",\"description\":\"If true, iteration failures don't stop the loop. Failed iterations return null\"},\"type\":{\"type\":\"string\",\"enum\":[\"whileloopflow\"]},\"parallel\":{\"type\":\"boolean\",\"description\":\"If true, iterations run concurrently (use with caution in while loops)\"},\"parallelism\":{\"description\":\"Maximum number of concurrent iterations when parallel=true\",\"$ref\":\"#/components/schemas/InputTransform\"},\"squash\":{\"type\":\"boolean\"}},\"required\":[\"modules\",\"skip_failures\",\"type\"]},\"BranchOne\":{\"type\":\"object\",\"description\":\"Conditional branching where only the first matching branch executes. Branches are evaluated in order, and the first one with a true expression runs. If no branches match, the default branch executes\",\"properties\":{\"branches\":{\"type\":\"array\",\"description\":\"Array of branches to evaluate in order. The first branch with expr evaluating to true executes\",\"items\":{\"type\":\"object\",\"properties\":{\"summary\":{\"type\":\"string\",\"description\":\"Short description of this branch condition\"},\"expr\":{\"type\":\"string\",\"description\":\"JavaScript expression that returns boolean. Can use 'results.step_id' or 'flow_input'. First true expr wins\"},\"modules\":{\"type\":\"array\",\"description\":\"Steps to execute if this branch's expr is true\",\"items\":{\"$ref\":\"#/components/schemas/FlowModule\"}}},\"required\":[\"modules\",\"expr\"]}},\"default\":{\"type\":\"array\",\"description\":\"Steps to execute if no branch expressions match\",\"items\":{\"$ref\":\"#/components/schemas/FlowModule\"}},\"type\":{\"type\":\"string\",\"enum\":[\"branchone\"]}},\"required\":[\"branches\",\"default\",\"type\"]},\"BranchAll\":{\"type\":\"object\",\"description\":\"Parallel branching where all branches execute simultaneously. Unlike BranchOne, all branches run regardless of conditions. Useful for executing independent tasks concurrently\",\"properties\":{\"branches\":{\"type\":\"array\",\"description\":\"Array of branches that all execute (either in parallel or sequentially)\",\"items\":{\"type\":\"object\",\"properties\":{\"summary\":{\"type\":\"string\",\"description\":\"Short description of this branch's purpose\"},\"skip_failure\":{\"type\":\"boolean\",\"description\":\"If true, failure in this branch doesn't fail the entire flow\"},\"modules\":{\"type\":\"array\",\"description\":\"Steps to execute in this branch\",\"items\":{\"$ref\":\"#/components/schemas/FlowModule\"}}},\"required\":[\"modules\"]}},\"type\":{\"type\":\"string\",\"enum\":[\"branchall\"]},\"parallel\":{\"type\":\"boolean\",\"description\":\"If true, all branches execute concurrently. If false, they execute sequentially\"}},\"required\":[\"branches\",\"type\"]},\"AgentTool\":{\"type\":\"object\",\"description\":\"A tool available to an AI agent. Can be a flow module or an external MCP (Model Context Protocol) tool\",\"properties\":{\"id\":{\"type\":\"string\",\"description\":\"Unique identifier for this tool. Cannot contain spaces - use underscores instead (e.g., 'get_user_data' not 'get user data')\"},\"summary\":{\"type\":\"string\",\"description\":\"The name the AI agent calls this tool by, not a human label. On a flowmodule tool it must match ^[a-zA-Z0-9_]+$ - letters, numbers and underscores only (e.g. 'search_documentation', not 'Search documentation') - and always be set; on an mcp, websearch or question tool it is a plain label. Put the human-readable explanation in 'description'.\"},\"description\":{\"type\":\"string\",\"description\":\"Free-text description of the tool given to the AI to decide when and how to call it. Overrides the description auto-derived from the underlying script.\"},\"job_token_scopes\":{\"type\":\"array\",\"nullable\":true,\"items\":{\"type\":\"string\"},\"description\":\"Scopes the token of this tool's jobs is restricted to, on top of the agent step's own restriction: a tool can only narrow it.\"},\"requires_approval\":{\"type\":\"boolean\",\"description\":\"Flowmodule and mcp tools only. Each call waits for a person to approve or reject it from the flow's run page or chat, without the agent holding a worker. Calls in the same turn that do not require approval run right away. A rejected call, or one nobody answers within 30 minutes, is reported to the AI as not run.\"},\"value\":{\"$ref\":\"#/components/schemas/ToolValue\"}},\"required\":[\"id\",\"value\"]},\"ToolValue\":{\"description\":\"The implementation of a tool. Can be a flow module (script/flow) or an MCP tool reference\",\"oneOf\":[{\"$ref\":\"#/components/schemas/FlowModuleTool\"},{\"$ref\":\"#/components/schemas/McpToolValue\"},{\"$ref\":\"#/components/schemas/WebsearchToolValue\"},{\"$ref\":\"#/components/schemas/QuestionToolValue\"}],\"discriminator\":{\"propertyName\":\"tool_type\",\"mapping\":{\"flowmodule\":\"#/components/schemas/FlowModuleTool\",\"mcp\":\"#/components/schemas/McpToolValue\",\"websearch\":\"#/components/schemas/WebsearchToolValue\",\"question\":\"#/components/schemas/QuestionToolValue\"}}},\"FlowModuleTool\":{\"description\":\"A tool implemented as a flow module (script, flow, etc.). The AI can call this like any other flow module\",\"allOf\":[{\"type\":\"object\",\"properties\":{\"tool_type\":{\"type\":\"string\",\"enum\":[\"flowmodule\"]}},\"required\":[\"tool_type\"]},{\"$ref\":\"#/components/schemas/FlowModuleValue\"}]},\"WebsearchToolValue\":{\"type\":\"object\",\"description\":\"A tool implemented as a websearch tool. The AI can call this like any other websearch tool\",\"properties\":{\"tool_type\":{\"type\":\"string\",\"enum\":[\"websearch\"]}},\"required\":[\"tool_type\"]},\"QuestionToolValue\":{\"type\":\"object\",\"description\":\"Built-in tool the AI calls as ask_question: the agent stops, releasing its worker, until someone answers from the flow's run page or chat or the question times out, then resumes with the answer as the tool result.\",\"properties\":{\"tool_type\":{\"type\":\"string\",\"enum\":[\"question\"]},\"timeout\":{\"type\":\"integer\",\"description\":\"Seconds to wait for an answer before the question is reported to the AI as timed out. Defaults to 1800.\"}},\"required\":[\"tool_type\"]},\"McpToolValue\":{\"type\":\"object\",\"description\":\"Reference to an external MCP (Model Context Protocol) tool. The AI can call tools from MCP servers\",\"properties\":{\"tool_type\":{\"type\":\"string\",\"enum\":[\"mcp\"]},\"resource_path\":{\"type\":\"string\",\"description\":\"Path to the MCP resource/server configuration\"},\"include_tools\":{\"type\":\"array\",\"description\":\"Whitelist of specific tools to include from this MCP server\",\"items\":{\"type\":\"string\"}},\"exclude_tools\":{\"type\":\"array\",\"description\":\"Blacklist of tools to exclude from this MCP server\",\"items\":{\"type\":\"string\"}}},\"required\":[\"tool_type\",\"resource_path\"]},\"AiAgent\":{\"type\":\"object\",\"description\":\"AI agent step that can use tools to accomplish tasks. The agent receives inputs and can call any of its configured tools to complete the task\",\"properties\":{\"input_transforms\":{\"type\":\"object\",\"description\":\"Input parameters for the AI agent mapped to their values\",\"properties\":{\"provider\":{\"$ref\":\"#/components/schemas/ProviderTransform\"},\"output_type\":{\"allOf\":[{\"$ref\":\"#/components/schemas/InputTransform\"}],\"description\":\"Output format type.\\nValid values: 'text' (default) - plain text response, 'image' - image generation\\n\"},\"user_message\":{\"allOf\":[{\"$ref\":\"#/components/schemas/InputTransform\"}],\"description\":\"The user's prompt/message to the AI agent. Supports variable interpolation with\\nflow.input syntax. Required unless memory is off and `previous_messages` supplies\\nthe prompt; image output always needs it.\\n\"},\"system_prompt\":{\"allOf\":[{\"$ref\":\"#/components/schemas/InputTransform\"}],\"description\":\"System instructions that guide the AI's behavior, persona, and response style. Optional.\"},\"streaming\":{\"allOf\":[{\"$ref\":\"#/components/schemas/InputTransform\"}],\"description\":\"Boolean. If true, stream the AI response incrementally.\\nStreaming events include: token_delta, reasoning_token_delta, tool_call, tool_call_arguments, tool_execution, tool_result\\n\"},\"memory\":{\"$ref\":\"#/components/schemas/MemoryTransform\"},\"memory_id\":{\"allOf\":[{\"$ref\":\"#/components/schemas/InputTransform\"}],\"description\":\"String. Names the memory this step reads and writes, overriding the memory id the run\\nwas started with (the chat conversation, an app chat session or the `memory_id` run\\nparameter). Leave unset to use the run's memory id. A fixed value shares one memory\\nacross every run; an expression such as `flow_input.customer_id` keeps one memory per\\nkey. When it evaluates to an empty value the agent runs without memory. Read only\\nwhile `memory` is `window` or `compaction`: it is ignored when memory is off, and an\\nolder `auto` or `manual` memory reads neither history input.\\n\"},\"previous_messages\":{\"allOf\":[{\"$ref\":\"#/components/schemas/InputTransform\"}],\"description\":\"Array of MemoryMessage. History supplied by the flow, sent between the system prompt\\nand the user message. Read only while `memory` is off or absent: managed memory\\nignores it, and an older `auto` or `manual` memory reads neither history input.\\n\"},\"output_schema\":{\"allOf\":[{\"$ref\":\"#/components/schemas/InputTransform\"}],\"description\":\"JSON Schema object defining structured output format. Used when you need the AI to return data in a specific shape.\\nSupports standard JSON Schema properties: type, properties, required, items, enum, pattern, minLength, maxLength, minimum, maximum, etc.\\nExample: { type: 'object', properties: { name: { type: 'string' }, age: { type: 'integer' } }, required: ['name'] }\\n\"},\"user_attachments\":{\"allOf\":[{\"$ref\":\"#/components/schemas/InputTransform\"}],\"description\":\"Array of file references (images or PDFs) for the AI agent.\\nFormat: Array<{ bucket: string, key: string }> - S3 object references\\nExample: [{ bucket: 'my-bucket', key: 'documents/report.pdf' }]\\n\"},\"enabled_tools\":{\"allOf\":[{\"$ref\":\"#/components/schemas/InputTransform\"}],\"description\":\"Array of strings naming which of the tools configured in `tools` the agent may call\\nthis run. Leaving it unset carries every one of them; an empty array carries none.\\nA tool is named as the model is shown it. An entry the model is shown nothing of is\\nnamed by what identifies it instead: an MCP server by its resource path, carrying\\nevery tool it exposes (which of them stays that entry's include_tools/exclude_tools),\\nand a websearch entry by the reserved name '__wm_web_search', whatever summary it carries\\n(no tool may take that name).\\nExample: ['get_user', 'u/admin/github_mcp', '__wm_web_search']\\n\"},\"max_completion_tokens\":{\"allOf\":[{\"$ref\":\"#/components/schemas/InputTransform\"}],\"description\":\"Integer. Maximum number of tokens the AI will generate in its response.\\nRange: 1 to 4,294,967,295. Typical values: 256-4096 for most use cases.\\n\"},\"temperature\":{\"allOf\":[{\"$ref\":\"#/components/schemas/InputTransform\"}],\"description\":\"Float. Controls randomness/creativity of responses.\\nRange: 0.0 to 2.0 (provider-dependent)\\n- 0.0 = deterministic, focused responses\\n- 0.7 = balanced (common default)\\n- 1.0+ = more creative/random\\n\"},\"max_iterations\":{\"allOf\":[{\"$ref\":\"#/components/schemas/InputTransform\"}],\"description\":\"Number. Limits how many times the agent can loop through reasoning and tool use.\\nRange: 1-1000.\\n\"},\"model\":{\"allOf\":[{\"$ref\":\"#/components/schemas/InputTransform\"}],\"description\":\"String. Only on a step linked to a saved agent (see `agent`): replaces the model\\nsaved on the agent for this step's runs, on the agent's own provider resource. An\\nempty value keeps the saved model. Set it to an expression such as\\n`flow_input.model` to choose the model per run.\\n\"},\"reasoning_effort\":{\"allOf\":[{\"$ref\":\"#/components/schemas/InputTransform\"}],\"description\":\"String. Only on a step linked to a saved agent (see `agent`): replaces the reasoning\\neffort saved on the agent for this step's runs, as a provider-native token (e.g.\\n'low', 'high', 'none'). An empty value sends no effort, so the model runs at its\\ndefault. Leave the input out to keep the saved effort, which holds only while the\\nstep runs the saved model. A step that is not linked sets both inside `provider`.\\n\"}}},\"tools\":{\"type\":\"array\",\"description\":\"Array of tools the agent can use. The agent decides which tools to call based on the task\",\"items\":{\"$ref\":\"#/components/schemas/AgentTool\"}},\"type\":{\"type\":\"string\",\"enum\":[\"aiagent\"]},\"tag\":{\"type\":\"string\",\"description\":\"Worker group tag for execution routing. If not set, the AI agent step runs on the flow's tag (default `flow`)\"},\"omit_output_from_conversation\":{\"type\":\"boolean\",\"default\":false,\"description\":\"If true, this AI agent step does not persist its assistant or tool messages to the flow conversation when chat mode is enabled.\"},\"agent\":{\"type\":\"string\",\"description\":\"Path of a reusable `ai_agent` resource (hybrid linking). When set, the agent brain\\nconfig (provider/model/system prompt/etc.) and tool set are resolved at runtime from\\nthat resource; the module's input_transforms then only carry the flow-local inputs\\n(user_message, user_attachments, enabled_tools and the history inputs memory_id and previous_messages)\\nand, optionally, the `model` and `reasoning_effort` overrides of what the agent saved.\\n\"},\"tool_inputs\":{\"type\":\"object\",\"description\":\"Host-local wiring for an agent's tool inputs, keyed by tool id then input key. Binds the\\nreferenced agent's tools to this flow's context (flow_input/results) without mutating the\\nshared resource; overlaid onto the tools' input_transforms at runtime \\u2014 including when\\n`agent` is unset, since a step forked for editing keeps these overrides until it is saved\\nback or unlinked.\\n\",\"additionalProperties\":{\"type\":\"object\",\"additionalProperties\":{\"$ref\":\"#/components/schemas/InputTransform\"}}},\"parallel\":{\"type\":\"boolean\",\"description\":\"If true, the agent can execute multiple tool calls in parallel\"}},\"required\":[\"type\",\"input_transforms\"]},\"AiDecision\":{\"type\":\"object\",\"description\":\"AI decision step: one call to a decision model (TypeSafe's Jev, Cloudflare's\\nJev-compatible Clef, or OpenAI's Decisions API) that answers typed questions about a\\nstate with calibrated probabilities, instead of generating text.\\nPrefer it over an AI agent to classify, route, score or check something: it is fast,\\ncheap and its answers are structured. Its result is { output: { : answer },\\nmodel, usage }, so a later step reads e.g. results..output.intent.choice. To route on\\nthe answers, follow it with a branchone whose branch exprs read\\nresults..output..choice. Usable as an AI agent tool, where the calling agent\\nsupplies the state.\\n\",\"properties\":{\"input_transforms\":{\"type\":\"object\",\"description\":\"Input parameters for the decision mapped to their values\",\"properties\":{\"provider\":{\"$ref\":\"#/components/schemas/ProviderTransform\"},\"state\":{\"allOf\":[{\"$ref\":\"#/components/schemas/InputTransform\"}],\"description\":\"What the questions are asked about: a string, an object or an array of strings.\\nAn object with descriptive keys holding only what the questions need works best.\\nExample: { message: flow_input.message, plan: results.a.plan }\\n\"},\"questions\":{\"allOf\":[{\"$ref\":\"#/components/schemas/InputTransform\"}],\"description\":\"Object mapping each question name to { type, instructions, criteria }, where type is:\\n- 'choice': criteria maps each option to its description (up to 255); the answer\\n has choice, probabilities and confidence\\n- 'score': criteria is an ordered array of 2 to 10 level descriptions; the answer\\n has score, legend, probabilities and confidence\\n- 'noul': yes/no, criteria optionally { true, false } descriptions; the answer has\\n noul, the probability of yes (0 to 1)\\nExample: { intent: { type: 'choice', instructions: 'What does the customer want?',\\ncriteria: { refund: 'Money back', bug: 'Something is broken' } } }\\n\"}},\"required\":[\"provider\",\"state\",\"questions\"]},\"type\":{\"type\":\"string\",\"enum\":[\"aidecision\"]},\"tag\":{\"type\":\"string\",\"description\":\"Worker group tag for execution routing. If not set, the step runs on the flow's tag (default `flow`)\"}},\"required\":[\"type\",\"input_transforms\"]},\"Identity\":{\"type\":\"object\",\"description\":\"Pass-through module that returns its input unchanged. Useful for flow structure or as a placeholder\",\"properties\":{\"type\":{\"type\":\"string\",\"enum\":[\"identity\"]},\"flow\":{\"type\":\"boolean\",\"description\":\"If true, marks this as a flow identity (special handling)\"}},\"required\":[\"type\"]},\"FlowStatus\":{\"type\":\"object\",\"properties\":{\"step\":{\"type\":\"integer\"},\"modules\":{\"type\":\"array\",\"items\":{\"$ref\":\"#/components/schemas/FlowStatusModule\"}},\"user_states\":{\"additionalProperties\":true},\"preprocessor_module\":{\"allOf\":[{\"$ref\":\"#/components/schemas/FlowStatusModule\"}]},\"failure_module\":{\"allOf\":[{\"$ref\":\"#/components/schemas/FlowStatusModule\"},{\"type\":\"object\",\"properties\":{\"parent_module\":{\"type\":\"string\"}}}]},\"retry\":{\"type\":\"object\",\"properties\":{\"fail_count\":{\"type\":\"integer\"},\"failed_jobs\":{\"type\":\"array\",\"items\":{\"type\":\"string\",\"format\":\"uuid\"}}}}},\"required\":[\"step\",\"modules\",\"failure_module\"]},\"FlowStatusModule\":{\"type\":\"object\",\"properties\":{\"type\":{\"type\":\"string\",\"enum\":[\"WaitingForPriorSteps\",\"WaitingForEvents\",\"WaitingForExecutor\",\"InProgress\",\"Success\",\"Failure\"]},\"id\":{\"type\":\"string\"},\"job\":{\"type\":\"string\",\"format\":\"uuid\"},\"count\":{\"type\":\"integer\"},\"progress\":{\"type\":\"integer\"},\"iterator\":{\"type\":\"object\",\"properties\":{\"index\":{\"type\":\"integer\"},\"itered\":{\"type\":\"array\",\"items\":{}},\"itered_len\":{\"type\":\"integer\"},\"args\":{}}},\"flow_jobs\":{\"type\":\"array\",\"items\":{\"type\":\"string\"}},\"flow_jobs_success\":{\"type\":\"array\",\"items\":{\"type\":\"boolean\"}},\"flow_jobs_duration\":{\"type\":\"object\",\"properties\":{\"started_at\":{\"type\":\"array\",\"items\":{\"type\":\"string\"}},\"duration_ms\":{\"type\":\"array\",\"items\":{\"type\":\"integer\"}}}},\"branch_chosen\":{\"type\":\"object\",\"properties\":{\"type\":{\"type\":\"string\",\"enum\":[\"branch\",\"default\"]},\"branch\":{\"type\":\"integer\"}},\"required\":[\"type\"]},\"branchall\":{\"type\":\"object\",\"properties\":{\"branch\":{\"type\":\"integer\"},\"len\":{\"type\":\"integer\"}},\"required\":[\"branch\",\"len\"]},\"approvers\":{\"type\":\"array\",\"items\":{\"type\":\"object\",\"properties\":{\"resume_id\":{\"type\":\"integer\"},\"approver\":{\"type\":\"string\"}},\"required\":[\"resume_id\",\"approver\"]}},\"failed_retries\":{\"type\":\"array\",\"items\":{\"type\":\"string\",\"format\":\"uuid\"}},\"skipped\":{\"type\":\"boolean\"},\"agent_actions\":{\"type\":\"array\",\"items\":{\"type\":\"object\",\"oneOf\":[{\"type\":\"object\",\"properties\":{\"job_id\":{\"type\":\"string\",\"format\":\"uuid\"},\"function_name\":{\"type\":\"string\"},\"type\":{\"type\":\"string\",\"enum\":[\"tool_call\"]},\"module_id\":{\"type\":\"string\"}},\"required\":[\"job_id\",\"function_name\",\"type\",\"module_id\"]},{\"type\":\"object\",\"properties\":{\"call_id\":{\"type\":\"string\",\"format\":\"uuid\"},\"function_name\":{\"type\":\"string\"},\"resource_path\":{\"type\":\"string\"},\"type\":{\"type\":\"string\",\"enum\":[\"mcp_tool_call\"]},\"arguments\":{\"type\":\"object\"}},\"required\":[\"call_id\",\"function_name\",\"resource_path\",\"type\"]},{\"type\":\"object\",\"properties\":{\"type\":{\"type\":\"string\",\"enum\":[\"web_search\"]}},\"required\":[\"type\"]},{\"type\":\"object\",\"properties\":{\"type\":{\"type\":\"string\",\"enum\":[\"approval\"]},\"call_id\":{\"type\":\"string\"},\"calls\":{\"type\":\"array\",\"items\":{\"type\":\"object\",\"properties\":{\"function_name\":{\"type\":\"string\"},\"arguments\":{}},\"required\":[\"function_name\",\"arguments\"]}},\"expires_at\":{\"type\":\"string\",\"format\":\"date-time\"}},\"required\":[\"type\",\"call_id\",\"calls\",\"expires_at\"]},{\"type\":\"object\",\"properties\":{\"type\":{\"type\":\"string\",\"enum\":[\"question\"]},\"call_id\":{\"type\":\"string\"},\"question\":{\"type\":\"string\"},\"choices\":{\"type\":\"array\",\"items\":{\"type\":\"string\"},\"description\":\"answers the model proposes; a free-text answer is always possible\"},\"multi_select\":{\"type\":\"boolean\",\"description\":\"whether several choices can be picked together\"},\"expires_at\":{\"type\":\"string\",\"format\":\"date-time\"}},\"required\":[\"type\",\"call_id\",\"question\",\"expires_at\"]},{\"type\":\"object\",\"properties\":{\"type\":{\"type\":\"string\",\"enum\":[\"message\"]}},\"required\":[\"content\",\"type\"]}]}},\"agent_actions_success\":{\"type\":\"array\",\"items\":{\"type\":\"boolean\"}}},\"required\":[\"type\"]}}", "resource": "# Global draft resource & variable instructions\n\n- Global mode writes complete draft payloads only; it does not save, deploy, run, scaffold local files, or generate metadata.\n- A resource draft is a workspace item: `{ type: 'resource', path, summary?, value, isDraft }`. `value` is a CreateResource body: `{ path, value, description?, resource_type, labels? }` where the inner `value` is the resource type's data shape.\n- Reading a variable returns `{ type: 'variable', path, summary?, isSecret, isDraft }` — never its value, secret or not. `isSecret` tells you whether the value is encrypted.\n- `write_variable` takes `{ path, value?, is_secret?, description?, is_oauth?, expires_at?, value_valid_until?, labels? }`. Creating a variable needs `value` and `is_secret`; editing one needs only the fields you are changing. Omitting `value` keeps the stored value, which is the only way to edit a secret variable — you cannot read its value, so passing any `value` you did not get from the user destroys it.\n- For secret fields in a resource value, create the variable with `write_variable` and `is_secret: true`, and deploy it before the resource (see \"Secrets\" in the reference below).\n- Reference formats inside resource values: `$var:g/all/name` (global), `$var:u/user/name` (user), `$var:f/folder/name` (folder). Reference another resource with `$res:path/to/resource`. The same strings are also how a resource or variable is passed as a run argument (see the run-argument rule in the resource reference below); what they are never valid as is a variable's own value.\n- Use `search_resource_types` to discover valid `resource_type` names and their JSON Schemas. Match the resource value to that schema.\n- For OAuth resources, the `is_oauth: true` flag is managed by Windmill's OAuth flow; global mode generally creates manual resources, not OAuth ones.\n\n# Windmill resource & variable reference\n\n# Windmill Resources\n\nResources store credentials and configuration for external services.\n\n## Resource Structure\n\n```json\n{\n \"value\": {\n \"host\": \"db.example.com\",\n \"port\": 5432,\n \"user\": \"admin\",\n \"password\": \"$var:g/all/db_password\",\n \"dbname\": \"production\"\n },\n \"description\": \"Production PostgreSQL database\",\n \"resource_type\": \"postgresql\"\n}\n```\n\n## Required Fields\n\n- `value` - Object containing the resource configuration\n- `resource_type` - Name of the resource type (e.g., \"postgresql\", \"slack\")\n\n## Agents\n\nAn agent, as the Agents page lists it, is a resource of type `ai_agent`. Its value holds the\nagent's provider, system prompt, tools and memory settings, and a flow step uses a saved agent by\nlinking its path.\n\n## Variable References\n\nReference variables in resource values:\n\n```json\n{\n \"value\": {\n \"api_key\": \"$var:g/all/api_key\",\n \"secret\": \"$var:u/admin/secret\"\n }\n}\n```\n\n**Reference formats:**\n- `$var:g/all/name` - Global variable\n- `$var:u/username/name` - User variable\n- `$var:f/folder/name` - Folder variable\n\n## Secrets\n\nNever put a secret (password, API key, token) inline in a resource value. Store it in a secret variable and reference that variable as `$var:`.\n\n- `$var:` is a reference, not a value: it resolves to the variable's value at run time. Never invent a value for a variable.\n- A resource that references a variable needs the variable to exist first, so create or deploy the variable before the resource.\n\n## Resource References\n\nReference other resources:\n\n```json\n{\n \"value\": {\n \"database\": \"$res:f/databases/postgres\"\n }\n}\n```\n\n## Passing a Resource or Variable as a Run Argument\n\nA script or flow argument typed as a resource (schema `format: resource-`) is passed as\nthe **bare string** `$res:` — the whole argument value. Same for a variable, with\n`$var:`. This applies everywhere job arguments are supplied: `wmill script run/preview`,\n`wmill flow run/preview`, the `runScriptByPath` / `runFlowByPath` API, a schedule's `args`, a\ntrigger's configured static args.\n\n```json\n{\n \"db\": \"$res:f/databases/postgres_prod\",\n \"api_token\": \"$var:g/all/api_token\"\n}\n```\n\nThe reference is resolved when the job runs, under the job's run-as identity — the caller for an\nordinary run, but the configured principal for a schedule, a trigger, or a runnable set to run on\nbehalf of someone else. The run fails if that identity cannot read the referenced resource or\nvariable.\n\n**Never wrap it in an object.** The resolver only rewrites a JSON value that *is* a string\nstarting with `$res:` / `$var:`; keys are never inspected. These are all wrong and are passed\nthrough to the script unchanged:\n\n```json\n{ \"db\": { \"$res\": \"f/databases/postgres_prod\" } }\n{ \"db\": { \"resource\": \"f/databases/postgres_prod\" } }\n{ \"db\": \"f/databases/postgres_prod\" }\n```\n\nThe string may sit anywhere a string can — a top-level argument, a nested object field\n(`{ \"gh_auth\": { \"token\": \"$var:g/all/gh_token\" } }`), or an array element (array elements are\nwalked only while nested at most two levels deep, and only for arrays of at most 1000 items).\nThe prefix must be on the string itself.\n\n## Common Resource Types\n\n### PostgreSQL\n```json\n{\n \"resource_type\": \"postgresql\",\n \"value\": {\n \"host\": \"localhost\",\n \"port\": 5432,\n \"user\": \"postgres\",\n \"password\": \"$var:g/all/pg_password\",\n \"dbname\": \"windmill\",\n \"sslmode\": \"prefer\"\n }\n}\n```\n\n### MySQL\n```json\n{\n \"resource_type\": \"mysql\",\n \"value\": {\n \"host\": \"localhost\",\n \"port\": 3306,\n \"user\": \"root\",\n \"password\": \"$var:g/all/mysql_password\",\n \"database\": \"myapp\"\n }\n}\n```\n\n### Slack\n```json\n{\n \"resource_type\": \"slack\",\n \"value\": {\n \"token\": \"$var:g/all/slack_token\"\n }\n}\n```\n\n### AWS S3\n```json\n{\n \"resource_type\": \"s3\",\n \"value\": {\n \"bucket\": \"my-bucket\",\n \"region\": \"us-east-1\",\n \"accessKeyId\": \"$var:g/all/aws_access_key\",\n \"secretAccessKey\": \"$var:g/all/aws_secret_key\"\n }\n}\n```\n\n### HTTP/API\n```json\n{\n \"resource_type\": \"http\",\n \"value\": {\n \"baseUrl\": \"https://api.example.com\",\n \"headers\": {\n \"Authorization\": \"Bearer $var:g/all/api_token\"\n }\n }\n}\n```\n\n### Kafka\n```json\n{\n \"resource_type\": \"kafka\",\n \"value\": {\n \"brokers\": \"broker1:9092,broker2:9092\",\n \"sasl_mechanism\": \"PLAIN\",\n \"security_protocol\": \"SASL_SSL\",\n \"username\": \"$var:g/all/kafka_user\",\n \"password\": \"$var:g/all/kafka_password\"\n }\n}\n```\n\n### NATS\n```json\n{\n \"resource_type\": \"nats\",\n \"value\": {\n \"servers\": [\"nats://localhost:4222\"],\n \"user\": \"$var:g/all/nats_user\",\n \"password\": \"$var:g/all/nats_password\"\n }\n}\n```\n\n### MQTT\n```json\n{\n \"resource_type\": \"mqtt\",\n \"value\": {\n \"host\": \"mqtt.example.com\",\n \"port\": 8883,\n \"username\": \"$var:g/all/mqtt_user\",\n \"password\": \"$var:g/all/mqtt_password\",\n \"tls\": true\n }\n}\n```\n\n## When No Resource Type Fits\n\nThe Windmill Hub publishes resource types for most services, and an instance gets them by syncing with the hub. When none fits the service:\n\n- If the instance is reported as not having synced the hub's types, mention that a superadmin can sync them: the hub most likely has one for the service. That holds for a type a hub script takes too: it is missing here until the sync, so say so before asking for a resource of it. Create one of your own only if the user still wants it, since after a sync the workspace would hold both.\n- Otherwise, or when the user prefers it to syncing, propose a custom resource type named `c_` holding the service's connection fields (base URL, account or region identifiers, credentials), as in \"Custom Resource Types\" below, and ask the user before creating it: every resource of that type and every script taking one depends on its fields.\n- A plain variable instead of a resource is fine when the user asks for it; without that, default to the resource, its secret in a variable it references.\n\n## Custom Resource Types\n\nA custom type's name starts with `c_`: the hub's types reach every instance under their plain names, so the prefix keeps a custom type from clashing with one synced later. Scripts and flows refer to the full name: `format: resource-c_custom_api`, `RT.CCustomApi` in TypeScript, a `c_custom_api` TypedDict in Python.\n\nCreate custom resource types with JSON Schema:\n\n```json\n{\n \"name\": \"c_custom_api\",\n \"schema\": {\n \"type\": \"object\",\n \"properties\": {\n \"base_url\": {\"type\": \"string\", \"format\": \"uri\"},\n \"api_key\": {\"type\": \"string\"},\n \"timeout\": {\"type\": \"integer\", \"default\": 30}\n },\n \"required\": [\"base_url\", \"api_key\"]\n },\n \"description\": \"Custom API connection\"\n}\n```\n\nSave as: `c_custom_api.resource-type.json`\n\n## OAuth Resources\n\nOAuth resources are managed through the Windmill UI and marked:\n\n```json\n{\n \"is_oauth\": true,\n \"account\": 123\n}\n```\n\nOAuth tokens are automatically refreshed by Windmill.\n\n## Using Resources in Scripts\n\n### TypeScript (Bun/Deno)\n```typescript\nexport async function main(db: RT.Postgresql) {\n // db contains the resource values\n const { host, port, user, password, dbname } = db;\n}\n```\n\n### Python\n```python\nclass postgresql(TypedDict):\n host: str\n port: int\n user: str\n password: str\n dbname: str\n\ndef main(db: postgresql):\n # db contains the resource values\n pass\n```\n\n", "app": "# Global draft app instructions\n\n- Global mode edits raw app drafts only; it does not save or deploy unless the user explicitly asks to deploy.\n- App drafts are addressed by workspace path. Follow the path conventions in the system prompt: default to `u//` for bare names; only use `f//` when the folder is known to exist. The first write tool snapshots the workspace app onto the draft, and subsequent writes accumulate.\n- To create a new app, use `init_app` with a path, optional summary, a framework (`react19` / `react18` / `svelte5`) and, for an app that stores data, its `data` setup. \"Starting a new app\" below decides the framework and when the data setup is asked. Ask the user each of its questions, suggested answer first, before `init_app` and before any SQL. `init_app` only records `data`: a new schema is yours to create with the datatable SQL tool. `init_app` errors if an app already exists at the path or a draft is already in flight; in that case, edit the existing one rather than re-initializing.\n- `init_app` seeds the starter inline runnables `greet`, `word_stats`, `slow_task`, `stream_text` so the demo tour works on first render. Replace or remove them once you start building real backend runnables.\n- Frontend file paths start with `/` (e.g. `/index.tsx`, `/App.tsx`, `/styles.css`). Use `write_app_file` / `patch_app_file` / `delete_app_file`.\n- Backend inline runnables are addressed as `backend//main.{ts|py}` from the file tools, but you create or update them via `write_app_runnable` / `delete_app_runnable` (which take the runnable shape directly: `{ name, type, inlineScript?, path?, staticInputs? }`).\n- `/wmill.d.ts` (or `wmill.ts`) is generated automatically from the backend runnables — never write it directly.\n- Inline runnables only support `bun` or `python3` in chat. Path runnables (`script`/`flow`/`hubscript`) reference an existing item.\n- When a path runnable points at a draft (see \"Draft code vs deployed code\" below), offer to deploy just that flow/script with deploy_workspace_item, not through the compare page.\n- The authoring reference below carries the TypeScript SDK. For a `python3` runnable, call `get_instructions` again with `subject: \"app\"` and `language: \"python3\"`.\n- Use `deploy_workspace_item` after explicit user deploy intent. The deploy tool bundles JS/CSS before saving the raw app.\n- Use `read_workspace_item` with `type: 'app'` for a metadata summary (file paths and runnable list, no contents). Use `read_app_file` to read an individual file; large files are truncated to a head slice, so pass `offset`/`limit` to page through the rest rather than re-reading the whole file.\n- To find where a symbol or string lives across the app, call `search_app` (greps every frontend file and inline runnable, returns matching `file:line` rows) instead of reading files one by one — then `read_app_file` only the ranges you need. The loop is list (`read_workspace_item`) → locate (`search_app`) → inspect (`read_app_file` with `offset`/`limit`).\n\n# Windmill raw app authoring reference\n\n# Windmill Raw Apps\n\nRaw apps let you build custom frontends with React or Svelte that connect to Windmill backend runnables and datatables.\n\n## App shape\n\nA raw app has three logical parts:\n\n- **Frontend** — bundled with esbuild from `index.tsx` as the entrypoint. Files include the entrypoint, components (`App.tsx`), styles, etc.\n- **Backend runnables** — server-side scripts the frontend calls, each addressed by a unique key.\n- **Data** — optional whitelisted datatables (managed PostgreSQL) that the backend runnables can query. The frontend never queries the database directly; backend runnables are the only bridge.\n\n## Starting a new app\n\nA new app gets the setup Windmill's own new-app dialog gives one: a framework, then where its data lives.\n\n### Framework\n\nUse the framework the user named. When they named none, follow what there is to follow: the app being edited, or the apps the request points at. With nothing to follow, use **React 19**, the recommended default, **without asking**. React 18 and Svelte 5 are for when they are asked for. These three are the only frameworks the raw app bundler builds. When the user asks to build or convert an app in another framework, write no code in it: say it is not available and offer these three instead.\n\n### Data setup\n\nWhen a new app has to store data and the user did not say where, **ask before creating anything**: no app, no schema, no table. Where the data lives is the user's decision, and tables created in the wrong place stay there. Look up the workspace's data tables first so every choice you offer exists, then ask, as proposed answers rather than open questions:\n\n1. **Data table**: which one to use, the default first (`main` when it exists, otherwise the first listed). Skip this one when the workspace has a single data table.\n2. **Schema**: where the app's new tables go.\n - A **new schema**, the usual choice, offered first. Suggest the first unused name among `app1`, `app2`, …\n - An **existing schema** of that data table, by name.\n - **None**: the tables go in `public`.\n3. **Tables**: only when that data table already holds tables the app could use, whether to **reuse** them (name them) or **create new ones**.\n\nDo not ask when:\n\n- the user already said where the data goes. A part they left out takes its default above: the default data table, a new `appN` schema, new tables;\n- the app, or its saved draft, already carries a data config (`data.datatable`, `data.schema` or `data.tables`). That config is the answer;\n- the app stores nothing.\n\nWith no data table in the workspace there is nothing to choose: say that one has to be configured in the workspace settings before the app can store data.\n\nA question left unanswered or dismissed is not a go-ahead for the defaults: stop there and say what is still needed.\n\nThen build what was chosen: the data table and schema become the app's `data.datatable` and `data.schema`, the tables it uses, reused or new, go in `data.tables`, and a new schema is created (`CREATE SCHEMA IF NOT EXISTS`) before the tables that go in it.\n\n### An app that arrives already set up\n\nAn app the user just started from the new-app dialog is already set up: its files are the framework template it was started with, and a `data` config it carries (`data.datatable`, `data.schema` or `data.tables`) is the data setup it was started with. Build that app in place, with that data config, and in that framework unless the user now names another. Do not ask for either, and do not create a second app. Only when it carries no data config and has to store data is the data setup still to ask.\n\n## Frontend\n\n### Entrypoint\n\nThe entrypoint is `index.tsx` for React and `index.ts` for Svelte. It is both the bundling entrypoint (the bundler is esbuild) and the **mount** entrypoint: the preview executes the bundle against an empty `
` and auto-renders nothing, so the entrypoint must mount a top-level `App` itself. Keep the UI in `App.tsx` / `App.svelte` and keep the entrypoint as the mount shim.\n\nReact (`index.tsx`):\n\n```tsx\nimport React from 'react'\nimport { createRoot } from 'react-dom/client'\nimport App from './App'\n\ncreateRoot(document.getElementById('root')!).render()\n```\n\nSvelte (`index.ts`): `mount(App, { target: document.getElementById('root')! })`.\n\n**Never replace the entrypoint with a bare component** (`export default function App() { ... }` and no mount call). A component that is defined but never mounted renders a blank screen with **no error thrown** — it never executes, so nothing reaches the console or the error overlay. If an app renders blank, check that the entrypoint still mounts `App` into `#root`.\n\n**Set the browser tab title with `document.title = '...'`** (or a `` the framework renders into `<head>`). The app has no `index.html` of its own, so a `<title>` written there is never served; the deployed app's page shows whatever `document.title` holds, and follows it when it changes.\n\n**Always begin every React file (`.tsx`/`.jsx`) that uses JSX with `import React from 'react'`.** esbuild uses the classic JSX transform, so `React` must be in scope wherever JSX appears — a missing import compiles fine but throws `React is not defined` at runtime, leaving a blank screen.\n\n### Generated bindings (`wmill.d.ts` / `wmill.ts`)\n\nThe frontend imports a generated module that mirrors the backend runnables. **Never write to it directly** — it gets regenerated whenever backend runnables change. Modifying it by hand will be overwritten.\n\n### Calling backend runnables\n\nImport the generated bindings and call the runnable like a function. `./wmill` is the **only** way the frontend reaches anything server-side — datatables, workspace items, external services. Never `fetch` the Windmill API from frontend code: the bundle holds no token and builds no API URL.\n\n| Export | Resolves to | Use it for |\n|---|---|---|\n| `backend.<key>(args)` | the runnable's result | the default — run and wait |\n| `backendAsync.<key>(args)` | the **job id** (a string) | long-running work you want to track |\n| `waitJob(jobId)` | the job's **result** (rejects if the job failed) | awaiting a `backendAsync` job |\n| `getJob(jobId)` | a `Job` (`{ type, success, result, duration_ms, ... }`) | polling status without blocking |\n| `streamJob(jobId, onUpdate?)` | the final result, calling `onUpdate` per chunk | showing output as it is produced |\n\nA runnable is always called with **one object** whose keys are its `main` parameters — `main(user_id: string, limit: number)` is called as `backend.get_users({ user_id, limit })`, never with positional arguments. A runnable without parameters is called with no argument. Resource and variable ids handed to the `wmill` client are paths (`u/<user>/<name>` or `f/<folder>/<name>`).\n\nRun and wait — the common case:\n\n```tsx\nimport { backend } from './wmill';\n\nconst user = await backend.get_user({ user_id: '123' });\n```\n\nStart a long job, then await it:\n\n```tsx\nimport { backendAsync, waitJob } from './wmill';\n\nconst jobId = await backendAsync.run_report({ month: '2026-08' }); // a string\nconst report = await waitJob(jobId); // the result itself\n```\n\nOr poll it without blocking, to render progress:\n\n```tsx\nimport { getJob } from './wmill';\n\nconst job = await getJob(jobId);\nif (job.type === 'CompletedJob') setReport(job.result);\n```\n\n`backendAsync` resolves a job id and nothing else — guard on it before storing or polling. A poll loop started on an `undefined` id never completes and shows as a row stuck \"running\" forever:\n\n```tsx\nconst jobId = await backendAsync.run_report(args);\nif (!jobId) throw new Error('run_report did not start a job');\n```\n\n**Never hand-write a job-polling runnable.** A backend runnable that calls `jobs/list`, or that returns `getResultMaybe(...)` for the frontend to poll, reimplements `backendAsync` + `waitJob` / `getJob` / `streamJob` — and it is what leads to guessing at base URLs and tokens.\n\n### Keeping data out of recorded demos\n\nAn app can be demoed by recording a session: every interaction becomes a step carrying a snapshot of the page, replayed publicly or on the Hub. Password inputs are masked automatically. Mark anything else that must not appear with `data-wm-no-record` — the whole marked subtree is dropped from every snapshot, along with its values and the step's own metadata:\n\n```tsx\n<label data-wm-no-record>\n Customer SSN <input value={ssn} onChange={onSsn} />\n</label>\n```\n\nApply it to customer data, internal notes and anything else a viewer of the demo should not see. It costs nothing when the app is never recorded.\n\n### Chat UIs over a flow in chat mode or a saved agent\n\nA flow deployed with chat mode on is a chat backend (streaming answer, tool calls, memory, conversation history). Do not drive it through a runnable: add `@windmill-labs/chat-sdk` to `package.json` and use it directly, it detects the app's Windmill and credential.\n\n```tsx\nimport { useWindmillChat } from '@windmill-labs/chat-sdk/react'\n\nconst chat = useWindmillChat({ flowPath: 'f/support/assistant' })\n// chat.messages ({ role, content, pending, success, tool? }), chat.status, chat.sendMessage(text), chat.stop()\n```\n\n`@windmill-labs/chat-sdk/ai-sdk` gives a `ChatTransport` for the Vercel AI SDK's `useChat`, `@windmill-labs/chat-sdk/assistant-ui` a runtime for assistant-ui. The flow must be deployed, not a draft. A sandboxed app needs `jobs:run` in its frontend SDK scopes, plus `flow_conversations:write` for the conversation sidebar; without them the chat keeps history in the browser.\n\n#### A saved agent: an `agent` runnable\n\nChat with a saved AI agent (an `ai_agent` resource) through an `agent` runnable, a path runnable whose `path` is the agent's. Each call runs one turn of the agent's chat as the app, so a sandboxed app declares no frontend SDK scope, viewers get no consent prompt and need no access to the agent. Prefer it in every app, sandboxed or not:\n\n```json\n{ \"chat\": { \"type\": \"agent\", \"path\": \"f/support/agent\" } }\n```\n\n```tsx\nimport { useWindmillChat } from '@windmill-labs/chat-sdk/react'\nimport * as wmill from './wmill'\n\nconst chat = useWindmillChat({ wmill, runnable: 'chat' })\n```\n\n`runnable` is the runnable's key; each runnable keeps its own conversations. The runnable takes `user_message` and `memory_id`, the conversation id, which the chat fills in: the agent remembers earlier turns of a conversation, and a signed-in viewer's conversations are theirs alone. Called directly as `backend.<key>({ user_message })` without `memory_id`, it is a single run with no conversation, for a one-off question. The chat needs an agent with managed memory. An agent whose memory is off keeps none: its runnable takes `previous_messages` (chat messages) instead of `memory_id`, and the app keeps the history itself. The chat keeps its transcript in the app's own storage. `chat.stop()` stops following without cancelling the turn, and a message sent while it still runs is refused with `TurnRunningError`. Attachments are not supported this way.\n\n## Backend runnables\n\nEach runnable has a unique key (used to call it from the frontend) and one of five types:\n\n| Type | What it is |\n|---|---|\n| `inline` | Custom code stored on the app itself. Most common for app-specific logic. |\n| `script` | Reference to an existing workspace script by path. |\n| `flow` | Reference to an existing workspace flow by path. |\n| `hubscript` | Reference to a hub script by path. |\n| `agent` | Reference to a saved AI agent by path. Each call is one turn of its chat (see the chat section above). |\n\n### Inline runnables\n\nInline runnables carry their own source code, and must expose a `main` function as their entrypoint.\n\n**TypeScript example** (runnable `get_user`):\n\n```typescript\nimport * as wmill from 'windmill-client';\n\nexport async function main(user_id: string) {\n const sql = wmill.datatable();\n const user = await sql`SELECT * FROM users WHERE id = ${user_id}`.fetchOne();\n return user;\n}\n```\n\n**Python example** (runnable `get_user`):\n\n```python\nimport wmill\n\ndef main(user_id: str):\n db = wmill.datatable()\n user = db.query('SELECT * FROM users WHERE id = $1', user_id).fetch_one()\n return user\n```\n\n#### Sharing code between runnables\n\nAn inline runnable can import another inline runnable of the same app by its id, as a relative import: `import { getDb } from './shared'` (TypeScript, Bun) or `from .shared import get_db` (Python). This works across TypeScript (Bun) runnables and across Python runnables, not between the two. The imported runnable's own dependencies are picked up, and it can import further runnables in turn. A runnable that only holds helpers needs no `main`; the frontend just never calls it. A TypeScript runnable whose id is `main` cannot be imported, because that name is taken by the entrypoint file of every TypeScript job: give shared code any other id.\n\n#### The `wmill` client is already authenticated\n\nAn inline runnable runs as an ordinary Windmill job. `import * as wmill from 'windmill-client'` (TypeScript) and `import wmill` (Python) are already pointed at this instance and this workspace — there is nothing to configure.\n\n**Don't read `WM_TOKEN` or `BASE_INTERNAL_URL` and build an API URL to `fetch`.** The client's own `setClient` already reads exactly those, and it also sets the credentials mode a raw app needs (`WM_RAW_APP` suppresses credentials, because a sandboxed bundle calls the API from an opaque origin that can never pair with `Access-Control-Allow-Origin: *`). Rebuilding that by hand drops the parts you can't see. Use `wmill.*` for everything Windmill, and `fetch` only for third-party APIs.\n\nUse only `wmill` functions the SDK actually exports; for an endpoint none of them covers, the generated service classes (`JobService`, `ScriptService`, ...) are importable from `windmill-client`. What is not available is a name you guessed at: `getBaseUrl` and `getWorkspaceToken` are inventions, not API.\n\n### Path runnables (script / flow / hubscript / agent)\n\nWhen `type` is `script`, `flow`, `hubscript` or `agent`, the runnable just stores a `path` to an existing workspace or hub item — no inline code. The referenced item's input/output schema becomes the runnable's surface; an agent's is `user_message` and `user_attachments`, plus `memory_id` when the agent keeps managed memory or `previous_messages` when its memory is off.\n\nBefore writing an inline runnable, look for a workspace script or flow that already does the job, or a Hub script (a prebuilt integration at `hub/<version>/<app>/<name>`) for a third-party service, and reference it instead of copying its logic.\n\n### Draft code vs deployed code\n\nThis decides whether an app works before anything is deployed:\n\n- **Inline runnables run the app's current code.** The editor sends the runnable's source with each request, so an inline runnable works in the preview with nothing deployed.\n- **Path runnables (`script` / `flow` / `hubscript` / `agent`) run the DEPLOYED item at that path.** So do `wmill.runFlow`, `wmill.runFlowAsync` and `wmill.runScriptByPath` called from inside a runnable. A draft — including a draft you just created — does not exist for them.\n\nSo an app wired to a flow you just wrote does nothing until **that flow is deployed**. The app itself does NOT have to be deployed for this: the preview runs the app's draft, so the referenced flow is the only thing that has to exist deployed.\n\nThat makes the fix a one-item deploy, not a release. Offer to deploy exactly the referenced flow or script and leave the app a draft the user keeps testing in the preview — do not push the whole change set through the review-and-deploy page, and do not ask the user to deploy the app, unless they said they want to ship it.\n\nDo NOT quietly reimplement the flow inside an inline runnable to dodge the deployment: that leaves the user with two copies of the same logic and an app that ignores the flow they asked for. Inline the logic only when the user actually wants it inline.\n\nPrefer a **path runnable of type `flow`** over an inline runnable that calls `wmill.runFlowAsync`. The path runnable gives the frontend the flow's real input schema and works with `backend` / `backendAsync` / `waitJob` like any other runnable; a hand-written wrapper gives up all of that.\n\n### Static inputs\n\n`staticInputs` is an optional `Record<string, any>` for arguments not overridable from the frontend. Useful with path runnables to pre-fill some args while leaving the rest to the frontend caller.\n\n## Who can open a deployed app\n\nA draft app is reachable by nobody; deploying is what exposes it, and its backend runnables with it. Otherwise only users with access to the app can open it, unless the app is opened to:\n\n- **anonymous** users: anyone with the URL, without logging in;\n- **guests**: anyone the instance's identity provider authenticates, whether or not they belong to the workspace.\n\nEither one lets those people run the app's backend runnables, so never open an app up unless the user asks.\nWhen a deploy widens who may open the app, tell the user in plain words.\n\n## Sandbox isolation and frontend API access\n\nNew apps are sandboxed: the frontend is isolated from the viewer's own Windmill session and reaches Windmill only through its backend runnables, plus whatever frontend API scopes the app declares, which each viewer approves before the app runs. With isolation turned off, the frontend runs with the viewer's full session. The scopes are `jobs:run`, `jobs:read`, `resources:read`, `variables:read`, `flow_conversations:read` and `flow_conversations:write`; grant only the ones the frontend calls. The viewer's identity needs no scope: it is in `window.ctx`, and whoami works with any of them.\n\nInside the sandbox, IndexedDB is unavailable, third-party sign-in and OAuth redirects fail, and requests to other services carry `Origin: null`, which an API that checks the origin rejects. Work around these first: call the service from a backend runnable, keep state in a data table or `localStorage`, or grant the frontend API scope the code needs. Suggest turning isolation off only when none of that works, and say plainly that it is a security risk: the app's code, and any XSS bug in it, then runs with the full Windmill permissions of everyone who opens the app.\nYou cannot turn isolation off; the user does it in the app's deploy settings.\n\n## Reading data as the viewer\n\nA backend runnable reads data as the app's identity (the publisher in publisher mode), the same for every viewer. An inline runnable can instead read data as the person using the app: its data table connections that name no role hold that viewer's roles, and object storage permission rules (which paths may be listed, read, written) are checked against the viewer. Resources, variables and everything else stay the app's, and an anonymous viewer is refused. Turn it on only when what the runnable reads should differ per viewer: row-level security on a data table, or per-user paths in object storage. Both are Enterprise Edition features.\nSet it with `viewerDataAccess: true` on the backend runnable.\n\n## Data Tables\n\nData tables are PostgreSQL databases managed by Windmill. Backend runnables query them via the `wmill` client; the frontend never queries them directly. **When the app needs to store or persist data** (user data, settings, application state, records, logs), use a data table.\n\n### Critical rules\n\n1. **Check what exists first**: look up the workspace's data tables and their tables before designing storage, and reuse a suitable table rather than creating another. Never assume a `main` data table exists.\n2. **Whitelisted tables only**: a runnable can only query tables listed in the app's `data.tables` config. Queries against unlisted tables fail at runtime, so register a new table there before using it.\n3. **No DDL inside runnables**: runnables only read and write rows (SELECT, INSERT, UPDATE, DELETE) on existing tables. Never CREATE, ALTER or DROP a table from a runnable.\n4. **Qualify table names**: an unqualified name means the `public` schema, so write every other table as `schema.table`, in table creation and queries alike. The app's `data` config sets the default datatable and schema its tables go in; use them consistently across runnables.\n5. **Pass the role**: when the app's `data.roles` gives a data table a role, every `wmill.datatable` call on it passes that role (`wmill.datatable('main', { role: 'analyst' })` in TypeScript, `wmill.datatable('main', role='analyst')` in Python). The role only reaches what it was granted, so a query outside it fails with `permission denied`.\n6. **Per-viewer rows**: a data table with no entry in `data.roles` is called with no role. Unless its default role is `admin`, the connection then holds the default role, if it may use it, plus every role it is a tenant of, and is refused when that is none. Whose roles those are follows the runnable's identity (see \"Reading data as the viewer\"). Row-level security policies written as `pg_has_role(current_user, '<role>', 'member')` then return the right rows with nothing added to the code. A role pins the connection to that one role either way, so a data table whose rows should differ per viewer gets no `data.roles` entry. Data table roles are an Enterprise Edition feature, self-hosted only.\n\n### Querying in TypeScript (Bun/Deno)\n\n```typescript\nimport * as wmill from 'windmill-client';\n\nexport async function main(user_id: string) {\n const sql = wmill.datatable(); // Or: wmill.datatable('other_datatable')\n\n // Parameterized queries (safe from SQL injection)\n const user = await sql`SELECT * FROM users WHERE id = ${user_id}`.fetchOne();\n const users = await sql`SELECT * FROM users WHERE active = ${true}`.fetch();\n\n // Insert/Update\n await sql`INSERT INTO users (name, email) VALUES (${name}, ${email})`.execute();\n await sql`UPDATE users SET name = ${newName} WHERE id = ${user_id}`.execute();\n\n return user;\n}\n```\n\n### Querying in Python\n\n```python\nimport wmill\n\ndef main(user_id: str):\n db = wmill.datatable() # Or: wmill.datatable('other_datatable')\n\n # Use $1, $2, etc. for parameters\n user = db.query('SELECT * FROM users WHERE id = $1', user_id).fetch_one()\n users = db.query('SELECT * FROM users WHERE active = $1', True).fetch()\n\n # Insert/Update\n db.query('INSERT INTO users (name, email) VALUES ($1, $2)', name, email).execute()\n db.query('UPDATE users SET name = $1 WHERE id = $2', new_name, user_id).execute()\n\n return user\n```\n\n## Best Practices\n\n1. **Check existing tables** before creating new ones — reuse beats schema growth.\n2. **Use parameterized queries** — never concatenate user input into SQL.\n3. **Terminate every datatable statement** — the tagged template and `db.query(...)` only build a statement. It runs when you call `fetch` / `fetchOne` / `fetchOneScalar` / `execute` (`fetch` / `fetch_one` / `fetch_one_scalar` / `execute` in Python). An INSERT or UPDATE without one writes nothing and raises nothing. Awaiting the statement itself is a no-op — it is not a promise.\n4. **Keep runnables focused** — one function per runnable; small surface area.\n5. **Use descriptive keys** — `get_user`, not `a`.\n6. **Always whitelist tables** — adding a runnable that queries a new table requires the table to be in `data.tables` first.\n7. **Mark sensitive UI with `data-wm-no-record`** — it is what keeps that data out of a recorded demo; passwords are handled for you.\n8. **Reach for `backendAsync` + `waitJob`** for long work — never a hand-written job-polling runnable.\n9. **Deploy what a path runnable points at** — a path runnable aimed at a draft fails at runtime; tell the user what needs deploying.\n10. **Use `@windmill-labs/chat-sdk` for a chat over a chat-mode flow or a saved agent** — never hand-roll a runnable that runs it and polls its stream; a saved agent is an `agent` runnable passed as `{ wmill, runnable }`.\n\n\n# TypeScript SDK (windmill-client)\n\nImport: import * as wmill from 'windmill-client'\n\nThe client configures itself from the job's environment — base URL, token and credentials mode\nare all set before your code runs, so there is nothing to initialize and no reason to read\nWM_TOKEN or BASE_INTERNAL_URL and build an API URL yourself. Reconstructing that by hand only\nreintroduces details the client already handles. Call the SDK for anything Windmill, and use raw\nHTTP for third-party APIs.\n\nThe helpers below are the surface to prefer. For an endpoint none of them covers, import the\ngenerated service classes (JobService, ScriptService, ...) from 'windmill-client' — they are not\nlisted here but they do exist. What does not exist is a helper name you guessed at: if it is\nneither listed below nor a service method, do not call it.\n\nTo know who is running the script, read the contextual variables rather than calling the API:\n`process.env.WM_END_USER_EMAIL || process.env.WM_EMAIL`. WM_END_USER_EMAIL is the app viewer when\nthe run was triggered from an app and empty otherwise (both variables are always defined), WM_EMAIL\nis the user the job is permissioned as. WM_USERNAME is the matching username.\n\nworkerHasInternalServer(): boolean\n\n/**\n * Initialize the Windmill client with authentication token and base URL\n * @param token - Authentication token (defaults to WM_TOKEN env variable)\n * @param baseUrl - API base URL (defaults to BASE_INTERNAL_URL or BASE_URL env variable)\n */\nsetClient(token?: string, baseUrl?: string): void\n\n/**\n * Create a client configuration from env variables\n * @returns client configuration\n */\ngetWorkspace(): string\n\n/**\n * Get a resource value by path\n * @param path path of the resource, default to internal state path\n * @param undefinedIfEmpty if the resource does not exist, return undefined instead of throwing an error\n * @returns resource value\n */\nasync getResource(path?: string, undefinedIfEmpty?: boolean): Promise<any>\n\n/**\n * Get the true root job id\n * @param jobId job id to get the root job id from (default to current job)\n * @returns root job id\n */\nasync getRootJobId(jobId?: string): Promise<string>\n\n/**\n * Run a script synchronously by its path and wait for the result\n * @param path - Script path in Windmill\n * @param args - Arguments to pass to the script\n * @param verbose - Enable verbose logging\n * @param tag - Override the worker tag the job runs on\n * @returns Script execution result\n */\nasync runScriptByPath(path: string, args: Record<string, any> | null = null, verbose: boolean = false, tag: string | null = null): Promise<any>\n\n/**\n * Run a script synchronously by its hash and wait for the result\n * @param hash_ - Script hash in Windmill\n * @param args - Arguments to pass to the script\n * @param verbose - Enable verbose logging\n * @param tag - Override the worker tag the job runs on\n * @returns Script execution result\n */\nasync runScriptByHash(hash_: string, args: Record<string, any> | null = null, verbose: boolean = false, tag: string | null = null): Promise<any>\n\n/**\n * Append a text to the result stream\n * @param text text to append to the result stream\n */\nappendToResultStream(text: string): void\n\n/**\n * Stream to the result stream\n * @param stream stream to stream to the result stream\n */\nasync streamResult(stream: AsyncIterable<string>): Promise<void>\n\n/**\n * Run a flow synchronously by its path and wait for the result\n * @param path - Flow path in Windmill\n * @param args - Arguments to pass to the flow\n * @param verbose - Enable verbose logging\n * @param tag - Override the worker tag the job runs on\n * @returns Flow execution result\n */\nasync runFlow(path: string | null = null, args: Record<string, any> | null = null, verbose: boolean = false, tag: string | null = null): Promise<any>\n\n/**\n * Wait for a job to complete and return its result\n * @param jobId - ID of the job to wait for\n * @param verbose - Enable verbose logging\n * @returns Job result when completed\n */\nasync waitJob(jobId: string, verbose: boolean = false): Promise<any>\n\n/**\n * Get the result of a completed job\n * @param jobId - ID of the completed job\n * @returns Job result\n */\nasync getResult(jobId: string): Promise<any>\n\n/**\n * Get the result of a job if completed, or its current status\n * @param jobId - ID of the job\n * @returns Object with started, completed, success, and result properties\n */\nasync getResultMaybe(jobId: string): Promise<any>\n\n/**\n * Cancel a queued or running job by ID.\n * @param jobId - UUID of the job to cancel\n * @param reason - Optional reason for cancellation\n * @returns Response message from the cancel endpoint\n */\nasync cancelJob(jobId: string, reason: string | undefined = undefined): Promise<string>\n\n/**\n * Run a script asynchronously by its path\n * @param path - Script path in Windmill\n * @param args - Arguments to pass to the script\n * @param scheduledInSeconds - Schedule execution for a future time (in seconds), or {@link RunScriptAsyncOptions}\n * `{ scheduledInSeconds?, tag?, retry? }`, e.g. `{ retry: { constant: { attempts: 3, seconds: 10 } } }`\n * @param tag - Override the worker tag the job runs on\n * @returns Job ID of the created job\n */\nasync runScriptByPathAsync(path: string, args: Record<string, any> | null = null, scheduledInSeconds: number | null | RunScriptAsyncOptions = null, tag: string | null = null): Promise<string>\n\n/**\n * Run a script asynchronously by its hash\n * @param hash_ - Script hash in Windmill\n * @param args - Arguments to pass to the script\n * @param scheduledInSeconds - Schedule execution for a future time (in seconds), or {@link RunScriptAsyncOptions}\n * `{ scheduledInSeconds?, tag?, retry? }`, e.g. `{ retry: { constant: { attempts: 3, seconds: 10 } } }`\n * @param tag - Override the worker tag the job runs on\n * @returns Job ID of the created job\n */\nasync runScriptByHashAsync(hash_: string, args: Record<string, any> | null = null, scheduledInSeconds: number | null | RunScriptAsyncOptions = null, tag: string | null = null): Promise<string>\n\n/**\n * Run a flow asynchronously by its path\n * @param path - Flow path in Windmill\n * @param args - Arguments to pass to the flow\n * @param scheduledInSeconds - Schedule execution for a future time (in seconds)\n * @param doNotTrackInParent - If false, tracks state in parent job (only use when fully awaiting the job)\n * @param tag - Override the worker tag the job runs on\n * @returns Job ID of the created job\n */\nasync runFlowAsync(path: string | null, args: Record<string, any> | null, scheduledInSeconds: number | null = null, // can only be set to false if this the job will be fully await and not concurrent with any other job // as otherwise the child flow and its own child will store their state in the parent job which will // lead to incorrectness and failures doNotTrackInParent: boolean = true, tag: string | null = null): Promise<string>\n\n/**\n * Resolve a resource value in case the default value was picked because the input payload was undefined\n * @param obj resource value or path of the resource under the format `$res:path`\n * @returns resource value\n */\nasync resolveDefaultResource(obj: any): Promise<any>\n\n/**\n * Get the state file path from environment variables\n * @returns State path string\n */\ngetStatePath(): string\n\n/**\n * Set a resource value by path\n * @param path path of the resource to set, default to state path\n * @param value new value of the resource to set\n * @param initializeToTypeIfNotExist if the resource does not exist, initialize it with this type\n */\nasync setResource(value: any, path?: string, initializeToTypeIfNotExist?: string): Promise<void>\n\n/**\n * Set the state\n * @param state state to set\n * @param path Optional state resource path override. Defaults to `getStatePath()`.\n */\nasync setState(state: any, path?: string): Promise<void>\n\n/**\n * Set the progress\n * Progress cannot go back and limited to 0% to 99% range\n * @param percent Progress to set in %\n * @param jobId? Job to set progress for\n */\nasync setProgress(percent: number, jobId?: any): Promise<void>\n\n/**\n * Get the progress\n * @param jobId? Job to get progress from\n * @returns Optional clamped between 0 and 100 progress value\n */\nasync getProgress(jobId?: any): Promise<number | null>\n\n/**\n * Whether the worker running this job has received its shutdown signal.\n * A draining worker waits for its current job to finish before exiting, so a\n * long-running script can poll this and return early to let the worker be replaced.\n * @param jobId? Job to check, defaults to the current job\n */\nasync workerIsDraining(jobId?: string): Promise<boolean>\n\n/**\n * Set a flow user state\n * @param key key of the state\n * @param value value of the state\n */\nasync setFlowUserState(key: string, value: any, errorIfNotPossible?: boolean): Promise<void>\n\n/**\n * Get a flow user state\n * @param path path of the variable\n */\nasync getFlowUserState(key: string, errorIfNotPossible?: boolean): Promise<any>\n\n/**\n * Get the state shared across executions\n * @param path Optional state resource path override. Defaults to `getStatePath()`.\n */\nasync getState(path?: string): Promise<any>\n\n/**\n * Get a variable by path\n * @param path path of the variable\n * @returns variable value\n */\nasync getVariable(path: string): Promise<string>\n\n/**\n * Set a variable by path, create if not exist\n * @param path path of the variable\n * @param value value of the variable\n * @param isSecretIfNotExist if the variable does not exist, create it as secret or not (default: false)\n * @param descriptionIfNotExist if the variable does not exist, create it with this description (default: \"\")\n */\nasync setVariable(path: string, value: string, isSecretIfNotExist?: boolean, descriptionIfNotExist?: string): Promise<void>\n\n/**\n * Build a PostgreSQL connection URL from a database resource\n * @param path - Path to the database resource\n * @returns PostgreSQL connection URL string\n */\nasync databaseUrlFromResource(path: string): Promise<string>\n\nasync polarsConnectionSettings(s3_resource_path: string | undefined): Promise<any>\n\nasync duckdbConnectionSettings(s3_resource_path: string | undefined): Promise<any>\n\n/**\n * Get S3 client settings from a resource or workspace default\n * @param s3_resource_path - Path to S3 resource (uses workspace default if undefined)\n * @param workspace - Workspace to read from (defaults to the `WM_WORKSPACE` env var)\n * @returns S3 client configuration settings\n */\nasync denoS3LightClientSettings(s3_resource_path: string | undefined, workspace: string | undefined = undefined): Promise<DenoS3LightClientSettings>\n\n/**\n * Load the content of a file stored in S3. If the s3ResourcePath is undefined, it will default to the workspace S3 resource.\n * \n * ```typescript\n * let fileContent = await wmill.loadS3FileContent(inputFile)\n * // if the file is a raw text file, it can be decoded and printed directly:\n * const text = new TextDecoder().decode(fileContentStream)\n * console.log(text);\n * ```\n * \n * @param workspace - Workspace to read from (defaults to the `WM_WORKSPACE` env var)\n */\nasync loadS3File(s3object: S3Object, s3ResourcePath: string | undefined = undefined, workspace: string | undefined = undefined): Promise<Uint8Array | undefined>\n\n/**\n * Load the content of a file stored in S3 as a stream. If the s3ResourcePath is undefined, it will default to the workspace S3 resource.\n * \n * ```typescript\n * let fileContentBlob = await wmill.loadS3FileStream(inputFile)\n * // if the content is plain text, the blob can be read directly:\n * console.log(await fileContentBlob.text());\n * ```\n * \n * @param workspace - Workspace to read from (defaults to the `WM_WORKSPACE` env var)\n */\nasync loadS3FileStream(s3object: S3Object, s3ResourcePath: string | undefined = undefined, workspace: string | undefined = undefined): Promise<Blob | undefined>\n\n/**\n * Persist a file to the S3 bucket. If the s3ResourcePath is undefined, it will default to the workspace S3 resource.\n * \n * ```typescript\n * const s3object = await writeS3File(s3Object, \"Hello Windmill!\")\n * const fileContentAsUtf8Str = (await s3object.toArray()).toString('utf-8')\n * console.log(fileContentAsUtf8Str)\n * ```\n * \n * @param workspace - Workspace to write to (defaults to the `WM_WORKSPACE` env var)\n */\nasync writeS3File(s3object: S3Object | undefined, fileContent: string | Blob, s3ResourcePath: string | undefined = undefined, contentType: string | undefined = undefined, contentDisposition: string | undefined = undefined, workspace: string | undefined = undefined): Promise<S3Object>\n\n/**\n * Permanently delete a file from S3 by key.\n * \n * ```typescript\n * await wmill.deleteS3File({ s3: \"path/to/file.txt\" })\n * ```\n * \n * @param s3object - S3 object identifying the file to delete (must have `s3` set)\n * @param workspace - Workspace to delete from (defaults to the `WM_WORKSPACE` env var)\n */\nasync deleteS3File(s3object: S3Object, workspace: string | undefined = undefined): Promise<void>\n\n/**\n * Sign S3 objects to be used by anonymous users in public apps\n * @param s3objects s3 objects to sign\n * @param expirySecs how long the signature stays valid, in seconds (default 43200 = 12h, clamped to [60, 604800])\n * @returns signed s3 objects\n */\nasync signS3Objects(s3objects: S3Object[], { expirySecs }: { expirySecs?: number } = {}): Promise<S3Object[]>\n\n/**\n * Sign S3 object to be used by anonymous users in public apps\n * @param s3object s3 object to sign\n * @param expirySecs how long the signature stays valid, in seconds (default 43200 = 12h, clamped to [60, 604800])\n * @returns signed s3 object\n */\nasync signS3Object(s3object: S3Object, { expirySecs }: { expirySecs?: number } = {}): Promise<S3Object>\n\n/**\n * Generate a presigned public URL for an array of S3 objects.\n * If an S3 object is not signed yet, it will be signed first.\n * @param s3Objects s3 objects to sign\n * @param expirySecs how long the signature stays valid, in seconds (default 43200 = 12h, clamped to [60, 604800])\n * @returns list of signed public URLs\n */\nasync getPresignedS3PublicUrls(s3Objects: S3Object[], { baseUrl, expirySecs }: { baseUrl?: string; expirySecs?: number } = {}): Promise<string[]>\n\n/**\n * Generate a presigned public URL for an S3 object. If the S3 object is not signed yet, it will be signed first.\n * @param s3Object s3 object to sign\n * @param expirySecs how long the signature stays valid, in seconds (default 43200 = 12h, clamped to [60, 604800])\n * @returns signed public URL\n */\nasync getPresignedS3PublicUrl(s3Objects: S3Object, { baseUrl, expirySecs }: { baseUrl?: string; expirySecs?: number } = {}): Promise<string>\n\n/**\n * Get URLs needed for resuming a flow after this step\n * @param approver approver name\n * @param flowLevel if true, generate resume URLs for the parent flow instead of the specific step.\n * This allows pre-approvals that can be consumed by any later suspend step in the same flow.\n * @returns approval page UI URL, resume and cancel API URLs for resuming the flow\n */\nasync getResumeUrls(approver?: string, flowLevel?: boolean): Promise<{\n approvalPage: string;\n resume: string;\n cancel: string;\n}>\n\n/**\n * Get an OIDC jwt token for auth to external services (e.g: Vault, AWS) (ee only)\n * @param audience audience of the token\n * @param expiresIn Optional number of seconds until the token expires\n * @returns jwt token\n */\nasync getIdToken(audience: string, expiresIn?: number): Promise<string>\n\n/**\n * Convert a base64-encoded string to Uint8Array\n * @param data - Base64-encoded string\n * @returns Decoded Uint8Array\n */\nbase64ToUint8Array(data: string): Uint8Array\n\n/**\n * Convert a Uint8Array to base64-encoded string\n * @param arrayBuffer - Uint8Array to encode\n * @returns Base64-encoded string\n */\nuint8ArrayToBase64(arrayBuffer: Uint8Array): string\n\n/**\n * Sends an interactive approval request via Slack, allowing optional customization of the message, approver, and form fields.\n * \n * **[Enterprise Edition Only]** To include form fields in the Slack approval request, go to **Advanced -> Suspend -> Form**\n * and define a form. Learn more at [Windmill Documentation](https://www.windmill.dev/docs/flows/flow_approval#form).\n * \n * @param {Object} options - The configuration options for the Slack approval request.\n * @param {string} options.slackResourcePath - The path to the Slack resource in Windmill.\n * @param {string} options.channelId - The Slack channel ID where the approval request will be sent.\n * @param {string} [options.message] - Optional custom message to include in the Slack approval request.\n * @param {string} [options.approver] - Optional user ID or name of the approver for the request.\n * @param {DefaultArgs} [options.defaultArgsJson] - Optional object defining or overriding the default arguments to a form field.\n * @param {Enums} [options.dynamicEnumsJson] - Optional object overriding the enum default values of an enum form field.\n * @param {string} [options.resumeButtonText] - Optional text for the resume button.\n * @param {string} [options.cancelButtonText] - Optional text for the cancel button.\n * \n * @returns {Promise<void>} Resolves when the Slack approval request is successfully sent.\n * \n * @throws {Error} If the function is not called within a flow or flow preview.\n * @throws {Error} If the `JobService.getSlackApprovalPayload` call fails.\n * \n * **Usage Example:**\n * ```typescript\n * await requestInteractiveSlackApproval({\n * slackResourcePath: \"/u/alex/my_slack_resource\",\n * channelId: \"admins-slack-channel\",\n * message: \"Please approve this request\",\n * approver: \"approver123\",\n * defaultArgsJson: { key1: \"value1\", key2: 42 },\n * dynamicEnumsJson: { foo: [\"choice1\", \"choice2\"], bar: [\"optionA\", \"optionB\"] },\n * resumeButtonText: \"Resume\",\n * cancelButtonText: \"Cancel\",\n * });\n * ```\n * \n * **Note:** This function requires execution within a Windmill flow or flow preview.\n */\nasync requestInteractiveSlackApproval({ slackResourcePath, channelId, message, approver, defaultArgsJson, dynamicEnumsJson, resumeButtonText, cancelButtonText, }: SlackApprovalOptions): Promise<void>\n\n/**\n * Sends an interactive approval request via Teams, allowing optional customization of the message, approver, and form fields.\n * \n * **[Enterprise Edition Only]** To include form fields in the Teams approval request, go to **Advanced -> Suspend -> Form**\n * and define a form. Learn more at [Windmill Documentation](https://www.windmill.dev/docs/flows/flow_approval#form).\n * \n * @param {Object} options - The configuration options for the Teams approval request.\n * @param {string} options.teamName - The Teams team name where the approval request will be sent.\n * @param {string} options.channelName - The Teams channel name where the approval request will be sent.\n * @param {string} [options.message] - Optional custom message to include in the Teams approval request.\n * @param {string} [options.approver] - Optional user ID or name of the approver for the request.\n * @param {DefaultArgs} [options.defaultArgsJson] - Optional object defining or overriding the default arguments to a form field.\n * @param {Enums} [options.dynamicEnumsJson] - Optional object overriding the enum default values of an enum form field.\n * \n * @returns {Promise<void>} Resolves when the Teams approval request is successfully sent.\n * \n * @throws {Error} If the function is not called within a flow or flow preview.\n * @throws {Error} If the `JobService.getTeamsApprovalPayload` call fails.\n * \n * **Usage Example:**\n * ```typescript\n * await requestInteractiveTeamsApproval({\n * teamName: \"admins-teams\",\n * channelName: \"admins-teams-channel\",\n * message: \"Please approve this request\",\n * approver: \"approver123\",\n * defaultArgsJson: { key1: \"value1\", key2: 42 },\n * dynamicEnumsJson: { foo: [\"choice1\", \"choice2\"], bar: [\"optionA\", \"optionB\"] },\n * });\n * ```\n * \n * **Note:** This function requires execution within a Windmill flow or flow preview.\n */\nasync requestInteractiveTeamsApproval({ teamName, channelName, message, approver, defaultArgsJson, dynamicEnumsJson, }: TeamsApprovalOptions): Promise<void>\n\nsetWorkflowCtx(ctx: WorkflowCtx | null): void\n\nasync sleep(seconds: number): Promise<void>\n\n/**\n * Execute `fn` inline and checkpoint the result. On replay the cached value is\n * returned without re-executing `fn`.\n * \n * `fn`'s result is encoded as JSON and decoded back before it is returned, so\n * the round that runs the body sees the same types every replay sees: a `Date`\n * comes back as a string, a `Map` as `{}`. {@link Jsonified} is that shape.\n * \n * Called from inside a task body, `fn` runs in place and nothing is\n * checkpointed: a task is a single job and is never replayed.\n */\nasync step<T>(name: string, fn: () => T | Promise<T>,): Promise<Jsonified<Awaited<T>>>\n\n/**\n * Create a task that dispatches to a separate Windmill script.\n * \n * @example\n * const extract = taskScript(\"f/data/extract\");\n * // inside workflow: await extract({ url: \"https://...\" })\n */\ntaskScript(path: string, options?: TaskOptions): (...args: any[]) => PromiseLike<any>\n\n/**\n * Create a task that dispatches to a separate Windmill flow.\n * \n * @example\n * const pipeline = taskFlow(\"f/etl/pipeline\");\n * // inside workflow: await pipeline({ input: data })\n */\ntaskFlow(path: string, options?: TaskOptions): (...args: any[]) => PromiseLike<any>\n\n/**\n * Mark an async function as a workflow-as-code entry point.\n * \n * The function must be **deterministic**: given the same inputs it must call\n * tasks in the same order on every replay. Branching on task results is fine\n * (results are replayed from checkpoint), but branching on external state\n * (current time, random values, external API calls) must use `step()` to\n * checkpoint the value so replays see the same result.\n */\nworkflow<T>(fn: (...args: any[]) => Promise<T>): void\n\n/**\n * Suspend the workflow and wait for an external approval.\n * \n * Pass `key` to name the step, then `getApprovalUrls(key)` yields the URLs that\n * resume exactly this approval — route them through your own channel. Without a\n * key the steps are named `approval`, `approval_2`, ...\n * \n * `skin: \"minimal\"` shows approvers only the request (form and approve/reject)\n * instead of the detailed page with the workflow's details. `description` is\n * shown above the form: a string, or a rich value such as `{ markdown: \"...\" }`.\n * \n * @example\n * const urls = await step(\"urls\", () => getApprovalUrls(\"manager\"));\n * await step(\"notify\", () => sendEmail(urls.resume, urls.cancel));\n * const { value, approver } = await waitForApproval({ key: \"manager\", timeout: 3600 });\n */\nwaitForApproval(options?: { timeout?: number; form?: object; selfApproval?: boolean; key?: string; skin?: \"detailed\" | \"minimal\"; description?: string | object; }): PromiseLike<{ value: any; approver: string; approved: boolean }>\n\n/**\n * Resume/cancel/approval-page URLs bound to one `waitForApproval` step.\n * \n * Unlike `getResumeUrls()`, which signs a random nonce, these address the very\n * `resume_job` record the step's built-in approval buttons use, so they are\n * stable across replays and safe to embed in a custom notification.\n * \n * `stepKey` must match the `key` given to `waitForApproval`. Keys must be unique\n * within a workflow; reusing one throws rather than silently renaming it. The URL\n * only resumes while that step is awaiting approval; used at any other moment it is\n * rejected rather than banking a row a different approval would consume. Send it\n * ahead of time — approvers just cannot act before the workflow reaches the step.\n * \n * `resume` and `cancel` are step-bound; `approvalPage` is not — it opens the job's\n * approval page, which acts on whichever approval is pending when it is used.\n * \n * @example\n * const urls = await step(\"urls\", () => getApprovalUrls(\"manager\"));\n * await step(\"notify\", () => sendEmail(urls.resume, urls.cancel));\n * await waitForApproval({ key: \"manager\" });\n */\nasync getApprovalUrls(stepKey: string = \"approval\", approver?: string): Promise<{\n approvalPage: string;\n resume: string;\n cancel: string;\n}>\n\n/**\n * Process items in parallel with optional concurrency control.\n * \n * Each item is processed by calling `fn(item)`, which should be a task().\n * Items are dispatched in batches of `concurrency` (default: all at once).\n * \n * @example\n * const process = task(async (item: string) => { ... });\n * const results = await parallel(items, process, { concurrency: 5 });\n */\nasync parallel<T, R>(items: T[], fn: (item: T) => PromiseLike<R> | R, options?: { concurrency?: number },): Promise<R[]>\n\n/**\n * Commit Kafka offsets for a trigger with auto_commit disabled.\n * @param triggerPath - Path to the Kafka trigger (from event.wm_trigger.trigger_path)\n * @param topic - Kafka topic name (from event.topic)\n * @param partition - Partition number (from event.partition)\n * @param offset - Message offset to commit (from event.offset)\n */\nasync commitKafkaOffsets(triggerPath: string, topic: string, partition: number, offset: number,): Promise<void>\n\n/**\n * Parse an S3 object from URI string or record format\n * @param s3Object - S3 object as URI string (`s3://storage/key`, `s3:///key`\n * for the default storage) or record. Any other string throws rather than\n * falling back to an auto-generated key: an auto key is requested by\n * omitting the object, and a fallback would silently misplace the upload\n * on any typo.\n * @returns S3 object record with storage and s3 key\n */\nparseS3Object(s3Object: S3Object): S3ObjectRecord\n\n/**\n * Create a SQL template function for PostgreSQL/datatable queries\n * @param name - Database/datatable name (default: \"main\")\n * @param opts.role - Connect as this data table role instead of the data table's default one.\n * Only meaningful on a data table under roles, and only for a role you are a tenant of.\n * @returns SQL template function for building parameterized queries\n * @example\n * let sql = wmill.datatable()\n * let name = 'Robin'\n * let age = 21\n * await sql`\n * SELECT * FROM friends\n * WHERE name = ${name} AND age = ${age}::int\n * `.fetch()\n * @example\n * // Read through a restricted role\n * let sql = wmill.datatable(\"main\", { role: \"analytics\" })\n */\ndatatable(name: string = \"main\", opts?: DatatableOptions): DatatableSqlTemplateFunction\n\n/**\n * Create a SQL template function for DuckDB/ducklake queries\n * @param name - DuckDB database name, optionally with a schema as `name:schema` (default: \"main\")\n * @returns SQL template function for building parameterized queries\n * @example\n * let sql = wmill.ducklake()\n * let name = 'Robin'\n * let age = 21\n * await sql`\n * SELECT * FROM friends\n * WHERE name = ${name} AND age = ${age}\n * `.fetch()\n * @example\n * // Target a specific schema within the ducklake\n * let sql = wmill.ducklake(\"my_lake:analytics\")\n */\nducklake(name: string = \"main\"): SqlTemplateFunction\n\n/**\n * Idempotently materialize `selectSql` into a ducklake table for one\n * partition (or the whole table when `partition` is omitted) — the client-side\n * equivalent of the `// materialize` engine.\n * With `uniqueKey` it upserts the slice (delete-by-key + insert); otherwise it\n * replaces it (whole table → `CREATE OR REPLACE`; partition → delete + insert).\n * Safe to re-run for the same partition (backfill / failure-recovery).\n * \n * Returns a lazy statement — call `.execute()` to run it:\n * `await wmill.upsertPartition({ table, selectSql, partition }).execute()`.\n */\nupsertPartition(opts: DucklakeMaterializeOptions): SqlStatement<any>\n\n/**\n * INSERT-only materialization (no dedup/replace) for append-only tables.\n * Re-running the same partition duplicates rows — use only for immutable\n * event-log sources.\n * \n * Returns a lazy statement — call `.execute()` to run it:\n * `await wmill.appendPartition({ table, selectSql, partition }).execute()`.\n */\nappendPartition(opts: Omit<DucklakeMaterializeOptions, \"uniqueKey\">,): SqlStatement<any>\n", "app.python3": "# Global draft app instructions\n\n- Global mode edits raw app drafts only; it does not save or deploy unless the user explicitly asks to deploy.\n- App drafts are addressed by workspace path. Follow the path conventions in the system prompt: default to `u/<current-user>/<name>` for bare names; only use `f/<folder>/<name>` when the folder is known to exist. The first write tool snapshots the workspace app onto the draft, and subsequent writes accumulate.\n- To create a new app, use `init_app` with a path, optional summary, a framework (`react19` / `react18` / `svelte5`) and, for an app that stores data, its `data` setup. \"Starting a new app\" below decides the framework and when the data setup is asked. Ask the user each of its questions, suggested answer first, before `init_app` and before any SQL. `init_app` only records `data`: a new schema is yours to create with the datatable SQL tool. `init_app` errors if an app already exists at the path or a draft is already in flight; in that case, edit the existing one rather than re-initializing.\n- `init_app` seeds the starter inline runnables `greet`, `word_stats`, `slow_task`, `stream_text` so the demo tour works on first render. Replace or remove them once you start building real backend runnables.\n- Frontend file paths start with `/` (e.g. `/index.tsx`, `/App.tsx`, `/styles.css`). Use `write_app_file` / `patch_app_file` / `delete_app_file`.\n- Backend inline runnables are addressed as `backend/<key>/main.{ts|py}` from the file tools, but you create or update them via `write_app_runnable` / `delete_app_runnable` (which take the runnable shape directly: `{ name, type, inlineScript?, path?, staticInputs? }`).\n- `/wmill.d.ts` (or `wmill.ts`) is generated automatically from the backend runnables — never write it directly.\n- Inline runnables only support `bun` or `python3` in chat. Path runnables (`script`/`flow`/`hubscript`) reference an existing item.\n- When a path runnable points at a draft (see \"Draft code vs deployed code\" below), offer to deploy just that flow/script with deploy_workspace_item, not through the compare page.\n- The authoring reference below carries the Python SDK, for `python3` inline runnables. For a `bun` runnable, call `get_instructions` again with `subject: \"app\"` and no language.\n- Use `deploy_workspace_item` after explicit user deploy intent. The deploy tool bundles JS/CSS before saving the raw app.\n- Use `read_workspace_item` with `type: 'app'` for a metadata summary (file paths and runnable list, no contents). Use `read_app_file` to read an individual file; large files are truncated to a head slice, so pass `offset`/`limit` to page through the rest rather than re-reading the whole file.\n- To find where a symbol or string lives across the app, call `search_app` (greps every frontend file and inline runnable, returns matching `file:line` rows) instead of reading files one by one — then `read_app_file` only the ranges you need. The loop is list (`read_workspace_item`) → locate (`search_app`) → inspect (`read_app_file` with `offset`/`limit`).\n\n# Windmill raw app authoring reference\n\n# Windmill Raw Apps\n\nRaw apps let you build custom frontends with React or Svelte that connect to Windmill backend runnables and datatables.\n\n## App shape\n\nA raw app has three logical parts:\n\n- **Frontend** — bundled with esbuild from `index.tsx` as the entrypoint. Files include the entrypoint, components (`App.tsx`), styles, etc.\n- **Backend runnables** — server-side scripts the frontend calls, each addressed by a unique key.\n- **Data** — optional whitelisted datatables (managed PostgreSQL) that the backend runnables can query. The frontend never queries the database directly; backend runnables are the only bridge.\n\n## Starting a new app\n\nA new app gets the setup Windmill's own new-app dialog gives one: a framework, then where its data lives.\n\n### Framework\n\nUse the framework the user named. When they named none, follow what there is to follow: the app being edited, or the apps the request points at. With nothing to follow, use **React 19**, the recommended default, **without asking**. React 18 and Svelte 5 are for when they are asked for. These three are the only frameworks the raw app bundler builds. When the user asks to build or convert an app in another framework, write no code in it: say it is not available and offer these three instead.\n\n### Data setup\n\nWhen a new app has to store data and the user did not say where, **ask before creating anything**: no app, no schema, no table. Where the data lives is the user's decision, and tables created in the wrong place stay there. Look up the workspace's data tables first so every choice you offer exists, then ask, as proposed answers rather than open questions:\n\n1. **Data table**: which one to use, the default first (`main` when it exists, otherwise the first listed). Skip this one when the workspace has a single data table.\n2. **Schema**: where the app's new tables go.\n - A **new schema**, the usual choice, offered first. Suggest the first unused name among `app1`, `app2`, …\n - An **existing schema** of that data table, by name.\n - **None**: the tables go in `public`.\n3. **Tables**: only when that data table already holds tables the app could use, whether to **reuse** them (name them) or **create new ones**.\n\nDo not ask when:\n\n- the user already said where the data goes. A part they left out takes its default above: the default data table, a new `appN` schema, new tables;\n- the app, or its saved draft, already carries a data config (`data.datatable`, `data.schema` or `data.tables`). That config is the answer;\n- the app stores nothing.\n\nWith no data table in the workspace there is nothing to choose: say that one has to be configured in the workspace settings before the app can store data.\n\nA question left unanswered or dismissed is not a go-ahead for the defaults: stop there and say what is still needed.\n\nThen build what was chosen: the data table and schema become the app's `data.datatable` and `data.schema`, the tables it uses, reused or new, go in `data.tables`, and a new schema is created (`CREATE SCHEMA IF NOT EXISTS`) before the tables that go in it.\n\n### An app that arrives already set up\n\nAn app the user just started from the new-app dialog is already set up: its files are the framework template it was started with, and a `data` config it carries (`data.datatable`, `data.schema` or `data.tables`) is the data setup it was started with. Build that app in place, with that data config, and in that framework unless the user now names another. Do not ask for either, and do not create a second app. Only when it carries no data config and has to store data is the data setup still to ask.\n\n## Frontend\n\n### Entrypoint\n\nThe entrypoint is `index.tsx` for React and `index.ts` for Svelte. It is both the bundling entrypoint (the bundler is esbuild) and the **mount** entrypoint: the preview executes the bundle against an empty `<div id=\"root\">` and auto-renders nothing, so the entrypoint must mount a top-level `App` itself. Keep the UI in `App.tsx` / `App.svelte` and keep the entrypoint as the mount shim.\n\nReact (`index.tsx`):\n\n```tsx\nimport React from 'react'\nimport { createRoot } from 'react-dom/client'\nimport App from './App'\n\ncreateRoot(document.getElementById('root')!).render(<App />)\n```\n\nSvelte (`index.ts`): `mount(App, { target: document.getElementById('root')! })`.\n\n**Never replace the entrypoint with a bare component** (`export default function App() { ... }` and no mount call). A component that is defined but never mounted renders a blank screen with **no error thrown** — it never executes, so nothing reaches the console or the error overlay. If an app renders blank, check that the entrypoint still mounts `App` into `#root`.\n\n**Set the browser tab title with `document.title = '...'`** (or a `<title>` the framework renders into `<head>`). The app has no `index.html` of its own, so a `<title>` written there is never served; the deployed app's page shows whatever `document.title` holds, and follows it when it changes.\n\n**Always begin every React file (`.tsx`/`.jsx`) that uses JSX with `import React from 'react'`.** esbuild uses the classic JSX transform, so `React` must be in scope wherever JSX appears — a missing import compiles fine but throws `React is not defined` at runtime, leaving a blank screen.\n\n### Generated bindings (`wmill.d.ts` / `wmill.ts`)\n\nThe frontend imports a generated module that mirrors the backend runnables. **Never write to it directly** — it gets regenerated whenever backend runnables change. Modifying it by hand will be overwritten.\n\n### Calling backend runnables\n\nImport the generated bindings and call the runnable like a function. `./wmill` is the **only** way the frontend reaches anything server-side — datatables, workspace items, external services. Never `fetch` the Windmill API from frontend code: the bundle holds no token and builds no API URL.\n\n| Export | Resolves to | Use it for |\n|---|---|---|\n| `backend.<key>(args)` | the runnable's result | the default — run and wait |\n| `backendAsync.<key>(args)` | the **job id** (a string) | long-running work you want to track |\n| `waitJob(jobId)` | the job's **result** (rejects if the job failed) | awaiting a `backendAsync` job |\n| `getJob(jobId)` | a `Job` (`{ type, success, result, duration_ms, ... }`) | polling status without blocking |\n| `streamJob(jobId, onUpdate?)` | the final result, calling `onUpdate` per chunk | showing output as it is produced |\n\nA runnable is always called with **one object** whose keys are its `main` parameters — `main(user_id: string, limit: number)` is called as `backend.get_users({ user_id, limit })`, never with positional arguments. A runnable without parameters is called with no argument. Resource and variable ids handed to the `wmill` client are paths (`u/<user>/<name>` or `f/<folder>/<name>`).\n\nRun and wait — the common case:\n\n```tsx\nimport { backend } from './wmill';\n\nconst user = await backend.get_user({ user_id: '123' });\n```\n\nStart a long job, then await it:\n\n```tsx\nimport { backendAsync, waitJob } from './wmill';\n\nconst jobId = await backendAsync.run_report({ month: '2026-08' }); // a string\nconst report = await waitJob(jobId); // the result itself\n```\n\nOr poll it without blocking, to render progress:\n\n```tsx\nimport { getJob } from './wmill';\n\nconst job = await getJob(jobId);\nif (job.type === 'CompletedJob') setReport(job.result);\n```\n\n`backendAsync` resolves a job id and nothing else — guard on it before storing or polling. A poll loop started on an `undefined` id never completes and shows as a row stuck \"running\" forever:\n\n```tsx\nconst jobId = await backendAsync.run_report(args);\nif (!jobId) throw new Error('run_report did not start a job');\n```\n\n**Never hand-write a job-polling runnable.** A backend runnable that calls `jobs/list`, or that returns `getResultMaybe(...)` for the frontend to poll, reimplements `backendAsync` + `waitJob` / `getJob` / `streamJob` — and it is what leads to guessing at base URLs and tokens.\n\n### Keeping data out of recorded demos\n\nAn app can be demoed by recording a session: every interaction becomes a step carrying a snapshot of the page, replayed publicly or on the Hub. Password inputs are masked automatically. Mark anything else that must not appear with `data-wm-no-record` — the whole marked subtree is dropped from every snapshot, along with its values and the step's own metadata:\n\n```tsx\n<label data-wm-no-record>\n Customer SSN <input value={ssn} onChange={onSsn} />\n</label>\n```\n\nApply it to customer data, internal notes and anything else a viewer of the demo should not see. It costs nothing when the app is never recorded.\n\n### Chat UIs over a flow in chat mode or a saved agent\n\nA flow deployed with chat mode on is a chat backend (streaming answer, tool calls, memory, conversation history). Do not drive it through a runnable: add `@windmill-labs/chat-sdk` to `package.json` and use it directly, it detects the app's Windmill and credential.\n\n```tsx\nimport { useWindmillChat } from '@windmill-labs/chat-sdk/react'\n\nconst chat = useWindmillChat({ flowPath: 'f/support/assistant' })\n// chat.messages ({ role, content, pending, success, tool? }), chat.status, chat.sendMessage(text), chat.stop()\n```\n\n`@windmill-labs/chat-sdk/ai-sdk` gives a `ChatTransport` for the Vercel AI SDK's `useChat`, `@windmill-labs/chat-sdk/assistant-ui` a runtime for assistant-ui. The flow must be deployed, not a draft. A sandboxed app needs `jobs:run` in its frontend SDK scopes, plus `flow_conversations:write` for the conversation sidebar; without them the chat keeps history in the browser.\n\n#### A saved agent: an `agent` runnable\n\nChat with a saved AI agent (an `ai_agent` resource) through an `agent` runnable, a path runnable whose `path` is the agent's. Each call runs one turn of the agent's chat as the app, so a sandboxed app declares no frontend SDK scope, viewers get no consent prompt and need no access to the agent. Prefer it in every app, sandboxed or not:\n\n```json\n{ \"chat\": { \"type\": \"agent\", \"path\": \"f/support/agent\" } }\n```\n\n```tsx\nimport { useWindmillChat } from '@windmill-labs/chat-sdk/react'\nimport * as wmill from './wmill'\n\nconst chat = useWindmillChat({ wmill, runnable: 'chat' })\n```\n\n`runnable` is the runnable's key; each runnable keeps its own conversations. The runnable takes `user_message` and `memory_id`, the conversation id, which the chat fills in: the agent remembers earlier turns of a conversation, and a signed-in viewer's conversations are theirs alone. Called directly as `backend.<key>({ user_message })` without `memory_id`, it is a single run with no conversation, for a one-off question. The chat needs an agent with managed memory. An agent whose memory is off keeps none: its runnable takes `previous_messages` (chat messages) instead of `memory_id`, and the app keeps the history itself. The chat keeps its transcript in the app's own storage. `chat.stop()` stops following without cancelling the turn, and a message sent while it still runs is refused with `TurnRunningError`. Attachments are not supported this way.\n\n## Backend runnables\n\nEach runnable has a unique key (used to call it from the frontend) and one of five types:\n\n| Type | What it is |\n|---|---|\n| `inline` | Custom code stored on the app itself. Most common for app-specific logic. |\n| `script` | Reference to an existing workspace script by path. |\n| `flow` | Reference to an existing workspace flow by path. |\n| `hubscript` | Reference to a hub script by path. |\n| `agent` | Reference to a saved AI agent by path. Each call is one turn of its chat (see the chat section above). |\n\n### Inline runnables\n\nInline runnables carry their own source code, and must expose a `main` function as their entrypoint.\n\n**TypeScript example** (runnable `get_user`):\n\n```typescript\nimport * as wmill from 'windmill-client';\n\nexport async function main(user_id: string) {\n const sql = wmill.datatable();\n const user = await sql`SELECT * FROM users WHERE id = ${user_id}`.fetchOne();\n return user;\n}\n```\n\n**Python example** (runnable `get_user`):\n\n```python\nimport wmill\n\ndef main(user_id: str):\n db = wmill.datatable()\n user = db.query('SELECT * FROM users WHERE id = $1', user_id).fetch_one()\n return user\n```\n\n#### Sharing code between runnables\n\nAn inline runnable can import another inline runnable of the same app by its id, as a relative import: `import { getDb } from './shared'` (TypeScript, Bun) or `from .shared import get_db` (Python). This works across TypeScript (Bun) runnables and across Python runnables, not between the two. The imported runnable's own dependencies are picked up, and it can import further runnables in turn. A runnable that only holds helpers needs no `main`; the frontend just never calls it. A TypeScript runnable whose id is `main` cannot be imported, because that name is taken by the entrypoint file of every TypeScript job: give shared code any other id.\n\n#### The `wmill` client is already authenticated\n\nAn inline runnable runs as an ordinary Windmill job. `import * as wmill from 'windmill-client'` (TypeScript) and `import wmill` (Python) are already pointed at this instance and this workspace — there is nothing to configure.\n\n**Don't read `WM_TOKEN` or `BASE_INTERNAL_URL` and build an API URL to `fetch`.** The client's own `setClient` already reads exactly those, and it also sets the credentials mode a raw app needs (`WM_RAW_APP` suppresses credentials, because a sandboxed bundle calls the API from an opaque origin that can never pair with `Access-Control-Allow-Origin: *`). Rebuilding that by hand drops the parts you can't see. Use `wmill.*` for everything Windmill, and `fetch` only for third-party APIs.\n\nUse only `wmill` functions the SDK actually exports; for an endpoint none of them covers, the generated service classes (`JobService`, `ScriptService`, ...) are importable from `windmill-client`. What is not available is a name you guessed at: `getBaseUrl` and `getWorkspaceToken` are inventions, not API.\n\n### Path runnables (script / flow / hubscript / agent)\n\nWhen `type` is `script`, `flow`, `hubscript` or `agent`, the runnable just stores a `path` to an existing workspace or hub item — no inline code. The referenced item's input/output schema becomes the runnable's surface; an agent's is `user_message` and `user_attachments`, plus `memory_id` when the agent keeps managed memory or `previous_messages` when its memory is off.\n\nBefore writing an inline runnable, look for a workspace script or flow that already does the job, or a Hub script (a prebuilt integration at `hub/<version>/<app>/<name>`) for a third-party service, and reference it instead of copying its logic.\n\n### Draft code vs deployed code\n\nThis decides whether an app works before anything is deployed:\n\n- **Inline runnables run the app's current code.** The editor sends the runnable's source with each request, so an inline runnable works in the preview with nothing deployed.\n- **Path runnables (`script` / `flow` / `hubscript` / `agent`) run the DEPLOYED item at that path.** So do `wmill.runFlow`, `wmill.runFlowAsync` and `wmill.runScriptByPath` called from inside a runnable. A draft — including a draft you just created — does not exist for them.\n\nSo an app wired to a flow you just wrote does nothing until **that flow is deployed**. The app itself does NOT have to be deployed for this: the preview runs the app's draft, so the referenced flow is the only thing that has to exist deployed.\n\nThat makes the fix a one-item deploy, not a release. Offer to deploy exactly the referenced flow or script and leave the app a draft the user keeps testing in the preview — do not push the whole change set through the review-and-deploy page, and do not ask the user to deploy the app, unless they said they want to ship it.\n\nDo NOT quietly reimplement the flow inside an inline runnable to dodge the deployment: that leaves the user with two copies of the same logic and an app that ignores the flow they asked for. Inline the logic only when the user actually wants it inline.\n\nPrefer a **path runnable of type `flow`** over an inline runnable that calls `wmill.runFlowAsync`. The path runnable gives the frontend the flow's real input schema and works with `backend` / `backendAsync` / `waitJob` like any other runnable; a hand-written wrapper gives up all of that.\n\n### Static inputs\n\n`staticInputs` is an optional `Record<string, any>` for arguments not overridable from the frontend. Useful with path runnables to pre-fill some args while leaving the rest to the frontend caller.\n\n## Who can open a deployed app\n\nA draft app is reachable by nobody; deploying is what exposes it, and its backend runnables with it. Otherwise only users with access to the app can open it, unless the app is opened to:\n\n- **anonymous** users: anyone with the URL, without logging in;\n- **guests**: anyone the instance's identity provider authenticates, whether or not they belong to the workspace.\n\nEither one lets those people run the app's backend runnables, so never open an app up unless the user asks.\nWhen a deploy widens who may open the app, tell the user in plain words.\n\n## Sandbox isolation and frontend API access\n\nNew apps are sandboxed: the frontend is isolated from the viewer's own Windmill session and reaches Windmill only through its backend runnables, plus whatever frontend API scopes the app declares, which each viewer approves before the app runs. With isolation turned off, the frontend runs with the viewer's full session. The scopes are `jobs:run`, `jobs:read`, `resources:read`, `variables:read`, `flow_conversations:read` and `flow_conversations:write`; grant only the ones the frontend calls. The viewer's identity needs no scope: it is in `window.ctx`, and whoami works with any of them.\n\nInside the sandbox, IndexedDB is unavailable, third-party sign-in and OAuth redirects fail, and requests to other services carry `Origin: null`, which an API that checks the origin rejects. Work around these first: call the service from a backend runnable, keep state in a data table or `localStorage`, or grant the frontend API scope the code needs. Suggest turning isolation off only when none of that works, and say plainly that it is a security risk: the app's code, and any XSS bug in it, then runs with the full Windmill permissions of everyone who opens the app.\nYou cannot turn isolation off; the user does it in the app's deploy settings.\n\n## Reading data as the viewer\n\nA backend runnable reads data as the app's identity (the publisher in publisher mode), the same for every viewer. An inline runnable can instead read data as the person using the app: its data table connections that name no role hold that viewer's roles, and object storage permission rules (which paths may be listed, read, written) are checked against the viewer. Resources, variables and everything else stay the app's, and an anonymous viewer is refused. Turn it on only when what the runnable reads should differ per viewer: row-level security on a data table, or per-user paths in object storage. Both are Enterprise Edition features.\nSet it with `viewerDataAccess: true` on the backend runnable.\n\n## Data Tables\n\nData tables are PostgreSQL databases managed by Windmill. Backend runnables query them via the `wmill` client; the frontend never queries them directly. **When the app needs to store or persist data** (user data, settings, application state, records, logs), use a data table.\n\n### Critical rules\n\n1. **Check what exists first**: look up the workspace's data tables and their tables before designing storage, and reuse a suitable table rather than creating another. Never assume a `main` data table exists.\n2. **Whitelisted tables only**: a runnable can only query tables listed in the app's `data.tables` config. Queries against unlisted tables fail at runtime, so register a new table there before using it.\n3. **No DDL inside runnables**: runnables only read and write rows (SELECT, INSERT, UPDATE, DELETE) on existing tables. Never CREATE, ALTER or DROP a table from a runnable.\n4. **Qualify table names**: an unqualified name means the `public` schema, so write every other table as `schema.table`, in table creation and queries alike. The app's `data` config sets the default datatable and schema its tables go in; use them consistently across runnables.\n5. **Pass the role**: when the app's `data.roles` gives a data table a role, every `wmill.datatable` call on it passes that role (`wmill.datatable('main', { role: 'analyst' })` in TypeScript, `wmill.datatable('main', role='analyst')` in Python). The role only reaches what it was granted, so a query outside it fails with `permission denied`.\n6. **Per-viewer rows**: a data table with no entry in `data.roles` is called with no role. Unless its default role is `admin`, the connection then holds the default role, if it may use it, plus every role it is a tenant of, and is refused when that is none. Whose roles those are follows the runnable's identity (see \"Reading data as the viewer\"). Row-level security policies written as `pg_has_role(current_user, '<role>', 'member')` then return the right rows with nothing added to the code. A role pins the connection to that one role either way, so a data table whose rows should differ per viewer gets no `data.roles` entry. Data table roles are an Enterprise Edition feature, self-hosted only.\n\n### Querying in TypeScript (Bun/Deno)\n\n```typescript\nimport * as wmill from 'windmill-client';\n\nexport async function main(user_id: string) {\n const sql = wmill.datatable(); // Or: wmill.datatable('other_datatable')\n\n // Parameterized queries (safe from SQL injection)\n const user = await sql`SELECT * FROM users WHERE id = ${user_id}`.fetchOne();\n const users = await sql`SELECT * FROM users WHERE active = ${true}`.fetch();\n\n // Insert/Update\n await sql`INSERT INTO users (name, email) VALUES (${name}, ${email})`.execute();\n await sql`UPDATE users SET name = ${newName} WHERE id = ${user_id}`.execute();\n\n return user;\n}\n```\n\n### Querying in Python\n\n```python\nimport wmill\n\ndef main(user_id: str):\n db = wmill.datatable() # Or: wmill.datatable('other_datatable')\n\n # Use $1, $2, etc. for parameters\n user = db.query('SELECT * FROM users WHERE id = $1', user_id).fetch_one()\n users = db.query('SELECT * FROM users WHERE active = $1', True).fetch()\n\n # Insert/Update\n db.query('INSERT INTO users (name, email) VALUES ($1, $2)', name, email).execute()\n db.query('UPDATE users SET name = $1 WHERE id = $2', new_name, user_id).execute()\n\n return user\n```\n\n## Best Practices\n\n1. **Check existing tables** before creating new ones — reuse beats schema growth.\n2. **Use parameterized queries** — never concatenate user input into SQL.\n3. **Terminate every datatable statement** — the tagged template and `db.query(...)` only build a statement. It runs when you call `fetch` / `fetchOne` / `fetchOneScalar` / `execute` (`fetch` / `fetch_one` / `fetch_one_scalar` / `execute` in Python). An INSERT or UPDATE without one writes nothing and raises nothing. Awaiting the statement itself is a no-op — it is not a promise.\n4. **Keep runnables focused** — one function per runnable; small surface area.\n5. **Use descriptive keys** — `get_user`, not `a`.\n6. **Always whitelist tables** — adding a runnable that queries a new table requires the table to be in `data.tables` first.\n7. **Mark sensitive UI with `data-wm-no-record`** — it is what keeps that data out of a recorded demo; passwords are handled for you.\n8. **Reach for `backendAsync` + `waitJob`** for long work — never a hand-written job-polling runnable.\n9. **Deploy what a path runnable points at** — a path runnable aimed at a draft fails at runtime; tell the user what needs deploying.\n10. **Use `@windmill-labs/chat-sdk` for a chat over a chat-mode flow or a saved agent** — never hand-roll a runnable that runs it and polls its stream; a saved agent is an `agent` runnable passed as `{ wmill, runnable }`.\n\n\n# Python SDK (wmill)\n\nImport: import wmill\n\nThe client configures itself from the job's environment — base URL, token and credentials mode\nare all set before your code runs, so there is nothing to initialize and no reason to read\nWM_TOKEN or BASE_INTERNAL_URL and build an API URL yourself. Reconstructing that by hand only\nreintroduces details the client already handles. Call the SDK for anything Windmill, and use raw\nHTTP for third-party APIs.\n\nThe functions below are the surface to prefer. For an endpoint none of them covers,\nwmill.Windmill().get(endpoint) and .post(endpoint) issue an authenticated request against this\ninstance. What does not exist is a function name you guessed at: if it is not listed below, do\nnot call it.\n\nTo know who is running the script, read the contextual variables rather than calling the API:\n`os.environ.get(\"WM_END_USER_EMAIL\") or os.environ.get(\"WM_EMAIL\")`. WM_END_USER_EMAIL is the app\nviewer when the run was triggered from an app and empty otherwise (both variables are always\ndefined), WM_EMAIL is the user the job is permissioned as. WM_USERNAME is the matching username.\n\ndef worker_has_internal_server() -> bool\n\ndef get_mocked_api() -> Optional[dict]\n\n# Get the HTTP client instance.\n# \n# Returns:\n# Configured httpx.Client for API requests\ndef get_client() -> httpx.Client\n\n# Make an HTTP GET request to the Windmill API.\n# \n# Args:\n# endpoint: API endpoint path\n# raise_for_status: Whether to raise an exception on HTTP errors\n# **kwargs: Additional arguments passed to httpx.get\n# \n# Returns:\n# HTTP response object\ndef get(endpoint, raise_for_status = True, **kwargs) -> httpx.Response\n\n# Make an HTTP POST request to the Windmill API.\n# \n# Args:\n# endpoint: API endpoint path\n# raise_for_status: Whether to raise an exception on HTTP errors\n# **kwargs: Additional arguments passed to httpx.post\n# \n# Returns:\n# HTTP response object\ndef post(endpoint, raise_for_status = True, **kwargs) -> httpx.Response\n\n# Create a new authentication token.\n# \n# Args:\n# duration: Token validity duration (default: 1 day)\n# \n# Returns:\n# New authentication token string\ndef create_token(duration = dt.timedelta(days=1)) -> str\n\n# Create a script job by path and return its job id.\n# \n# ``retry`` re-runs the job when it fails, with the policy a schedule takes,\n# e.g. ``{\"constant\": {\"attempts\": 3, \"seconds\": 10}}``. The returned id is\n# the first attempt's; each retry is a job of its own, recorded as a child of it.\ndef run_script_by_path_async(path: str, args: dict = None, scheduled_in_secs: int = None, tag: str = None, retry: dict = None) -> str\n\n# Create a script job by hash and return its job id. See ``run_script_by_path_async`` for ``retry``.\ndef run_script_by_hash_async(hash_: str, args: dict = None, scheduled_in_secs: int = None, tag: str = None, retry: dict = None) -> str\n\n# Create a flow job and return its job id.\ndef run_flow_async(path: str, args: dict = None, scheduled_in_secs: int = None, do_not_track_in_parent: bool = True, tag: str = None) -> str\n\n# Run script by path synchronously and return its result.\ndef run_script_by_path(path: str, args: dict = None, timeout: dt.timedelta | int | float | None = None, verbose: bool = False, cleanup: bool = True, assert_result_is_not_none: bool = False, tag: str = None) -> Any\n\n# Run script by hash synchronously and return its result.\ndef run_script_by_hash(hash_: str, args: dict = None, timeout: dt.timedelta | int | float | None = None, verbose: bool = False, cleanup: bool = True, assert_result_is_not_none: bool = False, tag: str = None) -> Any\n\n# Run a script on the current worker without creating a job.\n# \n# On agent workers (no internal server), falls back to running a normal\n# preview job and waiting for the result.\ndef run_inline_script_preview(content: str, language: str, args: dict = None) -> Any\n\n# Wait for a job to complete and return its result.\n# \n# Args:\n# job_id: ID of the job to wait for\n# timeout: Maximum time to wait (seconds or timedelta)\n# verbose: Enable verbose logging\n# cleanup: Register cleanup handler to cancel job on exit\n# assert_result_is_not_none: Raise exception if result is None\n# \n# Returns:\n# Job result when completed\n# \n# Raises:\n# TimeoutError: If timeout is reached\n# Exception: If job fails\ndef wait_job(job_id, timeout: dt.timedelta | int | float | None = None, verbose: bool = False, cleanup: bool = True, assert_result_is_not_none: bool = False)\n\n# Cancel a specific job by ID.\n# \n# Args:\n# job_id: UUID of the job to cancel\n# reason: Optional reason for cancellation\n# \n# Returns:\n# Response message from the cancel endpoint\ndef cancel_job(job_id: str, reason: str = None) -> str\n\n# Cancel currently running executions of the same script.\ndef cancel_running() -> dict\n\n# Get job details by ID.\n# \n# Args:\n# job_id: UUID of the job\n# \n# Returns:\n# Job details dictionary\ndef get_job(job_id: str) -> dict\n\n# Get the root job ID for a flow hierarchy.\n# \n# Args:\n# job_id: Job ID (defaults to current WM_JOB_ID)\n# \n# Returns:\n# Root job ID\ndef get_root_job_id(job_id: str | None = None) -> dict\n\n# Get an OIDC JWT token for authentication to external services.\n# \n# Args:\n# audience: Token audience (e.g., \"vault\", \"aws\")\n# expires_in: Optional expiration time in seconds\n# \n# Returns:\n# JWT token string\ndef get_id_token(audience: str, expires_in: int | None = None) -> str\n\n# Get the status of a job.\n# \n# Args:\n# job_id: UUID of the job\n# \n# Returns:\n# Job status: \"RUNNING\", \"WAITING\", or \"COMPLETED\"\ndef get_job_status(job_id: str) -> JobStatus\n\n# Get the result of a completed job.\n# \n# Args:\n# job_id: UUID of the completed job\n# assert_result_is_not_none: Raise exception if result is None\n# \n# Returns:\n# Job result\ndef get_result(job_id: str, assert_result_is_not_none: bool = True) -> Any\n\n# Get a variable value by path.\n# \n# Args:\n# path: Variable path in Windmill\n# \n# Returns:\n# Variable value as string\ndef get_variable(path: str) -> str\n\n# Set a variable value by path, creating it if it doesn't exist.\n# \n# Args:\n# path: Variable path in Windmill\n# value: Variable value to set\n# is_secret: Whether the variable should be secret (default: False)\ndef set_variable(path: str, value: str, is_secret: bool = False) -> None\n\n# Get a resource value by path.\n# \n# Args:\n# path: Resource path in Windmill\n# none_if_undefined: Return None instead of raising if not found\n# interpolated: if variables and resources are fully unrolled\n# \n# Returns:\n# Resource value dictionary or None\ndef get_resource(path: str, none_if_undefined: bool = False, interpolated: bool = True) -> dict | None\n\n# Set a resource value by path, creating it if it doesn't exist.\n# \n# Args:\n# value: Resource value to set\n# path: Resource path in Windmill\n# resource_type: Resource type for creation\ndef set_resource(value: Any, path: str, resource_type: str)\n\n# List resources from Windmill workspace.\n# \n# Args:\n# resource_type: Optional resource type to filter by (e.g., \"postgresql\", \"mysql\", \"s3\")\n# page: Optional page number for pagination\n# per_page: Optional number of results per page\n# \n# Returns:\n# List of resource dictionaries\ndef list_resources(resource_type: str = None, page: int = None, per_page: int = None) -> list[dict]\n\n# Set the workflow state.\n# \n# Args:\n# value: State value to set\n# path: Optional state resource path override.\ndef set_state(value: Any, path: str | None = None) -> None\n\n# Get the workflow state.\n# \n# Args:\n# path: Optional state resource path override.\n# \n# Returns:\n# State value or None if not set\ndef get_state(path: str | None = None) -> Any\n\n# Set job progress percentage (0-99).\n# \n# Args:\n# value: Progress percentage\n# job_id: Job ID (defaults to current WM_JOB_ID)\ndef set_progress(value: int, job_id: Optional[str] = None)\n\n# Get job progress percentage.\n# \n# Args:\n# job_id: Job ID (defaults to current WM_JOB_ID)\n# \n# Returns:\n# Progress value (0-100) or None if not set\ndef get_progress(job_id: Optional[str] = None) -> Any\n\n# Whether the worker running the job has received its shutdown signal.\n# \n# A draining worker waits for its current job to finish before exiting. A long-running\n# script can poll this and return early so the worker can be replaced.\n# \n# Args:\n# job_id: Job ID (defaults to current WM_JOB_ID)\n# \n# Returns:\n# True if the worker running the job is draining\ndef worker_is_draining(job_id: Optional[str] = None) -> bool\n\n# Set the user state of a flow at a given key\ndef set_flow_user_state(key: str, value: Any) -> None\n\n# Get the user state of a flow at a given key\ndef get_flow_user_state(key: str) -> Any\n\n# Get the Windmill server version.\n# \n# Returns:\n# Version string\ndef version()\n\n# Convenient helpers that takes an S3 resource as input and returns the settings necessary to\n# initiate an S3 connection from DuckDB.\n# \n# Without a resource path, the connection goes to the workspace storage through Windmill's\n# S3 proxy when that storage is S3: address it as ``s3://<bucket>/<key>`` with the\n# storage's own bucket, returned as ``s3_bucket``. Pass the resource path to connect with\n# the storage's own credentials instead.\ndef get_duckdb_connection_settings(s3_resource_path: str = '') -> DuckDbConnectionSettings | None\n\n# Convenient helpers that takes an S3 resource as input and returns the settings necessary to\n# initiate an S3 connection from Polars.\n# \n# Without a resource path, the connection goes to the workspace storage through Windmill's\n# S3 proxy when that storage is S3: address it as ``s3://<bucket>/<key>`` with the\n# storage's own bucket, returned as ``s3_bucket``. Pass the resource path to connect with\n# the storage's own credentials instead.\ndef get_polars_connection_settings(s3_resource_path: str = '') -> PolarsConnectionSettings\n\n# Convenient helpers that takes an S3 resource as input and returns the settings necessary to\n# initiate an S3 connection using boto3.\n# \n# Without a resource path, the connection goes to the workspace storage through Windmill's\n# S3 proxy when that storage is S3: pass the storage's own bucket as ``Bucket``. The proxy\n# serves object reads, writes, deletes, listing and multipart uploads of that bucket only;\n# presigned URLs, other buckets and bucket-level APIs need the storage's own credentials,\n# which passing the resource path returns.\ndef get_boto3_connection_settings(s3_resource_path: str = '') -> Boto3ConnectionSettings\n\n# Load a file from the workspace s3 bucket and returns its content as bytes.\n# \n# '''python\n# from wmill import S3Object\n# \n# s3_obj = S3Object(s3=\"/path/to/my_file.txt\")\n# my_obj_content = client.load_s3_file(s3_obj)\n# file_content = my_obj_content.decode(\"utf-8\")\n# '''\ndef load_s3_file(s3object: S3Object | str, s3_resource_path: str | None) -> bytes\n\n# Load a file from the workspace s3 bucket and returns the bytes stream.\n# \n# '''python\n# from wmill import S3Object\n# \n# s3_obj = S3Object(s3=\"/path/to/my_file.txt\")\n# with wmill.load_s3_file_reader(s3object, s3_resource_path) as file_reader:\n# print(file_reader.read())\n# '''\ndef load_s3_file_reader(s3object: S3Object | str, s3_resource_path: str | None) -> BufferedReader\n\n# Write a file to the workspace S3 bucket\n# \n# '''python\n# from wmill import S3Object\n# \n# s3_obj = S3Object(s3=\"/path/to/my_file.txt\")\n# \n# # for an in memory bytes array:\n# file_content = b'Hello Windmill!'\n# client.write_s3_file(s3_obj, file_content)\n# \n# # for a file:\n# with open(\"my_file.txt\", \"rb\") as my_file:\n# client.write_s3_file(s3_obj, my_file)\n# '''\ndef write_s3_file(s3object: S3Object | str | None, file_content: BufferedReader | bytes, s3_resource_path: str | None, content_type: str | None = None, content_disposition: str | None = None) -> S3Object\n\n# Permanently delete a file from the workspace S3 bucket.\n# \n# '''python\n# from wmill import S3Object\n# \n# s3_obj = S3Object(s3=\"/path/to/my_file.txt\")\n# client.delete_s3_object(s3_obj)\n# '''\ndef delete_s3_object(s3object: S3Object | str, s3_resource_path: str | None = None) -> None\n\n# Sign S3 objects for use by anonymous users in public apps.\n# \n# Args:\n# s3_objects: List of S3 objects to sign\n# expiry_secs: How long the signature stays valid, in seconds\n# (defaults to 43200 = 12h, clamped to [60, 604800])\n# \n# Returns:\n# List of signed S3 objects\ndef sign_s3_objects(s3_objects: list[S3Object | str], expiry_secs: int | None = None) -> list[S3Object]\n\n# Sign a single S3 object for use by anonymous users in public apps.\n# \n# Args:\n# s3_object: S3 object to sign\n# expiry_secs: How long the signature stays valid, in seconds\n# (defaults to 43200 = 12h, clamped to [60, 604800])\n# \n# Returns:\n# Signed S3 object\ndef sign_s3_object(s3_object: S3Object | str, expiry_secs: int | None = None) -> S3Object\n\n# Generate presigned public URLs for an array of S3 objects.\n# If an S3 object is not signed yet, it will be signed first.\n# \n# Args:\n# s3_objects: List of S3 objects to sign\n# base_url: Optional base URL for the presigned URLs (defaults to WM_BASE_URL)\n# expiry_secs: How long the signatures stay valid, in seconds\n# (defaults to 43200 = 12h, clamped to [60, 604800])\n# \n# Returns:\n# List of signed public URLs\n# \n# Example:\n# >>> s3_objs = [S3Object(s3=\"/path/to/file1.txt\"), S3Object(s3=\"/path/to/file2.txt\")]\n# >>> urls = client.get_presigned_s3_public_urls(s3_objs)\ndef get_presigned_s3_public_urls(s3_objects: list[S3Object | str], base_url: str | None = None, expiry_secs: int | None = None) -> list[str]\n\n# Generate a presigned public URL for an S3 object.\n# If the S3 object is not signed yet, it will be signed first.\n# \n# Args:\n# s3_object: S3 object to sign\n# base_url: Optional base URL for the presigned URL (defaults to WM_BASE_URL)\n# expiry_secs: How long the signature stays valid, in seconds\n# (defaults to 43200 = 12h, clamped to [60, 604800])\n# \n# Returns:\n# Signed public URL\n# \n# Example:\n# >>> s3_obj = S3Object(s3=\"/path/to/file.txt\")\n# >>> url = client.get_presigned_s3_public_url(s3_obj)\ndef get_presigned_s3_public_url(s3_object: S3Object | str, base_url: str | None = None, expiry_secs: int | None = None) -> str\n\n# Get the current user information.\n# \n# Returns:\n# User details dictionary\ndef whoami() -> dict\n\n# Get the current user information (alias for whoami).\n# \n# Returns:\n# User details dictionary\ndef user() -> dict\n\n# Get the state resource path from environment.\n# \n# Returns:\n# State path string\ndef state_path() -> str\n\n# Get the workflow state.\n# \n# Returns:\n# State value or None if not set\ndef state() -> Any\n\n# Set the state in the shared folder using pickle\ndef set_shared_state_pickle(value: Any, path: str = 'state.pickle') -> None\n\n# Get the state in the shared folder using pickle\ndef get_shared_state_pickle(path: str = 'state.pickle') -> Any\n\n# Set the state in the shared folder using pickle\ndef set_shared_state(value: Any, path: str = 'state.json') -> None\n\n# Get the state in the shared folder using pickle\ndef get_shared_state(path: str = 'state.json') -> None\n\n# Get URLs needed for resuming a flow after suspension.\n# \n# Args:\n# approver: Optional approver name\n# flow_level: If True, generate resume URLs for the parent flow instead of the\n# specific step. This allows pre-approvals that can be consumed by any later\n# suspend step in the same flow.\n# \n# Returns:\n# Dictionary with approvalPage, resume, and cancel URLs\ndef get_resume_urls(approver: str = None, flow_level: bool = None) -> dict\n\n# Get the resume URLs bound to one ``wait_for_approval`` step of this workflow.\n# \n# Args:\n# step_key: Checkpoint key of the approval step, as passed to\n# ``wait_for_approval(key=...)``\n# approver: Optional approver name\n# \n# Returns:\n# Dictionary with approvalPage, resume, and cancel URLs\ndef get_approval_urls(step_key: str = 'approval', approver: str = None) -> dict\n\n# Sends an interactive approval request via Slack, allowing optional customization of the message, approver, and form fields.\n# \n# **[Enterprise Edition Only]** To include form fields in the Slack approval request, use the \"Advanced -> Suspend -> Form\" functionality.\n# Learn more at: https://www.windmill.dev/docs/flows/flow_approval#form\n# \n# :param slack_resource_path: The path to the Slack resource in Windmill.\n# :type slack_resource_path: str\n# :param channel_id: The Slack channel ID where the approval request will be sent.\n# :type channel_id: str\n# :param message: Optional custom message to include in the Slack approval request.\n# :type message: str, optional\n# :param approver: Optional user ID or name of the approver for the request.\n# :type approver: str, optional\n# :param default_args_json: Optional dictionary defining or overriding the default arguments for form fields.\n# :type default_args_json: dict, optional\n# :param dynamic_enums_json: Optional dictionary overriding the enum default values of enum form fields.\n# :type dynamic_enums_json: dict, optional\n# \n# :raises Exception: If the function is not called within a flow or flow preview.\n# :raises Exception: If the required flow job or flow step environment variables are not set.\n# \n# :return: None\n# \n# **Usage Example:**\n# >>> client.request_interactive_slack_approval(\n# ... slack_resource_path=\"/u/alex/my_slack_resource\",\n# ... channel_id=\"admins-slack-channel\",\n# ... message=\"Please approve this request\",\n# ... approver=\"approver123\",\n# ... default_args_json={\"key1\": \"value1\", \"key2\": 42},\n# ... dynamic_enums_json={\"foo\": [\"choice1\", \"choice2\"], \"bar\": [\"optionA\", \"optionB\"]},\n# ... )\n# \n# **Notes:**\n# - This function must be executed within a Windmill flow or flow preview.\n# - The function checks for required environment variables (`WM_FLOW_JOB_ID`, `WM_FLOW_STEP_ID`) to ensure it is run in the appropriate context.\ndef request_interactive_slack_approval(slack_resource_path: str, channel_id: str, message: str = None, approver: str = None, default_args_json: dict = None, dynamic_enums_json: dict = None) -> None\n\n# Send a message to a Microsoft Teams conversation with conversation_id, where success is used to style the message\ndef send_teams_message(conversation_id: str, text: str, success: bool = True, card_block: dict = None)\n\n# Get a DataTable client for SQL queries.\n# \n# Args:\n# name: Database name (default: \"main\")\n# role: Connect as this data table role instead of the data table's default one.\n# Only meaningful on a data table under roles, and only for a role you are a\n# tenant of.\n# \n# Returns:\n# DataTableClient instance\ndef datatable(name: str = 'main', *, role: Optional[str] = None)\n\n# Get a DuckLake client for DuckDB queries.\n# \n# Args:\n# name: Database name (default: \"main\")\n# \n# Returns:\n# DucklakeClient instance\ndef ducklake(name: str = 'main')\n\ndef init_global_client(f)\n\ndef deprecate(in_favor_of: str)\n\n# Get the current workspace ID.\n# \n# Returns:\n# Workspace ID string\ndef get_workspace() -> str\n\ndef get_version() -> str\n\n# Create a script job and return its job ID.\n# \n# Args:\n# hash_or_path: Script hash or path (determined by presence of '/')\n# args: Script arguments\n# scheduled_in_secs: Delay before execution in seconds\n# tag: Override the worker tag the job runs on\n# \n# Returns:\n# Job ID string\ndef run_script_async(hash_or_path: str, args: Dict[str, Any] = None, scheduled_in_secs: int = None, tag: str = None) -> str\n\n# Run a script synchronously by hash and return its result.\n# \n# Args:\n# hash: Script hash\n# args: Script arguments\n# verbose: Enable verbose logging\n# assert_result_is_not_none: Raise exception if result is None\n# cleanup: Register cleanup handler to cancel job on exit\n# timeout: Maximum time to wait\n# tag: Override the worker tag the job runs on\n# \n# Returns:\n# Script result\ndef run_script_sync(hash: str, args: Dict[str, Any] = None, verbose: bool = False, assert_result_is_not_none: bool = True, cleanup: bool = True, timeout: dt.timedelta = None, tag: str = None) -> Any\n\n# Run a script synchronously by path and return its result.\n# \n# Args:\n# path: Script path\n# args: Script arguments\n# verbose: Enable verbose logging\n# assert_result_is_not_none: Raise exception if result is None\n# cleanup: Register cleanup handler to cancel job on exit\n# timeout: Maximum time to wait\n# tag: Override the worker tag the job runs on\n# \n# Returns:\n# Script result\ndef run_script_by_path_sync(path: str, args: Dict[str, Any] = None, verbose: bool = False, assert_result_is_not_none: bool = True, cleanup: bool = True, timeout: dt.timedelta = None, tag: str = None) -> Any\n\n# Convenient helpers that takes an S3 resource as input and returns the settings necessary to\n# initiate an S3 connection from DuckDB\ndef duckdb_connection_settings(s3_resource_path: str = '') -> DuckDbConnectionSettings\n\n# Convenient helpers that takes an S3 resource as input and returns the settings necessary to\n# initiate an S3 connection from Polars\ndef polars_connection_settings(s3_resource_path: str = '') -> PolarsConnectionSettings\n\n# Convenient helpers that takes an S3 resource as input and returns the settings necessary to\n# initiate an S3 connection using boto3\ndef boto3_connection_settings(s3_resource_path: str = '') -> Boto3ConnectionSettings\n\n# Get the state resource path from environment.\n# \n# Returns:\n# State path string\ndef get_state_path() -> str\n\n# Parse resource syntax from string.\ndef parse_resource_syntax(s: str) -> Optional[str]\n\n# Parse S3 object from a `s3://<storage>/<key>` URI string (`s3:///<key>`\n# for the default storage) or S3Object format. Any other string raises\n# rather than falling back to an auto-generated key: an auto key is\n# requested by omitting the object, and a fallback would silently misplace\n# the upload on any typo.\ndef parse_s3_object(s3_object: S3Object | str) -> S3Object\n\n# Parse variable syntax from string.\ndef parse_variable_syntax(s: str) -> Optional[str]\n\n# Append a text to the result stream.\n# \n# Args:\n# text: text to append to the result stream\ndef append_to_result_stream(text: str) -> None\n\n# Stream to the result stream.\n# \n# Args:\n# stream: stream to stream to the result stream\ndef stream_result(stream) -> None\n\n# Execute a SQL query against the DataTable.\n# \n# Args:\n# sql: SQL query string with $1, $2, etc. placeholders\n# *args: Positional arguments to bind to query placeholders\n# \n# Returns:\n# SqlQuery instance for fetching results\ndef query(sql: str, *args) -> SqlQuery\n\n# Idempotently materialize the rows of `select_sql` into ducklake\n# `table` for one `partition` (or the whole table when `partition` is\n# None). Client-side equivalent of the `// materialize` engine: with\n# `unique_key` it upserts within the slice (delete-by-key + insert);\n# without it, it replaces (whole table → CREATE OR REPLACE; partition →\n# delete the partition + insert). Re-running the same slice is safe — the\n# backfill / failure-recovery contract.\n# \n# The partition value is bound as a DuckDB arg (never string-interpolated)\n# so it cannot inject SQL. `select_sql` is trusted (your own query).\ndef upsert_partition(table: str, select_sql: str, partition: str = None, unique_key: str = None, partition_col: str = '_wm_partition', schema: str = None)\n\n# INSERT-only materialization (no dedup / no replace) for an immutable\n# event-log table — for one `partition`, or the whole table when\n# `partition` is None. NOTE: unlike `upsert_partition`, re-running the same\n# slice duplicates rows — use only for append-only sources.\ndef append_partition(table: str, select_sql: str, partition: str = None, partition_col: str = '_wm_partition', schema: str = None)\n\n# Read a materialized ducklake table, optionally a single partition.\ndef read(table: str, partition: str = None, partition_col: str = '_wm_partition', schema: str = None)\n\n# Execute query and fetch results.\n# \n# Args:\n# result_collection: Optional result collection mode\n# \n# Returns:\n# Query results\ndef fetch(result_collection: str | None = None)\n\n# Execute query and fetch first row of results.\n# \n# Returns:\n# First row of query results\ndef fetch_one()\n\n# Execute query and fetch first row of results. Return result as a scalar value.\n# \n# Returns:\n# First row of query result as a scalar value\ndef fetch_one_scalar()\n\n# Execute query and don't return any results.\n# \ndef execute()\n\n# DuckDB executor requires explicit argument types at declaration\n# These types exist in both DuckDB and Postgres\n# Check that the types exist if you plan to extend this function for other SQL engines.\ndef infer_sql_type(value) -> str\n\ndef parse_sql_client_name(name: str) -> tuple[str, Optional[str]]\n\n# Decorator that marks a function as a workflow task.\n# \n# Works in both WAC v1 (sync, HTTP-based dispatch) and WAC v2\n# (async, checkpoint/replay) modes:\n# \n# - **v2 (inside @workflow)**: dispatches as a checkpoint step.\n# - **v1 (WM_JOB_ID set, no @workflow)**: dispatches via HTTP API.\n# - **Standalone, or called from inside another v2 task**: executes the\n# function body directly. A task runs as a single job, so the tasks it\n# calls run in that same job, without their own options.\n# \n# A task runs as its own job, so its result is always encoded as JSON and\n# decoded back before the caller sees it: a ``datetime`` comes back as a\n# string, a tuple as a list.\n# \n# ``retry`` re-dispatches the task after a failure, inside ``@workflow`` only.\n# Every attempt is a step of its own (``call_api``, ``call_api#2``, ...) and\n# the wait between two of them is a durable sleep, so a retrying task holds no\n# worker while it backs off. Keys: ``attempts`` (retries after the first\n# failure, a whole number from 0 to 100), ``delay`` (seconds before the first\n# retry, sub-second delays dropped), ``multiplier`` (applied to the delay\n# after each attempt, 1 keeps it constant), ``max_delay`` (ceiling in\n# seconds). ``attempts`` is required, and an out-of-range or unknown key is\n# rejected where the policy is written.\n# \n# A workflow sleeps once per round, so tasks backing off in the same fan-out\n# wait one after another rather than together: the delay before a fan-out\n# retries is the sum of every backoff pending in it, not the longest one, and\n# it grows with both the width of the fan-out and ``attempts``. Retries with\n# no ``delay`` all go out in a single round.\n# \n# ``cache_ttl`` serves a previous result of the task for that many seconds\n# instead of running it again. A task is keyed on its step key (its name and\n# call order) and the workflow's input, not on the arguments it is called\n# with, so cache one only when whether it runs, and what it receives, follow\n# from the workflow's input alone. A ``task_script`` target is keyed on the\n# arguments it is called with. It has no effect on a ``task_flow`` target,\n# which keeps its flow's own cache policy.\n# \n# Usage::\n# \n# @task\n# async def extract_data(url: str): ...\n# \n# @task(path=\"f/external_script\", timeout=600, tag=\"gpu\")\n# async def run_external(x: int): ...\n# \n# @task(retry={\"attempts\": 3, \"delay\": 30, \"multiplier\": 2})\n# async def call_api(payload: dict): ...\ndef task(_func = None, *, path: Optional[str] = None, tag: Optional[str] = None, timeout: Optional[int] = None, cache_ttl: Optional[int] = None, priority: Optional[int] = None, concurrency_limit: Optional[int] = None, concurrency_key: Optional[str] = None, concurrency_time_window_s: Optional[int] = None, retry: Optional[dict] = None)\n\n# Create a task that dispatches to a separate Windmill script.\n# \n# ``retry`` takes the same policy as :func:`task`.\n# \n# Usage::\n# \n# extract = task_script(\"f/data/extract\", timeout=600)\n# \n# @workflow\n# async def main():\n# data = await extract(url=\"https://...\")\ndef task_script(path: str, *, timeout: Optional[int] = None, tag: Optional[str] = None, cache_ttl: Optional[int] = None, priority: Optional[int] = None, concurrency_limit: Optional[int] = None, concurrency_key: Optional[str] = None, concurrency_time_window_s: Optional[int] = None, retry: Optional[dict] = None)\n\n# Create a task that dispatches to a separate Windmill flow.\n# \n# ``retry`` takes the same policy as :func:`task`.\n# \n# Usage::\n# \n# pipeline = task_flow(\"f/etl/pipeline\", priority=10)\n# \n# @workflow\n# async def main():\n# result = await pipeline(input=data)\ndef task_flow(path: str, *, timeout: Optional[int] = None, tag: Optional[str] = None, cache_ttl: Optional[int] = None, priority: Optional[int] = None, concurrency_limit: Optional[int] = None, concurrency_key: Optional[str] = None, concurrency_time_window_s: Optional[int] = None, retry: Optional[dict] = None)\n\n# Decorator marking an async function as a workflow-as-code entry point.\n# \n# The function must be **deterministic**: given the same inputs it must call\n# tasks in the same order on every replay. Branching on task results is fine\n# (results are replayed from checkpoint), but branching on external state\n# (current time, random values, external API calls) must use ``step()`` to\n# checkpoint the value so replays see the same result.\ndef workflow(func)\n\n# Execute ``fn`` inline and checkpoint the result.\n# \n# On replay the cached value is returned without re-executing ``fn``.\n# Use for lightweight deterministic operations (timestamps, random IDs,\n# config reads) that should not incur the overhead of a child job.\n# \n# ``fn``'s result is encoded as JSON and decoded back before it is returned,\n# so the round that runs the body sees the same types every replay sees:\n# a ``datetime`` comes back as a string, a tuple as a list.\n# \n# Called from inside a task body, ``fn`` runs in place and nothing is\n# checkpointed: a task is a single job and is never replayed.\nasync def step(name: str, fn)\n\n# Server-side sleep — suspend the workflow for the given duration without holding a worker.\n# \n# Inside a @workflow, the parent job suspends and auto-resumes after ``seconds``.\n# Outside a workflow, or inside a task body, falls back to ``asyncio.sleep``.\nasync def sleep(seconds: int)\n\n# Suspend the workflow and wait for an external approval.\n# \n# Pass ``key`` to name the step, then ``get_approval_urls(key)`` yields the URLs\n# that resume exactly this approval — route them through your own channel.\n# Without a key the steps are named ``approval``, ``approval_2``, ...\n# \n# Returns a dict with ``value`` (form data), ``approver``, and ``approved``.\n# \n# Args:\n# timeout: Approval timeout in seconds (default 1800).\n# form: Optional form schema for the approval page.\n# self_approval: Whether the user who triggered the flow can approve it (default True).\n# key: Optional checkpoint key naming this approval step.\n# skin: ``\"minimal\"`` shows approvers only the request (form and approve/reject)\n# instead of the detailed page with the workflow's details.\n# description: Shown to approvers above the form: a string, or a rich value such as\n# ``{\"markdown\": \"...\"}``.\n# \n# Example::\n# \n# urls = await step(\"urls\", lambda: get_approval_urls(\"manager\"))\n# await step(\"notify\", lambda: send_email(urls[\"resume\"], urls[\"cancel\"]))\n# result = await wait_for_approval(key=\"manager\", timeout=3600)\nasync def wait_for_approval(timeout: int = 1800, form: dict | None = None, self_approval: bool = True, key: str | None = None, skin: Literal['detailed', 'minimal'] | None = None, description: str | dict | None = None) -> dict\n\n# Process items in parallel with optional concurrency control.\n# \n# Each item is processed by calling ``fn(item)``, which should be a @task.\n# Items are dispatched in batches of ``concurrency`` (default: all at once).\n# \n# Example::\n# \n# @task\n# async def process(item: str):\n# ...\n# \n# results = await parallel(items, process, concurrency=5)\nasync def parallel(items, fn, *, concurrency: Optional[int] = None)\n\n# Commit Kafka offsets for a trigger with auto_commit disabled.\n# \n# Args:\n# trigger_path: Path to the Kafka trigger (from event['wm_trigger']['trigger_path'])\n# topic: Kafka topic name (from event['topic'])\n# partition: Partition number (from event['partition'])\n# offset: Message offset to commit (from event['offset'])\ndef commit_kafka_offsets(trigger_path: str, topic: str, partition: int, offset: int) -> None\n\n", diff --git a/backend/windmill-types/src/flow_status.rs b/backend/windmill-types/src/flow_status.rs index 2fd5ef1184..71aba14cbb 100644 --- a/backend/windmill-types/src/flow_status.rs +++ b/backend/windmill-types/src/flow_status.rs @@ -218,6 +218,31 @@ pub enum AgentAction { }, Message {}, WebSearch {}, + /// The agent is parked until someone approves or rejects these calls of tools that require + /// it; it is answered once its `agent_actions_success` entry is written. `call_id` is the + /// first call's, and names the request. + Approval { + call_id: String, + calls: Vec<ApprovalCall>, + expires_at: chrono::DateTime<chrono::Utc>, + }, + /// The agent is parked until someone answers its question, the same way. + Question { + call_id: String, + question: String, + /// Answers the model proposes; a free-text answer is always possible. + #[serde(default, skip_serializing_if = "Vec::is_empty")] + choices: Vec<String>, + #[serde(default, skip_serializing_if = "std::ops::Not::not")] + multi_select: bool, + expires_at: chrono::DateTime<chrono::Utc>, + }, +} + +#[derive(Serialize, Deserialize, Debug, Clone)] +pub struct ApprovalCall { + pub function_name: String, + pub arguments: serde_json::Value, } #[derive(Serialize, Debug, Clone)] diff --git a/backend/windmill-types/src/flows.rs b/backend/windmill-types/src/flows.rs index 59f06ae4e9..979e6c1dee 100644 --- a/backend/windmill-types/src/flows.rs +++ b/backend/windmill-types/src/flows.rs @@ -386,8 +386,9 @@ impl FlowValue { for tool in tools { match &tool.value { ToolValue::FlowModule(module_value) => cb(module_value, &tool.id)?, - ToolValue::Mcp(_) => {} - ToolValue::Websearch(_) => {} + ToolValue::Mcp(_) + | ToolValue::Websearch(_) + | ToolValue::Question(_) => {} } } } @@ -943,6 +944,10 @@ pub struct AgentTool { /// Caps the token of this tool's jobs, on top of the agent step's own restriction. #[serde(default, skip_serializing_if = "Option::is_none")] pub job_token_scopes: Option<Vec<String>>, + /// A person approves each call before it runs; the agent waits without holding a worker. + /// Flow module and MCP tools only. + #[serde(default, skip_serializing_if = "std::ops::Not::not")] + pub requires_approval: bool, pub value: ToolValue, } @@ -972,8 +977,7 @@ impl From<&AgentTool> for Option<FlowModule> { job_token_scopes: tool.job_token_scopes.clone(), ..Default::default() }), - ToolValue::Mcp(_) => None, - ToolValue::Websearch(_) => None, + ToolValue::Mcp(_) | ToolValue::Websearch(_) | ToolValue::Question(_) => None, } } } @@ -984,6 +988,7 @@ pub enum ToolValue { FlowModule(FlowModuleValue), Mcp(McpToolValue), Websearch(WebsearchToolValue), + Question(QuestionToolValue), } // Custom deserializer for backward compatibility with old flows @@ -1002,6 +1007,7 @@ impl<'de> Deserialize<'de> for ToolValue { FlowModule(FlowModuleValue), Mcp(McpToolValue), Websearch(WebsearchToolValue), + Question(QuestionToolValue), } if let Ok(tagged) = TaggedToolValue::deserialize(&content) { @@ -1009,6 +1015,7 @@ impl<'de> Deserialize<'de> for ToolValue { TaggedToolValue::FlowModule(v) => ToolValue::FlowModule(v), TaggedToolValue::Mcp(v) => ToolValue::Mcp(v), TaggedToolValue::Websearch(v) => ToolValue::Websearch(v), + TaggedToolValue::Question(v) => ToolValue::Question(v), }); } @@ -1034,6 +1041,14 @@ pub struct McpToolValue { #[derive(Serialize, Deserialize, Debug, Clone, Default)] pub struct WebsearchToolValue {} +/// Lets the agent stop and wait for a person to answer a question it asks. +#[derive(Serialize, Deserialize, Debug, Clone, Default)] +pub struct QuestionToolValue { + /// Seconds to wait for an answer before the question is reported to the model as timed out. + #[serde(skip_serializing_if = "Option::is_none")] + pub timeout: Option<u32>, +} + fn is_none_or_empty_vec<T>(expr: &Option<Vec<T>>) -> bool { expr.is_none() || expr.as_ref().unwrap().is_empty() } diff --git a/backend/windmill-worker/src/ai/compaction.rs b/backend/windmill-worker/src/ai/compaction.rs index 82a79985e8..e4f3efed67 100644 --- a/backend/windmill-worker/src/ai/compaction.rs +++ b/backend/windmill-worker/src/ai/compaction.rs @@ -44,11 +44,55 @@ pub(crate) struct AgentHistory { last_request: Option<(usize, usize)>, } +/// An `AgentHistory` as a parked agent stores it. `OpenAIMessage` never serializes its +/// `agent_action`, so each message carries it alongside: the result and the flow viewer index +/// actions by it. +#[derive(serde::Serialize, serde::Deserialize)] +pub(crate) struct HistoryCheckpoint { + context: Vec<TaggedMessage>, + result: Vec<TaggedMessage>, +} + +#[derive(serde::Serialize, serde::Deserialize)] +struct TaggedMessage { + #[serde(flatten)] + message: OpenAIMessage, + #[serde(default, skip_serializing_if = "Option::is_none")] + agent_action: Option<windmill_common::flow_status::AgentAction>, +} + +fn tag(messages: &[OpenAIMessage]) -> Vec<TaggedMessage> { + messages + .iter() + .map(|m| TaggedMessage { message: m.clone(), agent_action: m.agent_action.clone() }) + .collect() +} + +fn untag(messages: Vec<TaggedMessage>) -> Vec<OpenAIMessage> { + messages + .into_iter() + .map(|t| OpenAIMessage { agent_action: t.agent_action, ..t.message }) + .collect() +} + impl AgentHistory { pub(crate) fn new(messages: Vec<OpenAIMessage>) -> Self { Self { result: messages.clone(), context: messages, last_request: None } } + pub(crate) fn checkpoint(&self) -> HistoryCheckpoint { + HistoryCheckpoint { context: tag(&self.context), result: tag(&self.result) } + } + + /// No usage measurement survives a park, so the next projection estimates the whole prompt. + pub(crate) fn from_checkpoint(checkpoint: HistoryCheckpoint) -> Self { + Self { + context: untag(checkpoint.context), + result: untag(checkpoint.result), + last_request: None, + } + } + pub(crate) fn context(&self) -> &[OpenAIMessage] { &self.context } @@ -676,6 +720,25 @@ async fn summarize_prefix( #[cfg(test)] mod tests { + // `OpenAIMessage` never serializes its action, and a parked agent's result and flow viewer + // index actions by it. + #[test] + fn checkpoint_keeps_agent_actions() { + use windmill_common::flow_status::AgentAction; + let mut tagged = message("assistant", "answer"); + tagged.agent_action = Some(AgentAction::Message {}); + let history = AgentHistory::new(vec![message("user", "question"), tagged]); + let json = serde_json::to_string(&history.checkpoint()).unwrap(); + let restored = AgentHistory::from_checkpoint(serde_json::from_str(&json).unwrap()); + let actions: Vec<bool> = restored + .result() + .iter() + .chain(restored.context()) + .map(|m| m.agent_action.is_some()) + .collect(); + assert_eq!(actions, [false, true, false, true]); + } + #[test] fn unusable_summaries_leave_context_and_usage_untouched() { let mut history = AgentHistory::new(vec![ diff --git a/backend/windmill-worker/src/ai/mod.rs b/backend/windmill-worker/src/ai/mod.rs index 6b99c12b50..8047ad5cc1 100644 --- a/backend/windmill-worker/src/ai/mod.rs +++ b/backend/windmill-worker/src/ai/mod.rs @@ -2,6 +2,7 @@ // This module will contain all AI-related execution logic pub mod compaction; +pub mod pause; pub mod stream_event_processor; pub mod tools; pub mod utils; diff --git a/backend/windmill-worker/src/ai/pause.rs b/backend/windmill-worker/src/ai/pause.rs new file mode 100644 index 0000000000..130cf24766 --- /dev/null +++ b/backend/windmill-worker/src/ai/pause.rs @@ -0,0 +1,377 @@ +//! A call of a tool that requires approval, or of the built-in question tool, parks the agent +//! instead of running. The agent stores its conversation, releases its worker the way a +//! workflow-as-code parent does (`suspend_wac_parent`), and is pulled again when `suspend` reaches +//! 0 (an answer, or a rejection) or `suspend_until` passes (the request timing out). +//! `resume_suspended` answers it like a WAC approval, since its queue row is the one suspended. +//! +//! The checkpoint row outlives the segment that reads it, so a job restarted after its worker died +//! resumes from it again. It is deleted by the monitor once the job leaves the queue. + +use chrono::{DateTime, Utc}; +use serde::{Deserialize, Serialize}; +use uuid::Uuid; +use windmill_ai::{ + ai_types::OpenAIToolCall, + types::{OpenAIContent, OpenAIMessage, TokenUsage, Tool, ToolDef, ToolDefFunction}, +}; +use windmill_common::{ + db::DB, + error::{self, Error}, + flow_status::{AgentAction, ApprovalCall}, + flows::QuestionToolValue, + worker::{to_raw_value, Connection}, +}; +use windmill_queue::MiniPulledJob; + +use crate::ai::compaction::HistoryCheckpoint; +use crate::ai::utils::find_unique_tool_name; +use crate::wac_executor::{end_wac_segment, suspend_wac_parent, WacPark}; + +/// The name a run enables the question tool by, reserved like `WEBSEARCH_ENABLED_NAME`: the +/// model-facing name may be renamed away from a flow module tool that already holds it. +pub(crate) const QUESTION_ENABLED_NAME: &str = "__wm_question"; + +/// Matches a suspended flow step's default. +const DEFAULT_TIMEOUT_SECS: u32 = 1800; + +pub(crate) fn question_timeout(value: &QuestionToolValue) -> u32 { + value.timeout.unwrap_or(DEFAULT_TIMEOUT_SECS).max(1) +} + +pub(crate) fn question_tool(timeout_secs: u32, existing: &[ToolDef]) -> Tool { + let parameters = serde_json::json!({ + "type": "object", + "properties": { + "question": { + "type": "string", + "description": "The question, as the person answering will read it." + }, + "choices": { + "type": "array", + "items": { "type": "string" }, + "description": "Answers to offer, when the likely answers are known. The person \ + can still answer in their own words." + }, + "multi_select": { + "type": "boolean", + "description": "Whether the person may pick several choices. The answer is then \ + a list." + } + }, + "required": ["question"], + }); + Tool { + def: ToolDef { + r#type: "function".to_string(), + function: ToolDefFunction { + name: find_unique_tool_name("ask_question", Some(existing)), + description: Some( + "Ask a person a question you cannot answer yourself, such as a choice only \ + they can make or information you do not have. This run stops until someone \ + answers from the flow's run page or chat, or the question times out, then \ + resumes with the answer as this tool's result." + .to_string(), + ), + parameters: to_raw_value(¶meters), + }, + }, + module: None, + mcp_source: None, + requires_approval: false, + question_timeout_secs: Some(timeout_secs), + } +} + +#[derive(Serialize, Deserialize, Clone, Debug)] +#[serde(tag = "kind", rename_all = "snake_case")] +pub(crate) enum PendingRequest { + /// Calls of tools that require approval, run once approved. + Approval { + calls: Vec<OpenAIToolCall>, + }, + Question { + function_name: String, + }, +} + +/// What the agent waits on, read back to answer it when it is pulled again. +#[derive(Serialize, Deserialize, Clone, Debug)] +pub(crate) struct PendingPause { + /// The question's call, or an approval's first call: the answer must name it. + pub call_id: String, + pub expires_at: DateTime<Utc>, + pub request: PendingRequest, + #[serde(skip)] + pub action: Option<AgentAction>, +} + +fn expires_at(timeout_secs: u32) -> DateTime<Utc> { + Utc::now() + chrono::Duration::seconds(timeout_secs as i64) +} + +/// The model's arguments turned into a park, or the error the model is answered with instead. +pub(crate) fn start_question( + timeout_secs: u32, + tool_call: &OpenAIToolCall, +) -> Result<PendingPause, String> { + let args: serde_json::Value = serde_json::from_str(&tool_call.function.arguments) + .map_err(|e| format!("Invalid arguments: {e}"))?; + let question = args + .get("question") + .and_then(|v| v.as_str()) + .map(str::trim) + .filter(|s| !s.is_empty()) + .ok_or("`question` is required")? + .to_string(); + let choices = args + .get("choices") + .and_then(|v| v.as_array()) + .into_iter() + .flatten() + .filter_map(|c| c.as_str().map(str::trim).filter(|s| !s.is_empty())) + .map(str::to_string) + .collect::<Vec<_>>(); + let multi_select = args + .get("multi_select") + .and_then(|v| v.as_bool()) + .unwrap_or(false); + let expires_at = expires_at(timeout_secs); + Ok(PendingPause { + call_id: tool_call.id.clone(), + expires_at, + request: PendingRequest::Question { function_name: tool_call.function.name.clone() }, + action: Some(AgentAction::Question { + call_id: tool_call.id.clone(), + question, + choices, + multi_select, + expires_at, + }), + }) +} + +/// One request for all of a turn's calls that require approval: they are answered together. +pub(crate) fn start_approval(calls: Vec<&OpenAIToolCall>) -> PendingPause { + let call_id = calls[0].id.clone(); + let expires_at = expires_at(DEFAULT_TIMEOUT_SECS); + let shown = calls + .iter() + .map(|call| ApprovalCall { + function_name: call.function.name.clone(), + arguments: serde_json::from_str(&call.function.arguments) + .unwrap_or_else(|_| serde_json::Value::String(call.function.arguments.clone())), + }) + .collect(); + PendingPause { + action: Some(AgentAction::Approval { call_id: call_id.clone(), calls: shown, expires_at }), + call_id, + expires_at, + request: PendingRequest::Approval { calls: calls.into_iter().cloned().collect() }, + } +} + +/// Everything `run_agent` holds across iterations that the next segment needs. +#[derive(Serialize, Deserialize)] +pub(crate) struct AgentCheckpoint { + pub history: HistoryCheckpoint, + pub actions: Vec<AgentAction>, + pub content: Option<OpenAIContent>, + pub usage: Option<TokenUsage>, + pub events: String, + pub reasoning: String, + pub next_iteration: usize, + pub pending: PendingPause, + /// `resume_job` rows never leave while the agent is queued, so each answer must skip the + /// ones earlier parks already read. + #[serde(default)] + pub consumed_resume_rows: Vec<Uuid>, +} + +pub(crate) async fn load_checkpoint( + db: &DB, + job_id: &Uuid, +) -> error::Result<Option<AgentCheckpoint>> { + let raw: Option<sqlx::types::Json<Box<serde_json::value::RawValue>>> = + sqlx::query_scalar("SELECT checkpoint FROM ai_agent_checkpoint WHERE job_id = $1") + .bind(job_id) + .fetch_optional(db) + .await?; + raw.map(|r| { + serde_json::from_str(r.0.get()) + .map_err(|e| Error::internal_err(format!("Invalid AI agent checkpoint: {e}"))) + }) + .transpose() +} + +pub(crate) enum ParkOutcome { + Parked, + /// A cancel reached the queue row first, so nothing was written. + Cancelled, +} + +/// Park the agent until its approval is answered or expires. +pub(crate) async fn park( + db: &DB, + conn: &Connection, + job: &MiniPulledJob, + checkpoint: &AgentCheckpoint, +) -> error::Result<ParkOutcome> { + let remaining_ms = (checkpoint.pending.expires_at - Utc::now()).num_milliseconds(); + let suspend_secs = (remaining_ms as f64 / 1000.0).max(1.0); + let checkpoint = serde_json::to_value(checkpoint).map_err(|e| { + Error::internal_err(format!("Failed to serialize AI agent checkpoint: {e}")) + })?; + let mut tx = db.begin().await?; + // One event: an answer, or a rejection, which zeroes `suspend` outright. + let segment_ms = + match suspend_wac_parent(&mut tx, &job.id, &job.workspace_id, 1, suspend_secs).await? { + WacPark::Parked(ms) => ms, + WacPark::Cancelled(_) => return Ok(ParkOutcome::Cancelled), + }; + sqlx::query( + "INSERT INTO ai_agent_checkpoint (job_id, workspace_id, checkpoint) VALUES ($1, $2, $3) + ON CONFLICT (job_id) DO UPDATE SET checkpoint = EXCLUDED.checkpoint", + ) + .bind(&job.id) + .bind(&job.workspace_id) + .bind(&checkpoint) + .execute(&mut *tx) + .await?; + tx.commit().await?; + end_wac_segment(conn, job, segment_ms); + Ok(ParkOutcome::Parked) +} + +pub(crate) enum Resumed { + /// The answer, and whether it counts as a success on the run page. + Answered(Answer, bool), + /// Woken by an answer to an earlier request; the parked one still waits. + StillPending, +} + +pub(crate) enum Answer { + /// The tool message answering the question. + Question(OpenAIMessage), + /// The approved calls run. + Run, + /// Each call is refused with this message. + Refuse(String), +} + +/// Read the answer to the parked request. +/// +/// `suspend` is zeroed in the same transaction as the read, so `resume_suspended` refuses any +/// answer sent while the agent runs instead of storing a row the next request would take. An answer +/// that names another request (the page sends the call id it shows) is read and ignored: a stale +/// page must not answer a request its user never saw. +pub(crate) async fn answer_pause( + db: &DB, + job_id: &Uuid, + pending: &PendingPause, + actions: &[AgentAction], + consumed_resume_rows: &mut Vec<Uuid>, +) -> error::Result<Resumed> { + let mut tx = db.begin().await?; + sqlx::query("UPDATE v2_job_queue SET suspend = 0 WHERE id = $1") + .bind(job_id) + .execute(&mut *tx) + .await?; + let rows: Vec<( + Uuid, + sqlx::types::Json<serde_json::Value>, + Option<String>, + bool, + )> = sqlx::query_as( + "SELECT id, value, approver, approved FROM resume_job + WHERE job = $1 AND id <> ALL($2) ORDER BY created_at ASC", + ) + .bind(job_id) + .bind(&*consumed_resume_rows) + .fetch_all(&mut *tx) + .await?; + tx.commit().await?; + consumed_resume_rows.extend(rows.iter().map(|(id, ..)| *id)); + + let answer = rows.into_iter().find(|(_, value, ..)| { + value + .0 + .get("call_id") + .and_then(|v| v.as_str()) + .map_or(true, |call_id| call_id == pending.call_id) + }); + let Some((_, value, approver, approved)) = answer else { + if Utc::now() < pending.expires_at { + return Ok(Resumed::StillPending); + } + let answer = match pending.request { + PendingRequest::Approval { .. } => Answer::Refuse( + "Not run: nobody approved this call before the request timed out.".to_string(), + ), + PendingRequest::Question { .. } => Answer::Question(question_message( + pending, + actions, + serde_json::json!({ + "timed_out": true, + "message": "Nobody answered before the question timed out.", + }), + )), + }; + return Ok(Resumed::Answered(answer, false)); + }; + let approver = approver.unwrap_or_else(|| "anonymous".to_string()); + let text = |key: &str| { + value + .0 + .get(key) + .and_then(|v| v.as_str()) + .map(str::trim) + .filter(|s| !s.is_empty()) + .map(str::to_string) + }; + let answer = match (&pending.request, approved) { + (PendingRequest::Approval { .. }, true) => Answer::Run, + (PendingRequest::Approval { .. }, false) => Answer::Refuse(match text("comment") { + Some(comment) => { + format!("Not run: {approver} rejected this call. Their comment: {comment}") + } + None => format!("Not run: {approver} rejected this call."), + }), + (PendingRequest::Question { .. }, true) => Answer::Question(question_message( + pending, + actions, + serde_json::json!({ + // A list when several choices were picked. + "answer": match value.0.get("answer") { + Some(serde_json::Value::Array(picked)) => serde_json::json!(picked), + _ => serde_json::json!(text("answer").unwrap_or_default()), + }, + "answered_by": approver, + }), + )), + (PendingRequest::Question { .. }, false) => Answer::Question(question_message( + pending, + actions, + serde_json::json!({ "declined": true, "declined_by": approver }), + )), + }; + Ok(Resumed::Answered(answer, approved)) +} + +fn question_message( + pending: &PendingPause, + actions: &[AgentAction], + result: serde_json::Value, +) -> OpenAIMessage { + let action = actions + .iter() + .rev() + .find(|a| matches!(a, AgentAction::Question { call_id, .. } if *call_id == pending.call_id)) + .cloned(); + OpenAIMessage { + role: "tool".to_string(), + content: Some(OpenAIContent::Text(result.to_string())), + tool_call_id: Some(pending.call_id.clone()), + agent_action: action, + ..Default::default() + } +} diff --git a/backend/windmill-worker/src/ai/stream_event_processor.rs b/backend/windmill-worker/src/ai/stream_event_processor.rs index c4d17f080a..7926b65f7a 100644 --- a/backend/windmill-worker/src/ai/stream_event_processor.rs +++ b/backend/windmill-worker/src/ai/stream_event_processor.rs @@ -26,14 +26,16 @@ impl Clone for StreamEventProcessor { } impl StreamEventProcessor { - /// Create a new StreamEventProcessor that persists events to the database. - pub fn new(conn: &Connection, job: &MiniPulledJob) -> Self { + /// Create a new StreamEventProcessor that persists events to the database, after the + /// `first_offset` events the job already streamed: a row written at an offset already taken + /// is appended to that row, out of order. + pub fn new(conn: &Connection, job: &MiniPulledJob, first_offset: i32) -> Self { let (tx, mut rx) = tokio::sync::mpsc::channel::<String>(100); let conn = conn.clone(); let job_id = job.id.clone(); let workspace_id = job.workspace_id.clone(); let handle = tokio::spawn(async move { - let mut offset = -1; + let mut offset = first_offset - 1; while let Some(event) = rx.recv().await { offset += 1; match tokio::time::timeout( diff --git a/backend/windmill-worker/src/ai/tools.rs b/backend/windmill-worker/src/ai/tools.rs index 35075566b7..ed1f5ad79c 100644 --- a/backend/windmill-worker/src/ai/tools.rs +++ b/backend/windmill-worker/src/ai/tools.rs @@ -1,3 +1,4 @@ +use crate::ai::pause::{start_approval, start_question, PendingPause}; use crate::ai::stream_event_processor::StreamEventProcessor; use crate::ai::utils::{ add_message_to_conversation, execute_mcp_tool, get_step_name_from_flow, @@ -97,12 +98,35 @@ pub async fn execute_tool_calls( actions: &mut Vec<AgentAction>, final_events_str: &mut String, structured_output_tool_name: &Option<String>, -) -> Result<(Vec<OpenAIMessage>, Option<OpenAIContent>, bool), Error> { + gate: ApprovalGate<'_>, +) -> Result<ToolCallsOutcome, Error> { let mut messages = Vec::new(); let mut used_structured_output_tool = false; let mut final_content = None; - let mut calls = tool_calls.iter().peekable(); + let CallPlan { to_run, refusals, deferred, pause } = plan_calls( + tool_calls, + tools, + &gate, + structured_output_tool_name.as_deref(), + ); + + // Answered calls were streamed as running when the agent parked. + let announced = matches!(gate, ApprovalGate::Ask); + for call in deferred.iter().chain(refusals.iter().map(|(call, _)| call)) { + if let Some(stream_event_processor) = ctx.stream_event_processor.filter(|_| announced) { + let event = StreamingEvent::ToolExecution { + call_id: call.id.clone(), + function_name: call.function.name.clone(), + }; + stream_event_processor.send(event, final_events_str).await?; + } + } + for (call, refusal) in refusals { + refuse_tool_call(&mut ctx, call, &refusal, &mut messages, final_events_str).await?; + } + + let mut calls = to_run.into_iter().peekable(); while let Some(tool_call) = calls.next() { // Stream tool call progress if let Some(stream_event_processor) = ctx.stream_event_processor { @@ -142,7 +166,6 @@ pub async fn execute_tool_calls( .find(|t| t.def.function.name == tool_call.function.name); if let Some(tool) = tool { - // Check if this is an MCP tool if let Some(mcp_source) = &tool.mcp_source { execute_mcp_tool_call( &mut ctx, @@ -155,7 +178,17 @@ pub async fn execute_tool_calls( ) .await?; } else if tool.module.is_some() && interpolating_args(tool_call) { - refuse_tool_call(&mut ctx, tool_call, &mut messages, final_events_str).await?; + let error_msg = "Tool call refused: its arguments could not be read, or reference \ + variables, resources or reserved names ($var:, $jsonvar:, \ + $res:, $encrypted:, $WM_)"; + refuse_tool_call( + &mut ctx, + tool_call, + error_msg, + &mut messages, + final_events_str, + ) + .await?; } else if tool.module.is_some() { let mut batch = vec![(tool_call, tool)]; while let Some(next_call) = calls.peek() { @@ -192,7 +225,114 @@ pub async fn execute_tool_calls( } } - Ok((messages, final_content, used_structured_output_tool)) + Ok(ToolCallsOutcome { messages, final_content, used_structured_output_tool, pause }) +} + +/// A turn's calls: run now, refused with a message, or held for a person's answer. +struct CallPlan<'a> { + to_run: Vec<&'a OpenAIToolCall>, + refusals: Vec<(&'a OpenAIToolCall, String)>, + deferred: Vec<&'a OpenAIToolCall>, + pause: Option<PendingPause>, +} + +fn plan_calls<'a>( + tool_calls: &'a [OpenAIToolCall], + tools: &[Tool], + gate: &ApprovalGate<'_>, + structured_output_tool_name: Option<&str>, +) -> CallPlan<'a> { + let tool_of = |call: &OpenAIToolCall| { + tools + .iter() + .find(|t| t.def.function.name == call.function.name) + }; + let mut plan = CallPlan { to_run: vec![], refusals: vec![], deferred: vec![], pause: None }; + match gate { + ApprovalGate::Answered(Some(refusal)) => plan + .refusals + .extend(tool_calls.iter().map(|call| (call, refusal.to_string()))), + ApprovalGate::Answered(None) => { + for call in tool_calls { + match tool_of(call) { + Some(_) => plan.to_run.push(call), + None => plan + .refusals + .push((call, "Not run: this tool is no longer available.".into())), + } + } + } + // Calls that need a person wait for the answer; every other call runs now. + ApprovalGate::Ask => { + // A call the run would refuse anyway is refused now rather than shown to the approver. + let held = |call: &OpenAIToolCall| { + tool_of(call).is_some_and(|t| { + t.requires_approval && !(t.module.is_some() && interpolating_args(call)) + }) + }; + let approval_calls: Vec<_> = tool_calls.iter().filter(|call| held(call)).collect(); + for call in tool_calls { + match tool_of(call) { + _ if held(call) => {} + Some(Tool { question_timeout_secs: Some(timeout_secs), .. }) => { + let refusal = if !approval_calls.is_empty() { + "Not run: ask it again once the pending approval is answered." + } else if plan.pause.is_some() { + "Not run: ask one question at a time." + } else { + match start_question(*timeout_secs, call) { + Ok(question) => { + plan.pause = Some(question); + plan.deferred.push(call); + continue; + } + Err(e) => { + plan.refusals.push((call, e)); + continue; + } + } + }; + plan.refusals.push((call, refusal.to_string())); + } + _ => plan.to_run.push(call), + } + } + if !approval_calls.is_empty() { + plan.deferred.extend(approval_calls.iter().copied()); + plan.pause = Some(start_approval(approval_calls)); + } + // The structured answer ends the run, so it cannot come before the answer it waits on. + if plan.pause.is_some() { + if let Some(at) = plan + .to_run + .iter() + .position(|c| Some(c.function.name.as_str()) == structured_output_tool_name) + { + plan.refusals.push(( + plan.to_run.remove(at), + "Not run: give your answer once the pending request is answered.".into(), + )); + } + } + } + } + plan +} + +pub struct ToolCallsOutcome { + pub messages: Vec<OpenAIMessage>, + pub final_content: Option<OpenAIContent>, + pub used_structured_output_tool: bool, + /// The turn asked a person something: the agent parks, those calls unanswered. + pub pause: Option<PendingPause>, +} + +pub enum ApprovalGate<'a> { + /// Park on calls of tools that require approval, and on a question. + Ask, + /// A person answered an approval request for these calls: run them, or refuse each with + /// this message. + Answered(Option<&'a str>), } /// Whether the model wrote an argument the tool's job would interpolate with the agent's token, @@ -207,15 +347,13 @@ fn interpolating_args(tool_call: &OpenAIToolCall) -> bool { async fn refuse_tool_call( ctx: &mut ToolExecutionContext<'_>, tool_call: &OpenAIToolCall, + error_msg: &str, messages: &mut Vec<OpenAIMessage>, final_events_str: &mut String, ) -> Result<(), Error> { - let error_msg = "Tool call refused: its arguments could not be read, or reference variables, \ - resources or reserved names ($var:, $jsonvar:, $res:, $encrypted:, $WM_)" - .to_string(); messages.push(OpenAIMessage { role: "tool".to_string(), - content: Some(OpenAIContent::Text(error_msg.clone())), + content: Some(OpenAIContent::Text(error_msg.to_string())), tool_call_id: Some(tool_call.id.clone()), ..Default::default() }); @@ -223,12 +361,12 @@ async fn refuse_tool_call( let event = StreamingEvent::ToolResult { call_id: tool_call.id.clone(), function_name: tool_call.function.name.clone(), - result: error_msg.clone(), + result: error_msg.to_string(), success: false, }; stream_event_processor.send(event, final_events_str).await?; } - let (content, extras) = windmill_tool_row(tool_call, false, &error_msg); + let (content, extras) = windmill_tool_row(tool_call, false, error_msg); let agent_job_id = ctx.job.id; add_tool_message_to_chat(ctx, Some(agent_job_id), &content, false, Some(extras)).await; Ok(()) @@ -1134,6 +1272,82 @@ mod tests { ); } + #[test] + fn only_calls_that_need_a_person_wait_for_one() { + use super::{plan_calls, ApprovalGate}; + use crate::ai::pause::PendingRequest; + use windmill_ai::types::{Tool, ToolDef, ToolDefFunction}; + let tool = |name: &str, requires_approval: bool, question: bool| Tool { + module: None, + def: ToolDef { + r#type: "function".to_string(), + function: ToolDefFunction { + name: name.to_string(), + description: None, + parameters: RawValue::from_string("{}".to_string()).unwrap(), + }, + }, + mcp_source: None, + requires_approval, + question_timeout_secs: question.then_some(60), + }; + let call = |id: &str, name: &str| OpenAIToolCall { + id: id.to_string(), + function: OpenAIFunction { + name: name.to_string(), + arguments: r#"{"question":"which one?"}"#.to_string(), + }, + r#type: "function".to_string(), + extra_content: None, + }; + let tools = [ + tool("list", false, false), + tool("delete", true, false), + tool("ask", false, true), + ]; + let ids = + |calls: &[&OpenAIToolCall]| calls.iter().map(|c| c.id.clone()).collect::<Vec<_>>(); + + let calls = [ + call("1", "list"), + call("2", "delete"), + call("3", "ask"), + call("4", "delete"), + call("5", "answer"), + ]; + let plan = plan_calls(&calls, &tools, &ApprovalGate::Ask, Some("answer")); + assert_eq!(ids(&plan.to_run), ["1"]); + assert_eq!(ids(&plan.deferred), ["2", "4"]); + assert_eq!( + plan.refusals + .iter() + .map(|(c, _)| c.id.as_str()) + .collect::<Vec<_>>(), + ["3", "5"] + ); + let pause = plan.pause.unwrap(); + assert_eq!(pause.call_id, "2"); + assert!(matches!(pause.request, PendingRequest::Approval { calls } if calls.len() == 2)); + + let calls = [call("1", "ask"), call("2", "list"), call("3", "ask")]; + let plan = plan_calls(&calls, &tools, &ApprovalGate::Ask, Some("answer")); + assert_eq!(ids(&plan.to_run), ["2"]); + assert_eq!(ids(&plan.deferred), ["1"]); + assert_eq!(plan.refusals.len(), 1); + + let calls = [call("1", "delete"), call("2", "gone")]; + let plan = plan_calls(&calls, &tools, &ApprovalGate::Answered(None), None); + assert_eq!(ids(&plan.to_run), ["1"]); + assert_eq!(plan.refusals[0].0.id, "2"); + let plan = plan_calls( + &calls, + &tools, + &ApprovalGate::Answered(Some("rejected")), + None, + ); + assert!(plan.to_run.is_empty() && plan.refusals.len() == 2); + } + #[test] fn a_model_written_reference_is_caught_however_it_is_spelled() { let call = |arguments: &str| OpenAIToolCall { diff --git a/backend/windmill-worker/src/ai/utils.rs b/backend/windmill-worker/src/ai/utils.rs index ccf2e0ef88..084b3cfe04 100644 --- a/backend/windmill-worker/src/ai/utils.rs +++ b/backend/windmill-worker/src/ai/utils.rs @@ -307,6 +307,40 @@ pub async fn update_flow_status_module_with_actions_success( Ok(()) } +/// Record the outcome of the last of `action_count` actions, dropping any recorded past it. +pub async fn set_flow_status_module_last_action_success( + db: &DB, + parent_job: &Uuid, + action_count: usize, + action_success: bool, +) -> Result<(), Error> { + if let Step::Step { idx: step, .. } = get_step_of_flow_status(db, parent_job.to_owned()).await? + { + sqlx::query( + "UPDATE v2_job_status SET + flow_status = jsonb_set( + flow_status, + array['modules', $2::TEXT, 'agent_actions_success'], + COALESCE(( + SELECT jsonb_agg(e ORDER BY i) + FROM jsonb_array_elements( + flow_status->'modules'->$2->'agent_actions_success' + ) WITH ORDINALITY AS t(e, i) + WHERE i < $3 + ), '[]'::jsonb) || to_jsonb(ARRAY[$4::bool]) + ) + WHERE id = $1", + ) + .bind(parent_job) + .bind(step as i32) + .bind(action_count as i64) + .bind(action_success) + .execute(db) + .await?; + } + Ok(()) +} + /// Get step name from the flow module (summary if exists, else id) pub fn get_step_name_from_flow( summary: Option<&str>, @@ -405,6 +439,8 @@ fn convert_mcp_tools_to_windmill_tools( tool_name: mcp_tool.name.to_string(), resource_path: resource_path.to_string(), }), + requires_approval: false, + question_timeout_secs: None, }) }) .collect() diff --git a/backend/windmill-worker/src/ai_executor.rs b/backend/windmill-worker/src/ai_executor.rs index 6c37f67f2e..4b426ef29e 100644 --- a/backend/windmill-worker/src/ai_executor.rs +++ b/backend/windmill-worker/src/ai_executor.rs @@ -2,13 +2,19 @@ use crate::ai::compaction::{ memory_within_capacity, persisted_bytes, AgentHistory, CompactionRequest, CompactionTrigger, Compactor, }; -use crate::ai::tools::{execute_tool_calls, ToolAbortHandles, ToolExecutionContext}; +use crate::ai::pause::{ + answer_pause, load_checkpoint, park, question_timeout, question_tool, AgentCheckpoint, Answer, + ParkOutcome, PendingRequest, Resumed, QUESTION_ENABLED_NAME, +}; +use crate::ai::tools::{ + execute_tool_calls, ApprovalGate, ToolAbortHandles, ToolCallsOutcome, ToolExecutionContext, +}; use crate::ai::utils::{ add_message_to_conversation, any_tool_needs_previous_result, cleanup_mcp_clients, filter_schema_by_input_transforms, find_unique_tool_name, get_flow_context, get_flow_job_runnable_and_raw_flow, get_step_name_from_flow, load_mcp_tools, - parse_raw_script_schema, update_flow_status_module_with_actions, - update_flow_status_module_with_actions_success, + parse_raw_script_schema, set_flow_status_module_last_action_success, + update_flow_status_module_with_actions, update_flow_status_module_with_actions_success, }; use crate::memory_common::MAX_MEMORY_SIZE_BYTES; use crate::memory_oss::{memory_storage_capacity_bytes, read_from_memory, write_to_memory}; @@ -17,7 +23,10 @@ use async_recursion::async_recursion; use regex::Regex; use serde_json::value::RawValue; use sha2::Digest; -use std::{collections::HashMap, sync::Arc}; +use std::{ + collections::{HashMap, HashSet}, + sync::Arc, +}; use uuid::Uuid; #[cfg(feature = "bedrock")] use windmill_ai::ai_bedrock::check_env_credentials; @@ -42,7 +51,7 @@ use windmill_ai::{ proxy::{ common_outbound_headers, needs_unavailable_oauth_exchange, retain_effective_credentials, }, - query_builder::{BuildRequestArgs, ParsedResponse}, + query_builder::{BuildRequestArgs, ParsedResponse, StreamEventSink}, retry::{as_transient, into_final_error, response_error, send_error, Backoff, MAX_RETRIES}, types::*, utils::{pinned_ai_client_for, should_use_structured_output_tool}, @@ -585,6 +594,9 @@ fn flow_module_tool_name(summary: Option<&str>) -> Result<&str, Error> { Some(name) if name == WEBSEARCH_ENABLED_NAME => Err(Error::internal_err(format!( "Invalid tool name: {name:?} is reserved for enabling web search" ))), + Some(name) if name == QUESTION_ENABLED_NAME => Err(Error::internal_err(format!( + "Invalid tool name: {name:?} is reserved for the question tool" + ))), Some(name) if TOOL_NAME_REGEX.is_match(name) => Ok(name), other => Err(Error::internal_err(format!("Invalid tool name: {other:?}"))), } @@ -601,6 +613,7 @@ fn tool_enabled_name(tool: &AgentTool) -> Option<&str> { match &tool.value { ToolValue::Mcp(mcp) => Some(mcp.resource_path.trim_start_matches("$res:")), ToolValue::Websearch(_) => Some(WEBSEARCH_ENABLED_NAME), + ToolValue::Question(_) => Some(QUESTION_ENABLED_NAME), _ => tool.summary.as_deref(), } } @@ -898,6 +911,23 @@ pub async fn handle_ai_agent_job( // constrain a shared resource); don't advertise them — invoking one would only fail the depth // check as a third level. let tools = if direct_parent_job_kind == JobKind::AIAgent { + // A nested agent writes no flow status, so nothing would show a question or an approval + // request, and its parent agent holds a worker while it waits: it cannot park either. A + // tool that requires approval is dropped rather than run unapproved. + let (dropped, tools): (Vec<_>, Vec<_>) = + tools.into_iter().partition(|t| t.requires_approval); + if !dropped.is_empty() { + let names: Vec<&str> = dropped + .iter() + .map(|t| tool_enabled_name(t).unwrap_or(&t.id)) + .collect(); + let message = format!( + "Tools that require approval are left out of an agent used as a tool, which cannot \ + wait for an answer: {}\n", + names.join(", ") + ); + append_logs(&job.id, &job.workspace_id, message, conn).await; + } tools .into_iter() .filter(|t| { @@ -905,7 +935,7 @@ pub async fn handle_ai_agent_job( &t.value, ToolValue::FlowModule( FlowModuleValue::AIAgent { .. } | FlowModuleValue::AIDecision { .. } - ) + ) | ToolValue::Question(_) ) }) .collect() @@ -935,8 +965,17 @@ pub async fn handle_ai_agent_job( #[allow(unused_mut)] let mut mcp_configs: Vec<crate::ai::utils::McpResourceConfig> = Vec::new(); let mut has_websearch = false; + let mut question_timeout_secs = None; + // Flow module tool ids and MCP resource paths whose calls each wait for approval. + let mut approval_required: HashSet<String> = HashSet::new(); for tool in tools { + if tool.requires_approval { + approval_required.insert(match &tool.value { + ToolValue::Mcp(mcp) => mcp.resource_path.trim_start_matches("$res:").to_string(), + _ => tool.id.clone(), + }); + } match &tool.value { #[allow(unused_variables)] ToolValue::Mcp(mcp_config) => { @@ -981,6 +1020,9 @@ pub async fn handle_ai_agent_job( tracing::debug!("WebSearch tool enabled"); has_websearch = true; } + ToolValue::Question(question) => { + question_timeout_secs = Some(question_timeout(question)); + } } } @@ -990,6 +1032,7 @@ pub async fn handle_ai_agent_job( let db = db; let job = job; let user_description = tool_descriptions.get(&t.id).cloned(); + let requires_approval = approval_required.contains(&t.id); async move { let summary = flow_module_tool_name(t.summary.as_deref())?; @@ -1124,8 +1167,10 @@ pub async fn handle_ai_agent_job( }), }, }, + requires_approval, module: Some(t), mcp_source: None, + question_timeout_secs: None, }) } })) @@ -1137,11 +1182,21 @@ pub async fn handle_ai_agent_job( let mcp_clients = if !mcp_configs.is_empty() { let (clients, mcp_tools) = load_mcp_tools(db, &job.workspace_id, mcp_configs, client).await?; - tools.extend(mcp_tools); + tools.extend(mcp_tools.into_iter().map(|mut tool| { + tool.requires_approval = tool + .mcp_source + .as_ref() + .is_some_and(|s| approval_required.contains(&s.resource_path)); + tool + })); clients } else { HashMap::new() }; + if let Some(timeout_secs) = question_timeout_secs { + let defs: Vec<ToolDef> = tools.iter().map(|t| t.def.clone()).collect(); + tools.push(question_tool(timeout_secs, &defs)); + } if let Some(enabled) = enabled_tools { let matchable: Vec<&str> = roster_names.iter().map(|s| s.as_str()).collect(); @@ -1265,7 +1320,10 @@ pub async fn handle_ai_agent_job( } }, }; - if result.is_err() { + if result + .as_ref() + .is_err_and(|e| !matches!(e, Error::WacSuspended(_))) + { for handle in tool_abort_handles.lock().unwrap().drain(..) { handle.abort(); } @@ -1275,6 +1333,34 @@ pub async fn handle_ai_agent_job( result } +/// Park the agent on its pending approval, as the error `run_agent` returns. +async fn park_agent( + db: &DB, + conn: &Connection, + job: &MiniPulledJob, + checkpoint: &AgentCheckpoint, + cancel_rx: &tokio::sync::watch::Receiver<bool>, +) -> Error { + match park(db, conn, job, checkpoint).await { + Ok(ParkOutcome::Parked) => Error::WacSuspended(format!( + "AI agent {} parked on {}", + job.id, checkpoint.pending.call_id + )), + Ok(ParkOutcome::Cancelled) => { + // The cancel is on the queue row but not yet seen by the poller, which is what + // completes the job as cancelled rather than failed. Wait for it to notice. + let mut cancel_rx = cancel_rx.clone(); + let _ = tokio::time::timeout( + std::time::Duration::from_secs(30), + cancel_rx.wait_for(|cancelled| *cancelled), + ) + .await; + Error::ExecutionErr("Job cancelled".to_string()) + } + Err(e) => e, + } +} + /// OpenAI rejects a `prompt_cache_key` over 64 characters /// (`Invalid 'prompt_cache_key': string too long`), and a runnable path alone can pass /// that. Fold an over-long key into a digest of itself: same step still yields the same @@ -1380,6 +1466,27 @@ pub async fn run_agent( // Fetch flow context for input transforms context, chat and memory let mut flow_context = get_flow_context(db, job).await; + // Set when the job parked on an approval or a question and has been pulled again. Read + // whatever the roster says now: a linked agent can lose a tool while one of its runs is parked. + let resumed = match load_checkpoint(db, &job.id).await? { + Some(mut checkpoint) => { + let answer = answer_pause( + db, + &job.id, + &checkpoint.pending, + &checkpoint.actions, + &mut checkpoint.consumed_resume_rows, + ) + .await?; + match answer { + Resumed::StillPending => { + return Err(park_agent(db, conn, job, &checkpoint, &cancel_rx).await) + } + Resumed::Answered(message, success) => Some((checkpoint, message, success)), + } + } + None => None, + }; // The run's memory id is also the chat conversation id, which a step's own memory id never // replaces. @@ -1437,7 +1544,7 @@ pub async fn run_agent( return Err(Error::internal_err(missing.to_string())); } - if matches!(output_type, OutputType::Text) { + if matches!(output_type, OutputType::Text) && resumed.is_none() { match &history { HistorySource::Messages(provided) => messages.extend(provided.iter().cloned()), HistorySource::Managed { memory_id, bound } => { @@ -1538,10 +1645,27 @@ pub async fn run_agent( } } - let mut messages = AgentHistory::new(messages); - let mut actions = vec![]; - let mut content = None; - let mut final_usage: Option<TokenUsage> = None; + let mut final_events_str = String::new(); + let mut final_reasoning = String::new(); + let mut first_iteration = 0; + let mut consumed_resume_rows = vec![]; + let mut resumed_answer = None; + let (mut messages, mut actions, mut content, mut final_usage) = match resumed { + Some((checkpoint, message, success)) => { + final_events_str = checkpoint.events; + final_reasoning = checkpoint.reasoning; + first_iteration = checkpoint.next_iteration; + consumed_resume_rows = checkpoint.consumed_resume_rows; + resumed_answer = Some((checkpoint.pending, message, success)); + ( + AgentHistory::from_checkpoint(checkpoint.history), + checkpoint.actions, + checkpoint.content, + checkpoint.usage, + ) + } + None => (AgentHistory::new(messages), vec![], None, None), + }; // Check if this provider supports tools with the current output type let supports_tools = query_builder.supports_tools_with_output_type(output_type); @@ -1596,13 +1720,12 @@ pub async fn run_agent( let user_wants_streaming = streaming_requested(args.streaming); *has_stream = user_wants_streaming && is_text_output; - let mut final_events_str = String::new(); - let mut final_reasoning = String::new(); - // Always create a StreamEventProcessor for text output (use silent mode if user doesn't want streaming) - let stream_event_processor = if is_text_output { + let mut stream_event_processor = if is_text_output { if user_wants_streaming { - Some(StreamEventProcessor::new(conn, job)) + // Each streamed event is one line of the accumulated string. + let streamed = final_events_str.lines().count() as i32; + Some(StreamEventProcessor::new(conn, job, streamed)) } else { Some(StreamEventProcessor::new_silent()) } @@ -1670,8 +1793,81 @@ pub async fn run_agent( windmill_ai::providers::anthropic::FederatedAccessToken, > = None; + if let Some((pending, answer, success)) = resumed_answer { + if let Some(parent_job) = parent_job { + // Rewritten whole rather than appended: a job restarted after its worker died + // resumes from the same checkpoint and must not record the answer twice. + update_flow_status_module_with_actions(db, parent_job, &actions).await?; + set_flow_status_module_last_action_success(db, parent_job, actions.len(), success) + .await?; + } + match (pending.request, answer) { + (PendingRequest::Question { function_name }, Answer::Question(message)) => { + if let (Some(processor), Some(OpenAIContent::Text(result))) = + (stream_event_processor.as_ref(), message.content.as_ref()) + { + let event = StreamingEvent::ToolResult { + call_id: pending.call_id.clone(), + function_name, + result: result.clone(), + success, + }; + processor.send(event, &mut final_events_str).await?; + } + messages.push(message); + } + (PendingRequest::Approval { calls }, answer) => { + let refusal = match &answer { + Answer::Refuse(refusal) => Some(refusal.as_str()), + _ => None, + }; + let tool_execution_ctx = ToolExecutionContext { + db, + conn, + job, + parent_job, + summary: &summary, + flow_step_id_override, + client, + worker_dir, + base_internal_url, + worker_name, + hostname, + occupancy_metrics, + killpill_rx, + stream_event_processor: stream_event_processor.as_ref(), + flow_context: &mut flow_context, + omit_output_from_conversation, + preserve_step_tags, + reasoning: None, + previous_result: &previous_result, + id_context: &id_context, + tool_abort_handles: tool_abort_handles.clone(), + job_completed_tx: job_completed_tx.clone(), + }; + let outcome = execute_tool_calls( + tool_execution_ctx, + &calls, + &tools, + mcp_clients, + &mut actions, + &mut final_events_str, + &structured_output_tool_name, + ApprovalGate::Answered(refusal), + ) + .await?; + messages.extend(outcome.messages); + } + (PendingRequest::Question { .. }, _) => { + return Err(Error::internal_err( + "A question was answered as an approval".to_string(), + )) + } + } + } + // Main agent loop - for i in 0..max_iterations { + for i in first_iteration..max_iterations { // Check if parent was canceled — stop iterating but let current tool calls finish if *cancel_rx.borrow() { return Err(Error::ExecutionErr("Job cancelled".to_string())); @@ -2277,17 +2473,22 @@ pub async fn run_agent( job_completed_tx: job_completed_tx.clone(), }; - let (tool_messages, tool_content, tool_used_structured_output) = - execute_tool_calls( - tool_execution_ctx, - &tool_calls, - &tools, - mcp_clients, - &mut actions, - &mut final_events_str, - &structured_output_tool_name, - ) - .await?; + let ToolCallsOutcome { + messages: tool_messages, + final_content: tool_content, + used_structured_output_tool: tool_used_structured_output, + pause, + } = execute_tool_calls( + tool_execution_ctx, + &tool_calls, + &tools, + mcp_clients, + &mut actions, + &mut final_events_str, + &structured_output_tool_name, + ApprovalGate::Ask, + ) + .await?; messages.extend(tool_messages); @@ -2331,6 +2532,42 @@ pub async fn run_agent( } used_structured_output_tool = tool_used_structured_output; + if let Some(mut pending) = pause { + actions.extend(pending.action.take()); + // The next segment streams from where this one stops, so this one's events + // must be written first. + if let Some(handle) = stream_event_processor.take().and_then(|p| p.to_handle()) + { + let _ = handle.await; + } + let checkpoint = AgentCheckpoint { + history: messages.checkpoint(), + actions: actions.clone(), + content: content.clone(), + usage: final_usage.clone(), + events: final_events_str, + reasoning: final_reasoning, + next_iteration: i + 1, + pending, + consumed_resume_rows, + }; + let parked = park_agent(db, conn, job, &checkpoint, &cancel_rx).await; + // Written once parked: the run page offers an answer only for a request that + // `resume_suspended` can take. The park is committed, so a failure here only + // costs the page its banner. + if let (Error::WacSuspended(_), Some(parent_job)) = (&parked, parent_job) { + if let Err(e) = + update_flow_status_module_with_actions(db, parent_job, &actions).await + { + tracing::error!( + "Failed to show the pending request of {}: {e}", + job.id + ); + } + } + return Err(parked); + } + // Check cancellation after tool calls complete to avoid a wasted LLM call if *cancel_rx.borrow() { return Err(Error::ExecutionErr("Job cancelled".to_string())); @@ -3068,6 +3305,7 @@ mod tests { its.insert(key.to_string(), js(expr)); AgentTool { job_token_scopes: None, + requires_approval: false, id: id.to_string(), summary: None, description: None, @@ -3096,6 +3334,7 @@ mod tests { script_tool("b", "y", "keep_me"), AgentTool { job_token_scopes: None, + requires_approval: false, id: "m".to_string(), summary: None, description: None, @@ -3144,6 +3383,7 @@ mod tests { fn named(id: &str, summary: &str) -> AgentTool { AgentTool { job_token_scopes: None, + requires_approval: false, id: id.to_string(), summary: Some(summary.to_string()), description: None, @@ -3160,6 +3400,7 @@ mod tests { fn mcp(id: &str, summary: &str, path: &str) -> AgentTool { AgentTool { job_token_scopes: None, + requires_approval: false, id: id.to_string(), summary: Some(summary.to_string()), description: None, @@ -3173,6 +3414,7 @@ mod tests { fn websearch(id: &str, summary: Option<&str>) -> AgentTool { AgentTool { job_token_scopes: None, + requires_approval: false, id: id.to_string(), summary: summary.map(str::to_string), description: None, diff --git a/chat-sdk/README.md b/chat-sdk/README.md index 2106d35bee..3c6b4ee5ed 100644 --- a/chat-sdk/README.md +++ b/chat-sdk/README.md @@ -244,6 +244,7 @@ interface ChatState { history: 'server' | 'local' | 'none' loadingMessages: boolean hasMoreMessages: boolean + runningJobId?: string // the flow job the running turn follows } interface ChatMessage { diff --git a/chat-sdk/src/chat.ts b/chat-sdk/src/chat.ts index 2d48d383a0..69832d7ec7 100644 --- a/chat-sdk/src/chat.ts +++ b/chat-sdk/src/chat.ts @@ -305,6 +305,7 @@ class ChatImpl implements Chat { async #followTurn(turn: Turn, isNew: boolean): Promise<void> { let nextTurn: RunningTurn | undefined + this.#set({ runningJobId: turn.jobId }) try { const stopPolling = this.#state.history === 'server' ? this.#startPolling(turn) : () => {} let result: unknown @@ -327,6 +328,7 @@ class ChatImpl implements Chat { this.#failTurn(turn, e) } finally { if (this.#turn === turn) this.#turn = undefined + if (this.#state.runningJobId === turn.jobId) this.#set({ runningJobId: undefined }) } if (nextTurn) await this.resumeTurn(nextTurn) } diff --git a/chat-sdk/src/types.ts b/chat-sdk/src/types.ts index ad9f30cbfb..c6a48574aa 100644 --- a/chat-sdk/src/types.ts +++ b/chat-sdk/src/types.ts @@ -80,6 +80,8 @@ export interface ChatState { history: HistoryMode loadingMessages: boolean hasMoreMessages: boolean + /** The flow job the running turn follows, once it is known. */ + runningJobId?: string } export type TokenSource = string | (() => string | Promise<string>) diff --git a/cli/src/commands/lint/flow_semantics.ts b/cli/src/commands/lint/flow_semantics.ts index 26b72a8867..619f3afed9 100644 --- a/cli/src/commands/lint/flow_semantics.ts +++ b/cli/src/commands/lint/flow_semantics.ts @@ -9,6 +9,12 @@ // frontend/src/lib/components/flows/agentToolUtils.ts applies the same rules. const TOOL_NAME_REGEX = /^[a-zA-Z0-9_]+$/; const WEBSEARCH_ENABLED_NAME = "__wm_web_search"; +// The worker's `*_ENABLED_NAME`s: built-in tools, each named by its reserved name. +const BUILTIN_ENABLED_NAMES = new Set([ + WEBSEARCH_ENABLED_NAME, + "__wm_question", +]); +const BUILTIN_TOOL_TYPES = new Set(["websearch", "question"]); // `forbiddenIds` in frontend/src/lib/components/flows/idUtils.ts. const RESERVED_IDS = new Set([ @@ -134,10 +140,10 @@ function checkAgentTools( if (!Array.isArray(tools)) return; const seen = new Map<string, number>(); tools.forEach((tool: any, i: number) => { - // An mcp entry exposes its server's own tool names and a websearch entry is - // named by `WEBSEARCH_ENABLED_NAME`; neither summary reaches the model. + // An mcp entry exposes its server's own tool names and a built-in entry is + // named by its reserved name; neither summary reaches the model. const kind = tool?.value?.tool_type; - if (kind === "mcp" || kind === "websearch") return; + if (kind === "mcp" || BUILTIN_TOOL_TYPES.has(kind)) return; const at = `${agent.pointer}/value/tools/${i}`; const name = tool?.summary; if (typeof name !== "string" || name.length === 0) { @@ -152,9 +158,9 @@ function checkAgentTools( ); return; } - if (name === WEBSEARCH_ENABLED_NAME) { + if (BUILTIN_ENABLED_NAMES.has(name)) { report.errors.push( - `${at} tool name '${name}' is reserved for enabling web search`, + `${at} tool name '${name}' is reserved for a built-in tool`, ); return; } diff --git a/cli/src/guidance/skills.gen.ts b/cli/src/guidance/skills.gen.ts index 6a0d6f47f4..c01bad21b7 100644 --- a/cli/src/guidance/skills.gen.ts +++ b/cli/src/guidance/skills.gen.ts @@ -5912,7 +5912,10 @@ value: An \`aiagent\` module runs an LLM that can call tools. Each entry of \`value.tools\` is a module-shaped object with an extra \`value.tool_type\`: \`flowmodule\` for a script/flow tool, \`mcp\` for an MCP server -tool, \`websearch\` for web search. +tool, \`websearch\` for web search, \`question\` for a built-in \`ask_question\` tool (the agent stops, +without holding a worker, until someone answers from the run page or the chat; optional +\`value.timeout\` in seconds, default 1800). Set \`requires_approval: true\` on a \`flowmodule\` or \`mcp\` +tool to have a person approve or reject each of its calls before it runs. \`\`\`json { @@ -6008,9 +6011,9 @@ needs becomes unreachable. ### Tool Naming Rules -These rules cover \`flowmodule\` tools, the ones the agent calls by name. A \`websearch\` tool's -\`summary\` is a plain label (\`Web Search\`), and an \`mcp\` tool exposes the MCP server's own tool -names, so neither is name-checked at all — leave those summaries as they are. +These rules cover \`flowmodule\` tools, the ones the agent calls by name. A \`websearch\` or \`question\` +tool's \`summary\` is a plain label (\`Web Search\`), and an \`mcp\` tool exposes the MCP +server's own tool names, so none is name-checked at all — leave those summaries as they are. - A flowmodule tool's \`summary\` is the **name the agent calls it by**, not a human label. Put the human-readable explanation in \`description\` @@ -6455,7 +6458,7 @@ Reference a specific resource using \`$res:\` prefix: ## OpenFlow Schema -{"OpenFlow":{"type":"object","description":"Top-level flow definition containing metadata, configuration, and the flow structure","properties":{"summary":{"type":"string","description":"Short description of what this flow does"},"description":{"type":"string","description":"Detailed documentation for this flow"},"value":{"$ref":"#/components/schemas/FlowValue"},"schema":{"type":"object","description":"JSON Schema for flow inputs. Use this to define input parameters, their types, defaults, and validation. For resource inputs, set type to 'object' and format to 'resource-<type>' (e.g., 'resource-stripe')"},"on_behalf_of_email":{"type":"string","description":"Address of the account the flow runs on behalf of. Derived from on_behalf_of on read; accepted on write, where it is resolved to the account it names."},"on_behalf_of":{"type":"string","description":"The flow runs with the permissions of this identity: u/{username}, g/{group}, or a bare email when the username is itself email-shaped. The only stored half of the identity; on_behalf_of_email is derived from it. Omit it when writing and it is resolved from that address instead."}},"required":["summary","value"]},"FlowValue":{"type":"object","description":"The flow structure containing modules and optional preprocessor/failure handlers","properties":{"modules":{"type":"array","description":"Array of steps that execute in sequence. Each step can be a script, subflow, loop, or branch","items":{"$ref":"#/components/schemas/FlowModule"}},"failure_module":{"description":"Special module that executes when the flow fails. Receives error object with message, name, stack, and step_id. Must have id 'failure'. Only supports script/rawscript types","$ref":"#/components/schemas/FlowModule"},"preprocessor_module":{"description":"Special module that runs before the first step on external triggers. Must have id 'preprocessor'. Only supports script/rawscript types. Cannot reference other step results","$ref":"#/components/schemas/FlowModule"},"same_worker":{"type":"boolean","description":"If true, all steps run on the same worker for better performance"},"preserve_step_tags":{"type":"boolean","description":"If true and the flow runs on a custom worker tag, steps that declare their own non-empty tag run on it instead of inheriting the flow tag. Steps without their own tag still inherit the flow tag."},"concurrent_limit":{"type":"number","description":"Maximum number of concurrent executions of this flow"},"concurrency_key":{"type":"string","description":"Expression to group concurrent executions (e.g., by user ID)"},"concurrency_time_window_s":{"type":"number","description":"Time window in seconds for concurrent_limit"},"debounce_delay_s":{"type":"integer","description":"Delay in seconds to debounce flow executions"},"debounce_key":{"type":"string","description":"Expression to group debounced executions"},"debounce_args_to_accumulate":{"type":"array","description":"Arguments to accumulate across debounced executions","items":{"type":"string"}},"max_total_debouncing_time":{"type":"integer","description":"Maximum total time in seconds that a job can be debounced"},"max_total_debounces_amount":{"type":"integer","description":"Maximum number of times a job can be debounced"},"skip_expr":{"type":"string","description":"JavaScript expression to conditionally skip the entire flow"},"cache_ttl":{"type":"number","description":"Cache duration in seconds for flow results"},"cache_ignore_s3_path":{"type":"boolean"},"delete_after_secs":{"type":"integer","description":"If set, delete the flow job's args, result and logs after this many seconds following job completion"},"flow_env":{"type":"object","description":"Environment variables available to all steps. Values can be strings, JSON values, or special references: '$var:path' (workspace variable) or '$res:path' (resource).","additionalProperties":{}},"priority":{"type":"number","description":"Execution priority (higher numbers run first)"},"early_return":{"type":"string","description":"Id of the step whose result a sync webhook returns as soon as that step completes, while the rest of the flow keeps running. When the step does not run, or fails while the flow has a failure module, the flow's final result is returned instead."},"chat_input_enabled":{"type":"boolean","description":"Whether this flow accepts chat-style input"},"notes":{"type":"array","description":"Sticky notes attached to the flow","items":{"$ref":"#/components/schemas/FlowNote"}},"groups":{"type":"array","description":"Semantic groups of modules for organizational purposes","items":{"$ref":"#/components/schemas/FlowGroup"}}},"required":["modules"]},"Retry":{"type":"object","description":"Retry configuration for failed module executions","properties":{"constant":{"type":"object","description":"Retry with constant delay between attempts","properties":{"attempts":{"type":"integer","description":"Number of retry attempts"},"seconds":{"type":"integer","description":"Seconds to wait between retries"}}},"exponential":{"type":"object","description":"Retry with exponential backoff: the n-th retry waits multiplier \\u00d7 seconds^n","properties":{"attempts":{"type":"integer","description":"Number of retry attempts"},"multiplier":{"type":"integer","description":"Multiplier for exponential backoff"},"seconds":{"type":"integer","minimum":1,"description":"Base of the exponential (seconds); the n-th retry waits multiplier \\u00d7 seconds^n, where n counts constant retries too"},"random_factor":{"type":"integer","minimum":0,"maximum":100,"description":"Random jitter percentage (0-100) to avoid thundering herd"}}},"retry_if":{"$ref":"#/components/schemas/RetryIf"}}},"FlowNote":{"type":"object","description":"A sticky note attached to a flow for documentation and annotation","properties":{"id":{"type":"string","description":"Unique identifier for the note"},"text":{"type":"string","description":"Content of the note"},"position":{"type":"object","description":"Position of the note in the flow editor","properties":{"x":{"type":"number","description":"X coordinate"},"y":{"type":"number","description":"Y coordinate"}},"required":["x","y"]},"size":{"type":"object","description":"Size of the note in the flow editor","properties":{"width":{"type":"number","description":"Width in pixels"},"height":{"type":"number","description":"Height in pixels"}},"required":["width","height"]},"color":{"type":"string","description":"Color of the note, one of: yellow, blue, green, purple, pink, orange, red, cyan, lime, gray. Any other value renders unstyled."},"type":{"type":"string","enum":["free","group"],"description":"Type of note - 'free' for standalone notes. 'group' notes are deprecated; segment a flow with FlowValue.groups instead."},"locked":{"type":"boolean","default":false,"description":"Whether the note is locked and cannot be edited or moved"},"contained_node_ids":{"type":"array","items":{"type":"string"},"description":"For group notes, the IDs of nodes contained within this group"}},"required":["id","text","color","type"]},"FlowGroup":{"type":"object","description":"A semantic group of flow modules for organizational purposes. Does not affect execution \\u2014 modules remain in their original position in the flow. Groups provide naming and collapsibility in the editor. Members are computed dynamically from all nodes on paths between start_id and end_id.","properties":{"summary":{"type":"string","description":"Display name for this group"},"note":{"type":"string","description":"Markdown note shown below the group header"},"autocollapse":{"type":"boolean","default":false,"description":"If true, this group is collapsed by default in the flow editor. UI hint only."},"start_id":{"type":"string","description":"ID of the first flow module in this group (topological entry point)"},"end_id":{"type":"string","description":"ID of the last flow module in this group (topological exit point)"},"color":{"type":"string","description":"Color for the group in the flow editor, one of: yellow, blue, green, purple, pink, orange, red, cyan, lime, gray. Omit it to let the editor pick one."}},"required":["start_id","end_id"]},"RetryIf":{"type":"object","description":"Conditional retry based on error or result","properties":{"expr":{"type":"string","description":"JavaScript expression that returns true to retry. Has access to 'result' and 'error' variables"}},"required":["expr"]},"StopAfterIf":{"type":"object","description":"Early termination condition for a module","properties":{"skip_if_stopped":{"type":"boolean","description":"If true, following steps are skipped when this condition triggers"},"expr":{"type":"string","description":"JavaScript expression evaluated after the module runs. Can use 'result' (step's result) or 'flow_input'. Return true to stop"},"error_message":{"type":"string","nullable":true,"description":"Custom error message when stopping with an error. Mutually exclusive with skip_if_stopped. If set to a non-empty string, the flow stops with this error. If empty string, a default error message is used. If null or omitted, no error is raised."},"error_include_result":{"type":"boolean","description":"When stopping with an error (error_message set), embed the stopping step's own result inside the raised error object (as error.result) instead of discarding it. The top-level result stays { error }. Defaults to false."}},"required":["expr"]},"FlowModule":{"type":"object","description":"A single step in a flow. Can be a script, subflow, loop, or branch","properties":{"id":{"type":"string","description":"Unique identifier for this step. Used to reference results via 'results.step_id'. Must be a valid identifier (alphanumeric, underscore, hyphen)"},"value":{"$ref":"#/components/schemas/FlowModuleValue"},"stop_after_if":{"description":"Early termination condition evaluated after this step completes","$ref":"#/components/schemas/StopAfterIf"},"stop_after_all_iters_if":{"description":"For loops only - early termination condition evaluated after all iterations complete","$ref":"#/components/schemas/StopAfterIf"},"skip_if":{"type":"object","description":"Conditionally skip this step based on previous results or flow inputs","properties":{"expr":{"type":"string","description":"JavaScript expression that returns true to skip. Can use 'flow_input' or 'results.<step_id>'"}},"required":["expr"]},"sleep":{"description":"Delay before executing this step (in seconds or as expression)","$ref":"#/components/schemas/InputTransform"},"cache_ttl":{"type":"number","description":"Cache duration in seconds for this step's results"},"cache_ignore_s3_path":{"type":"boolean"},"timeout":{"description":"Maximum execution time in seconds (static value or expression)","$ref":"#/components/schemas/InputTransform"},"delete_after_secs":{"type":"integer","description":"If set, delete the step's args, result and logs after this many seconds following job completion"},"summary":{"type":"string","description":"Short description of what this step does"},"mock":{"type":"object","description":"Mock configuration for testing without executing the actual step","properties":{"enabled":{"type":"boolean","description":"If true, return mock value instead of executing"},"return_value":{"description":"Value to return when mocked"}}},"suspend":{"type":"object","description":"Configuration for approval/resume steps that wait for user input","properties":{"required_events":{"type":"integer","description":"Number of approvals required before continuing"},"timeout":{"type":"integer","description":"Timeout in seconds before auto-continuing or canceling"},"resume_form":{"type":"object","description":"Form schema for collecting input when resuming","properties":{"schema":{"type":"object","description":"JSON Schema for the resume form"}}},"user_auth_required":{"type":"boolean","description":"If true, only authenticated users can approve"},"user_groups_required":{"description":"Expression or list of groups that can approve","$ref":"#/components/schemas/InputTransform"},"self_approval_disabled":{"type":"boolean","description":"If true, the user who started the flow cannot approve"},"hide_cancel":{"type":"boolean","description":"If true, hide the cancel button on the approval form"},"continue_on_disapprove_timeout":{"type":"boolean","description":"If true, continue flow on timeout instead of canceling"},"skin":{"type":"string","enum":["detailed","minimal"],"description":"How the approval request is presented, on the approval page and in Slack/Teams approval messages. 'detailed' (used when unset) shows the flow details (arguments, graph, approvers); 'minimal' shows only the request: the step description, form and approve/reject actions"}}},"priority":{"type":"number","description":"Execution priority for this step (higher numbers run first)"},"continue_on_error":{"type":"boolean","description":"If true, flow continues even if this step fails"},"job_token_scopes":{"type":"array","nullable":true,"items":{"type":"string"},"description":"Scopes the token of this step's jobs is restricted to (domain:action[:resource], e.g. oidc:write), on top of the flow's own restriction: a step can only narrow it. Applies to everything the step runs (loop and branch bodies, AI agent tools)."},"retry":{"description":"Retry configuration if this step fails","$ref":"#/components/schemas/Retry"},"debouncing":{"description":"Debounce configuration for this step (EE only)","type":"object","properties":{"debounce_delay_s":{"type":"integer","description":"Delay in seconds to debounce this step's executions across flow runs"},"debounce_key":{"type":"string","description":"Expression to group debounced executions. Supports $workspace and $args[name]. Default: $workspace/flow/<flow_path>-<step_id>"},"debounce_args_to_accumulate":{"type":"array","description":"Array-type arguments to accumulate across debounced executions","items":{"type":"string"}},"max_total_debouncing_time":{"type":"integer","description":"Maximum total time in seconds before forced execution"},"max_total_debounces_amount":{"type":"integer","description":"Maximum number of debounces before forced execution"}}}},"required":["value","id"]},"InputTransform":{"description":"Maps input parameters for a step. Can be a static value or a JavaScript expression that references previous results or flow inputs","oneOf":[{"$ref":"#/components/schemas/StaticTransform"},{"$ref":"#/components/schemas/JavascriptTransform"},{"$ref":"#/components/schemas/AiTransform"}],"discriminator":{"propertyName":"type","mapping":{"static":"#/components/schemas/StaticTransform","javascript":"#/components/schemas/JavascriptTransform","ai":"#/components/schemas/AiTransform"}}},"StaticTransform":{"type":"object","description":"Static value passed directly to the step. Use for hardcoded values or resource references like '$res:path/to/resource'","properties":{"value":{"description":"The static value. For resources, use format '$res:path/to/resource'"},"type":{"type":"string","enum":["static"]}},"required":["type"]},"JavascriptTransform":{"type":"object","description":"JavaScript expression evaluated at runtime. Can reference previous step results via 'results.step_id' or flow inputs via 'flow_input.property'. Inside for loops, use 'flow_input.iter.value' for the current iteration value (in while loops it equals 'flow_input.iter.index')","properties":{"expr":{"type":"string","description":"JavaScript expression returning the value. Available variables - results (object with all previous step results), flow_input (flow inputs), flow_input.iter (in loops)"},"type":{"type":"string","enum":["javascript"]}},"required":["expr","type"]},"AiTransform":{"type":"object","description":"Value resolved by the AI runtime for this input. The AI engine decides how to satisfy the parameter.","properties":{"type":{"type":"string","enum":["ai"]}},"required":["type"]},"AIProviderKind":{"type":"string","description":"Supported AI provider types","enum":["openai","azure_openai","azure_foundry","anthropic","mistral","deepseek","googleai","groq","openrouter","togetherai","customai","aws_bedrock","typesafe","cloudflare"]},"ProviderConfig":{"type":"object","description":"Complete AI provider configuration with resource reference and model selection","properties":{"kind":{"$ref":"#/components/schemas/AIProviderKind"},"resource":{"type":"string","description":"Resource reference in format '$res:{resource_path}' pointing to provider credentials"},"model":{"type":"string","description":"Model identifier (e.g., 'gpt-4', 'claude-3-opus-20240229', 'gemini-pro')"},"reasoning_effort":{"type":"string","description":"Provider-native reasoning effort token (e.g. 'low', 'high', 'none') for models that support extended thinking. Optional; unset leaves the provider default."}},"required":["kind","resource","model"]},"StaticProviderTransform":{"type":"object","description":"Static provider configuration passed directly to the AI agent","properties":{"value":{"$ref":"#/components/schemas/ProviderConfig"},"type":{"type":"string","enum":["static"]}},"required":["type","value"]},"ProviderTransform":{"description":"Provider configuration - can be static (ProviderConfig), JavaScript expression, or AI-determined","oneOf":[{"$ref":"#/components/schemas/StaticProviderTransform"},{"$ref":"#/components/schemas/JavascriptTransform"},{"$ref":"#/components/schemas/AiTransform"}],"discriminator":{"propertyName":"type","mapping":{"static":"#/components/schemas/StaticProviderTransform","javascript":"#/components/schemas/JavascriptTransform","ai":"#/components/schemas/AiTransform"}}},"MemoryOff":{"type":"object","description":"No conversation memory/context","properties":{"kind":{"type":"string","enum":["off"]}},"required":["kind"]},"MemoryWindow":{"type":"object","description":"Keeps the most recent messages of the memory named by the run's memory id (or the step's\\n\`memory_id\`). Without a memory id the agent runs without memory.\\n","properties":{"kind":{"type":"string","enum":["window"]},"context_length":{"type":"integer","description":"Number of most recent messages to load and store. 0 turns memory off."}},"required":["kind","context_length"]},"MemoryAuto":{"type":"object","deprecated":true,"description":"Deprecated, still read as it was written: the run's memory id, else the \`memory_id\` here.\\nThe step's own \`memory_id\` is not read while this kind is set; switch the kind to \`window\`\\nto use it. Without a \`context_length\`, or with 0, it is \`off\` and reads \`previous_messages\`.\\n","properties":{"kind":{"type":"string","enum":["auto"]},"context_length":{"type":"integer","description":"Maximum number of messages to retain in context"},"memory_id":{"type":"string","description":"Identifier for persistent memory across agent invocations"}},"required":["kind"]},"MemoryCompaction":{"type":"object","description":"Keeps the whole memory named by the run's memory id (or the step's \`memory_id\`), replacing\\nits older part with a summary as the conversation approaches the model's context window.\\nWithout a memory id the agent runs without memory, and compaction bounds the run's own loop.\\n","properties":{"kind":{"type":"string","enum":["compaction"]},"context_window":{"type":"integer","description":"Overrides the context window looked up from the model, in tokens. Only a model\\nWindmill does not know needs one; those fall back to 128000.\\n"}},"required":["kind"]},"MemoryMessage":{"type":"object","description":"A single message in conversation history","properties":{"role":{"type":"string","enum":["user","assistant","system"]},"content":{"type":"string"}},"required":["role","content"]},"MemoryManual":{"type":"object","deprecated":true,"description":"Deprecated, still read as it was written. Move the step to \`off\` with \`previous_messages\` instead.","properties":{"kind":{"type":"string","enum":["manual"]},"messages":{"type":"array","items":{"$ref":"#/components/schemas/MemoryMessage"}}},"required":["kind","messages"]},"MemoryConfig":{"description":"Managed memory, stored by Windmill and replayed with each request. The memory is named by a memory id, see \`memory_id\`. While it is off, a step can supply its history in \`previous_messages\`.","oneOf":[{"$ref":"#/components/schemas/MemoryOff"},{"$ref":"#/components/schemas/MemoryWindow"},{"$ref":"#/components/schemas/MemoryCompaction"},{"$ref":"#/components/schemas/MemoryAuto"},{"$ref":"#/components/schemas/MemoryManual"}],"discriminator":{"propertyName":"kind","mapping":{"off":"#/components/schemas/MemoryOff","window":"#/components/schemas/MemoryWindow","compaction":"#/components/schemas/MemoryCompaction","auto":"#/components/schemas/MemoryAuto","manual":"#/components/schemas/MemoryManual"}}},"StaticMemoryTransform":{"type":"object","description":"Static memory configuration passed directly to the AI agent","properties":{"value":{"$ref":"#/components/schemas/MemoryConfig"},"type":{"type":"string","enum":["static"]}},"required":["type","value"]},"MemoryTransform":{"description":"Memory configuration - can be static (MemoryConfig), JavaScript expression, or AI-determined","oneOf":[{"$ref":"#/components/schemas/StaticMemoryTransform"},{"$ref":"#/components/schemas/JavascriptTransform"},{"$ref":"#/components/schemas/AiTransform"}],"discriminator":{"propertyName":"type","mapping":{"static":"#/components/schemas/StaticMemoryTransform","javascript":"#/components/schemas/JavascriptTransform","ai":"#/components/schemas/AiTransform"}}},"FlowModuleValue":{"description":"The actual implementation of a flow step. Can be a script (inline or referenced), subflow, loop, branch, or special module type","oneOf":[{"$ref":"#/components/schemas/RawScript"},{"$ref":"#/components/schemas/PathScript"},{"$ref":"#/components/schemas/PathFlow"},{"$ref":"#/components/schemas/ForloopFlow"},{"$ref":"#/components/schemas/WhileloopFlow"},{"$ref":"#/components/schemas/BranchOne"},{"$ref":"#/components/schemas/BranchAll"},{"$ref":"#/components/schemas/Identity"},{"$ref":"#/components/schemas/AiAgent"},{"$ref":"#/components/schemas/AiDecision"}],"discriminator":{"propertyName":"type","mapping":{"rawscript":"#/components/schemas/RawScript","script":"#/components/schemas/PathScript","flow":"#/components/schemas/PathFlow","forloopflow":"#/components/schemas/ForloopFlow","whileloopflow":"#/components/schemas/WhileloopFlow","branchone":"#/components/schemas/BranchOne","branchall":"#/components/schemas/BranchAll","identity":"#/components/schemas/Identity","aiagent":"#/components/schemas/AiAgent","aidecision":"#/components/schemas/AiDecision"}}},"RawScript":{"type":"object","description":"Inline script with code defined directly in the flow. Use 'bun' as default language if unspecified. The script receives arguments from input_transforms","properties":{"input_transforms":{"type":"object","description":"Map of parameter names to their values (static or JavaScript expressions). These become the script's input arguments","additionalProperties":{"$ref":"#/components/schemas/InputTransform"}},"content":{"type":"string","description":"The script source code. Should export a 'main' function"},"language":{"type":"string","description":"Programming language for this script","enum":["deno","bun","bunnative","python3","go","bash","powershell","postgresql","mysql","bigquery","snowflake","mssql","oracledb","graphql","nativets","php","rust","ansible","csharp","nu","java","ruby","rlang","duckdb"]},"path":{"type":"string","description":"Optional path for saving this script"},"lock":{"type":"string","description":"Lock file content for dependencies"},"type":{"type":"string","enum":["rawscript"]},"tag":{"type":"string","description":"Worker group tag for execution routing"},"concurrent_limit":{"type":"number","description":"Maximum concurrent executions of this script"},"concurrency_time_window_s":{"type":"number","description":"Time window for concurrent_limit"},"custom_concurrency_key":{"type":"string","description":"Custom key for grouping concurrent executions"},"is_trigger":{"type":"boolean","description":"If true, this script is a trigger that can start the flow"},"assets":{"type":"array","description":"External resources this script accesses (S3 objects, resources, etc.)","items":{"type":"object","required":["path","kind"],"properties":{"path":{"type":"string","description":"Path to the asset"},"kind":{"type":"string","description":"Type of asset","enum":["s3object","resource","ducklake","datatable","volume","dbt"]},"access_type":{"type":"string","nullable":true,"description":"Access level for this asset","enum":["r","w","rw"]},"alt_access_type":{"type":"string","nullable":true,"description":"Alternative access level","enum":["r","w","rw"]}}}}},"required":["type","content","language","input_transforms"]},"PathScript":{"type":"object","description":"Reference to an existing script by path. Use this when calling a previously saved script instead of writing inline code","properties":{"input_transforms":{"type":"object","description":"Map of parameter names to their values (static or JavaScript expressions). These become the script's input arguments","additionalProperties":{"$ref":"#/components/schemas/InputTransform"}},"path":{"type":"string","description":"Path to the script in the workspace (e.g., 'f/scripts/send_email')"},"hash":{"type":"string","description":"Optional specific version hash of the script to use"},"type":{"type":"string","enum":["script"]},"tag_override":{"type":"string","description":"Override the script's default worker group tag"},"is_trigger":{"type":"boolean","description":"If true, this script is a trigger that can start the flow"}},"required":["type","path","input_transforms"]},"PathFlow":{"type":"object","description":"Reference to an existing flow by path. Use this to call another flow as a subflow","properties":{"input_transforms":{"type":"object","description":"Map of parameter names to their values (static or JavaScript expressions). These become the subflow's input arguments","additionalProperties":{"$ref":"#/components/schemas/InputTransform"}},"path":{"type":"string","description":"Path to the flow in the workspace (e.g., 'f/flows/process_user')"},"type":{"type":"string","enum":["flow"]}},"required":["type","path","input_transforms"]},"ForloopFlow":{"type":"object","description":"Executes nested modules in a loop over an iterator. Inside the loop, use 'flow_input.iter.value' to access the current iteration value, and 'flow_input.iter.index' for the index. Supports parallel execution for better performance on I/O-bound operations","properties":{"modules":{"type":"array","description":"Steps to execute for each iteration. These can reference the iteration value via 'flow_input.iter.value'","items":{"$ref":"#/components/schemas/FlowModule"}},"iterator":{"description":"JavaScript expression that returns an array to iterate over. Can reference 'results.step_id' or 'flow_input'","$ref":"#/components/schemas/InputTransform"},"skip_failures":{"type":"boolean","description":"If true, iteration failures don't stop the loop. Failed iterations return null"},"type":{"type":"string","enum":["forloopflow"]},"parallel":{"type":"boolean","description":"If true, iterations run concurrently (faster for I/O-bound operations). Use with parallelism to control concurrency"},"parallelism":{"description":"Maximum number of concurrent iterations when parallel=true. Limits resource usage. Can be static number or expression","$ref":"#/components/schemas/InputTransform"},"squash":{"type":"boolean"}},"required":["modules","iterator","skip_failures","type"]},"WhileloopFlow":{"type":"object","description":"Executes nested modules repeatedly until stopped. The implicit iterator is the iteration counter, so 'flow_input.iter.value' equals 'flow_input.iter.index' (0, 1, 2, ...) and never carries state. To carry state across iterations, a step reads its own previous-iteration result via 'results.<its_own_id>' with a first-iteration fallback - the loop's stop_after_if must then be on that inner step (a plain single-step body with stop_after_if on the loop module does not resolve 'results' across iterations and never terminates); plain counters can instead be derived from 'flow_input.iter.index', which works in every configuration. stop_after_if is evaluated after each iteration - on the loop module 'result' is the last iteration's result","properties":{"modules":{"type":"array","description":"Steps to execute in each iteration","items":{"$ref":"#/components/schemas/FlowModule"}},"skip_failures":{"type":"boolean","description":"If true, iteration failures don't stop the loop. Failed iterations return null"},"type":{"type":"string","enum":["whileloopflow"]},"parallel":{"type":"boolean","description":"If true, iterations run concurrently (use with caution in while loops)"},"parallelism":{"description":"Maximum number of concurrent iterations when parallel=true","$ref":"#/components/schemas/InputTransform"},"squash":{"type":"boolean"}},"required":["modules","skip_failures","type"]},"BranchOne":{"type":"object","description":"Conditional branching where only the first matching branch executes. Branches are evaluated in order, and the first one with a true expression runs. If no branches match, the default branch executes","properties":{"branches":{"type":"array","description":"Array of branches to evaluate in order. The first branch with expr evaluating to true executes","items":{"type":"object","properties":{"summary":{"type":"string","description":"Short description of this branch condition"},"expr":{"type":"string","description":"JavaScript expression that returns boolean. Can use 'results.step_id' or 'flow_input'. First true expr wins"},"modules":{"type":"array","description":"Steps to execute if this branch's expr is true","items":{"$ref":"#/components/schemas/FlowModule"}}},"required":["modules","expr"]}},"default":{"type":"array","description":"Steps to execute if no branch expressions match","items":{"$ref":"#/components/schemas/FlowModule"}},"type":{"type":"string","enum":["branchone"]}},"required":["branches","default","type"]},"BranchAll":{"type":"object","description":"Parallel branching where all branches execute simultaneously. Unlike BranchOne, all branches run regardless of conditions. Useful for executing independent tasks concurrently","properties":{"branches":{"type":"array","description":"Array of branches that all execute (either in parallel or sequentially)","items":{"type":"object","properties":{"summary":{"type":"string","description":"Short description of this branch's purpose"},"skip_failure":{"type":"boolean","description":"If true, failure in this branch doesn't fail the entire flow"},"modules":{"type":"array","description":"Steps to execute in this branch","items":{"$ref":"#/components/schemas/FlowModule"}}},"required":["modules"]}},"type":{"type":"string","enum":["branchall"]},"parallel":{"type":"boolean","description":"If true, all branches execute concurrently. If false, they execute sequentially"}},"required":["branches","type"]},"AgentTool":{"type":"object","description":"A tool available to an AI agent. Can be a flow module or an external MCP (Model Context Protocol) tool","properties":{"id":{"type":"string","description":"Unique identifier for this tool. Cannot contain spaces - use underscores instead (e.g., 'get_user_data' not 'get user data')"},"summary":{"type":"string","description":"The name the AI agent calls this tool by, not a human label. On a flowmodule tool it must match ^[a-zA-Z0-9_]+$ - letters, numbers and underscores only (e.g. 'search_documentation', not 'Search documentation') - and always be set; on an mcp or websearch tool it is a plain label. Put the human-readable explanation in 'description'."},"description":{"type":"string","description":"Free-text description of the tool given to the AI to decide when and how to call it. Overrides the description auto-derived from the underlying script."},"job_token_scopes":{"type":"array","nullable":true,"items":{"type":"string"},"description":"Scopes the token of this tool's jobs is restricted to, on top of the agent step's own restriction: a tool can only narrow it."},"value":{"$ref":"#/components/schemas/ToolValue"}},"required":["id","value"]},"ToolValue":{"description":"The implementation of a tool. Can be a flow module (script/flow) or an MCP tool reference","oneOf":[{"$ref":"#/components/schemas/FlowModuleTool"},{"$ref":"#/components/schemas/McpToolValue"},{"$ref":"#/components/schemas/WebsearchToolValue"}],"discriminator":{"propertyName":"tool_type","mapping":{"flowmodule":"#/components/schemas/FlowModuleTool","mcp":"#/components/schemas/McpToolValue","websearch":"#/components/schemas/WebsearchToolValue"}}},"FlowModuleTool":{"description":"A tool implemented as a flow module (script, flow, etc.). The AI can call this like any other flow module","allOf":[{"type":"object","properties":{"tool_type":{"type":"string","enum":["flowmodule"]}},"required":["tool_type"]},{"$ref":"#/components/schemas/FlowModuleValue"}]},"WebsearchToolValue":{"type":"object","description":"A tool implemented as a websearch tool. The AI can call this like any other websearch tool","properties":{"tool_type":{"type":"string","enum":["websearch"]}},"required":["tool_type"]},"McpToolValue":{"type":"object","description":"Reference to an external MCP (Model Context Protocol) tool. The AI can call tools from MCP servers","properties":{"tool_type":{"type":"string","enum":["mcp"]},"resource_path":{"type":"string","description":"Path to the MCP resource/server configuration"},"include_tools":{"type":"array","description":"Whitelist of specific tools to include from this MCP server","items":{"type":"string"}},"exclude_tools":{"type":"array","description":"Blacklist of tools to exclude from this MCP server","items":{"type":"string"}}},"required":["tool_type","resource_path"]},"AiAgent":{"type":"object","description":"AI agent step that can use tools to accomplish tasks. The agent receives inputs and can call any of its configured tools to complete the task","properties":{"input_transforms":{"type":"object","description":"Input parameters for the AI agent mapped to their values","properties":{"provider":{"$ref":"#/components/schemas/ProviderTransform"},"output_type":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"Output format type.\\nValid values: 'text' (default) - plain text response, 'image' - image generation\\n"},"user_message":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"The user's prompt/message to the AI agent. Supports variable interpolation with\\nflow.input syntax. Required unless memory is off and \`previous_messages\` supplies\\nthe prompt; image output always needs it.\\n"},"system_prompt":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"System instructions that guide the AI's behavior, persona, and response style. Optional."},"streaming":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"Boolean. If true, stream the AI response incrementally.\\nStreaming events include: token_delta, reasoning_token_delta, tool_call, tool_call_arguments, tool_execution, tool_result\\n"},"memory":{"$ref":"#/components/schemas/MemoryTransform"},"memory_id":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"String. Names the memory this step reads and writes, overriding the memory id the run\\nwas started with (the chat conversation, an app chat session or the \`memory_id\` run\\nparameter). Leave unset to use the run's memory id. A fixed value shares one memory\\nacross every run; an expression such as \`flow_input.customer_id\` keeps one memory per\\nkey. When it evaluates to an empty value the agent runs without memory. Read only\\nwhile \`memory\` is \`window\` or \`compaction\`: it is ignored when memory is off, and an\\nolder \`auto\` or \`manual\` memory reads neither history input.\\n"},"previous_messages":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"Array of MemoryMessage. History supplied by the flow, sent between the system prompt\\nand the user message. Read only while \`memory\` is off or absent: managed memory\\nignores it, and an older \`auto\` or \`manual\` memory reads neither history input.\\n"},"output_schema":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"JSON Schema object defining structured output format. Used when you need the AI to return data in a specific shape.\\nSupports standard JSON Schema properties: type, properties, required, items, enum, pattern, minLength, maxLength, minimum, maximum, etc.\\nExample: { type: 'object', properties: { name: { type: 'string' }, age: { type: 'integer' } }, required: ['name'] }\\n"},"user_attachments":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"Array of file references (images or PDFs) for the AI agent.\\nFormat: Array<{ bucket: string, key: string }> - S3 object references\\nExample: [{ bucket: 'my-bucket', key: 'documents/report.pdf' }]\\n"},"enabled_tools":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"Array of strings naming which of the tools configured in \`tools\` the agent may call\\nthis run. Leaving it unset carries every one of them; an empty array carries none.\\nA tool is named as the model is shown it. An entry the model is shown nothing of is\\nnamed by what identifies it instead: an MCP server by its resource path, carrying\\nevery tool it exposes (which of them stays that entry's include_tools/exclude_tools),\\nand a websearch entry by the reserved name '__wm_web_search', whatever summary it carries\\n(no tool may take that name).\\nExample: ['get_user', 'u/admin/github_mcp', '__wm_web_search']\\n"},"max_completion_tokens":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"Integer. Maximum number of tokens the AI will generate in its response.\\nRange: 1 to 4,294,967,295. Typical values: 256-4096 for most use cases.\\n"},"temperature":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"Float. Controls randomness/creativity of responses.\\nRange: 0.0 to 2.0 (provider-dependent)\\n- 0.0 = deterministic, focused responses\\n- 0.7 = balanced (common default)\\n- 1.0+ = more creative/random\\n"},"max_iterations":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"Number. Limits how many times the agent can loop through reasoning and tool use.\\nRange: 1-1000.\\n"},"model":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"String. Only on a step linked to a saved agent (see \`agent\`): replaces the model\\nsaved on the agent for this step's runs, on the agent's own provider resource. An\\nempty value keeps the saved model. Set it to an expression such as\\n\`flow_input.model\` to choose the model per run.\\n"},"reasoning_effort":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"String. Only on a step linked to a saved agent (see \`agent\`): replaces the reasoning\\neffort saved on the agent for this step's runs, as a provider-native token (e.g.\\n'low', 'high', 'none'). An empty value sends no effort, so the model runs at its\\ndefault. Leave the input out to keep the saved effort, which holds only while the\\nstep runs the saved model. A step that is not linked sets both inside \`provider\`.\\n"}}},"tools":{"type":"array","description":"Array of tools the agent can use. The agent decides which tools to call based on the task","items":{"$ref":"#/components/schemas/AgentTool"}},"type":{"type":"string","enum":["aiagent"]},"tag":{"type":"string","description":"Worker group tag for execution routing. If not set, the AI agent step runs on the flow's tag (default \`flow\`)"},"omit_output_from_conversation":{"type":"boolean","default":false,"description":"If true, this AI agent step does not persist its assistant or tool messages to the flow conversation when chat mode is enabled."},"agent":{"type":"string","description":"Path of a reusable \`ai_agent\` resource (hybrid linking). When set, the agent brain\\nconfig (provider/model/system prompt/etc.) and tool set are resolved at runtime from\\nthat resource; the module's input_transforms then only carry the flow-local inputs\\n(user_message, user_attachments, enabled_tools and the history inputs memory_id and previous_messages)\\nand, optionally, the \`model\` and \`reasoning_effort\` overrides of what the agent saved.\\n"},"tool_inputs":{"type":"object","description":"Host-local wiring for an agent's tool inputs, keyed by tool id then input key. Binds the\\nreferenced agent's tools to this flow's context (flow_input/results) without mutating the\\nshared resource; overlaid onto the tools' input_transforms at runtime \\u2014 including when\\n\`agent\` is unset, since a step forked for editing keeps these overrides until it is saved\\nback or unlinked.\\n","additionalProperties":{"type":"object","additionalProperties":{"$ref":"#/components/schemas/InputTransform"}}},"parallel":{"type":"boolean","description":"If true, the agent can execute multiple tool calls in parallel"}},"required":["type","input_transforms"]},"AiDecision":{"type":"object","description":"AI decision step: one call to a decision model (TypeSafe's Jev, Cloudflare's\\nJev-compatible Clef, or OpenAI's Decisions API) that answers typed questions about a\\nstate with calibrated probabilities, instead of generating text.\\nPrefer it over an AI agent to classify, route, score or check something: it is fast,\\ncheap and its answers are structured. Its result is { output: { <question name>: answer },\\nmodel, usage }, so a later step reads e.g. results.<id>.output.intent.choice. To route on\\nthe answers, follow it with a branchone whose branch exprs read\\nresults.<id>.output.<question>.choice. Usable as an AI agent tool, where the calling agent\\nsupplies the state.\\n","properties":{"input_transforms":{"type":"object","description":"Input parameters for the decision mapped to their values","properties":{"provider":{"$ref":"#/components/schemas/ProviderTransform"},"state":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"What the questions are asked about: a string, an object or an array of strings.\\nAn object with descriptive keys holding only what the questions need works best.\\nExample: { message: flow_input.message, plan: results.a.plan }\\n"},"questions":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"Object mapping each question name to { type, instructions, criteria }, where type is:\\n- 'choice': criteria maps each option to its description (up to 255); the answer\\n has choice, probabilities and confidence\\n- 'score': criteria is an ordered array of 2 to 10 level descriptions; the answer\\n has score, legend, probabilities and confidence\\n- 'noul': yes/no, criteria optionally { true, false } descriptions; the answer has\\n noul, the probability of yes (0 to 1)\\nExample: { intent: { type: 'choice', instructions: 'What does the customer want?',\\ncriteria: { refund: 'Money back', bug: 'Something is broken' } } }\\n"}},"required":["provider","state","questions"]},"type":{"type":"string","enum":["aidecision"]},"tag":{"type":"string","description":"Worker group tag for execution routing. If not set, the step runs on the flow's tag (default \`flow\`)"}},"required":["type","input_transforms"]},"Identity":{"type":"object","description":"Pass-through module that returns its input unchanged. Useful for flow structure or as a placeholder","properties":{"type":{"type":"string","enum":["identity"]},"flow":{"type":"boolean","description":"If true, marks this as a flow identity (special handling)"}},"required":["type"]},"FlowStatus":{"type":"object","properties":{"step":{"type":"integer"},"modules":{"type":"array","items":{"$ref":"#/components/schemas/FlowStatusModule"}},"user_states":{"additionalProperties":true},"preprocessor_module":{"allOf":[{"$ref":"#/components/schemas/FlowStatusModule"}]},"failure_module":{"allOf":[{"$ref":"#/components/schemas/FlowStatusModule"},{"type":"object","properties":{"parent_module":{"type":"string"}}}]},"retry":{"type":"object","properties":{"fail_count":{"type":"integer"},"failed_jobs":{"type":"array","items":{"type":"string","format":"uuid"}}}}},"required":["step","modules","failure_module"]},"FlowStatusModule":{"type":"object","properties":{"type":{"type":"string","enum":["WaitingForPriorSteps","WaitingForEvents","WaitingForExecutor","InProgress","Success","Failure"]},"id":{"type":"string"},"job":{"type":"string","format":"uuid"},"count":{"type":"integer"},"progress":{"type":"integer"},"iterator":{"type":"object","properties":{"index":{"type":"integer"},"itered":{"type":"array","items":{}},"itered_len":{"type":"integer"},"args":{}}},"flow_jobs":{"type":"array","items":{"type":"string"}},"flow_jobs_success":{"type":"array","items":{"type":"boolean"}},"flow_jobs_duration":{"type":"object","properties":{"started_at":{"type":"array","items":{"type":"string"}},"duration_ms":{"type":"array","items":{"type":"integer"}}}},"branch_chosen":{"type":"object","properties":{"type":{"type":"string","enum":["branch","default"]},"branch":{"type":"integer"}},"required":["type"]},"branchall":{"type":"object","properties":{"branch":{"type":"integer"},"len":{"type":"integer"}},"required":["branch","len"]},"approvers":{"type":"array","items":{"type":"object","properties":{"resume_id":{"type":"integer"},"approver":{"type":"string"}},"required":["resume_id","approver"]}},"failed_retries":{"type":"array","items":{"type":"string","format":"uuid"}},"skipped":{"type":"boolean"},"agent_actions":{"type":"array","items":{"type":"object","oneOf":[{"type":"object","properties":{"job_id":{"type":"string","format":"uuid"},"function_name":{"type":"string"},"type":{"type":"string","enum":["tool_call"]},"module_id":{"type":"string"}},"required":["job_id","function_name","type","module_id"]},{"type":"object","properties":{"call_id":{"type":"string","format":"uuid"},"function_name":{"type":"string"},"resource_path":{"type":"string"},"type":{"type":"string","enum":["mcp_tool_call"]},"arguments":{"type":"object"}},"required":["call_id","function_name","resource_path","type"]},{"type":"object","properties":{"type":{"type":"string","enum":["web_search"]}},"required":["type"]},{"type":"object","properties":{"type":{"type":"string","enum":["message"]}},"required":["content","type"]}]}},"agent_actions_success":{"type":"array","items":{"type":"boolean"}}},"required":["type"]}} +{"OpenFlow":{"type":"object","description":"Top-level flow definition containing metadata, configuration, and the flow structure","properties":{"summary":{"type":"string","description":"Short description of what this flow does"},"description":{"type":"string","description":"Detailed documentation for this flow"},"value":{"$ref":"#/components/schemas/FlowValue"},"schema":{"type":"object","description":"JSON Schema for flow inputs. Use this to define input parameters, their types, defaults, and validation. For resource inputs, set type to 'object' and format to 'resource-<type>' (e.g., 'resource-stripe')"},"on_behalf_of_email":{"type":"string","description":"Address of the account the flow runs on behalf of. Derived from on_behalf_of on read; accepted on write, where it is resolved to the account it names."},"on_behalf_of":{"type":"string","description":"The flow runs with the permissions of this identity: u/{username}, g/{group}, or a bare email when the username is itself email-shaped. The only stored half of the identity; on_behalf_of_email is derived from it. Omit it when writing and it is resolved from that address instead."}},"required":["summary","value"]},"FlowValue":{"type":"object","description":"The flow structure containing modules and optional preprocessor/failure handlers","properties":{"modules":{"type":"array","description":"Array of steps that execute in sequence. Each step can be a script, subflow, loop, or branch","items":{"$ref":"#/components/schemas/FlowModule"}},"failure_module":{"description":"Special module that executes when the flow fails. Receives error object with message, name, stack, and step_id. Must have id 'failure'. Only supports script/rawscript types","$ref":"#/components/schemas/FlowModule"},"preprocessor_module":{"description":"Special module that runs before the first step on external triggers. Must have id 'preprocessor'. Only supports script/rawscript types. Cannot reference other step results","$ref":"#/components/schemas/FlowModule"},"same_worker":{"type":"boolean","description":"If true, all steps run on the same worker for better performance"},"preserve_step_tags":{"type":"boolean","description":"If true and the flow runs on a custom worker tag, steps that declare their own non-empty tag run on it instead of inheriting the flow tag. Steps without their own tag still inherit the flow tag."},"concurrent_limit":{"type":"number","description":"Maximum number of concurrent executions of this flow"},"concurrency_key":{"type":"string","description":"Expression to group concurrent executions (e.g., by user ID)"},"concurrency_time_window_s":{"type":"number","description":"Time window in seconds for concurrent_limit"},"debounce_delay_s":{"type":"integer","description":"Delay in seconds to debounce flow executions"},"debounce_key":{"type":"string","description":"Expression to group debounced executions"},"debounce_args_to_accumulate":{"type":"array","description":"Arguments to accumulate across debounced executions","items":{"type":"string"}},"max_total_debouncing_time":{"type":"integer","description":"Maximum total time in seconds that a job can be debounced"},"max_total_debounces_amount":{"type":"integer","description":"Maximum number of times a job can be debounced"},"skip_expr":{"type":"string","description":"JavaScript expression to conditionally skip the entire flow"},"cache_ttl":{"type":"number","description":"Cache duration in seconds for flow results"},"cache_ignore_s3_path":{"type":"boolean"},"delete_after_secs":{"type":"integer","description":"If set, delete the flow job's args, result and logs after this many seconds following job completion"},"flow_env":{"type":"object","description":"Environment variables available to all steps. Values can be strings, JSON values, or special references: '$var:path' (workspace variable) or '$res:path' (resource).","additionalProperties":{}},"priority":{"type":"number","description":"Execution priority (higher numbers run first)"},"early_return":{"type":"string","description":"Id of the step whose result a sync webhook returns as soon as that step completes, while the rest of the flow keeps running. When the step does not run, or fails while the flow has a failure module, the flow's final result is returned instead."},"chat_input_enabled":{"type":"boolean","description":"Whether this flow accepts chat-style input"},"notes":{"type":"array","description":"Sticky notes attached to the flow","items":{"$ref":"#/components/schemas/FlowNote"}},"groups":{"type":"array","description":"Semantic groups of modules for organizational purposes","items":{"$ref":"#/components/schemas/FlowGroup"}}},"required":["modules"]},"Retry":{"type":"object","description":"Retry configuration for failed module executions","properties":{"constant":{"type":"object","description":"Retry with constant delay between attempts","properties":{"attempts":{"type":"integer","description":"Number of retry attempts"},"seconds":{"type":"integer","description":"Seconds to wait between retries"}}},"exponential":{"type":"object","description":"Retry with exponential backoff: the n-th retry waits multiplier \\u00d7 seconds^n","properties":{"attempts":{"type":"integer","description":"Number of retry attempts"},"multiplier":{"type":"integer","description":"Multiplier for exponential backoff"},"seconds":{"type":"integer","minimum":1,"description":"Base of the exponential (seconds); the n-th retry waits multiplier \\u00d7 seconds^n, where n counts constant retries too"},"random_factor":{"type":"integer","minimum":0,"maximum":100,"description":"Random jitter percentage (0-100) to avoid thundering herd"}}},"retry_if":{"$ref":"#/components/schemas/RetryIf"}}},"FlowNote":{"type":"object","description":"A sticky note attached to a flow for documentation and annotation","properties":{"id":{"type":"string","description":"Unique identifier for the note"},"text":{"type":"string","description":"Content of the note"},"position":{"type":"object","description":"Position of the note in the flow editor","properties":{"x":{"type":"number","description":"X coordinate"},"y":{"type":"number","description":"Y coordinate"}},"required":["x","y"]},"size":{"type":"object","description":"Size of the note in the flow editor","properties":{"width":{"type":"number","description":"Width in pixels"},"height":{"type":"number","description":"Height in pixels"}},"required":["width","height"]},"color":{"type":"string","description":"Color of the note, one of: yellow, blue, green, purple, pink, orange, red, cyan, lime, gray. Any other value renders unstyled."},"type":{"type":"string","enum":["free","group"],"description":"Type of note - 'free' for standalone notes. 'group' notes are deprecated; segment a flow with FlowValue.groups instead."},"locked":{"type":"boolean","default":false,"description":"Whether the note is locked and cannot be edited or moved"},"contained_node_ids":{"type":"array","items":{"type":"string"},"description":"For group notes, the IDs of nodes contained within this group"}},"required":["id","text","color","type"]},"FlowGroup":{"type":"object","description":"A semantic group of flow modules for organizational purposes. Does not affect execution \\u2014 modules remain in their original position in the flow. Groups provide naming and collapsibility in the editor. Members are computed dynamically from all nodes on paths between start_id and end_id.","properties":{"summary":{"type":"string","description":"Display name for this group"},"note":{"type":"string","description":"Markdown note shown below the group header"},"autocollapse":{"type":"boolean","default":false,"description":"If true, this group is collapsed by default in the flow editor. UI hint only."},"start_id":{"type":"string","description":"ID of the first flow module in this group (topological entry point)"},"end_id":{"type":"string","description":"ID of the last flow module in this group (topological exit point)"},"color":{"type":"string","description":"Color for the group in the flow editor, one of: yellow, blue, green, purple, pink, orange, red, cyan, lime, gray. Omit it to let the editor pick one."}},"required":["start_id","end_id"]},"RetryIf":{"type":"object","description":"Conditional retry based on error or result","properties":{"expr":{"type":"string","description":"JavaScript expression that returns true to retry. Has access to 'result' and 'error' variables"}},"required":["expr"]},"StopAfterIf":{"type":"object","description":"Early termination condition for a module","properties":{"skip_if_stopped":{"type":"boolean","description":"If true, following steps are skipped when this condition triggers"},"expr":{"type":"string","description":"JavaScript expression evaluated after the module runs. Can use 'result' (step's result) or 'flow_input'. Return true to stop"},"error_message":{"type":"string","nullable":true,"description":"Custom error message when stopping with an error. Mutually exclusive with skip_if_stopped. If set to a non-empty string, the flow stops with this error. If empty string, a default error message is used. If null or omitted, no error is raised."},"error_include_result":{"type":"boolean","description":"When stopping with an error (error_message set), embed the stopping step's own result inside the raised error object (as error.result) instead of discarding it. The top-level result stays { error }. Defaults to false."}},"required":["expr"]},"FlowModule":{"type":"object","description":"A single step in a flow. Can be a script, subflow, loop, or branch","properties":{"id":{"type":"string","description":"Unique identifier for this step. Used to reference results via 'results.step_id'. Must be a valid identifier (alphanumeric, underscore, hyphen)"},"value":{"$ref":"#/components/schemas/FlowModuleValue"},"stop_after_if":{"description":"Early termination condition evaluated after this step completes","$ref":"#/components/schemas/StopAfterIf"},"stop_after_all_iters_if":{"description":"For loops only - early termination condition evaluated after all iterations complete","$ref":"#/components/schemas/StopAfterIf"},"skip_if":{"type":"object","description":"Conditionally skip this step based on previous results or flow inputs","properties":{"expr":{"type":"string","description":"JavaScript expression that returns true to skip. Can use 'flow_input' or 'results.<step_id>'"}},"required":["expr"]},"sleep":{"description":"Delay before executing this step (in seconds or as expression)","$ref":"#/components/schemas/InputTransform"},"cache_ttl":{"type":"number","description":"Cache duration in seconds for this step's results"},"cache_ignore_s3_path":{"type":"boolean"},"timeout":{"description":"Maximum execution time in seconds (static value or expression)","$ref":"#/components/schemas/InputTransform"},"delete_after_secs":{"type":"integer","description":"If set, delete the step's args, result and logs after this many seconds following job completion"},"summary":{"type":"string","description":"Short description of what this step does"},"mock":{"type":"object","description":"Mock configuration for testing without executing the actual step","properties":{"enabled":{"type":"boolean","description":"If true, return mock value instead of executing"},"return_value":{"description":"Value to return when mocked"}}},"suspend":{"type":"object","description":"Configuration for approval/resume steps that wait for user input","properties":{"required_events":{"type":"integer","description":"Number of approvals required before continuing"},"timeout":{"type":"integer","description":"Timeout in seconds before auto-continuing or canceling"},"resume_form":{"type":"object","description":"Form schema for collecting input when resuming","properties":{"schema":{"type":"object","description":"JSON Schema for the resume form"}}},"user_auth_required":{"type":"boolean","description":"If true, only authenticated users can approve"},"user_groups_required":{"description":"Expression or list of groups that can approve","$ref":"#/components/schemas/InputTransform"},"self_approval_disabled":{"type":"boolean","description":"If true, the user who started the flow cannot approve"},"hide_cancel":{"type":"boolean","description":"If true, hide the cancel button on the approval form"},"continue_on_disapprove_timeout":{"type":"boolean","description":"If true, continue flow on timeout instead of canceling"},"skin":{"type":"string","enum":["detailed","minimal"],"description":"How the approval request is presented, on the approval page and in Slack/Teams approval messages. 'detailed' (used when unset) shows the flow details (arguments, graph, approvers); 'minimal' shows only the request: the step description, form and approve/reject actions"}}},"priority":{"type":"number","description":"Execution priority for this step (higher numbers run first)"},"continue_on_error":{"type":"boolean","description":"If true, flow continues even if this step fails"},"job_token_scopes":{"type":"array","nullable":true,"items":{"type":"string"},"description":"Scopes the token of this step's jobs is restricted to (domain:action[:resource], e.g. oidc:write), on top of the flow's own restriction: a step can only narrow it. Applies to everything the step runs (loop and branch bodies, AI agent tools)."},"retry":{"description":"Retry configuration if this step fails","$ref":"#/components/schemas/Retry"},"debouncing":{"description":"Debounce configuration for this step (EE only)","type":"object","properties":{"debounce_delay_s":{"type":"integer","description":"Delay in seconds to debounce this step's executions across flow runs"},"debounce_key":{"type":"string","description":"Expression to group debounced executions. Supports $workspace and $args[name]. Default: $workspace/flow/<flow_path>-<step_id>"},"debounce_args_to_accumulate":{"type":"array","description":"Array-type arguments to accumulate across debounced executions","items":{"type":"string"}},"max_total_debouncing_time":{"type":"integer","description":"Maximum total time in seconds before forced execution"},"max_total_debounces_amount":{"type":"integer","description":"Maximum number of debounces before forced execution"}}}},"required":["value","id"]},"InputTransform":{"description":"Maps input parameters for a step. Can be a static value or a JavaScript expression that references previous results or flow inputs","oneOf":[{"$ref":"#/components/schemas/StaticTransform"},{"$ref":"#/components/schemas/JavascriptTransform"},{"$ref":"#/components/schemas/AiTransform"}],"discriminator":{"propertyName":"type","mapping":{"static":"#/components/schemas/StaticTransform","javascript":"#/components/schemas/JavascriptTransform","ai":"#/components/schemas/AiTransform"}}},"StaticTransform":{"type":"object","description":"Static value passed directly to the step. Use for hardcoded values or resource references like '$res:path/to/resource'","properties":{"value":{"description":"The static value. For resources, use format '$res:path/to/resource'"},"type":{"type":"string","enum":["static"]}},"required":["type"]},"JavascriptTransform":{"type":"object","description":"JavaScript expression evaluated at runtime. Can reference previous step results via 'results.step_id' or flow inputs via 'flow_input.property'. Inside for loops, use 'flow_input.iter.value' for the current iteration value (in while loops it equals 'flow_input.iter.index')","properties":{"expr":{"type":"string","description":"JavaScript expression returning the value. Available variables - results (object with all previous step results), flow_input (flow inputs), flow_input.iter (in loops)"},"type":{"type":"string","enum":["javascript"]}},"required":["expr","type"]},"AiTransform":{"type":"object","description":"Value resolved by the AI runtime for this input. The AI engine decides how to satisfy the parameter.","properties":{"type":{"type":"string","enum":["ai"]}},"required":["type"]},"AIProviderKind":{"type":"string","description":"Supported AI provider types","enum":["openai","azure_openai","azure_foundry","anthropic","mistral","deepseek","googleai","groq","openrouter","togetherai","customai","aws_bedrock","typesafe","cloudflare"]},"ProviderConfig":{"type":"object","description":"Complete AI provider configuration with resource reference and model selection","properties":{"kind":{"$ref":"#/components/schemas/AIProviderKind"},"resource":{"type":"string","description":"Resource reference in format '$res:{resource_path}' pointing to provider credentials"},"model":{"type":"string","description":"Model identifier (e.g., 'gpt-4', 'claude-3-opus-20240229', 'gemini-pro')"},"reasoning_effort":{"type":"string","description":"Provider-native reasoning effort token (e.g. 'low', 'high', 'none') for models that support extended thinking. Optional; unset leaves the provider default."}},"required":["kind","resource","model"]},"StaticProviderTransform":{"type":"object","description":"Static provider configuration passed directly to the AI agent","properties":{"value":{"$ref":"#/components/schemas/ProviderConfig"},"type":{"type":"string","enum":["static"]}},"required":["type","value"]},"ProviderTransform":{"description":"Provider configuration - can be static (ProviderConfig), JavaScript expression, or AI-determined","oneOf":[{"$ref":"#/components/schemas/StaticProviderTransform"},{"$ref":"#/components/schemas/JavascriptTransform"},{"$ref":"#/components/schemas/AiTransform"}],"discriminator":{"propertyName":"type","mapping":{"static":"#/components/schemas/StaticProviderTransform","javascript":"#/components/schemas/JavascriptTransform","ai":"#/components/schemas/AiTransform"}}},"MemoryOff":{"type":"object","description":"No conversation memory/context","properties":{"kind":{"type":"string","enum":["off"]}},"required":["kind"]},"MemoryWindow":{"type":"object","description":"Keeps the most recent messages of the memory named by the run's memory id (or the step's\\n\`memory_id\`). Without a memory id the agent runs without memory.\\n","properties":{"kind":{"type":"string","enum":["window"]},"context_length":{"type":"integer","description":"Number of most recent messages to load and store. 0 turns memory off."}},"required":["kind","context_length"]},"MemoryAuto":{"type":"object","deprecated":true,"description":"Deprecated, still read as it was written: the run's memory id, else the \`memory_id\` here.\\nThe step's own \`memory_id\` is not read while this kind is set; switch the kind to \`window\`\\nto use it. Without a \`context_length\`, or with 0, it is \`off\` and reads \`previous_messages\`.\\n","properties":{"kind":{"type":"string","enum":["auto"]},"context_length":{"type":"integer","description":"Maximum number of messages to retain in context"},"memory_id":{"type":"string","description":"Identifier for persistent memory across agent invocations"}},"required":["kind"]},"MemoryCompaction":{"type":"object","description":"Keeps the whole memory named by the run's memory id (or the step's \`memory_id\`), replacing\\nits older part with a summary as the conversation approaches the model's context window.\\nWithout a memory id the agent runs without memory, and compaction bounds the run's own loop.\\n","properties":{"kind":{"type":"string","enum":["compaction"]},"context_window":{"type":"integer","description":"Overrides the context window looked up from the model, in tokens. Only a model\\nWindmill does not know needs one; those fall back to 128000.\\n"}},"required":["kind"]},"MemoryMessage":{"type":"object","description":"A single message in conversation history","properties":{"role":{"type":"string","enum":["user","assistant","system"]},"content":{"type":"string"}},"required":["role","content"]},"MemoryManual":{"type":"object","deprecated":true,"description":"Deprecated, still read as it was written. Move the step to \`off\` with \`previous_messages\` instead.","properties":{"kind":{"type":"string","enum":["manual"]},"messages":{"type":"array","items":{"$ref":"#/components/schemas/MemoryMessage"}}},"required":["kind","messages"]},"MemoryConfig":{"description":"Managed memory, stored by Windmill and replayed with each request. The memory is named by a memory id, see \`memory_id\`. While it is off, a step can supply its history in \`previous_messages\`.","oneOf":[{"$ref":"#/components/schemas/MemoryOff"},{"$ref":"#/components/schemas/MemoryWindow"},{"$ref":"#/components/schemas/MemoryCompaction"},{"$ref":"#/components/schemas/MemoryAuto"},{"$ref":"#/components/schemas/MemoryManual"}],"discriminator":{"propertyName":"kind","mapping":{"off":"#/components/schemas/MemoryOff","window":"#/components/schemas/MemoryWindow","compaction":"#/components/schemas/MemoryCompaction","auto":"#/components/schemas/MemoryAuto","manual":"#/components/schemas/MemoryManual"}}},"StaticMemoryTransform":{"type":"object","description":"Static memory configuration passed directly to the AI agent","properties":{"value":{"$ref":"#/components/schemas/MemoryConfig"},"type":{"type":"string","enum":["static"]}},"required":["type","value"]},"MemoryTransform":{"description":"Memory configuration - can be static (MemoryConfig), JavaScript expression, or AI-determined","oneOf":[{"$ref":"#/components/schemas/StaticMemoryTransform"},{"$ref":"#/components/schemas/JavascriptTransform"},{"$ref":"#/components/schemas/AiTransform"}],"discriminator":{"propertyName":"type","mapping":{"static":"#/components/schemas/StaticMemoryTransform","javascript":"#/components/schemas/JavascriptTransform","ai":"#/components/schemas/AiTransform"}}},"FlowModuleValue":{"description":"The actual implementation of a flow step. Can be a script (inline or referenced), subflow, loop, branch, or special module type","oneOf":[{"$ref":"#/components/schemas/RawScript"},{"$ref":"#/components/schemas/PathScript"},{"$ref":"#/components/schemas/PathFlow"},{"$ref":"#/components/schemas/ForloopFlow"},{"$ref":"#/components/schemas/WhileloopFlow"},{"$ref":"#/components/schemas/BranchOne"},{"$ref":"#/components/schemas/BranchAll"},{"$ref":"#/components/schemas/Identity"},{"$ref":"#/components/schemas/AiAgent"},{"$ref":"#/components/schemas/AiDecision"}],"discriminator":{"propertyName":"type","mapping":{"rawscript":"#/components/schemas/RawScript","script":"#/components/schemas/PathScript","flow":"#/components/schemas/PathFlow","forloopflow":"#/components/schemas/ForloopFlow","whileloopflow":"#/components/schemas/WhileloopFlow","branchone":"#/components/schemas/BranchOne","branchall":"#/components/schemas/BranchAll","identity":"#/components/schemas/Identity","aiagent":"#/components/schemas/AiAgent","aidecision":"#/components/schemas/AiDecision"}}},"RawScript":{"type":"object","description":"Inline script with code defined directly in the flow. Use 'bun' as default language if unspecified. The script receives arguments from input_transforms","properties":{"input_transforms":{"type":"object","description":"Map of parameter names to their values (static or JavaScript expressions). These become the script's input arguments","additionalProperties":{"$ref":"#/components/schemas/InputTransform"}},"content":{"type":"string","description":"The script source code. 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Use this when calling a previously saved script instead of writing inline code","properties":{"input_transforms":{"type":"object","description":"Map of parameter names to their values (static or JavaScript expressions). These become the script's input arguments","additionalProperties":{"$ref":"#/components/schemas/InputTransform"}},"path":{"type":"string","description":"Path to the script in the workspace (e.g., 'f/scripts/send_email')"},"hash":{"type":"string","description":"Optional specific version hash of the script to use"},"type":{"type":"string","enum":["script"]},"tag_override":{"type":"string","description":"Override the script's default worker group tag"},"is_trigger":{"type":"boolean","description":"If true, this script is a trigger that can start the flow"}},"required":["type","path","input_transforms"]},"PathFlow":{"type":"object","description":"Reference to an existing flow by path. Use this to call another flow as a subflow","properties":{"input_transforms":{"type":"object","description":"Map of parameter names to their values (static or JavaScript expressions). These become the subflow's input arguments","additionalProperties":{"$ref":"#/components/schemas/InputTransform"}},"path":{"type":"string","description":"Path to the flow in the workspace (e.g., 'f/flows/process_user')"},"type":{"type":"string","enum":["flow"]}},"required":["type","path","input_transforms"]},"ForloopFlow":{"type":"object","description":"Executes nested modules in a loop over an iterator. Inside the loop, use 'flow_input.iter.value' to access the current iteration value, and 'flow_input.iter.index' for the index. Supports parallel execution for better performance on I/O-bound operations","properties":{"modules":{"type":"array","description":"Steps to execute for each iteration. These can reference the iteration value via 'flow_input.iter.value'","items":{"$ref":"#/components/schemas/FlowModule"}},"iterator":{"description":"JavaScript expression that returns an array to iterate over. Can reference 'results.step_id' or 'flow_input'","$ref":"#/components/schemas/InputTransform"},"skip_failures":{"type":"boolean","description":"If true, iteration failures don't stop the loop. Failed iterations return null"},"type":{"type":"string","enum":["forloopflow"]},"parallel":{"type":"boolean","description":"If true, iterations run concurrently (faster for I/O-bound operations). Use with parallelism to control concurrency"},"parallelism":{"description":"Maximum number of concurrent iterations when parallel=true. Limits resource usage. 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Failed iterations return null"},"type":{"type":"string","enum":["whileloopflow"]},"parallel":{"type":"boolean","description":"If true, iterations run concurrently (use with caution in while loops)"},"parallelism":{"description":"Maximum number of concurrent iterations when parallel=true","$ref":"#/components/schemas/InputTransform"},"squash":{"type":"boolean"}},"required":["modules","skip_failures","type"]},"BranchOne":{"type":"object","description":"Conditional branching where only the first matching branch executes. Branches are evaluated in order, and the first one with a true expression runs. If no branches match, the default branch executes","properties":{"branches":{"type":"array","description":"Array of branches to evaluate in order. The first branch with expr evaluating to true executes","items":{"type":"object","properties":{"summary":{"type":"string","description":"Short description of this branch condition"},"expr":{"type":"string","description":"JavaScript expression that returns boolean. Can use 'results.step_id' or 'flow_input'. First true expr wins"},"modules":{"type":"array","description":"Steps to execute if this branch's expr is true","items":{"$ref":"#/components/schemas/FlowModule"}}},"required":["modules","expr"]}},"default":{"type":"array","description":"Steps to execute if no branch expressions match","items":{"$ref":"#/components/schemas/FlowModule"}},"type":{"type":"string","enum":["branchone"]}},"required":["branches","default","type"]},"BranchAll":{"type":"object","description":"Parallel branching where all branches execute simultaneously. Unlike BranchOne, all branches run regardless of conditions. Useful for executing independent tasks concurrently","properties":{"branches":{"type":"array","description":"Array of branches that all execute (either in parallel or sequentially)","items":{"type":"object","properties":{"summary":{"type":"string","description":"Short description of this branch's purpose"},"skip_failure":{"type":"boolean","description":"If true, failure in this branch doesn't fail the entire flow"},"modules":{"type":"array","description":"Steps to execute in this branch","items":{"$ref":"#/components/schemas/FlowModule"}}},"required":["modules"]}},"type":{"type":"string","enum":["branchall"]},"parallel":{"type":"boolean","description":"If true, all branches execute concurrently. If false, they execute sequentially"}},"required":["branches","type"]},"AgentTool":{"type":"object","description":"A tool available to an AI agent. Can be a flow module or an external MCP (Model Context Protocol) tool","properties":{"id":{"type":"string","description":"Unique identifier for this tool. Cannot contain spaces - use underscores instead (e.g., 'get_user_data' not 'get user data')"},"summary":{"type":"string","description":"The name the AI agent calls this tool by, not a human label. On a flowmodule tool it must match ^[a-zA-Z0-9_]+$ - letters, numbers and underscores only (e.g. 'search_documentation', not 'Search documentation') - and always be set; on an mcp, websearch or question tool it is a plain label. Put the human-readable explanation in 'description'."},"description":{"type":"string","description":"Free-text description of the tool given to the AI to decide when and how to call it. Overrides the description auto-derived from the underlying script."},"job_token_scopes":{"type":"array","nullable":true,"items":{"type":"string"},"description":"Scopes the token of this tool's jobs is restricted to, on top of the agent step's own restriction: a tool can only narrow it."},"requires_approval":{"type":"boolean","description":"Flowmodule and mcp tools only. Each call waits for a person to approve or reject it from the flow's run page or chat, without the agent holding a worker. Calls in the same turn that do not require approval run right away. A rejected call, or one nobody answers within 30 minutes, is reported to the AI as not run."},"value":{"$ref":"#/components/schemas/ToolValue"}},"required":["id","value"]},"ToolValue":{"description":"The implementation of a tool. Can be a flow module (script/flow) or an MCP tool reference","oneOf":[{"$ref":"#/components/schemas/FlowModuleTool"},{"$ref":"#/components/schemas/McpToolValue"},{"$ref":"#/components/schemas/WebsearchToolValue"},{"$ref":"#/components/schemas/QuestionToolValue"}],"discriminator":{"propertyName":"tool_type","mapping":{"flowmodule":"#/components/schemas/FlowModuleTool","mcp":"#/components/schemas/McpToolValue","websearch":"#/components/schemas/WebsearchToolValue","question":"#/components/schemas/QuestionToolValue"}}},"FlowModuleTool":{"description":"A tool implemented as a flow module (script, flow, etc.). The AI can call this like any other flow module","allOf":[{"type":"object","properties":{"tool_type":{"type":"string","enum":["flowmodule"]}},"required":["tool_type"]},{"$ref":"#/components/schemas/FlowModuleValue"}]},"WebsearchToolValue":{"type":"object","description":"A tool implemented as a websearch tool. The AI can call this like any other websearch tool","properties":{"tool_type":{"type":"string","enum":["websearch"]}},"required":["tool_type"]},"QuestionToolValue":{"type":"object","description":"Built-in tool the AI calls as ask_question: the agent stops, releasing its worker, until someone answers from the flow's run page or chat or the question times out, then resumes with the answer as the tool result.","properties":{"tool_type":{"type":"string","enum":["question"]},"timeout":{"type":"integer","description":"Seconds to wait for an answer before the question is reported to the AI as timed out. Defaults to 1800."}},"required":["tool_type"]},"McpToolValue":{"type":"object","description":"Reference to an external MCP (Model Context Protocol) tool. The AI can call tools from MCP servers","properties":{"tool_type":{"type":"string","enum":["mcp"]},"resource_path":{"type":"string","description":"Path to the MCP resource/server configuration"},"include_tools":{"type":"array","description":"Whitelist of specific tools to include from this MCP server","items":{"type":"string"}},"exclude_tools":{"type":"array","description":"Blacklist of tools to exclude from this MCP server","items":{"type":"string"}}},"required":["tool_type","resource_path"]},"AiAgent":{"type":"object","description":"AI agent step that can use tools to accomplish tasks. The agent receives inputs and can call any of its configured tools to complete the task","properties":{"input_transforms":{"type":"object","description":"Input parameters for the AI agent mapped to their values","properties":{"provider":{"$ref":"#/components/schemas/ProviderTransform"},"output_type":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"Output format type.\\nValid values: 'text' (default) - plain text response, 'image' - image generation\\n"},"user_message":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"The user's prompt/message to the AI agent. Supports variable interpolation with\\nflow.input syntax. Required unless memory is off and \`previous_messages\` supplies\\nthe prompt; image output always needs it.\\n"},"system_prompt":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"System instructions that guide the AI's behavior, persona, and response style. Optional."},"streaming":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"Boolean. If true, stream the AI response incrementally.\\nStreaming events include: token_delta, reasoning_token_delta, tool_call, tool_call_arguments, tool_execution, tool_result\\n"},"memory":{"$ref":"#/components/schemas/MemoryTransform"},"memory_id":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"String. Names the memory this step reads and writes, overriding the memory id the run\\nwas started with (the chat conversation, an app chat session or the \`memory_id\` run\\nparameter). Leave unset to use the run's memory id. A fixed value shares one memory\\nacross every run; an expression such as \`flow_input.customer_id\` keeps one memory per\\nkey. When it evaluates to an empty value the agent runs without memory. Read only\\nwhile \`memory\` is \`window\` or \`compaction\`: it is ignored when memory is off, and an\\nolder \`auto\` or \`manual\` memory reads neither history input.\\n"},"previous_messages":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"Array of MemoryMessage. History supplied by the flow, sent between the system prompt\\nand the user message. Read only while \`memory\` is off or absent: managed memory\\nignores it, and an older \`auto\` or \`manual\` memory reads neither history input.\\n"},"output_schema":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"JSON Schema object defining structured output format. Used when you need the AI to return data in a specific shape.\\nSupports standard JSON Schema properties: type, properties, required, items, enum, pattern, minLength, maxLength, minimum, maximum, etc.\\nExample: { type: 'object', properties: { name: { type: 'string' }, age: { type: 'integer' } }, required: ['name'] }\\n"},"user_attachments":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"Array of file references (images or PDFs) for the AI agent.\\nFormat: Array<{ bucket: string, key: string }> - S3 object references\\nExample: [{ bucket: 'my-bucket', key: 'documents/report.pdf' }]\\n"},"enabled_tools":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"Array of strings naming which of the tools configured in \`tools\` the agent may call\\nthis run. Leaving it unset carries every one of them; an empty array carries none.\\nA tool is named as the model is shown it. An entry the model is shown nothing of is\\nnamed by what identifies it instead: an MCP server by its resource path, carrying\\nevery tool it exposes (which of them stays that entry's include_tools/exclude_tools),\\nand a websearch entry by the reserved name '__wm_web_search', whatever summary it carries\\n(no tool may take that name).\\nExample: ['get_user', 'u/admin/github_mcp', '__wm_web_search']\\n"},"max_completion_tokens":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"Integer. Maximum number of tokens the AI will generate in its response.\\nRange: 1 to 4,294,967,295. Typical values: 256-4096 for most use cases.\\n"},"temperature":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"Float. Controls randomness/creativity of responses.\\nRange: 0.0 to 2.0 (provider-dependent)\\n- 0.0 = deterministic, focused responses\\n- 0.7 = balanced (common default)\\n- 1.0+ = more creative/random\\n"},"max_iterations":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"Number. Limits how many times the agent can loop through reasoning and tool use.\\nRange: 1-1000.\\n"},"model":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"String. Only on a step linked to a saved agent (see \`agent\`): replaces the model\\nsaved on the agent for this step's runs, on the agent's own provider resource. An\\nempty value keeps the saved model. Set it to an expression such as\\n\`flow_input.model\` to choose the model per run.\\n"},"reasoning_effort":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"String. Only on a step linked to a saved agent (see \`agent\`): replaces the reasoning\\neffort saved on the agent for this step's runs, as a provider-native token (e.g.\\n'low', 'high', 'none'). An empty value sends no effort, so the model runs at its\\ndefault. Leave the input out to keep the saved effort, which holds only while the\\nstep runs the saved model. A step that is not linked sets both inside \`provider\`.\\n"}}},"tools":{"type":"array","description":"Array of tools the agent can use. The agent decides which tools to call based on the task","items":{"$ref":"#/components/schemas/AgentTool"}},"type":{"type":"string","enum":["aiagent"]},"tag":{"type":"string","description":"Worker group tag for execution routing. If not set, the AI agent step runs on the flow's tag (default \`flow\`)"},"omit_output_from_conversation":{"type":"boolean","default":false,"description":"If true, this AI agent step does not persist its assistant or tool messages to the flow conversation when chat mode is enabled."},"agent":{"type":"string","description":"Path of a reusable \`ai_agent\` resource (hybrid linking). When set, the agent brain\\nconfig (provider/model/system prompt/etc.) and tool set are resolved at runtime from\\nthat resource; the module's input_transforms then only carry the flow-local inputs\\n(user_message, user_attachments, enabled_tools and the history inputs memory_id and previous_messages)\\nand, optionally, the \`model\` and \`reasoning_effort\` overrides of what the agent saved.\\n"},"tool_inputs":{"type":"object","description":"Host-local wiring for an agent's tool inputs, keyed by tool id then input key. Binds the\\nreferenced agent's tools to this flow's context (flow_input/results) without mutating the\\nshared resource; overlaid onto the tools' input_transforms at runtime \\u2014 including when\\n\`agent\` is unset, since a step forked for editing keeps these overrides until it is saved\\nback or unlinked.\\n","additionalProperties":{"type":"object","additionalProperties":{"$ref":"#/components/schemas/InputTransform"}}},"parallel":{"type":"boolean","description":"If true, the agent can execute multiple tool calls in parallel"}},"required":["type","input_transforms"]},"AiDecision":{"type":"object","description":"AI decision step: one call to a decision model (TypeSafe's Jev, Cloudflare's\\nJev-compatible Clef, or OpenAI's Decisions API) that answers typed questions about a\\nstate with calibrated probabilities, instead of generating text.\\nPrefer it over an AI agent to classify, route, score or check something: it is fast,\\ncheap and its answers are structured. Its result is { output: { <question name>: answer },\\nmodel, usage }, so a later step reads e.g. results.<id>.output.intent.choice. To route on\\nthe answers, follow it with a branchone whose branch exprs read\\nresults.<id>.output.<question>.choice. Usable as an AI agent tool, where the calling agent\\nsupplies the state.\\n","properties":{"input_transforms":{"type":"object","description":"Input parameters for the decision mapped to their values","properties":{"provider":{"$ref":"#/components/schemas/ProviderTransform"},"state":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"What the questions are asked about: a string, an object or an array of strings.\\nAn object with descriptive keys holding only what the questions need works best.\\nExample: { message: flow_input.message, plan: results.a.plan }\\n"},"questions":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"Object mapping each question name to { type, instructions, criteria }, where type is:\\n- 'choice': criteria maps each option to its description (up to 255); the answer\\n has choice, probabilities and confidence\\n- 'score': criteria is an ordered array of 2 to 10 level descriptions; the answer\\n has score, legend, probabilities and confidence\\n- 'noul': yes/no, criteria optionally { true, false } descriptions; the answer has\\n noul, the probability of yes (0 to 1)\\nExample: { intent: { type: 'choice', instructions: 'What does the customer want?',\\ncriteria: { refund: 'Money back', bug: 'Something is broken' } } }\\n"}},"required":["provider","state","questions"]},"type":{"type":"string","enum":["aidecision"]},"tag":{"type":"string","description":"Worker group tag for execution routing. If not set, the step runs on the flow's tag (default \`flow\`)"}},"required":["type","input_transforms"]},"Identity":{"type":"object","description":"Pass-through module that returns its input unchanged. Useful for flow structure or as a placeholder","properties":{"type":{"type":"string","enum":["identity"]},"flow":{"type":"boolean","description":"If true, marks this as a flow identity (special handling)"}},"required":["type"]},"FlowStatus":{"type":"object","properties":{"step":{"type":"integer"},"modules":{"type":"array","items":{"$ref":"#/components/schemas/FlowStatusModule"}},"user_states":{"additionalProperties":true},"preprocessor_module":{"allOf":[{"$ref":"#/components/schemas/FlowStatusModule"}]},"failure_module":{"allOf":[{"$ref":"#/components/schemas/FlowStatusModule"},{"type":"object","properties":{"parent_module":{"type":"string"}}}]},"retry":{"type":"object","properties":{"fail_count":{"type":"integer"},"failed_jobs":{"type":"array","items":{"type":"string","format":"uuid"}}}}},"required":["step","modules","failure_module"]},"FlowStatusModule":{"type":"object","properties":{"type":{"type":"string","enum":["WaitingForPriorSteps","WaitingForEvents","WaitingForExecutor","InProgress","Success","Failure"]},"id":{"type":"string"},"job":{"type":"string","format":"uuid"},"count":{"type":"integer"},"progress":{"type":"integer"},"iterator":{"type":"object","properties":{"index":{"type":"integer"},"itered":{"type":"array","items":{}},"itered_len":{"type":"integer"},"args":{}}},"flow_jobs":{"type":"array","items":{"type":"string"}},"flow_jobs_success":{"type":"array","items":{"type":"boolean"}},"flow_jobs_duration":{"type":"object","properties":{"started_at":{"type":"array","items":{"type":"string"}},"duration_ms":{"type":"array","items":{"type":"integer"}}}},"branch_chosen":{"type":"object","properties":{"type":{"type":"string","enum":["branch","default"]},"branch":{"type":"integer"}},"required":["type"]},"branchall":{"type":"object","properties":{"branch":{"type":"integer"},"len":{"type":"integer"}},"required":["branch","len"]},"approvers":{"type":"array","items":{"type":"object","properties":{"resume_id":{"type":"integer"},"approver":{"type":"string"}},"required":["resume_id","approver"]}},"failed_retries":{"type":"array","items":{"type":"string","format":"uuid"}},"skipped":{"type":"boolean"},"agent_actions":{"type":"array","items":{"type":"object","oneOf":[{"type":"object","properties":{"job_id":{"type":"string","format":"uuid"},"function_name":{"type":"string"},"type":{"type":"string","enum":["tool_call"]},"module_id":{"type":"string"}},"required":["job_id","function_name","type","module_id"]},{"type":"object","properties":{"call_id":{"type":"string","format":"uuid"},"function_name":{"type":"string"},"resource_path":{"type":"string"},"type":{"type":"string","enum":["mcp_tool_call"]},"arguments":{"type":"object"}},"required":["call_id","function_name","resource_path","type"]},{"type":"object","properties":{"type":{"type":"string","enum":["web_search"]}},"required":["type"]},{"type":"object","properties":{"type":{"type":"string","enum":["approval"]},"call_id":{"type":"string"},"calls":{"type":"array","items":{"type":"object","properties":{"function_name":{"type":"string"},"arguments":{}},"required":["function_name","arguments"]}},"expires_at":{"type":"string","format":"date-time"}},"required":["type","call_id","calls","expires_at"]},{"type":"object","properties":{"type":{"type":"string","enum":["question"]},"call_id":{"type":"string"},"question":{"type":"string"},"choices":{"type":"array","items":{"type":"string"},"description":"answers the model proposes; a free-text answer is always possible"},"multi_select":{"type":"boolean","description":"whether several choices can be picked together"},"expires_at":{"type":"string","format":"date-time"}},"required":["type","call_id","question","expires_at"]},{"type":"object","properties":{"type":{"type":"string","enum":["message"]}},"required":["content","type"]}]}},"agent_actions_success":{"type":"array","items":{"type":"boolean"}}},"required":["type"]}} `, "raw-app": `--- name: raw-app diff --git a/docs/reusable-ai-agents.md b/docs/reusable-ai-agents.md index 5eac5e964c..3d3163470f 100644 --- a/docs/reusable-ai-agents.md +++ b/docs/reusable-ai-agents.md @@ -156,6 +156,51 @@ older editor baked into `memory` stays a fallback behind the run's id until the *Keep as memory id* or *Use the run's memory id*. In a chat flow it is dropped on save, since the conversation id always took precedence there. +## Approval and questions + +Two things park the agent rather than run: a call of a tool with `requires_approval` (flow module +and MCP tools), and a call of the built-in `question` tool, which the model sees as `ask_question`. +Both live in `windmill-worker/src/ai/pause.rs`. + +- **Park.** In a turn that calls such tools, every other call runs right away. The calls that + require approval are gathered into one request, answered together; a question is its own request, + so a turn that also asks for approval has its question refused, as is a second question. The + worker stores the conversation, actions, usage, accumulated stream, next iteration and the + waiting calls in `ai_agent_checkpoint`, then parks the agent's own queue row with + `suspend_wac_parent`: `suspend = 1`, `suspend_until` at the timeout (1800s for an approval, the + question tool's `timeout` otherwise). The job is not completed, its worker is free, and the flow + stays on the step. +- **Answer.** `resume_suspended` with the agent job's id already treats a self-suspended job like a + WAC approval: it inserts the `resume_job` row and decrements, or zeroes on a rejection, the + agent's own `suspend`. The run page offers the form from the pending `approval` or `question` + agent action (Approve/Reject with the calls and their arguments, or the question with its + `choices` and a text answer, sent as a list when `multi_select`), and so does a chat flow's chat, + on the waiting call's tool card while the turn's top-level agent step waits (it polls the turn's + flow job only when a top-level agent step has such a tool or links a saved agent, read off the + flow rather than the stream, which a non-streaming agent leaves empty: the card is then added at + the end of the turn). Both send that request's `call_id` in the payload. There are no signed resume URLs, Slack or Teams messages, + approval page or approver conditions for it: whoever can answer a suspended step without + conditions can answer it. +- **Resume.** The suspended pull takes the row back and `run_agent` finds the checkpoint. In one + transaction it zeroes `suspend`, so `resume_suspended` refuses answers while the agent runs, and + reads the unread `resume_job` rows. The first one naming the parked request (or naming none) + answers it; one naming an earlier request, from a page left open, is read and ignored, and the + agent parks again for the time left. Approved calls then run as any call would; rejected ones, + and those still unanswered at the timeout, are answered as not run, with the approver's comment. + A call whose tool left the roster while parked is answered as no longer available. The agent + then skips memory and the prompt and continues the loop. The step's stream continues at the + offset the first segment reached. Resolution is live here too: a linked agent edited while + parked resumes with its new definition. +- **Cleanup.** The checkpoint row stays while the job is queued, so a job restarted after its + worker died resumes from it, and reads the same answer again: approved calls that ran before + the worker died run again. The monitor deletes rows whose job left the queue; the table has no + foreign key, since one would lock `v2_job_queue` on every write. +- **Limits.** A nested agent tool is never offered the question tool or a tool that requires + approval: it writes no flow status, and its parent holds a worker while it runs. The banner at the + top of the run page shows only a request from a top-level step, as does the chat; one from a step + inside a loop or branch is answered from its graph node. The chat transcript of a chat flow + records neither the request nor its answer. + ## Drafts The agent editor edits the resource through a **per-user resource draft** (`draft` table, diff --git a/frontend/src/lib/components/AgentApprovalRequest.svelte b/frontend/src/lib/components/AgentApprovalRequest.svelte new file mode 100644 index 0000000000..04f7f69430 --- /dev/null +++ b/frontend/src/lib/components/AgentApprovalRequest.svelte @@ -0,0 +1,122 @@ +<script lang="ts"> + import { answerAgentRequest, type AgentRequest } from './agentRequest' + import { Button } from './common' + import TextInput from './text_input/TextInput.svelte' + import ApprovalActions from './approvals/ApprovalActions.svelte' + import { displayDate } from '$lib/utils' + + interface Props { + /** The workspace the job ran in, never the navigation workspace. */ + workspaceId: string + /** The agent step's own job: it is the one parked, so it is the one answered. */ + agentJobId: string + /** Its call id goes with the answer, so a page left open on an earlier request cannot + * answer the one the agent waits on now. */ + request: AgentRequest + /** Whether the request still waits for an answer. */ + pending: boolean + } + + let { workspaceId, agentJobId, request, pending }: Props = $props() + + let text = $state('') + let picked = $state<string[]>([]) + let answered = $state<boolean | undefined>(undefined) + + const choices = $derived(request.type === 'question' ? (request.choices ?? []) : []) + const multiSelect = $derived(request.type === 'question' && !!request.multi_select) + // A typed answer joins the picked choices when several can be picked, and replaces the pick + // otherwise. + const answer = $derived.by((): string | string[] => { + const typed = text.trim() + if (multiSelect) return typed ? [...picked, typed] : picked + return typed || picked[0] || '' + }) + + function pick(choice: string) { + if (multiSelect) { + picked = picked.includes(choice) ? picked.filter((c) => c !== choice) : [...picked, choice] + } else { + picked = [choice] + text = '' + } + } + + async function onAnswer(approved: boolean) { + const value = request.type === 'question' ? answer : text.trim() + await answerAgentRequest(workspaceId, { agentJobId, action: request }, approved, value) + answered = approved + } +</script> + +<div class="flex flex-col gap-2 w-full text-xs"> + {#if request.type === 'question'} + <div class="text-emphasis font-semibold">The agent {pending ? 'asks' : 'asked'} a question</div> + <div class="text-primary whitespace-pre-wrap">{request.question}</div> + {:else} + <div class="text-emphasis font-semibold"> + The agent {pending ? 'asks' : 'asked'} to run {request.calls.length === 1 + ? 'this call' + : 'these calls'} + </div> + {#each request.calls as call, i (i)} + <div class="flex flex-col gap-1"> + <span class="font-mono text-primary">{call.function_name}</span> + <pre + class="text-2xs bg-surface-secondary rounded-md p-2 overflow-auto max-h-40 whitespace-pre-wrap break-all" + >{JSON.stringify(call.arguments, null, 2)}</pre + > + </div> + {/each} + {/if} + {#if answered !== undefined} + <div class="text-secondary"> + {#if request.type === 'question'} + {answered ? 'Answered' : 'Declined'}, the agent resumes shortly. + {:else} + {answered ? 'Approved' : 'Rejected'}, the agent resumes shortly. + {/if} + </div> + {:else if pending} + <div class="text-hint">Expires {displayDate(request.expires_at)}</div> + {#if choices.length > 0} + <div class="flex flex-wrap gap-2"> + {#each choices as choice (choice)} + <Button + variant="default" + unifiedSize="sm" + selected={picked.includes(choice)} + onClick={() => pick(choice)} + > + {choice} + </Button> + {/each} + </div> + {/if} + <TextInput + bind:value={text} + inputProps={{ + placeholder: + request.type === 'question' + ? choices.length > 0 + ? 'Or answer in your own words' + : 'Your answer' + : 'Reason for the agent, if you reject (optional)', + oninput: () => { + if (!multiSelect) picked = [] + } + }} + size="sm" + /> + {#if request.type === 'question'} + <ApprovalActions + approveLabel="Send answer" + rejectTitle="Decline to answer" + approveDisabled={answer.length === 0} + {onAnswer} + /> + {:else} + <ApprovalActions approveLabel="Approve" rejectTitle="Reject" {onAnswer} /> + {/if} + {/if} +</div> diff --git a/frontend/src/lib/components/FlowStatusViewerInner.svelte b/frontend/src/lib/components/FlowStatusViewerInner.svelte index 489d6c4769..dea1be12f9 100644 --- a/frontend/src/lib/components/FlowStatusViewerInner.svelte +++ b/frontend/src/lib/components/FlowStatusViewerInner.svelte @@ -48,11 +48,14 @@ AI_TOOL_MESSAGE_PREFIX, AI_MCP_TOOL_CALL_PREFIX, AI_WEBSEARCH_PREFIX, + AI_APPROVAL_PREFIX, + AI_QUESTION_PREFIX, getAgentActionStateId, getToolCallId } from './graph/renderers/nodes/AIToolNode.svelte' import JobAssetsViewer from './assets/JobAssetsViewer.svelte' import McpToolCallDetails from './McpToolCallDetails.svelte' + import AgentApprovalRequest from './AgentApprovalRequest.svelte' import GfmMarkdown from './GfmMarkdown.svelte' import JobOtelTraces from './JobOtelTraces.svelte' import JobDetailHeader from './runs/JobDetailHeader.svelte' @@ -780,6 +783,10 @@ job_id: action.job_id, type: success != undefined ? (success ? 'Success' : 'Failure') : 'InProgress' }) + } else if (action.type == 'approval' || action.type == 'question') { + setModuleState(stateId, { + type: success != undefined ? (success ? 'Success' : 'Failure') : 'WaitingForEvents' + }) } else if (action.type == 'mcp_tool_call') { setModuleState(stateId, { type: success != undefined ? (success ? 'Success' : 'Failure') : 'InProgress' @@ -2127,6 +2134,25 @@ {/if} {:else if selectedNode?.startsWith(AI_WEBSEARCH_PREFIX)} <Alert type="info" title="Web search was used in this step" /> + {:else if selectedNode?.startsWith(AI_APPROVAL_PREFIX) || selectedNode?.startsWith(AI_QUESTION_PREFIX)} + {@const [, agentModuleId, actionIndex] = selectedNode.split('-')} + {@const agentNode = localModuleStates?.[agentModuleId]} + {@const approvalIndex = parseInt(actionIndex)} + {@const approval = agentNode?.agent_actions?.[approvalIndex]} + {#if (approval?.type === 'approval' || approval?.type === 'question') && agentNode?.job_id} + <div class="p-4"> + <!-- One form per request: its answered state must not carry over to the next. --> + {#key `${agentNode.job_id}-${approval.call_id}`} + <AgentApprovalRequest + workspaceId={job.workspace_id ?? ''} + agentJobId={agentNode.job_id} + request={approval} + pending={job.type === 'QueuedJob' && + agentNode?.agent_actions_success?.[approvalIndex] === undefined} + /> + {/key} + </div> + {/if} {:else if selectedNode} {@const node = localModuleStates[selectedNode]} {#if selectedNode == 'end'} diff --git a/frontend/src/lib/components/FlowStatusWaitingForEvents.svelte b/frontend/src/lib/components/FlowStatusWaitingForEvents.svelte index 5774e5a2ef..df10e64692 100644 --- a/frontend/src/lib/components/FlowStatusWaitingForEvents.svelte +++ b/frontend/src/lib/components/FlowStatusWaitingForEvents.svelte @@ -1,11 +1,10 @@ <script lang="ts"> import { mergeSchema } from '$lib/common' import { type Job, JobService } from '$lib/gen' - import { sendUserToast } from '$lib/toast' - import { ExternalLink, X } from 'lucide-svelte' + import { ExternalLink } from 'lucide-svelte' import DisplayResult from './DisplayResult.svelte' import Tooltip from './Tooltip.svelte' - import { Button } from './common' + import ApprovalActions from './approvals/ApprovalActions.svelte' import SchemaForm from './SchemaForm.svelte' import { twMerge } from 'tailwind-merge' import { untrack } from 'svelte' @@ -54,7 +53,6 @@ default_payload = args approvalPageUrl = job_result?.['approvalPage'] - actionTaken = false hide_cancel = job?.raw_flow?.modules?.[approvalStep]?.suspend?.hide_cancel ?? false schema = mergeSchema( job?.raw_flow?.modules?.[approvalStep]?.suspend?.resume_form?.schema ?? {}, @@ -62,31 +60,21 @@ ) } - let loading = $state(false) - let actionTaken = $state(false) async function continu(approve: boolean) { if (!workspaceId) { - sendUserToast('Cannot resume: the job has no workspace', true) - return - } - loading = true - try { - await JobService.resumeSuspended({ - workspace: workspaceId, - jobId: job?.id ?? '', - requestBody: { - payload: approve ? (default_payload as any) : undefined, - approved: approve - } - }) - actionTaken = true - onAction?.(approve) - } catch (e: any) { - sendUserToast(e?.body ?? e?.message ?? 'Failed', true) - } finally { - loading = false + throw new Error('Cannot resume: the job has no workspace') } + await JobService.resumeSuspended({ + workspace: workspaceId, + jobId: job?.id ?? '', + requestBody: { + payload: approve ? (default_payload as any) : undefined, + approved: approve + } + }) + onAction?.(approve) } + let approvalStep = $derived((job?.flow_status?.step ?? 1) - 1) // Everything this panel shows (description, resume form enums, approval page) is // fetched from the suspended job — a recording carries none of it — and Resume / @@ -108,34 +96,16 @@ <DisplayResult {workspaceId} noControls result={description} language={job?.language} /> <div class="mt-2"></div> {/if} - <div> - <div class={twMerge('flex gap-2 items-center', light ? 'flex-col' : 'flex-row ')}> - {#if !hide_cancel} - <div> - <Button - title="Cancel the step" - iconOnly - startIcon={{ icon: X }} - variant="default" - disabled={loading || actionTaken} - destructive - unifiedSize="md" - on:click={() => continu(false)} - /> - </div> - {/if} - <div> - <Button - variant="accent" - onClick={() => continu(true)} - disabled={loading || actionTaken} - unifiedSize="md" - > - Resume - <Tooltip class="text-white">Resume or approve this suspended step</Tooltip> - </Button> - </div> - + <!-- A new approval step gets usable buttons again. --> + {#key job?.flow_status?.modules?.[approvalStep]?.job} + <ApprovalActions + approveLabel="Resume" + approveTooltip="Resume or approve this suspended step" + rejectTitle="Cancel the step" + hideReject={hide_cancel} + {light} + onAnswer={continu} + > {#if approvalPageUrl} <a href={approvalPageUrl} @@ -161,7 +131,7 @@ variable </Tooltip> {/if} - </div> - </div> + </ApprovalActions> + {/key} </div> {/if} diff --git a/frontend/src/lib/components/JobStatus.svelte b/frontend/src/lib/components/JobStatus.svelte index 5e79303371..30fd5f0a27 100644 --- a/frontend/src/lib/components/JobStatus.svelte +++ b/frontend/src/lib/components/JobStatus.svelte @@ -2,6 +2,7 @@ import { displayDate, msToReadableTime } from '$lib/utils' import type { CompletedJob, QueuedJob } from '$lib/gen' import Badge from './common/badge/Badge.svelte' + import { isSuspended } from './agentRequest' import { forLater } from '$lib/forLater' import { Circle } from 'lucide-svelte' import NoWorkerWithTagWarning from './runs/NoWorkerWithTagWarning.svelte' @@ -58,7 +59,7 @@ /> {/if} </Badge> -{:else if job && 'running' in job && job.running && job.suspend} +{:else if job && 'running' in job && job.running && isSuspended(job)} <div> <Badge {large} color="violet"> Suspended diff --git a/frontend/src/lib/components/agentRequest.ts b/frontend/src/lib/components/agentRequest.ts new file mode 100644 index 0000000000..879cec08a3 --- /dev/null +++ b/frontend/src/lib/components/agentRequest.ts @@ -0,0 +1,60 @@ +import { JobService, type FlowStatus, type FlowStatusModule } from '$lib/gen' + +export type AgentRequest = Extract< + NonNullable<FlowStatusModule['agent_actions']>[number], + { type: 'approval' | 'question' } +> + +/** The approval or question an agent step's actions end on, while nobody has answered it. */ +export function waitingRequest( + mod: Pick<FlowStatusModule, 'agent_actions' | 'agent_actions_success'> +) { + const actions = mod.agent_actions + const last = actions?.[actions.length - 1] + if ( + !last || + (last.type !== 'approval' && last.type !== 'question') || + mod.agent_actions_success?.[actions!.length - 1] !== undefined + ) { + return undefined + } + return last +} + +/** The approval or question a flow's current agent step is parked on: the step stays in + * progress while its own job waits. */ +export function pendingAgentApproval(job: { flow_status?: FlowStatus } | undefined) { + const mod = job?.flow_status?.modules?.[job?.flow_status?.step] + if (mod?.type !== 'InProgress' || !mod.job) return undefined + const action = waitingRequest(mod) + return action && { agentJobId: mod.job, action } +} + +/** Suspended, as the run's badge and icon say: an approval step, or an agent waiting on a person. */ +export function isSuspended(job: { suspend?: number; flow_status?: FlowStatus }) { + return !!job.suspend || !!pendingAgentApproval(job) +} + +export type PendingAgentRequest = NonNullable<ReturnType<typeof pendingAgentApproval>> + +/** `answer` is the question's answer, a list when several choices were picked, or the reason given + * with a rejection. Its call id goes with the answer, so a page left open on an earlier request + * cannot answer the one waiting now. */ +export async function answerAgentRequest( + workspace: string, + { agentJobId, action }: PendingAgentRequest, + approved: boolean, + answer?: string | string[] +) { + await JobService.resumeSuspended({ + workspace, + jobId: agentJobId, + requestBody: { + approved, + payload: { + call_id: action.call_id, + ...(answer?.length ? { [action.type === 'question' ? 'answer' : 'comment']: answer } : {}) + } + } + }) +} diff --git a/frontend/src/lib/components/agentTrace.ts b/frontend/src/lib/components/agentTrace.ts index 392e8b00c9..013d4a65ac 100644 --- a/frontend/src/lib/components/agentTrace.ts +++ b/frontend/src/lib/components/agentTrace.ts @@ -90,6 +90,15 @@ export function buildAgentTrace(messages: AgentMessage[]): AgentTraceEntry[] { entries.push({ kind: 'search' }) continue } + if (action?.type === 'question') { + entries.push({ + kind: 'tool', + name: 'Ask a question', + args: message.tool_call_id ? argsByCallId.get(message.tool_call_id) : undefined, + result: contentText(message.content) + }) + continue + } // Every message this run produced is tagged, including the agent narrating // its next move and its final answer. Untagged ones are the prompt, the // question, or a previous turn replayed out of memory — history loses its diff --git a/frontend/src/lib/components/approvals/ApprovalActions.svelte b/frontend/src/lib/components/approvals/ApprovalActions.svelte new file mode 100644 index 0000000000..f55d6a5e49 --- /dev/null +++ b/frontend/src/lib/components/approvals/ApprovalActions.svelte @@ -0,0 +1,76 @@ +<script lang="ts"> + import type { Snippet } from 'svelte' + import { X } from 'lucide-svelte' + import { twMerge } from 'tailwind-merge' + import { sendUserToast } from '$lib/toast' + import { Button } from '../common' + import Tooltip from '../Tooltip.svelte' + + interface Props { + approveLabel: string + approveTooltip?: string + rejectTitle: string + hideReject?: boolean + /** Stacks the buttons, for the graph's popover. */ + light?: boolean + /** Holds the approve button back, e.g. until an answer is typed. */ + approveDisabled?: boolean + /** Throws to report a failure; the buttons stay usable then. */ + onAnswer: (approved: boolean) => Promise<void> + /** Shown after the buttons, on the same row. */ + children?: Snippet + } + + let { + approveLabel, + approveTooltip, + rejectTitle, + hideReject = false, + light = false, + approveDisabled = false, + onAnswer, + children + }: Props = $props() + + let loading = $state(false) + let answered = $state(false) + + async function answer(approved: boolean) { + loading = true + try { + await onAnswer(approved) + answered = true + } catch (e: any) { + sendUserToast(e?.body ?? e?.message ?? 'Failed', true) + } finally { + loading = false + } + } +</script> + +<div class={twMerge('flex gap-2 items-center', light ? 'flex-col' : 'flex-row')}> + {#if !hideReject} + <Button + title={rejectTitle} + iconOnly + startIcon={{ icon: X }} + variant="default" + disabled={loading || answered} + destructive + unifiedSize="md" + onClick={() => answer(false)} + /> + {/if} + <Button + variant="accent" + onClick={() => answer(true)} + disabled={loading || answered || approveDisabled} + unifiedSize="md" + > + {approveLabel} + {#if approveTooltip} + <Tooltip class="text-white">{approveTooltip}</Tooltip> + {/if} + </Button> + {@render children?.()} +</div> diff --git a/frontend/src/lib/components/copilot/chat/flow/openFlow.json b/frontend/src/lib/components/copilot/chat/flow/openFlow.json index c9d3322bdb..fc9911edf2 100644 --- a/frontend/src/lib/components/copilot/chat/flow/openFlow.json +++ b/frontend/src/lib/components/copilot/chat/flow/openFlow.json @@ -1 +1 @@ -{"openapi":"3.0.3","info":{"version":"1.830.0","title":"OpenFlow Spec","contact":{"name":"Ruben Fiszel","email":"ruben@windmill.dev","url":"https://windmill.dev"},"license":{"name":"Apache 2.0","url":"https://www.apache.org/licenses/LICENSE-2.0.html"}},"paths":{},"externalDocs":{"description":"documentation portal","url":"https://windmill.dev"},"components":{"schemas":{"OpenFlow":{"type":"object","description":"Top-level flow definition containing metadata, configuration, and the flow structure","properties":{"summary":{"type":"string","description":"Short description of what this flow does"},"description":{"type":"string","description":"Detailed documentation for this flow"},"value":{"$ref":"#/components/schemas/FlowValue"},"schema":{"type":"object","description":"JSON Schema for flow inputs. Use this to define input parameters, their types, defaults, and validation. For resource inputs, set type to 'object' and format to 'resource-<type>' (e.g., 'resource-stripe')"},"on_behalf_of_email":{"type":"string","description":"Address of the account the flow runs on behalf of. Derived from on_behalf_of on read; accepted on write, where it is resolved to the account it names."},"on_behalf_of":{"type":"string","description":"The flow runs with the permissions of this identity: u/{username}, g/{group}, or a bare email when the username is itself email-shaped. The only stored half of the identity; on_behalf_of_email is derived from it. Omit it when writing and it is resolved from that address instead."}},"required":["summary","value"]},"FlowValue":{"type":"object","description":"The flow structure containing modules and optional preprocessor/failure handlers","properties":{"modules":{"type":"array","description":"Array of steps that execute in sequence. Each step can be a script, subflow, loop, or branch","items":{"$ref":"#/components/schemas/FlowModule"}},"failure_module":{"description":"Special module that executes when the flow fails. Receives error object with message, name, stack, and step_id. Must have id 'failure'. Only supports script/rawscript types","$ref":"#/components/schemas/FlowModule"},"preprocessor_module":{"description":"Special module that runs before the first step on external triggers. Must have id 'preprocessor'. Only supports script/rawscript types. Cannot reference other step results","$ref":"#/components/schemas/FlowModule"},"same_worker":{"type":"boolean","description":"If true, all steps run on the same worker for better performance"},"preserve_step_tags":{"type":"boolean","description":"If true and the flow runs on a custom worker tag, steps that declare their own non-empty tag run on it instead of inheriting the flow tag. Steps without their own tag still inherit the flow tag."},"concurrent_limit":{"type":"number","description":"Maximum number of concurrent executions of this flow"},"concurrency_key":{"type":"string","description":"Expression to group concurrent executions (e.g., by user ID)"},"concurrency_time_window_s":{"type":"number","description":"Time window in seconds for concurrent_limit"},"debounce_delay_s":{"type":"integer","description":"Delay in seconds to debounce flow executions"},"debounce_key":{"type":"string","description":"Expression to group debounced executions"},"debounce_args_to_accumulate":{"type":"array","description":"Arguments to accumulate across debounced executions","items":{"type":"string"}},"max_total_debouncing_time":{"type":"integer","description":"Maximum total time in seconds that a job can be debounced"},"max_total_debounces_amount":{"type":"integer","description":"Maximum number of times a job can be debounced"},"skip_expr":{"type":"string","description":"JavaScript expression to conditionally skip the entire flow"},"cache_ttl":{"type":"number","description":"Cache duration in seconds for flow results"},"cache_ignore_s3_path":{"type":"boolean"},"delete_after_secs":{"type":"integer","description":"If set, delete the flow job's args, result and logs after this many seconds following job completion"},"flow_env":{"type":"object","description":"Environment variables available to all steps. Values can be strings, JSON values, or special references: '$var:path' (workspace variable) or '$res:path' (resource).","additionalProperties":{}},"priority":{"type":"number","description":"Execution priority (higher numbers run first)"},"early_return":{"type":"string","description":"Id of the step whose result a sync webhook returns as soon as that step completes, while the rest of the flow keeps running. When the step does not run, or fails while the flow has a failure module, the flow's final result is returned instead."},"chat_input_enabled":{"type":"boolean","description":"Whether this flow accepts chat-style input"},"notes":{"type":"array","description":"Sticky notes attached to the flow","items":{"$ref":"#/components/schemas/FlowNote"}},"groups":{"type":"array","description":"Semantic groups of modules for organizational purposes","items":{"$ref":"#/components/schemas/FlowGroup"}}},"required":["modules"]},"Retry":{"type":"object","description":"Retry configuration for failed module executions","properties":{"constant":{"type":"object","description":"Retry with constant delay between attempts","properties":{"attempts":{"type":"integer","description":"Number of retry attempts"},"seconds":{"type":"integer","description":"Seconds to wait between retries"}}},"exponential":{"type":"object","description":"Retry with exponential backoff: the n-th retry waits multiplier × seconds^n","properties":{"attempts":{"type":"integer","description":"Number of retry attempts"},"multiplier":{"type":"integer","description":"Multiplier for exponential backoff"},"seconds":{"type":"integer","minimum":1,"description":"Base of the exponential (seconds); the n-th retry waits multiplier × seconds^n, where n counts constant retries too"},"random_factor":{"type":"integer","minimum":0,"maximum":100,"description":"Random jitter percentage (0-100) to avoid thundering herd"}}},"retry_if":{"$ref":"#/components/schemas/RetryIf"}}},"FlowNote":{"type":"object","description":"A sticky note attached to a flow for documentation and annotation","properties":{"id":{"type":"string","description":"Unique identifier for the note"},"text":{"type":"string","description":"Content of the note"},"position":{"type":"object","description":"Position of the note in the flow editor","properties":{"x":{"type":"number","description":"X coordinate"},"y":{"type":"number","description":"Y coordinate"}},"required":["x","y"]},"size":{"type":"object","description":"Size of the note in the flow editor","properties":{"width":{"type":"number","description":"Width in pixels"},"height":{"type":"number","description":"Height in pixels"}},"required":["width","height"]},"color":{"type":"string","description":"Color of the note, one of: yellow, blue, green, purple, pink, orange, red, cyan, lime, gray. Any other value renders unstyled."},"type":{"type":"string","enum":["free","group"],"description":"Type of note - 'free' for standalone notes. 'group' notes are deprecated; segment a flow with FlowValue.groups instead."},"locked":{"type":"boolean","default":false,"description":"Whether the note is locked and cannot be edited or moved"},"contained_node_ids":{"type":"array","items":{"type":"string"},"description":"For group notes, the IDs of nodes contained within this group"}},"required":["id","text","color","type"]},"FlowGroup":{"type":"object","description":"A semantic group of flow modules for organizational purposes. Does not affect execution — modules remain in their original position in the flow. Groups provide naming and collapsibility in the editor. Members are computed dynamically from all nodes on paths between start_id and end_id.","properties":{"summary":{"type":"string","description":"Display name for this group"},"note":{"type":"string","description":"Markdown note shown below the group header"},"autocollapse":{"type":"boolean","default":false,"description":"If true, this group is collapsed by default in the flow editor. UI hint only."},"start_id":{"type":"string","description":"ID of the first flow module in this group (topological entry point)"},"end_id":{"type":"string","description":"ID of the last flow module in this group (topological exit point)"},"color":{"type":"string","description":"Color for the group in the flow editor, one of: yellow, blue, green, purple, pink, orange, red, cyan, lime, gray. Omit it to let the editor pick one."}},"required":["start_id","end_id"]},"RetryIf":{"type":"object","description":"Conditional retry based on error or result","properties":{"expr":{"type":"string","description":"JavaScript expression that returns true to retry. Has access to 'result' and 'error' variables"}},"required":["expr"]},"StopAfterIf":{"type":"object","description":"Early termination condition for a module","properties":{"skip_if_stopped":{"type":"boolean","description":"If true, following steps are skipped when this condition triggers"},"expr":{"type":"string","description":"JavaScript expression evaluated after the module runs. Can use 'result' (step's result) or 'flow_input'. Return true to stop"},"error_message":{"type":"string","nullable":true,"description":"Custom error message when stopping with an error. Mutually exclusive with skip_if_stopped. If set to a non-empty string, the flow stops with this error. If empty string, a default error message is used. If null or omitted, no error is raised."},"error_include_result":{"type":"boolean","description":"When stopping with an error (error_message set), embed the stopping step's own result inside the raised error object (as error.result) instead of discarding it. The top-level result stays { error }. Defaults to false."}},"required":["expr"]},"FlowModule":{"type":"object","description":"A single step in a flow. Can be a script, subflow, loop, or branch","properties":{"id":{"type":"string","description":"Unique identifier for this step. Used to reference results via 'results.step_id'. Must be a valid identifier (alphanumeric, underscore, hyphen)"},"value":{"$ref":"#/components/schemas/FlowModuleValue"},"stop_after_if":{"description":"Early termination condition evaluated after this step completes","$ref":"#/components/schemas/StopAfterIf"},"stop_after_all_iters_if":{"description":"For loops only - early termination condition evaluated after all iterations complete","$ref":"#/components/schemas/StopAfterIf"},"skip_if":{"type":"object","description":"Conditionally skip this step based on previous results or flow inputs","properties":{"expr":{"type":"string","description":"JavaScript expression that returns true to skip. Can use 'flow_input' or 'results.<step_id>'"}},"required":["expr"]},"sleep":{"description":"Delay before executing this step (in seconds or as expression)","$ref":"#/components/schemas/InputTransform"},"cache_ttl":{"type":"number","description":"Cache duration in seconds for this step's results"},"cache_ignore_s3_path":{"type":"boolean"},"timeout":{"description":"Maximum execution time in seconds (static value or expression)","$ref":"#/components/schemas/InputTransform"},"delete_after_secs":{"type":"integer","description":"If set, delete the step's args, result and logs after this many seconds following job completion"},"summary":{"type":"string","description":"Short description of what this step does"},"mock":{"type":"object","description":"Mock configuration for testing without executing the actual step","properties":{"enabled":{"type":"boolean","description":"If true, return mock value instead of executing"},"return_value":{"description":"Value to return when mocked"}}},"suspend":{"type":"object","description":"Configuration for approval/resume steps that wait for user input","properties":{"required_events":{"type":"integer","description":"Number of approvals required before continuing"},"timeout":{"type":"integer","description":"Timeout in seconds before auto-continuing or canceling"},"resume_form":{"type":"object","description":"Form schema for collecting input when resuming","properties":{"schema":{"type":"object","description":"JSON Schema for the resume form"}}},"user_auth_required":{"type":"boolean","description":"If true, only authenticated users can approve"},"user_groups_required":{"description":"Expression or list of groups that can approve","$ref":"#/components/schemas/InputTransform"},"self_approval_disabled":{"type":"boolean","description":"If true, the user who started the flow cannot approve"},"hide_cancel":{"type":"boolean","description":"If true, hide the cancel button on the approval form"},"continue_on_disapprove_timeout":{"type":"boolean","description":"If true, continue flow on timeout instead of canceling"},"skin":{"type":"string","enum":["detailed","minimal"],"description":"How the approval request is presented, on the approval page and in Slack/Teams approval messages. 'detailed' (used when unset) shows the flow details (arguments, graph, approvers); 'minimal' shows only the request: the step description, form and approve/reject actions"}}},"priority":{"type":"number","description":"Execution priority for this step (higher numbers run first)"},"continue_on_error":{"type":"boolean","description":"If true, flow continues even if this step fails"},"job_token_scopes":{"type":"array","nullable":true,"items":{"type":"string"},"description":"Scopes the token of this step's jobs is restricted to (domain:action[:resource], e.g. oidc:write), on top of the flow's own restriction: a step can only narrow it. Applies to everything the step runs (loop and branch bodies, AI agent tools)."},"retry":{"description":"Retry configuration if this step fails","$ref":"#/components/schemas/Retry"},"debouncing":{"description":"Debounce configuration for this step (EE only)","type":"object","properties":{"debounce_delay_s":{"type":"integer","description":"Delay in seconds to debounce this step's executions across flow runs"},"debounce_key":{"type":"string","description":"Expression to group debounced executions. Supports $workspace and $args[name]. Default: $workspace/flow/<flow_path>-<step_id>"},"debounce_args_to_accumulate":{"type":"array","description":"Array-type arguments to accumulate across debounced executions","items":{"type":"string"}},"max_total_debouncing_time":{"type":"integer","description":"Maximum total time in seconds before forced execution"},"max_total_debounces_amount":{"type":"integer","description":"Maximum number of debounces before forced execution"}}}},"required":["value","id"]},"InputTransform":{"description":"Maps input parameters for a step. Can be a static value or a JavaScript expression that references previous results or flow inputs","oneOf":[{"$ref":"#/components/schemas/StaticTransform"},{"$ref":"#/components/schemas/JavascriptTransform"},{"$ref":"#/components/schemas/AiTransform"}],"discriminator":{"propertyName":"type"}},"StaticTransform":{"type":"object","description":"Static value passed directly to the step. Use for hardcoded values or resource references like '$res:path/to/resource'","properties":{"value":{"description":"The static value. For resources, use format '$res:path/to/resource'"},"type":{"type":"string","enum":["static"]}},"required":["type"]},"JavascriptTransform":{"type":"object","description":"JavaScript expression evaluated at runtime. Can reference previous step results via 'results.step_id' or flow inputs via 'flow_input.property'. Inside for loops, use 'flow_input.iter.value' for the current iteration value (in while loops it equals 'flow_input.iter.index')","properties":{"expr":{"type":"string","description":"JavaScript expression returning the value. Available variables - results (object with all previous step results), flow_input (flow inputs), flow_input.iter (in loops)"},"type":{"type":"string","enum":["javascript"]}},"required":["expr","type"]},"AiTransform":{"type":"object","description":"Value resolved by the AI runtime for this input. The AI engine decides how to satisfy the parameter.","properties":{"type":{"type":"string","enum":["ai"]}},"required":["type"]},"AIProviderKind":{"type":"string","description":"Supported AI provider types","enum":["openai","azure_openai","azure_foundry","anthropic","mistral","deepseek","googleai","groq","openrouter","togetherai","customai","aws_bedrock","typesafe","cloudflare"]},"ProviderConfig":{"type":"object","description":"Complete AI provider configuration with resource reference and model selection","properties":{"kind":{"$ref":"#/components/schemas/AIProviderKind"},"resource":{"type":"string","description":"Resource reference in format '$res:{resource_path}' pointing to provider credentials"},"model":{"type":"string","description":"Model identifier (e.g., 'gpt-4', 'claude-3-opus-20240229', 'gemini-pro')"},"reasoning_effort":{"type":"string","description":"Provider-native reasoning effort token (e.g. 'low', 'high', 'none') for models that support extended thinking. Optional; unset leaves the provider default."}},"required":["kind","resource","model"]},"StaticProviderTransform":{"type":"object","description":"Static provider configuration passed directly to the AI agent","properties":{"value":{"$ref":"#/components/schemas/ProviderConfig"},"type":{"type":"string","enum":["static"]}},"required":["type","value"]},"ProviderTransform":{"description":"Provider configuration - can be static (ProviderConfig), JavaScript expression, or AI-determined","oneOf":[{"$ref":"#/components/schemas/StaticProviderTransform"},{"$ref":"#/components/schemas/JavascriptTransform"},{"$ref":"#/components/schemas/AiTransform"}],"discriminator":{"propertyName":"type"}},"MemoryOff":{"type":"object","description":"No conversation memory/context","properties":{"kind":{"type":"string","enum":["off"]}},"required":["kind"]},"MemoryWindow":{"type":"object","description":"Keeps the most recent messages of the memory named by the run's memory id (or the step's\n`memory_id`). Without a memory id the agent runs without memory.\n","properties":{"kind":{"type":"string","enum":["window"]},"context_length":{"type":"integer","description":"Number of most recent messages to load and store. 0 turns memory off."}},"required":["kind","context_length"]},"MemoryAuto":{"type":"object","deprecated":true,"description":"Deprecated, still read as it was written: the run's memory id, else the `memory_id` here.\nThe step's own `memory_id` is not read while this kind is set; switch the kind to `window`\nto use it. Without a `context_length`, or with 0, it is `off` and reads `previous_messages`.\n","properties":{"kind":{"type":"string","enum":["auto"]},"context_length":{"type":"integer","description":"Maximum number of messages to retain in context"},"memory_id":{"type":"string","description":"Identifier for persistent memory across agent invocations"}},"required":["kind"]},"MemoryCompaction":{"type":"object","description":"Keeps the whole memory named by the run's memory id (or the step's `memory_id`), replacing\nits older part with a summary as the conversation approaches the model's context window.\nWithout a memory id the agent runs without memory, and compaction bounds the run's own loop.\n","properties":{"kind":{"type":"string","enum":["compaction"]},"context_window":{"type":"integer","description":"Overrides the context window looked up from the model, in tokens. Only a model\nWindmill does not know needs one; those fall back to 128000.\n"}},"required":["kind"]},"MemoryMessage":{"type":"object","description":"A single message in conversation history","properties":{"role":{"type":"string","enum":["user","assistant","system"]},"content":{"type":"string"}},"required":["role","content"]},"MemoryManual":{"type":"object","deprecated":true,"description":"Deprecated, still read as it was written. Move the step to `off` with `previous_messages` instead.","properties":{"kind":{"type":"string","enum":["manual"]},"messages":{"type":"array","items":{"$ref":"#/components/schemas/MemoryMessage"}}},"required":["kind","messages"]},"MemoryConfig":{"description":"Managed memory, stored by Windmill and replayed with each request. The memory is named by a memory id, see `memory_id`. While it is off, a step can supply its history in `previous_messages`.","oneOf":[{"$ref":"#/components/schemas/MemoryOff"},{"$ref":"#/components/schemas/MemoryWindow"},{"$ref":"#/components/schemas/MemoryCompaction"},{"$ref":"#/components/schemas/MemoryAuto"},{"$ref":"#/components/schemas/MemoryManual"}],"discriminator":{"propertyName":"kind"}},"StaticMemoryTransform":{"type":"object","description":"Static memory configuration passed directly to the AI agent","properties":{"value":{"$ref":"#/components/schemas/MemoryConfig"},"type":{"type":"string","enum":["static"]}},"required":["type","value"]},"MemoryTransform":{"description":"Memory configuration - can be static (MemoryConfig), JavaScript expression, or AI-determined","oneOf":[{"$ref":"#/components/schemas/StaticMemoryTransform"},{"$ref":"#/components/schemas/JavascriptTransform"},{"$ref":"#/components/schemas/AiTransform"}],"discriminator":{"propertyName":"type"}},"FlowModuleValue":{"description":"The actual implementation of a flow step. Can be a script (inline or referenced), subflow, loop, branch, or special module type","oneOf":[{"$ref":"#/components/schemas/RawScript"},{"$ref":"#/components/schemas/PathScript"},{"$ref":"#/components/schemas/PathFlow"},{"$ref":"#/components/schemas/ForloopFlow"},{"$ref":"#/components/schemas/WhileloopFlow"},{"$ref":"#/components/schemas/BranchOne"},{"$ref":"#/components/schemas/BranchAll"},{"$ref":"#/components/schemas/Identity"},{"$ref":"#/components/schemas/AiAgent"},{"$ref":"#/components/schemas/AiDecision"}],"discriminator":{"propertyName":"type"}},"RawScript":{"type":"object","description":"Inline script with code defined directly in the flow. Use 'bun' as default language if unspecified. The script receives arguments from input_transforms","properties":{"input_transforms":{"type":"object","description":"Map of parameter names to their values (static or JavaScript expressions). These become the script's input arguments","additionalProperties":{"$ref":"#/components/schemas/InputTransform"}},"content":{"type":"string","description":"The script source code. Should export a 'main' function"},"language":{"type":"string","description":"Programming language for this script","enum":["deno","bun","bunnative","python3","go","bash","powershell","postgresql","mysql","bigquery","snowflake","mssql","oracledb","graphql","nativets","php","rust","ansible","csharp","nu","java","ruby","rlang","duckdb"]},"path":{"type":"string","description":"Optional path for saving this script"},"lock":{"type":"string","description":"Lock file content for dependencies"},"type":{"type":"string","enum":["rawscript"]},"tag":{"type":"string","description":"Worker group tag for execution routing"},"concurrent_limit":{"type":"number","description":"Maximum concurrent executions of this script"},"concurrency_time_window_s":{"type":"number","description":"Time window for concurrent_limit"},"custom_concurrency_key":{"type":"string","description":"Custom key for grouping concurrent executions"},"is_trigger":{"type":"boolean","description":"If true, this script is a trigger that can start the flow"},"assets":{"type":"array","description":"External resources this script accesses (S3 objects, resources, etc.)","items":{"type":"object","required":["path","kind"],"properties":{"path":{"type":"string","description":"Path to the asset"},"kind":{"type":"string","description":"Type of asset","enum":["s3object","resource","ducklake","datatable","volume","dbt"]},"access_type":{"type":"string","nullable":true,"description":"Access level for this asset","enum":["r","w","rw",null]},"alt_access_type":{"type":"string","nullable":true,"description":"Alternative access level","enum":["r","w","rw",null]}}}}},"required":["type","content","language","input_transforms"]},"PathScript":{"type":"object","description":"Reference to an existing script by path. Use this when calling a previously saved script instead of writing inline code","properties":{"input_transforms":{"type":"object","description":"Map of parameter names to their values (static or JavaScript expressions). These become the script's input arguments","additionalProperties":{"$ref":"#/components/schemas/InputTransform"}},"path":{"type":"string","description":"Path to the script in the workspace (e.g., 'f/scripts/send_email')"},"hash":{"type":"string","description":"Optional specific version hash of the script to use"},"type":{"type":"string","enum":["script"]},"tag_override":{"type":"string","description":"Override the script's default worker group tag"},"is_trigger":{"type":"boolean","description":"If true, this script is a trigger that can start the flow"}},"required":["type","path","input_transforms"]},"PathFlow":{"type":"object","description":"Reference to an existing flow by path. Use this to call another flow as a subflow","properties":{"input_transforms":{"type":"object","description":"Map of parameter names to their values (static or JavaScript expressions). These become the subflow's input arguments","additionalProperties":{"$ref":"#/components/schemas/InputTransform"}},"path":{"type":"string","description":"Path to the flow in the workspace (e.g., 'f/flows/process_user')"},"type":{"type":"string","enum":["flow"]}},"required":["type","path","input_transforms"]},"ForloopFlow":{"type":"object","description":"Executes nested modules in a loop over an iterator. Inside the loop, use 'flow_input.iter.value' to access the current iteration value, and 'flow_input.iter.index' for the index. Supports parallel execution for better performance on I/O-bound operations","properties":{"modules":{"type":"array","description":"Steps to execute for each iteration. These can reference the iteration value via 'flow_input.iter.value'","items":{"$ref":"#/components/schemas/FlowModule"}},"iterator":{"description":"JavaScript expression that returns an array to iterate over. Can reference 'results.step_id' or 'flow_input'","$ref":"#/components/schemas/InputTransform"},"skip_failures":{"type":"boolean","description":"If true, iteration failures don't stop the loop. Failed iterations return null"},"type":{"type":"string","enum":["forloopflow"]},"parallel":{"type":"boolean","description":"If true, iterations run concurrently (faster for I/O-bound operations). Use with parallelism to control concurrency"},"parallelism":{"description":"Maximum number of concurrent iterations when parallel=true. Limits resource usage. Can be static number or expression","$ref":"#/components/schemas/InputTransform"},"squash":{"type":"boolean"}},"required":["modules","iterator","skip_failures","type"]},"WhileloopFlow":{"type":"object","description":"Executes nested modules repeatedly until stopped. The implicit iterator is the iteration counter, so 'flow_input.iter.value' equals 'flow_input.iter.index' (0, 1, 2, ...) and never carries state. To carry state across iterations, a step reads its own previous-iteration result via 'results.<its_own_id>' with a first-iteration fallback - the loop's stop_after_if must then be on that inner step (a plain single-step body with stop_after_if on the loop module does not resolve 'results' across iterations and never terminates); plain counters can instead be derived from 'flow_input.iter.index', which works in every configuration. stop_after_if is evaluated after each iteration - on the loop module 'result' is the last iteration's result","properties":{"modules":{"type":"array","description":"Steps to execute in each iteration","items":{"$ref":"#/components/schemas/FlowModule"}},"skip_failures":{"type":"boolean","description":"If true, iteration failures don't stop the loop. Failed iterations return null"},"type":{"type":"string","enum":["whileloopflow"]},"parallel":{"type":"boolean","description":"If true, iterations run concurrently (use with caution in while loops)"},"parallelism":{"description":"Maximum number of concurrent iterations when parallel=true","$ref":"#/components/schemas/InputTransform"},"squash":{"type":"boolean"}},"required":["modules","skip_failures","type"]},"BranchOne":{"type":"object","description":"Conditional branching where only the first matching branch executes. Branches are evaluated in order, and the first one with a true expression runs. If no branches match, the default branch executes","properties":{"branches":{"type":"array","description":"Array of branches to evaluate in order. The first branch with expr evaluating to true executes","items":{"type":"object","properties":{"summary":{"type":"string","description":"Short description of this branch condition"},"expr":{"type":"string","description":"JavaScript expression that returns boolean. Can use 'results.step_id' or 'flow_input'. First true expr wins"},"modules":{"type":"array","description":"Steps to execute if this branch's expr is true","items":{"$ref":"#/components/schemas/FlowModule"}}},"required":["modules","expr"]}},"default":{"type":"array","description":"Steps to execute if no branch expressions match","items":{"$ref":"#/components/schemas/FlowModule"}},"type":{"type":"string","enum":["branchone"]}},"required":["branches","default","type"]},"BranchAll":{"type":"object","description":"Parallel branching where all branches execute simultaneously. Unlike BranchOne, all branches run regardless of conditions. Useful for executing independent tasks concurrently","properties":{"branches":{"type":"array","description":"Array of branches that all execute (either in parallel or sequentially)","items":{"type":"object","properties":{"summary":{"type":"string","description":"Short description of this branch's purpose"},"skip_failure":{"type":"boolean","description":"If true, failure in this branch doesn't fail the entire flow"},"modules":{"type":"array","description":"Steps to execute in this branch","items":{"$ref":"#/components/schemas/FlowModule"}}},"required":["modules"]}},"type":{"type":"string","enum":["branchall"]},"parallel":{"type":"boolean","description":"If true, all branches execute concurrently. If false, they execute sequentially"}},"required":["branches","type"]},"AgentTool":{"type":"object","description":"A tool available to an AI agent. Can be a flow module or an external MCP (Model Context Protocol) tool","properties":{"id":{"type":"string","description":"Unique identifier for this tool. Cannot contain spaces - use underscores instead (e.g., 'get_user_data' not 'get user data')"},"summary":{"type":"string","description":"The name the AI agent calls this tool by, not a human label. On a flowmodule tool it must match ^[a-zA-Z0-9_]+$ - letters, numbers and underscores only (e.g. 'search_documentation', not 'Search documentation') - and always be set; on an mcp or websearch tool it is a plain label. Put the human-readable explanation in 'description'."},"description":{"type":"string","description":"Free-text description of the tool given to the AI to decide when and how to call it. Overrides the description auto-derived from the underlying script."},"job_token_scopes":{"type":"array","nullable":true,"items":{"type":"string"},"description":"Scopes the token of this tool's jobs is restricted to, on top of the agent step's own restriction: a tool can only narrow it."},"value":{"$ref":"#/components/schemas/ToolValue"}},"required":["id","value"]},"ToolValue":{"description":"The implementation of a tool. Can be a flow module (script/flow) or an MCP tool reference","oneOf":[{"$ref":"#/components/schemas/FlowModuleTool"},{"$ref":"#/components/schemas/McpToolValue"},{"$ref":"#/components/schemas/WebsearchToolValue"}]},"FlowModuleTool":{"description":"A tool implemented as a flow module (script, flow, etc.). The AI can call this like any other flow module","allOf":[{"type":"object","properties":{"tool_type":{"type":"string","enum":["flowmodule"]}},"required":["tool_type"]},{"$ref":"#/components/schemas/FlowModuleValue"}]},"WebsearchToolValue":{"type":"object","description":"A tool implemented as a websearch tool. The AI can call this like any other websearch tool","properties":{"tool_type":{"type":"string","enum":["websearch"]}},"required":["tool_type"]},"McpToolValue":{"type":"object","description":"Reference to an external MCP (Model Context Protocol) tool. The AI can call tools from MCP servers","properties":{"tool_type":{"type":"string","enum":["mcp"]},"resource_path":{"type":"string","description":"Path to the MCP resource/server configuration"},"include_tools":{"type":"array","description":"Whitelist of specific tools to include from this MCP server","items":{"type":"string"}},"exclude_tools":{"type":"array","description":"Blacklist of tools to exclude from this MCP server","items":{"type":"string"}}},"required":["tool_type","resource_path"]},"AiAgent":{"type":"object","description":"AI agent step that can use tools to accomplish tasks. The agent receives inputs and can call any of its configured tools to complete the task","properties":{"input_transforms":{"type":"object","description":"Input parameters for the AI agent mapped to their values","properties":{"provider":{"$ref":"#/components/schemas/ProviderTransform"},"output_type":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"Output format type.\nValid values: 'text' (default) - plain text response, 'image' - image generation\n"},"user_message":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"The user's prompt/message to the AI agent. Supports variable interpolation with\nflow.input syntax. Required unless memory is off and `previous_messages` supplies\nthe prompt; image output always needs it.\n"},"system_prompt":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"System instructions that guide the AI's behavior, persona, and response style. Optional."},"streaming":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"Boolean. If true, stream the AI response incrementally.\nStreaming events include: token_delta, reasoning_token_delta, tool_call, tool_call_arguments, tool_execution, tool_result\n"},"memory":{"$ref":"#/components/schemas/MemoryTransform"},"memory_id":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"String. Names the memory this step reads and writes, overriding the memory id the run\nwas started with (the chat conversation, an app chat session or the `memory_id` run\nparameter). Leave unset to use the run's memory id. A fixed value shares one memory\nacross every run; an expression such as `flow_input.customer_id` keeps one memory per\nkey. When it evaluates to an empty value the agent runs without memory. Read only\nwhile `memory` is `window` or `compaction`: it is ignored when memory is off, and an\nolder `auto` or `manual` memory reads neither history input.\n"},"previous_messages":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"Array of MemoryMessage. History supplied by the flow, sent between the system prompt\nand the user message. Read only while `memory` is off or absent: managed memory\nignores it, and an older `auto` or `manual` memory reads neither history input.\n"},"output_schema":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"JSON Schema object defining structured output format. Used when you need the AI to return data in a specific shape.\nSupports standard JSON Schema properties: type, properties, required, items, enum, pattern, minLength, maxLength, minimum, maximum, etc.\nExample: { type: 'object', properties: { name: { type: 'string' }, age: { type: 'integer' } }, required: ['name'] }\n"},"user_attachments":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"Array of file references (images or PDFs) for the AI agent.\nFormat: Array<{ bucket: string, key: string }> - S3 object references\nExample: [{ bucket: 'my-bucket', key: 'documents/report.pdf' }]\n"},"enabled_tools":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"Array of strings naming which of the tools configured in `tools` the agent may call\nthis run. Leaving it unset carries every one of them; an empty array carries none.\nA tool is named as the model is shown it. An entry the model is shown nothing of is\nnamed by what identifies it instead: an MCP server by its resource path, carrying\nevery tool it exposes (which of them stays that entry's include_tools/exclude_tools),\nand a websearch entry by the reserved name '__wm_web_search', whatever summary it carries\n(no tool may take that name).\nExample: ['get_user', 'u/admin/github_mcp', '__wm_web_search']\n"},"max_completion_tokens":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"Integer. Maximum number of tokens the AI will generate in its response.\nRange: 1 to 4,294,967,295. Typical values: 256-4096 for most use cases.\n"},"temperature":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"Float. Controls randomness/creativity of responses.\nRange: 0.0 to 2.0 (provider-dependent)\n- 0.0 = deterministic, focused responses\n- 0.7 = balanced (common default)\n- 1.0+ = more creative/random\n"},"max_iterations":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"Number. Limits how many times the agent can loop through reasoning and tool use.\nRange: 1-1000.\n"}}},"tools":{"type":"array","description":"Array of tools the agent can use. The agent decides which tools to call based on the task","items":{"$ref":"#/components/schemas/AgentTool"}},"type":{"type":"string","enum":["aiagent"]},"tag":{"type":"string","description":"Worker group tag for execution routing. If not set, the AI agent step runs on the flow's tag (default `flow`)"},"omit_output_from_conversation":{"type":"boolean","default":false,"description":"If true, this AI agent step does not persist its assistant or tool messages to the flow conversation when chat mode is enabled."},"agent":{"type":"string","description":"Path of a reusable `ai_agent` resource (hybrid linking). When set, the agent brain\nconfig (provider/model/system prompt/etc.) and tool set are resolved at runtime from\nthat resource; the module's input_transforms then only carry the flow-local inputs\n(user_message, user_attachments, enabled_tools and the history inputs memory_id and previous_messages).\n"},"tool_inputs":{"type":"object","description":"Host-local wiring for an agent's tool inputs, keyed by tool id then input key. Binds the\nreferenced agent's tools to this flow's context (flow_input/results) without mutating the\nshared resource; overlaid onto the tools' input_transforms at runtime — including when\n`agent` is unset, since a step forked for editing keeps these overrides until it is saved\nback or unlinked.\n","additionalProperties":{"type":"object","additionalProperties":{"$ref":"#/components/schemas/InputTransform"}}},"parallel":{"type":"boolean","description":"If true, the agent can execute multiple tool calls in parallel"}},"required":["type","input_transforms"]},"AiDecision":{"type":"object","description":"AI decision step: one call to a decision model (TypeSafe's Jev, Cloudflare's\nJev-compatible Clef, or OpenAI's Decisions API) that answers typed questions about a\nstate with calibrated probabilities, instead of generating text.\nPrefer it over an AI agent to classify, route, score or check something: it is fast,\ncheap and its answers are structured. Its result is { output: { <question name>: answer },\nmodel, usage }, so a later step reads e.g. results.<id>.output.intent.choice. To route on\nthe answers, follow it with a branchone whose branch exprs read\nresults.<id>.output.<question>.choice. Usable as an AI agent tool, where the calling agent\nsupplies the state.\n","properties":{"input_transforms":{"type":"object","description":"Input parameters for the decision mapped to their values","properties":{"provider":{"$ref":"#/components/schemas/ProviderTransform"},"state":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"What the questions are asked about: a string, an object or an array of strings.\nAn object with descriptive keys holding only what the questions need works best.\nExample: { message: flow_input.message, plan: results.a.plan }\n"},"questions":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"Object mapping each question name to { type, instructions, criteria }, where type is:\n- 'choice': criteria maps each option to its description (up to 255); the answer\n has choice, probabilities and confidence\n- 'score': criteria is an ordered array of 2 to 10 level descriptions; the answer\n has score, legend, probabilities and confidence\n- 'noul': yes/no, criteria optionally { true, false } descriptions; the answer has\n noul, the probability of yes (0 to 1)\nExample: { intent: { type: 'choice', instructions: 'What does the customer want?',\ncriteria: { refund: 'Money back', bug: 'Something is broken' } } }\n"}},"required":["provider","state","questions"]},"type":{"type":"string","enum":["aidecision"]},"tag":{"type":"string","description":"Worker group tag for execution routing. If not set, the step runs on the flow's tag (default `flow`)"}},"required":["type","input_transforms"]},"Identity":{"type":"object","description":"Pass-through module that returns its input unchanged. Useful for flow structure or as a placeholder","properties":{"type":{"type":"string","enum":["identity"]},"flow":{"type":"boolean","description":"If true, marks this as a flow identity (special handling)"}},"required":["type"]},"FlowStatus":{"type":"object","properties":{"step":{"type":"integer"},"modules":{"type":"array","items":{"$ref":"#/components/schemas/FlowStatusModule"}},"user_states":{"additionalProperties":true},"preprocessor_module":{"allOf":[{"$ref":"#/components/schemas/FlowStatusModule"}]},"failure_module":{"allOf":[{"$ref":"#/components/schemas/FlowStatusModule"},{"type":"object","properties":{"parent_module":{"type":"string"}}}]},"retry":{"type":"object","properties":{"fail_count":{"type":"integer"},"failed_jobs":{"type":"array","items":{"type":"string","format":"uuid"}}}}},"required":["step","modules","failure_module"]},"FlowStatusModule":{"type":"object","properties":{"type":{"type":"string","enum":["WaitingForPriorSteps","WaitingForEvents","WaitingForExecutor","InProgress","Success","Failure"]},"id":{"type":"string"},"job":{"type":"string","format":"uuid"},"count":{"type":"integer"},"progress":{"type":"integer"},"iterator":{"type":"object","properties":{"index":{"type":"integer"},"itered":{"type":"array","items":{}},"itered_len":{"type":"integer"},"args":{}}},"flow_jobs":{"type":"array","items":{"type":"string"}},"flow_jobs_success":{"type":"array","items":{"type":"boolean"}},"flow_jobs_duration":{"type":"object","properties":{"started_at":{"type":"array","items":{"type":"string"}},"duration_ms":{"type":"array","items":{"type":"integer"}}}},"branch_chosen":{"type":"object","properties":{"type":{"type":"string","enum":["branch","default"]},"branch":{"type":"integer"}},"required":["type"]},"branchall":{"type":"object","properties":{"branch":{"type":"integer"},"len":{"type":"integer"}},"required":["branch","len"]},"approvers":{"type":"array","items":{"type":"object","properties":{"resume_id":{"type":"integer"},"approver":{"type":"string"}},"required":["resume_id","approver"]}},"failed_retries":{"type":"array","items":{"type":"string","format":"uuid"}},"skipped":{"type":"boolean"},"agent_actions":{"type":"array","items":{"type":"object","oneOf":[{"type":"object","properties":{"job_id":{"type":"string","format":"uuid"},"function_name":{"type":"string"},"type":{"type":"string","enum":["tool_call"]},"module_id":{"type":"string"}},"required":["job_id","function_name","type","module_id"]},{"type":"object","properties":{"call_id":{"type":"string","format":"uuid"},"function_name":{"type":"string"},"resource_path":{"type":"string"},"type":{"type":"string","enum":["mcp_tool_call"]},"arguments":{"type":"object"}},"required":["call_id","function_name","resource_path","type"]},{"type":"object","properties":{"type":{"type":"string","enum":["web_search"]}},"required":["type"]},{"type":"object","properties":{"type":{"type":"string","enum":["message"]}},"required":["content","type"]}]}},"agent_actions_success":{"type":"array","items":{"type":"boolean"}}},"required":["type"]}}}} \ No newline at end of file +{"openapi":"3.0.3","info":{"version":"1.846.1","title":"OpenFlow Spec","contact":{"name":"Ruben Fiszel","email":"ruben@windmill.dev","url":"https://windmill.dev"},"license":{"name":"Apache 2.0","url":"https://www.apache.org/licenses/LICENSE-2.0.html"}},"paths":{},"externalDocs":{"description":"documentation portal","url":"https://windmill.dev"},"components":{"schemas":{"OpenFlow":{"type":"object","description":"Top-level flow definition containing metadata, configuration, and the flow structure","properties":{"summary":{"type":"string","description":"Short description of what this flow does"},"description":{"type":"string","description":"Detailed documentation for this flow"},"value":{"$ref":"#/components/schemas/FlowValue"},"schema":{"type":"object","description":"JSON Schema for flow inputs. Use this to define input parameters, their types, defaults, and validation. For resource inputs, set type to 'object' and format to 'resource-<type>' (e.g., 'resource-stripe')"},"on_behalf_of_email":{"type":"string","description":"Address of the account the flow runs on behalf of. Derived from on_behalf_of on read; accepted on write, where it is resolved to the account it names."},"on_behalf_of":{"type":"string","description":"The flow runs with the permissions of this identity: u/{username}, g/{group}, or a bare email when the username is itself email-shaped. The only stored half of the identity; on_behalf_of_email is derived from it. Omit it when writing and it is resolved from that address instead."}},"required":["summary","value"]},"FlowValue":{"type":"object","description":"The flow structure containing modules and optional preprocessor/failure handlers","properties":{"modules":{"type":"array","description":"Array of steps that execute in sequence. Each step can be a script, subflow, loop, or branch","items":{"$ref":"#/components/schemas/FlowModule"}},"failure_module":{"description":"Special module that executes when the flow fails. Receives error object with message, name, stack, and step_id. Must have id 'failure'. Only supports script/rawscript types","$ref":"#/components/schemas/FlowModule"},"preprocessor_module":{"description":"Special module that runs before the first step on external triggers. Must have id 'preprocessor'. Only supports script/rawscript types. Cannot reference other step results","$ref":"#/components/schemas/FlowModule"},"same_worker":{"type":"boolean","description":"If true, all steps run on the same worker for better performance"},"preserve_step_tags":{"type":"boolean","description":"If true and the flow runs on a custom worker tag, steps that declare their own non-empty tag run on it instead of inheriting the flow tag. Steps without their own tag still inherit the flow tag."},"concurrent_limit":{"type":"number","description":"Maximum number of concurrent executions of this flow"},"concurrency_key":{"type":"string","description":"Expression to group concurrent executions (e.g., by user ID)"},"concurrency_time_window_s":{"type":"number","description":"Time window in seconds for concurrent_limit"},"debounce_delay_s":{"type":"integer","description":"Delay in seconds to debounce flow executions"},"debounce_key":{"type":"string","description":"Expression to group debounced executions"},"debounce_args_to_accumulate":{"type":"array","description":"Arguments to accumulate across debounced executions","items":{"type":"string"}},"max_total_debouncing_time":{"type":"integer","description":"Maximum total time in seconds that a job can be debounced"},"max_total_debounces_amount":{"type":"integer","description":"Maximum number of times a job can be debounced"},"skip_expr":{"type":"string","description":"JavaScript expression to conditionally skip the entire flow"},"cache_ttl":{"type":"number","description":"Cache duration in seconds for flow results"},"cache_ignore_s3_path":{"type":"boolean"},"delete_after_secs":{"type":"integer","description":"If set, delete the flow job's args, result and logs after this many seconds following job completion"},"flow_env":{"type":"object","description":"Environment variables available to all steps. Values can be strings, JSON values, or special references: '$var:path' (workspace variable) or '$res:path' (resource).","additionalProperties":{}},"priority":{"type":"number","description":"Execution priority (higher numbers run first)"},"early_return":{"type":"string","description":"Id of the step whose result a sync webhook returns as soon as that step completes, while the rest of the flow keeps running. When the step does not run, or fails while the flow has a failure module, the flow's final result is returned instead."},"chat_input_enabled":{"type":"boolean","description":"Whether this flow accepts chat-style input"},"notes":{"type":"array","description":"Sticky notes attached to the flow","items":{"$ref":"#/components/schemas/FlowNote"}},"groups":{"type":"array","description":"Semantic groups of modules for organizational purposes","items":{"$ref":"#/components/schemas/FlowGroup"}}},"required":["modules"]},"Retry":{"type":"object","description":"Retry configuration for failed module executions","properties":{"constant":{"type":"object","description":"Retry with constant delay between attempts","properties":{"attempts":{"type":"integer","description":"Number of retry attempts"},"seconds":{"type":"integer","description":"Seconds to wait between retries"}}},"exponential":{"type":"object","description":"Retry with exponential backoff: the n-th retry waits multiplier × seconds^n","properties":{"attempts":{"type":"integer","description":"Number of retry attempts"},"multiplier":{"type":"integer","description":"Multiplier for exponential backoff"},"seconds":{"type":"integer","minimum":1,"description":"Base of the exponential (seconds); the n-th retry waits multiplier × seconds^n, where n counts constant retries too"},"random_factor":{"type":"integer","minimum":0,"maximum":100,"description":"Random jitter percentage (0-100) to avoid thundering herd"}}},"retry_if":{"$ref":"#/components/schemas/RetryIf"}}},"FlowNote":{"type":"object","description":"A sticky note attached to a flow for documentation and annotation","properties":{"id":{"type":"string","description":"Unique identifier for the note"},"text":{"type":"string","description":"Content of the note"},"position":{"type":"object","description":"Position of the note in the flow editor","properties":{"x":{"type":"number","description":"X coordinate"},"y":{"type":"number","description":"Y coordinate"}},"required":["x","y"]},"size":{"type":"object","description":"Size of the note in the flow editor","properties":{"width":{"type":"number","description":"Width in pixels"},"height":{"type":"number","description":"Height in pixels"}},"required":["width","height"]},"color":{"type":"string","description":"Color of the note, one of: yellow, blue, green, purple, pink, orange, red, cyan, lime, gray. Any other value renders unstyled."},"type":{"type":"string","enum":["free","group"],"description":"Type of note - 'free' for standalone notes. 'group' notes are deprecated; segment a flow with FlowValue.groups instead."},"locked":{"type":"boolean","default":false,"description":"Whether the note is locked and cannot be edited or moved"},"contained_node_ids":{"type":"array","items":{"type":"string"},"description":"For group notes, the IDs of nodes contained within this group"}},"required":["id","text","color","type"]},"FlowGroup":{"type":"object","description":"A semantic group of flow modules for organizational purposes. Does not affect execution — modules remain in their original position in the flow. Groups provide naming and collapsibility in the editor. Members are computed dynamically from all nodes on paths between start_id and end_id.","properties":{"summary":{"type":"string","description":"Display name for this group"},"note":{"type":"string","description":"Markdown note shown below the group header"},"autocollapse":{"type":"boolean","default":false,"description":"If true, this group is collapsed by default in the flow editor. UI hint only."},"start_id":{"type":"string","description":"ID of the first flow module in this group (topological entry point)"},"end_id":{"type":"string","description":"ID of the last flow module in this group (topological exit point)"},"color":{"type":"string","description":"Color for the group in the flow editor, one of: yellow, blue, green, purple, pink, orange, red, cyan, lime, gray. Omit it to let the editor pick one."}},"required":["start_id","end_id"]},"RetryIf":{"type":"object","description":"Conditional retry based on error or result","properties":{"expr":{"type":"string","description":"JavaScript expression that returns true to retry. Has access to 'result' and 'error' variables"}},"required":["expr"]},"StopAfterIf":{"type":"object","description":"Early termination condition for a module","properties":{"skip_if_stopped":{"type":"boolean","description":"If true, following steps are skipped when this condition triggers"},"expr":{"type":"string","description":"JavaScript expression evaluated after the module runs. Can use 'result' (step's result) or 'flow_input'. Return true to stop"},"error_message":{"type":"string","nullable":true,"description":"Custom error message when stopping with an error. Mutually exclusive with skip_if_stopped. If set to a non-empty string, the flow stops with this error. If empty string, a default error message is used. If null or omitted, no error is raised."},"error_include_result":{"type":"boolean","description":"When stopping with an error (error_message set), embed the stopping step's own result inside the raised error object (as error.result) instead of discarding it. The top-level result stays { error }. Defaults to false."}},"required":["expr"]},"FlowModule":{"type":"object","description":"A single step in a flow. Can be a script, subflow, loop, or branch","properties":{"id":{"type":"string","description":"Unique identifier for this step. Used to reference results via 'results.step_id'. Must be a valid identifier (alphanumeric, underscore, hyphen)"},"value":{"$ref":"#/components/schemas/FlowModuleValue"},"stop_after_if":{"description":"Early termination condition evaluated after this step completes","$ref":"#/components/schemas/StopAfterIf"},"stop_after_all_iters_if":{"description":"For loops only - early termination condition evaluated after all iterations complete","$ref":"#/components/schemas/StopAfterIf"},"skip_if":{"type":"object","description":"Conditionally skip this step based on previous results or flow inputs","properties":{"expr":{"type":"string","description":"JavaScript expression that returns true to skip. Can use 'flow_input' or 'results.<step_id>'"}},"required":["expr"]},"sleep":{"description":"Delay before executing this step (in seconds or as expression)","$ref":"#/components/schemas/InputTransform"},"cache_ttl":{"type":"number","description":"Cache duration in seconds for this step's results"},"cache_ignore_s3_path":{"type":"boolean"},"timeout":{"description":"Maximum execution time in seconds (static value or expression)","$ref":"#/components/schemas/InputTransform"},"delete_after_secs":{"type":"integer","description":"If set, delete the step's args, result and logs after this many seconds following job completion"},"summary":{"type":"string","description":"Short description of what this step does"},"mock":{"type":"object","description":"Mock configuration for testing without executing the actual step","properties":{"enabled":{"type":"boolean","description":"If true, return mock value instead of executing"},"return_value":{"description":"Value to return when mocked"}}},"suspend":{"type":"object","description":"Configuration for approval/resume steps that wait for user input","properties":{"required_events":{"type":"integer","description":"Number of approvals required before continuing"},"timeout":{"type":"integer","description":"Timeout in seconds before auto-continuing or canceling"},"resume_form":{"type":"object","description":"Form schema for collecting input when resuming","properties":{"schema":{"type":"object","description":"JSON Schema for the resume form"}}},"user_auth_required":{"type":"boolean","description":"If true, only authenticated users can approve"},"user_groups_required":{"description":"Expression or list of groups that can approve","$ref":"#/components/schemas/InputTransform"},"self_approval_disabled":{"type":"boolean","description":"If true, the user who started the flow cannot approve"},"hide_cancel":{"type":"boolean","description":"If true, hide the cancel button on the approval form"},"continue_on_disapprove_timeout":{"type":"boolean","description":"If true, continue flow on timeout instead of canceling"},"skin":{"type":"string","enum":["detailed","minimal"],"description":"How the approval request is presented, on the approval page and in Slack/Teams approval messages. 'detailed' (used when unset) shows the flow details (arguments, graph, approvers); 'minimal' shows only the request: the step description, form and approve/reject actions"}}},"priority":{"type":"number","description":"Execution priority for this step (higher numbers run first)"},"continue_on_error":{"type":"boolean","description":"If true, flow continues even if this step fails"},"job_token_scopes":{"type":"array","nullable":true,"items":{"type":"string"},"description":"Scopes the token of this step's jobs is restricted to (domain:action[:resource], e.g. oidc:write), on top of the flow's own restriction: a step can only narrow it. Applies to everything the step runs (loop and branch bodies, AI agent tools)."},"retry":{"description":"Retry configuration if this step fails","$ref":"#/components/schemas/Retry"},"debouncing":{"description":"Debounce configuration for this step (EE only)","type":"object","properties":{"debounce_delay_s":{"type":"integer","description":"Delay in seconds to debounce this step's executions across flow runs"},"debounce_key":{"type":"string","description":"Expression to group debounced executions. Supports $workspace and $args[name]. Default: $workspace/flow/<flow_path>-<step_id>"},"debounce_args_to_accumulate":{"type":"array","description":"Array-type arguments to accumulate across debounced executions","items":{"type":"string"}},"max_total_debouncing_time":{"type":"integer","description":"Maximum total time in seconds before forced execution"},"max_total_debounces_amount":{"type":"integer","description":"Maximum number of debounces before forced execution"}}}},"required":["value","id"]},"InputTransform":{"description":"Maps input parameters for a step. Can be a static value or a JavaScript expression that references previous results or flow inputs","oneOf":[{"$ref":"#/components/schemas/StaticTransform"},{"$ref":"#/components/schemas/JavascriptTransform"},{"$ref":"#/components/schemas/AiTransform"}],"discriminator":{"propertyName":"type"}},"StaticTransform":{"type":"object","description":"Static value passed directly to the step. Use for hardcoded values or resource references like '$res:path/to/resource'","properties":{"value":{"description":"The static value. For resources, use format '$res:path/to/resource'"},"type":{"type":"string","enum":["static"]}},"required":["type"]},"JavascriptTransform":{"type":"object","description":"JavaScript expression evaluated at runtime. Can reference previous step results via 'results.step_id' or flow inputs via 'flow_input.property'. Inside for loops, use 'flow_input.iter.value' for the current iteration value (in while loops it equals 'flow_input.iter.index')","properties":{"expr":{"type":"string","description":"JavaScript expression returning the value. Available variables - results (object with all previous step results), flow_input (flow inputs), flow_input.iter (in loops)"},"type":{"type":"string","enum":["javascript"]}},"required":["expr","type"]},"AiTransform":{"type":"object","description":"Value resolved by the AI runtime for this input. The AI engine decides how to satisfy the parameter.","properties":{"type":{"type":"string","enum":["ai"]}},"required":["type"]},"AIProviderKind":{"type":"string","description":"Supported AI provider types","enum":["openai","azure_openai","azure_foundry","anthropic","mistral","deepseek","googleai","groq","openrouter","togetherai","customai","aws_bedrock","typesafe","cloudflare"]},"ProviderConfig":{"type":"object","description":"Complete AI provider configuration with resource reference and model selection","properties":{"kind":{"$ref":"#/components/schemas/AIProviderKind"},"resource":{"type":"string","description":"Resource reference in format '$res:{resource_path}' pointing to provider credentials"},"model":{"type":"string","description":"Model identifier (e.g., 'gpt-4', 'claude-3-opus-20240229', 'gemini-pro')"},"reasoning_effort":{"type":"string","description":"Provider-native reasoning effort token (e.g. 'low', 'high', 'none') for models that support extended thinking. Optional; unset leaves the provider default."}},"required":["kind","resource","model"]},"StaticProviderTransform":{"type":"object","description":"Static provider configuration passed directly to the AI agent","properties":{"value":{"$ref":"#/components/schemas/ProviderConfig"},"type":{"type":"string","enum":["static"]}},"required":["type","value"]},"ProviderTransform":{"description":"Provider configuration - can be static (ProviderConfig), JavaScript expression, or AI-determined","oneOf":[{"$ref":"#/components/schemas/StaticProviderTransform"},{"$ref":"#/components/schemas/JavascriptTransform"},{"$ref":"#/components/schemas/AiTransform"}],"discriminator":{"propertyName":"type"}},"MemoryOff":{"type":"object","description":"No conversation memory/context","properties":{"kind":{"type":"string","enum":["off"]}},"required":["kind"]},"MemoryWindow":{"type":"object","description":"Keeps the most recent messages of the memory named by the run's memory id (or the step's\n`memory_id`). Without a memory id the agent runs without memory.\n","properties":{"kind":{"type":"string","enum":["window"]},"context_length":{"type":"integer","description":"Number of most recent messages to load and store. 0 turns memory off."}},"required":["kind","context_length"]},"MemoryAuto":{"type":"object","deprecated":true,"description":"Deprecated, still read as it was written: the run's memory id, else the `memory_id` here.\nThe step's own `memory_id` is not read while this kind is set; switch the kind to `window`\nto use it. Without a `context_length`, or with 0, it is `off` and reads `previous_messages`.\n","properties":{"kind":{"type":"string","enum":["auto"]},"context_length":{"type":"integer","description":"Maximum number of messages to retain in context"},"memory_id":{"type":"string","description":"Identifier for persistent memory across agent invocations"}},"required":["kind"]},"MemoryCompaction":{"type":"object","description":"Keeps the whole memory named by the run's memory id (or the step's `memory_id`), replacing\nits older part with a summary as the conversation approaches the model's context window.\nWithout a memory id the agent runs without memory, and compaction bounds the run's own loop.\n","properties":{"kind":{"type":"string","enum":["compaction"]},"context_window":{"type":"integer","description":"Overrides the context window looked up from the model, in tokens. Only a model\nWindmill does not know needs one; those fall back to 128000.\n"}},"required":["kind"]},"MemoryMessage":{"type":"object","description":"A single message in conversation history","properties":{"role":{"type":"string","enum":["user","assistant","system"]},"content":{"type":"string"}},"required":["role","content"]},"MemoryManual":{"type":"object","deprecated":true,"description":"Deprecated, still read as it was written. Move the step to `off` with `previous_messages` instead.","properties":{"kind":{"type":"string","enum":["manual"]},"messages":{"type":"array","items":{"$ref":"#/components/schemas/MemoryMessage"}}},"required":["kind","messages"]},"MemoryConfig":{"description":"Managed memory, stored by Windmill and replayed with each request. The memory is named by a memory id, see `memory_id`. While it is off, a step can supply its history in `previous_messages`.","oneOf":[{"$ref":"#/components/schemas/MemoryOff"},{"$ref":"#/components/schemas/MemoryWindow"},{"$ref":"#/components/schemas/MemoryCompaction"},{"$ref":"#/components/schemas/MemoryAuto"},{"$ref":"#/components/schemas/MemoryManual"}],"discriminator":{"propertyName":"kind"}},"StaticMemoryTransform":{"type":"object","description":"Static memory configuration passed directly to the AI agent","properties":{"value":{"$ref":"#/components/schemas/MemoryConfig"},"type":{"type":"string","enum":["static"]}},"required":["type","value"]},"MemoryTransform":{"description":"Memory configuration - can be static (MemoryConfig), JavaScript expression, or AI-determined","oneOf":[{"$ref":"#/components/schemas/StaticMemoryTransform"},{"$ref":"#/components/schemas/JavascriptTransform"},{"$ref":"#/components/schemas/AiTransform"}],"discriminator":{"propertyName":"type"}},"FlowModuleValue":{"description":"The actual implementation of a flow step. Can be a script (inline or referenced), subflow, loop, branch, or special module type","oneOf":[{"$ref":"#/components/schemas/RawScript"},{"$ref":"#/components/schemas/PathScript"},{"$ref":"#/components/schemas/PathFlow"},{"$ref":"#/components/schemas/ForloopFlow"},{"$ref":"#/components/schemas/WhileloopFlow"},{"$ref":"#/components/schemas/BranchOne"},{"$ref":"#/components/schemas/BranchAll"},{"$ref":"#/components/schemas/Identity"},{"$ref":"#/components/schemas/AiAgent"},{"$ref":"#/components/schemas/AiDecision"}],"discriminator":{"propertyName":"type"}},"RawScript":{"type":"object","description":"Inline script with code defined directly in the flow. Use 'bun' as default language if unspecified. The script receives arguments from input_transforms","properties":{"input_transforms":{"type":"object","description":"Map of parameter names to their values (static or JavaScript expressions). These become the script's input arguments","additionalProperties":{"$ref":"#/components/schemas/InputTransform"}},"content":{"type":"string","description":"The script source code. Should export a 'main' function"},"language":{"type":"string","description":"Programming language for this script","enum":["deno","bun","bunnative","python3","go","bash","powershell","postgresql","mysql","bigquery","snowflake","mssql","oracledb","graphql","nativets","php","rust","ansible","csharp","nu","java","ruby","rlang","duckdb"]},"path":{"type":"string","description":"Optional path for saving this script"},"lock":{"type":"string","description":"Lock file content for dependencies"},"type":{"type":"string","enum":["rawscript"]},"tag":{"type":"string","description":"Worker group tag for execution routing"},"concurrent_limit":{"type":"number","description":"Maximum concurrent executions of this script"},"concurrency_time_window_s":{"type":"number","description":"Time window for concurrent_limit"},"custom_concurrency_key":{"type":"string","description":"Custom key for grouping concurrent executions"},"is_trigger":{"type":"boolean","description":"If true, this script is a trigger that can start the flow"},"assets":{"type":"array","description":"External resources this script accesses (S3 objects, resources, etc.)","items":{"type":"object","required":["path","kind"],"properties":{"path":{"type":"string","description":"Path to the asset"},"kind":{"type":"string","description":"Type of asset","enum":["s3object","resource","ducklake","datatable","volume","dbt"]},"access_type":{"type":"string","nullable":true,"description":"Access level for this asset","enum":["r","w","rw",null]},"alt_access_type":{"type":"string","nullable":true,"description":"Alternative access level","enum":["r","w","rw",null]}}}}},"required":["type","content","language","input_transforms"]},"PathScript":{"type":"object","description":"Reference to an existing script by path. Use this when calling a previously saved script instead of writing inline code","properties":{"input_transforms":{"type":"object","description":"Map of parameter names to their values (static or JavaScript expressions). These become the script's input arguments","additionalProperties":{"$ref":"#/components/schemas/InputTransform"}},"path":{"type":"string","description":"Path to the script in the workspace (e.g., 'f/scripts/send_email')"},"hash":{"type":"string","description":"Optional specific version hash of the script to use"},"type":{"type":"string","enum":["script"]},"tag_override":{"type":"string","description":"Override the script's default worker group tag"},"is_trigger":{"type":"boolean","description":"If true, this script is a trigger that can start the flow"}},"required":["type","path","input_transforms"]},"PathFlow":{"type":"object","description":"Reference to an existing flow by path. Use this to call another flow as a subflow","properties":{"input_transforms":{"type":"object","description":"Map of parameter names to their values (static or JavaScript expressions). These become the subflow's input arguments","additionalProperties":{"$ref":"#/components/schemas/InputTransform"}},"path":{"type":"string","description":"Path to the flow in the workspace (e.g., 'f/flows/process_user')"},"type":{"type":"string","enum":["flow"]}},"required":["type","path","input_transforms"]},"ForloopFlow":{"type":"object","description":"Executes nested modules in a loop over an iterator. Inside the loop, use 'flow_input.iter.value' to access the current iteration value, and 'flow_input.iter.index' for the index. Supports parallel execution for better performance on I/O-bound operations","properties":{"modules":{"type":"array","description":"Steps to execute for each iteration. These can reference the iteration value via 'flow_input.iter.value'","items":{"$ref":"#/components/schemas/FlowModule"}},"iterator":{"description":"JavaScript expression that returns an array to iterate over. Can reference 'results.step_id' or 'flow_input'","$ref":"#/components/schemas/InputTransform"},"skip_failures":{"type":"boolean","description":"If true, iteration failures don't stop the loop. Failed iterations return null"},"type":{"type":"string","enum":["forloopflow"]},"parallel":{"type":"boolean","description":"If true, iterations run concurrently (faster for I/O-bound operations). Use with parallelism to control concurrency"},"parallelism":{"description":"Maximum number of concurrent iterations when parallel=true. Limits resource usage. Can be static number or expression","$ref":"#/components/schemas/InputTransform"},"squash":{"type":"boolean"}},"required":["modules","iterator","skip_failures","type"]},"WhileloopFlow":{"type":"object","description":"Executes nested modules repeatedly until stopped. The implicit iterator is the iteration counter, so 'flow_input.iter.value' equals 'flow_input.iter.index' (0, 1, 2, ...) and never carries state. To carry state across iterations, a step reads its own previous-iteration result via 'results.<its_own_id>' with a first-iteration fallback - the loop's stop_after_if must then be on that inner step (a plain single-step body with stop_after_if on the loop module does not resolve 'results' across iterations and never terminates); plain counters can instead be derived from 'flow_input.iter.index', which works in every configuration. stop_after_if is evaluated after each iteration - on the loop module 'result' is the last iteration's result","properties":{"modules":{"type":"array","description":"Steps to execute in each iteration","items":{"$ref":"#/components/schemas/FlowModule"}},"skip_failures":{"type":"boolean","description":"If true, iteration failures don't stop the loop. Failed iterations return null"},"type":{"type":"string","enum":["whileloopflow"]},"parallel":{"type":"boolean","description":"If true, iterations run concurrently (use with caution in while loops)"},"parallelism":{"description":"Maximum number of concurrent iterations when parallel=true","$ref":"#/components/schemas/InputTransform"},"squash":{"type":"boolean"}},"required":["modules","skip_failures","type"]},"BranchOne":{"type":"object","description":"Conditional branching where only the first matching branch executes. Branches are evaluated in order, and the first one with a true expression runs. If no branches match, the default branch executes","properties":{"branches":{"type":"array","description":"Array of branches to evaluate in order. The first branch with expr evaluating to true executes","items":{"type":"object","properties":{"summary":{"type":"string","description":"Short description of this branch condition"},"expr":{"type":"string","description":"JavaScript expression that returns boolean. Can use 'results.step_id' or 'flow_input'. First true expr wins"},"modules":{"type":"array","description":"Steps to execute if this branch's expr is true","items":{"$ref":"#/components/schemas/FlowModule"}}},"required":["modules","expr"]}},"default":{"type":"array","description":"Steps to execute if no branch expressions match","items":{"$ref":"#/components/schemas/FlowModule"}},"type":{"type":"string","enum":["branchone"]}},"required":["branches","default","type"]},"BranchAll":{"type":"object","description":"Parallel branching where all branches execute simultaneously. Unlike BranchOne, all branches run regardless of conditions. Useful for executing independent tasks concurrently","properties":{"branches":{"type":"array","description":"Array of branches that all execute (either in parallel or sequentially)","items":{"type":"object","properties":{"summary":{"type":"string","description":"Short description of this branch's purpose"},"skip_failure":{"type":"boolean","description":"If true, failure in this branch doesn't fail the entire flow"},"modules":{"type":"array","description":"Steps to execute in this branch","items":{"$ref":"#/components/schemas/FlowModule"}}},"required":["modules"]}},"type":{"type":"string","enum":["branchall"]},"parallel":{"type":"boolean","description":"If true, all branches execute concurrently. If false, they execute sequentially"}},"required":["branches","type"]},"AgentTool":{"type":"object","description":"A tool available to an AI agent. Can be a flow module or an external MCP (Model Context Protocol) tool","properties":{"id":{"type":"string","description":"Unique identifier for this tool. Cannot contain spaces - use underscores instead (e.g., 'get_user_data' not 'get user data')"},"summary":{"type":"string","description":"The name the AI agent calls this tool by, not a human label. On a flowmodule tool it must match ^[a-zA-Z0-9_]+$ - letters, numbers and underscores only (e.g. 'search_documentation', not 'Search documentation') - and always be set; on an mcp, websearch or question tool it is a plain label. Put the human-readable explanation in 'description'."},"description":{"type":"string","description":"Free-text description of the tool given to the AI to decide when and how to call it. Overrides the description auto-derived from the underlying script."},"job_token_scopes":{"type":"array","nullable":true,"items":{"type":"string"},"description":"Scopes the token of this tool's jobs is restricted to, on top of the agent step's own restriction: a tool can only narrow it."},"requires_approval":{"type":"boolean","description":"Flowmodule and mcp tools only. Each call waits for a person to approve or reject it from the flow's run page or chat, without the agent holding a worker. Calls in the same turn that do not require approval run right away. A rejected call, or one nobody answers within 30 minutes, is reported to the AI as not run."},"value":{"$ref":"#/components/schemas/ToolValue"}},"required":["id","value"]},"ToolValue":{"description":"The implementation of a tool. Can be a flow module (script/flow) or an MCP tool reference","oneOf":[{"$ref":"#/components/schemas/FlowModuleTool"},{"$ref":"#/components/schemas/McpToolValue"},{"$ref":"#/components/schemas/WebsearchToolValue"},{"$ref":"#/components/schemas/QuestionToolValue"}]},"FlowModuleTool":{"description":"A tool implemented as a flow module (script, flow, etc.). The AI can call this like any other flow module","allOf":[{"type":"object","properties":{"tool_type":{"type":"string","enum":["flowmodule"]}},"required":["tool_type"]},{"$ref":"#/components/schemas/FlowModuleValue"}]},"WebsearchToolValue":{"type":"object","description":"A tool implemented as a websearch tool. The AI can call this like any other websearch tool","properties":{"tool_type":{"type":"string","enum":["websearch"]}},"required":["tool_type"]},"QuestionToolValue":{"type":"object","description":"Built-in tool the AI calls as ask_question: the agent stops, releasing its worker, until someone answers from the flow's run page or chat or the question times out, then resumes with the answer as the tool result.","properties":{"tool_type":{"type":"string","enum":["question"]},"timeout":{"type":"integer","description":"Seconds to wait for an answer before the question is reported to the AI as timed out. Defaults to 1800."}},"required":["tool_type"]},"McpToolValue":{"type":"object","description":"Reference to an external MCP (Model Context Protocol) tool. The AI can call tools from MCP servers","properties":{"tool_type":{"type":"string","enum":["mcp"]},"resource_path":{"type":"string","description":"Path to the MCP resource/server configuration"},"include_tools":{"type":"array","description":"Whitelist of specific tools to include from this MCP server","items":{"type":"string"}},"exclude_tools":{"type":"array","description":"Blacklist of tools to exclude from this MCP server","items":{"type":"string"}}},"required":["tool_type","resource_path"]},"AiAgent":{"type":"object","description":"AI agent step that can use tools to accomplish tasks. The agent receives inputs and can call any of its configured tools to complete the task","properties":{"input_transforms":{"type":"object","description":"Input parameters for the AI agent mapped to their values","properties":{"provider":{"$ref":"#/components/schemas/ProviderTransform"},"output_type":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"Output format type.\nValid values: 'text' (default) - plain text response, 'image' - image generation\n"},"user_message":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"The user's prompt/message to the AI agent. Supports variable interpolation with\nflow.input syntax. Required unless memory is off and `previous_messages` supplies\nthe prompt; image output always needs it.\n"},"system_prompt":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"System instructions that guide the AI's behavior, persona, and response style. Optional."},"streaming":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"Boolean. If true, stream the AI response incrementally.\nStreaming events include: token_delta, reasoning_token_delta, tool_call, tool_call_arguments, tool_execution, tool_result\n"},"memory":{"$ref":"#/components/schemas/MemoryTransform"},"memory_id":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"String. Names the memory this step reads and writes, overriding the memory id the run\nwas started with (the chat conversation, an app chat session or the `memory_id` run\nparameter). Leave unset to use the run's memory id. A fixed value shares one memory\nacross every run; an expression such as `flow_input.customer_id` keeps one memory per\nkey. When it evaluates to an empty value the agent runs without memory. Read only\nwhile `memory` is `window` or `compaction`: it is ignored when memory is off, and an\nolder `auto` or `manual` memory reads neither history input.\n"},"previous_messages":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"Array of MemoryMessage. History supplied by the flow, sent between the system prompt\nand the user message. Read only while `memory` is off or absent: managed memory\nignores it, and an older `auto` or `manual` memory reads neither history input.\n"},"output_schema":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"JSON Schema object defining structured output format. Used when you need the AI to return data in a specific shape.\nSupports standard JSON Schema properties: type, properties, required, items, enum, pattern, minLength, maxLength, minimum, maximum, etc.\nExample: { type: 'object', properties: { name: { type: 'string' }, age: { type: 'integer' } }, required: ['name'] }\n"},"user_attachments":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"Array of file references (images or PDFs) for the AI agent.\nFormat: Array<{ bucket: string, key: string }> - S3 object references\nExample: [{ bucket: 'my-bucket', key: 'documents/report.pdf' }]\n"},"enabled_tools":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"Array of strings naming which of the tools configured in `tools` the agent may call\nthis run. Leaving it unset carries every one of them; an empty array carries none.\nA tool is named as the model is shown it. An entry the model is shown nothing of is\nnamed by what identifies it instead: an MCP server by its resource path, carrying\nevery tool it exposes (which of them stays that entry's include_tools/exclude_tools),\nand a websearch entry by the reserved name '__wm_web_search', whatever summary it carries\n(no tool may take that name).\nExample: ['get_user', 'u/admin/github_mcp', '__wm_web_search']\n"},"max_completion_tokens":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"Integer. Maximum number of tokens the AI will generate in its response.\nRange: 1 to 4,294,967,295. Typical values: 256-4096 for most use cases.\n"},"temperature":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"Float. Controls randomness/creativity of responses.\nRange: 0.0 to 2.0 (provider-dependent)\n- 0.0 = deterministic, focused responses\n- 0.7 = balanced (common default)\n- 1.0+ = more creative/random\n"},"max_iterations":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"Number. Limits how many times the agent can loop through reasoning and tool use.\nRange: 1-1000.\n"},"model":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"String. Only on a step linked to a saved agent (see `agent`): replaces the model\nsaved on the agent for this step's runs, on the agent's own provider resource. An\nempty value keeps the saved model. Set it to an expression such as\n`flow_input.model` to choose the model per run.\n"},"reasoning_effort":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"String. Only on a step linked to a saved agent (see `agent`): replaces the reasoning\neffort saved on the agent for this step's runs, as a provider-native token (e.g.\n'low', 'high', 'none'). An empty value sends no effort, so the model runs at its\ndefault. Leave the input out to keep the saved effort, which holds only while the\nstep runs the saved model. A step that is not linked sets both inside `provider`.\n"}}},"tools":{"type":"array","description":"Array of tools the agent can use. The agent decides which tools to call based on the task","items":{"$ref":"#/components/schemas/AgentTool"}},"type":{"type":"string","enum":["aiagent"]},"tag":{"type":"string","description":"Worker group tag for execution routing. If not set, the AI agent step runs on the flow's tag (default `flow`)"},"omit_output_from_conversation":{"type":"boolean","default":false,"description":"If true, this AI agent step does not persist its assistant or tool messages to the flow conversation when chat mode is enabled."},"agent":{"type":"string","description":"Path of a reusable `ai_agent` resource (hybrid linking). When set, the agent brain\nconfig (provider/model/system prompt/etc.) and tool set are resolved at runtime from\nthat resource; the module's input_transforms then only carry the flow-local inputs\n(user_message, user_attachments, enabled_tools and the history inputs memory_id and previous_messages)\nand, optionally, the `model` and `reasoning_effort` overrides of what the agent saved.\n"},"tool_inputs":{"type":"object","description":"Host-local wiring for an agent's tool inputs, keyed by tool id then input key. Binds the\nreferenced agent's tools to this flow's context (flow_input/results) without mutating the\nshared resource; overlaid onto the tools' input_transforms at runtime — including when\n`agent` is unset, since a step forked for editing keeps these overrides until it is saved\nback or unlinked.\n","additionalProperties":{"type":"object","additionalProperties":{"$ref":"#/components/schemas/InputTransform"}}},"parallel":{"type":"boolean","description":"If true, the agent can execute multiple tool calls in parallel"}},"required":["type","input_transforms"]},"AiDecision":{"type":"object","description":"AI decision step: one call to a decision model (TypeSafe's Jev, Cloudflare's\nJev-compatible Clef, or OpenAI's Decisions API) that answers typed questions about a\nstate with calibrated probabilities, instead of generating text.\nPrefer it over an AI agent to classify, route, score or check something: it is fast,\ncheap and its answers are structured. Its result is { output: { <question name>: answer },\nmodel, usage }, so a later step reads e.g. results.<id>.output.intent.choice. To route on\nthe answers, follow it with a branchone whose branch exprs read\nresults.<id>.output.<question>.choice. Usable as an AI agent tool, where the calling agent\nsupplies the state.\n","properties":{"input_transforms":{"type":"object","description":"Input parameters for the decision mapped to their values","properties":{"provider":{"$ref":"#/components/schemas/ProviderTransform"},"state":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"What the questions are asked about: a string, an object or an array of strings.\nAn object with descriptive keys holding only what the questions need works best.\nExample: { message: flow_input.message, plan: results.a.plan }\n"},"questions":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"Object mapping each question name to { type, instructions, criteria }, where type is:\n- 'choice': criteria maps each option to its description (up to 255); the answer\n has choice, probabilities and confidence\n- 'score': criteria is an ordered array of 2 to 10 level descriptions; the answer\n has score, legend, probabilities and confidence\n- 'noul': yes/no, criteria optionally { true, false } descriptions; the answer has\n noul, the probability of yes (0 to 1)\nExample: { intent: { type: 'choice', instructions: 'What does the customer want?',\ncriteria: { refund: 'Money back', bug: 'Something is broken' } } }\n"}},"required":["provider","state","questions"]},"type":{"type":"string","enum":["aidecision"]},"tag":{"type":"string","description":"Worker group tag for execution routing. If not set, the step runs on the flow's tag (default `flow`)"}},"required":["type","input_transforms"]},"Identity":{"type":"object","description":"Pass-through module that returns its input unchanged. Useful for flow structure or as a placeholder","properties":{"type":{"type":"string","enum":["identity"]},"flow":{"type":"boolean","description":"If true, marks this as a flow identity (special handling)"}},"required":["type"]},"FlowStatus":{"type":"object","properties":{"step":{"type":"integer"},"modules":{"type":"array","items":{"$ref":"#/components/schemas/FlowStatusModule"}},"user_states":{"additionalProperties":true},"preprocessor_module":{"allOf":[{"$ref":"#/components/schemas/FlowStatusModule"}]},"failure_module":{"allOf":[{"$ref":"#/components/schemas/FlowStatusModule"},{"type":"object","properties":{"parent_module":{"type":"string"}}}]},"retry":{"type":"object","properties":{"fail_count":{"type":"integer"},"failed_jobs":{"type":"array","items":{"type":"string","format":"uuid"}}}}},"required":["step","modules","failure_module"]},"FlowStatusModule":{"type":"object","properties":{"type":{"type":"string","enum":["WaitingForPriorSteps","WaitingForEvents","WaitingForExecutor","InProgress","Success","Failure"]},"id":{"type":"string"},"job":{"type":"string","format":"uuid"},"count":{"type":"integer"},"progress":{"type":"integer"},"iterator":{"type":"object","properties":{"index":{"type":"integer"},"itered":{"type":"array","items":{}},"itered_len":{"type":"integer"},"args":{}}},"flow_jobs":{"type":"array","items":{"type":"string"}},"flow_jobs_success":{"type":"array","items":{"type":"boolean"}},"flow_jobs_duration":{"type":"object","properties":{"started_at":{"type":"array","items":{"type":"string"}},"duration_ms":{"type":"array","items":{"type":"integer"}}}},"branch_chosen":{"type":"object","properties":{"type":{"type":"string","enum":["branch","default"]},"branch":{"type":"integer"}},"required":["type"]},"branchall":{"type":"object","properties":{"branch":{"type":"integer"},"len":{"type":"integer"}},"required":["branch","len"]},"approvers":{"type":"array","items":{"type":"object","properties":{"resume_id":{"type":"integer"},"approver":{"type":"string"}},"required":["resume_id","approver"]}},"failed_retries":{"type":"array","items":{"type":"string","format":"uuid"}},"skipped":{"type":"boolean"},"agent_actions":{"type":"array","items":{"type":"object","oneOf":[{"type":"object","properties":{"job_id":{"type":"string","format":"uuid"},"function_name":{"type":"string"},"type":{"type":"string","enum":["tool_call"]},"module_id":{"type":"string"}},"required":["job_id","function_name","type","module_id"]},{"type":"object","properties":{"call_id":{"type":"string","format":"uuid"},"function_name":{"type":"string"},"resource_path":{"type":"string"},"type":{"type":"string","enum":["mcp_tool_call"]},"arguments":{"type":"object"}},"required":["call_id","function_name","resource_path","type"]},{"type":"object","properties":{"type":{"type":"string","enum":["web_search"]}},"required":["type"]},{"type":"object","properties":{"type":{"type":"string","enum":["approval"]},"call_id":{"type":"string"},"calls":{"type":"array","items":{"type":"object","properties":{"function_name":{"type":"string"},"arguments":{}},"required":["function_name","arguments"]}},"expires_at":{"type":"string","format":"date-time"}},"required":["type","call_id","calls","expires_at"]},{"type":"object","properties":{"type":{"type":"string","enum":["question"]},"call_id":{"type":"string"},"question":{"type":"string"},"choices":{"type":"array","items":{"type":"string"},"description":"answers the model proposes; a free-text answer is always possible"},"multi_select":{"type":"boolean","description":"whether several choices can be picked together"},"expires_at":{"type":"string","format":"date-time"}},"required":["type","call_id","question","expires_at"]},{"type":"object","properties":{"type":{"type":"string","enum":["message"]}},"required":["content","type"]}]}},"agent_actions_success":{"type":"array","items":{"type":"boolean"}}},"required":["type"]}}}} \ No newline at end of file diff --git a/frontend/src/lib/components/copilot/chat/flow/openFlowZod.gen.ts b/frontend/src/lib/components/copilot/chat/flow/openFlowZod.gen.ts index d83ef70207..0ead3cee63 100644 --- a/frontend/src/lib/components/copilot/chat/flow/openFlowZod.gen.ts +++ b/frontend/src/lib/components/copilot/chat/flow/openFlowZod.gen.ts @@ -1,7 +1,7 @@ import { z } from "zod" -export const flowModuleValueSchema = z.discriminatedUnion("type", [z.object({ "input_transforms": z.record(z.string(), z.discriminatedUnion("type", [z.object({ "value": z.any().describe("The static value. For resources, use format '$res:path/to/resource'").optional(), "type": z.literal("static") }).describe("Static value passed directly to the step. Use for hardcoded values or resource references like '$res:path/to/resource'"), z.object({ "expr": z.string().describe("JavaScript expression returning the value. Available variables - results (object with all previous step results), flow_input (flow inputs), flow_input.iter (in loops)"), "type": z.literal("javascript") }).describe("JavaScript expression evaluated at runtime. Can reference previous step results via 'results.step_id' or flow inputs via 'flow_input.property'. Inside for loops, use 'flow_input.iter.value' for the current iteration value (in while loops it equals 'flow_input.iter.index')"), z.object({ "type": z.literal("ai") }).describe("Value resolved by the AI runtime for this input. The AI engine decides how to satisfy the parameter.")]).describe("Maps input parameters for a step. Can be a static value or a JavaScript expression that references previous results or flow inputs")).describe("Map of parameter names to their values (static or JavaScript expressions). These become the script's input arguments"), "content": z.string().describe("The script source code. Should export a 'main' function"), "language": z.enum(["deno","bun","bunnative","python3","go","bash","powershell","postgresql","mysql","bigquery","snowflake","mssql","oracledb","graphql","nativets","php","rust","ansible","csharp","nu","java","ruby","rlang","duckdb"]).describe("Programming language for this script"), "path": z.string().describe("Optional path for saving this script").optional(), "lock": z.string().describe("Lock file content for dependencies").optional(), "type": z.literal("rawscript"), "tag": z.string().describe("Worker group tag for execution routing").optional(), "concurrent_limit": z.number().describe("Maximum concurrent executions of this script").optional(), "concurrency_time_window_s": z.number().describe("Time window for concurrent_limit").optional(), "custom_concurrency_key": z.string().describe("Custom key for grouping concurrent executions").optional(), "is_trigger": z.boolean().describe("If true, this script is a trigger that can start the flow").optional(), "assets": z.array(z.object({ "path": z.string().describe("Path to the asset"), "kind": z.enum(["s3object","resource","ducklake","datatable","volume","dbt"]).describe("Type of asset"), "access_type": z.union([z.literal("r"), z.literal("w"), z.literal("rw"), z.literal(null)]).nullable().describe("Access level for this asset").optional(), "alt_access_type": z.union([z.literal("r"), z.literal("w"), z.literal("rw"), z.literal(null)]).nullable().describe("Alternative access level").optional() })).describe("External resources this script accesses (S3 objects, resources, etc.)").optional() }).describe("Inline script with code defined directly in the flow. Use 'bun' as default language if unspecified. The script receives arguments from input_transforms"), z.object({ "input_transforms": z.record(z.string(), z.discriminatedUnion("type", [z.object({ "value": z.any().describe("The static value. For resources, use format '$res:path/to/resource'").optional(), "type": z.literal("static") }).describe("Static value passed directly to the step. Use for hardcoded values or resource references like '$res:path/to/resource'"), z.object({ "expr": z.string().describe("JavaScript expression returning the value. Available variables - results (object with all previous step results), flow_input (flow inputs), flow_input.iter (in loops)"), "type": z.literal("javascript") }).describe("JavaScript expression evaluated at runtime. Can reference previous step results via 'results.step_id' or flow inputs via 'flow_input.property'. Inside for loops, use 'flow_input.iter.value' for the current iteration value (in while loops it equals 'flow_input.iter.index')"), z.object({ "type": z.literal("ai") }).describe("Value resolved by the AI runtime for this input. The AI engine decides how to satisfy the parameter.")]).describe("Maps input parameters for a step. Can be a static value or a JavaScript expression that references previous results or flow inputs")).describe("Map of parameter names to their values (static or JavaScript expressions). These become the script's input arguments"), "path": z.string().describe("Path to the script in the workspace (e.g., 'f/scripts/send_email')"), "hash": z.string().describe("Optional specific version hash of the script to use").optional(), "type": z.literal("script"), "tag_override": z.string().describe("Override the script's default worker group tag").optional(), "is_trigger": z.boolean().describe("If true, this script is a trigger that can start the flow").optional() }).describe("Reference to an existing script by path. Use this when calling a previously saved script instead of writing inline code"), z.object({ "input_transforms": z.record(z.string(), z.discriminatedUnion("type", [z.object({ "value": z.any().describe("The static value. For resources, use format '$res:path/to/resource'").optional(), "type": z.literal("static") }).describe("Static value passed directly to the step. 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If set to a non-empty string, the flow stops with this error. If empty string, a default error message is used. If null or omitted, no error is raised.").optional(), "error_include_result": z.boolean().describe("When stopping with an error (error_message set), embed the stopping step's own result inside the raised error object (as error.result) instead of discarding it. The top-level result stays { error }. Defaults to false.").optional() }).describe("Early termination condition for a module").optional(), "skip_if": z.object({ "expr": z.string().describe("JavaScript expression that returns true to skip. Can use 'flow_input' or 'results.<step_id>'") }).describe("Conditionally skip this step based on previous results or flow inputs").optional(), "sleep": z.discriminatedUnion("type", [z.object({ "value": z.any().describe("The static value. For resources, use format '$res:path/to/resource'").optional(), "type": z.literal("static") }).describe("Static value passed directly to the step. 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Can be a static value or a JavaScript expression that references previous results or flow inputs").optional(), "cache_ttl": z.number().describe("Cache duration in seconds for this step's results").optional(), "cache_ignore_s3_path": z.boolean().optional(), "timeout": z.discriminatedUnion("type", [z.object({ "value": z.any().describe("The static value. For resources, use format '$res:path/to/resource'").optional(), "type": z.literal("static") }).describe("Static value passed directly to the step. Use for hardcoded values or resource references like '$res:path/to/resource'"), z.object({ "expr": z.string().describe("JavaScript expression returning the value. Available variables - results (object with all previous step results), flow_input (flow inputs), flow_input.iter (in loops)"), "type": z.literal("javascript") }).describe("JavaScript expression evaluated at runtime. Can reference previous step results via 'results.step_id' or flow inputs via 'flow_input.property'. 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Can be a static value or a JavaScript expression that references previous results or flow inputs").optional(), "delete_after_secs": z.number().int().describe("If set, delete the step's args, result and logs after this many seconds following job completion").optional(), "summary": z.string().describe("Short description of what this step does").optional(), "mock": z.object({ "enabled": z.boolean().describe("If true, return mock value instead of executing").optional(), "return_value": z.any().describe("Value to return when mocked").optional() }).describe("Mock configuration for testing without executing the actual step").optional(), "suspend": z.object({ "required_events": z.number().int().describe("Number of approvals required before continuing").optional(), "timeout": z.number().int().describe("Timeout in seconds before auto-continuing or canceling").optional(), "resume_form": z.object({ "schema": z.record(z.string(), z.any()).describe("JSON Schema for the resume form").optional() }).describe("Form schema for collecting input when resuming").optional(), "user_auth_required": z.boolean().describe("If true, only authenticated users can approve").optional(), "user_groups_required": z.discriminatedUnion("type", [z.object({ "value": z.any().describe("The static value. 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Applies to everything the step runs (loop and branch bodies, AI agent tools).").optional(), "retry": z.object({ "constant": z.object({ "attempts": z.number().int().describe("Number of retry attempts").optional(), "seconds": z.number().int().describe("Seconds to wait between retries").optional() }).describe("Retry with constant delay between attempts").optional(), "exponential": z.object({ "attempts": z.number().int().describe("Number of retry attempts").optional(), "multiplier": z.number().int().describe("Multiplier for exponential backoff").optional(), "seconds": z.number().int().gte(1).describe("Base of the exponential (seconds); the n-th retry waits multiplier × seconds^n, where n counts constant retries too").optional(), "random_factor": z.number().int().gte(0).lte(100).describe("Random jitter percentage (0-100) to avoid thundering herd").optional() }).describe("Retry with exponential backoff: the n-th retry waits multiplier × seconds^n").optional(), "retry_if": z.object({ "expr": z.string().describe("JavaScript expression that returns true to retry. 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Optional; unset leaves the provider default.").optional() }).describe("Complete AI provider configuration with resource reference and model selection"), "type": z.literal("static") }).describe("Static provider configuration passed directly to the AI agent"), z.object({ "expr": z.string().describe("JavaScript expression returning the value. Available variables - results (object with all previous step results), flow_input (flow inputs), flow_input.iter (in loops)"), "type": z.literal("javascript") }).describe("JavaScript expression evaluated at runtime. Can reference previous step results via 'results.step_id' or flow inputs via 'flow_input.property'. Inside for loops, use 'flow_input.iter.value' for the current iteration value (in while loops it equals 'flow_input.iter.index')"), z.object({ "type": z.literal("ai") }).describe("Value resolved by the AI runtime for this input. The AI engine decides how to satisfy the parameter.")]).describe("Provider configuration - can be static (ProviderConfig), JavaScript expression, or AI-determined").optional(), "output_type": z.discriminatedUnion("type", [z.object({ "value": z.any().describe("The static value. For resources, use format '$res:path/to/resource'").optional(), "type": z.literal("static") }).describe("Static value passed directly to the step. Use for hardcoded values or resource references like '$res:path/to/resource'"), z.object({ "expr": z.string().describe("JavaScript expression returning the value. Available variables - results (object with all previous step results), flow_input (flow inputs), flow_input.iter (in loops)"), "type": z.literal("javascript") }).describe("JavaScript expression evaluated at runtime. Can reference previous step results via 'results.step_id' or flow inputs via 'flow_input.property'. Inside for loops, use 'flow_input.iter.value' for the current iteration value (in while loops it equals 'flow_input.iter.index')"), z.object({ "type": z.literal("ai") }).describe("Value resolved by the AI runtime for this input. The AI engine decides how to satisfy the parameter.")]).describe("Maps input parameters for a step. Can be a static value or a JavaScript expression that references previous results or flow inputs").describe("Output format type.\nValid values: 'text' (default) - plain text response, 'image' - image generation\n").optional(), "user_message": z.discriminatedUnion("type", [z.object({ "value": z.any().describe("The static value. For resources, use format '$res:path/to/resource'").optional(), "type": z.literal("static") }).describe("Static value passed directly to the step. Use for hardcoded values or resource references like '$res:path/to/resource'"), z.object({ "expr": z.string().describe("JavaScript expression returning the value. Available variables - results (object with all previous step results), flow_input (flow inputs), flow_input.iter (in loops)"), "type": z.literal("javascript") }).describe("JavaScript expression evaluated at runtime. Can reference previous step results via 'results.step_id' or flow inputs via 'flow_input.property'. Inside for loops, use 'flow_input.iter.value' for the current iteration value (in while loops it equals 'flow_input.iter.index')"), z.object({ "type": z.literal("ai") }).describe("Value resolved by the AI runtime for this input. The AI engine decides how to satisfy the parameter.")]).describe("Maps input parameters for a step. Can be a static value or a JavaScript expression that references previous results or flow inputs").describe("The user's prompt/message to the AI agent. Supports variable interpolation with\nflow.input syntax. Required unless memory is off and `previous_messages` supplies\nthe prompt; image output always needs it.\n").optional(), "system_prompt": z.discriminatedUnion("type", [z.object({ "value": z.any().describe("The static value. For resources, use format '$res:path/to/resource'").optional(), "type": z.literal("static") }).describe("Static value passed directly to the step. Use for hardcoded values or resource references like '$res:path/to/resource'"), z.object({ "expr": z.string().describe("JavaScript expression returning the value. Available variables - results (object with all previous step results), flow_input (flow inputs), flow_input.iter (in loops)"), "type": z.literal("javascript") }).describe("JavaScript expression evaluated at runtime. Can reference previous step results via 'results.step_id' or flow inputs via 'flow_input.property'. Inside for loops, use 'flow_input.iter.value' for the current iteration value (in while loops it equals 'flow_input.iter.index')"), z.object({ "type": z.literal("ai") }).describe("Value resolved by the AI runtime for this input. The AI engine decides how to satisfy the parameter.")]).describe("Maps input parameters for a step. Can be a static value or a JavaScript expression that references previous results or flow inputs").describe("System instructions that guide the AI's behavior, persona, and response style. Optional.").optional(), "streaming": z.discriminatedUnion("type", [z.object({ "value": z.any().describe("The static value. For resources, use format '$res:path/to/resource'").optional(), "type": z.literal("static") }).describe("Static value passed directly to the step. Use for hardcoded values or resource references like '$res:path/to/resource'"), z.object({ "expr": z.string().describe("JavaScript expression returning the value. Available variables - results (object with all previous step results), flow_input (flow inputs), flow_input.iter (in loops)"), "type": z.literal("javascript") }).describe("JavaScript expression evaluated at runtime. Can reference previous step results via 'results.step_id' or flow inputs via 'flow_input.property'. Inside for loops, use 'flow_input.iter.value' for the current iteration value (in while loops it equals 'flow_input.iter.index')"), z.object({ "type": z.literal("ai") }).describe("Value resolved by the AI runtime for this input. The AI engine decides how to satisfy the parameter.")]).describe("Maps input parameters for a step. Can be a static value or a JavaScript expression that references previous results or flow inputs").describe("Boolean. If true, stream the AI response incrementally.\nStreaming events include: token_delta, reasoning_token_delta, tool_call, tool_call_arguments, tool_execution, tool_result\n").optional(), "memory": z.discriminatedUnion("type", [z.object({ "value": z.discriminatedUnion("kind", [z.object({ "kind": z.literal("off") }).describe("No conversation memory/context"), z.object({ "kind": z.literal("window"), "context_length": z.number().int().describe("Number of most recent messages to load and store. 0 turns memory off.") }).describe("Keeps the most recent messages of the memory named by the run's memory id (or the step's\n`memory_id`). Without a memory id the agent runs without memory.\n"), z.object({ "kind": z.literal("compaction"), "context_window": z.number().int().describe("Overrides the context window looked up from the model, in tokens. Only a model\nWindmill does not know needs one; those fall back to 128000.\n").optional() }).describe("Keeps the whole memory named by the run's memory id (or the step's `memory_id`), replacing\nits older part with a summary as the conversation approaches the model's context window.\nWithout a memory id the agent runs without memory, and compaction bounds the run's own loop.\n"), z.object({ "kind": z.literal("auto"), "context_length": z.number().int().describe("Maximum number of messages to retain in context").optional(), "memory_id": z.string().describe("Identifier for persistent memory across agent invocations").optional() }).describe("Deprecated, still read as it was written: the run's memory id, else the `memory_id` here.\nThe step's own `memory_id` is not read while this kind is set; switch the kind to `window`\nto use it. Without a `context_length`, or with 0, it is `off` and reads `previous_messages`.\n"), z.object({ "kind": z.literal("manual"), "messages": z.array(z.object({ "role": z.enum(["user","assistant","system"]), "content": z.string() }).describe("A single message in conversation history")) }).describe("Deprecated, still read as it was written. Move the step to `off` with `previous_messages` instead.")]).describe("Managed memory, stored by Windmill and replayed with each request. The memory is named by a memory id, see `memory_id`. While it is off, a step can supply its history in `previous_messages`."), "type": z.literal("static") }).describe("Static memory configuration passed directly to the AI agent"), z.object({ "expr": z.string().describe("JavaScript expression returning the value. Available variables - results (object with all previous step results), flow_input (flow inputs), flow_input.iter (in loops)"), "type": z.literal("javascript") }).describe("JavaScript expression evaluated at runtime. Can reference previous step results via 'results.step_id' or flow inputs via 'flow_input.property'. Inside for loops, use 'flow_input.iter.value' for the current iteration value (in while loops it equals 'flow_input.iter.index')"), z.object({ "type": z.literal("ai") }).describe("Value resolved by the AI runtime for this input. The AI engine decides how to satisfy the parameter.")]).describe("Memory configuration - can be static (MemoryConfig), JavaScript expression, or AI-determined").optional(), "memory_id": z.discriminatedUnion("type", [z.object({ "value": z.any().describe("The static value. For resources, use format '$res:path/to/resource'").optional(), "type": z.literal("static") }).describe("Static value passed directly to the step. Use for hardcoded values or resource references like '$res:path/to/resource'"), z.object({ "expr": z.string().describe("JavaScript expression returning the value. Available variables - results (object with all previous step results), flow_input (flow inputs), flow_input.iter (in loops)"), "type": z.literal("javascript") }).describe("JavaScript expression evaluated at runtime. Can reference previous step results via 'results.step_id' or flow inputs via 'flow_input.property'. Inside for loops, use 'flow_input.iter.value' for the current iteration value (in while loops it equals 'flow_input.iter.index')"), z.object({ "type": z.literal("ai") }).describe("Value resolved by the AI runtime for this input. The AI engine decides how to satisfy the parameter.")]).describe("Maps input parameters for a step. Can be a static value or a JavaScript expression that references previous results or flow inputs").describe("String. Names the memory this step reads and writes, overriding the memory id the run\nwas started with (the chat conversation, an app chat session or the `memory_id` run\nparameter). Leave unset to use the run's memory id. A fixed value shares one memory\nacross every run; an expression such as `flow_input.customer_id` keeps one memory per\nkey. When it evaluates to an empty value the agent runs without memory. Read only\nwhile `memory` is `window` or `compaction`: it is ignored when memory is off, and an\nolder `auto` or `manual` memory reads neither history input.\n").optional(), "previous_messages": z.discriminatedUnion("type", [z.object({ "value": z.any().describe("The static value. For resources, use format '$res:path/to/resource'").optional(), "type": z.literal("static") }).describe("Static value passed directly to the step. Use for hardcoded values or resource references like '$res:path/to/resource'"), z.object({ "expr": z.string().describe("JavaScript expression returning the value. Available variables - results (object with all previous step results), flow_input (flow inputs), flow_input.iter (in loops)"), "type": z.literal("javascript") }).describe("JavaScript expression evaluated at runtime. Can reference previous step results via 'results.step_id' or flow inputs via 'flow_input.property'. Inside for loops, use 'flow_input.iter.value' for the current iteration value (in while loops it equals 'flow_input.iter.index')"), z.object({ "type": z.literal("ai") }).describe("Value resolved by the AI runtime for this input. The AI engine decides how to satisfy the parameter.")]).describe("Maps input parameters for a step. Can be a static value or a JavaScript expression that references previous results or flow inputs").describe("Array of MemoryMessage. History supplied by the flow, sent between the system prompt\nand the user message. Read only while `memory` is off or absent: managed memory\nignores it, and an older `auto` or `manual` memory reads neither history input.\n").optional(), "output_schema": z.discriminatedUnion("type", [z.object({ "value": z.any().describe("The static value. For resources, use format '$res:path/to/resource'").optional(), "type": z.literal("static") }).describe("Static value passed directly to the step. Use for hardcoded values or resource references like '$res:path/to/resource'"), z.object({ "expr": z.string().describe("JavaScript expression returning the value. Available variables - results (object with all previous step results), flow_input (flow inputs), flow_input.iter (in loops)"), "type": z.literal("javascript") }).describe("JavaScript expression evaluated at runtime. Can reference previous step results via 'results.step_id' or flow inputs via 'flow_input.property'. Inside for loops, use 'flow_input.iter.value' for the current iteration value (in while loops it equals 'flow_input.iter.index')"), z.object({ "type": z.literal("ai") }).describe("Value resolved by the AI runtime for this input. The AI engine decides how to satisfy the parameter.")]).describe("Maps input parameters for a step. Can be a static value or a JavaScript expression that references previous results or flow inputs").describe("JSON Schema object defining structured output format. Used when you need the AI to return data in a specific shape.\nSupports standard JSON Schema properties: type, properties, required, items, enum, pattern, minLength, maxLength, minimum, maximum, etc.\nExample: { type: 'object', properties: { name: { type: 'string' }, age: { type: 'integer' } }, required: ['name'] }\n").optional(), "user_attachments": z.discriminatedUnion("type", [z.object({ "value": z.any().describe("The static value. For resources, use format '$res:path/to/resource'").optional(), "type": z.literal("static") }).describe("Static value passed directly to the step. Use for hardcoded values or resource references like '$res:path/to/resource'"), z.object({ "expr": z.string().describe("JavaScript expression returning the value. Available variables - results (object with all previous step results), flow_input (flow inputs), flow_input.iter (in loops)"), "type": z.literal("javascript") }).describe("JavaScript expression evaluated at runtime. Can reference previous step results via 'results.step_id' or flow inputs via 'flow_input.property'. Inside for loops, use 'flow_input.iter.value' for the current iteration value (in while loops it equals 'flow_input.iter.index')"), z.object({ "type": z.literal("ai") }).describe("Value resolved by the AI runtime for this input. The AI engine decides how to satisfy the parameter.")]).describe("Maps input parameters for a step. Can be a static value or a JavaScript expression that references previous results or flow inputs").describe("Array of file references (images or PDFs) for the AI agent.\nFormat: Array<{ bucket: string, key: string }> - S3 object references\nExample: [{ bucket: 'my-bucket', key: 'documents/report.pdf' }]\n").optional(), "enabled_tools": z.discriminatedUnion("type", [z.object({ "value": z.any().describe("The static value. For resources, use format '$res:path/to/resource'").optional(), "type": z.literal("static") }).describe("Static value passed directly to the step. Use for hardcoded values or resource references like '$res:path/to/resource'"), z.object({ "expr": z.string().describe("JavaScript expression returning the value. Available variables - results (object with all previous step results), flow_input (flow inputs), flow_input.iter (in loops)"), "type": z.literal("javascript") }).describe("JavaScript expression evaluated at runtime. Can reference previous step results via 'results.step_id' or flow inputs via 'flow_input.property'. Inside for loops, use 'flow_input.iter.value' for the current iteration value (in while loops it equals 'flow_input.iter.index')"), z.object({ "type": z.literal("ai") }).describe("Value resolved by the AI runtime for this input. The AI engine decides how to satisfy the parameter.")]).describe("Maps input parameters for a step. Can be a static value or a JavaScript expression that references previous results or flow inputs").describe("Array of strings naming which of the tools configured in `tools` the agent may call\nthis run. Leaving it unset carries every one of them; an empty array carries none.\nA tool is named as the model is shown it. An entry the model is shown nothing of is\nnamed by what identifies it instead: an MCP server by its resource path, carrying\nevery tool it exposes (which of them stays that entry's include_tools/exclude_tools),\nand a websearch entry by the reserved name '__wm_web_search', whatever summary it carries\n(no tool may take that name).\nExample: ['get_user', 'u/admin/github_mcp', '__wm_web_search']\n").optional(), "max_completion_tokens": z.discriminatedUnion("type", [z.object({ "value": z.any().describe("The static value. For resources, use format '$res:path/to/resource'").optional(), "type": z.literal("static") }).describe("Static value passed directly to the step. Use for hardcoded values or resource references like '$res:path/to/resource'"), z.object({ "expr": z.string().describe("JavaScript expression returning the value. Available variables - results (object with all previous step results), flow_input (flow inputs), flow_input.iter (in loops)"), "type": z.literal("javascript") }).describe("JavaScript expression evaluated at runtime. Can reference previous step results via 'results.step_id' or flow inputs via 'flow_input.property'. Inside for loops, use 'flow_input.iter.value' for the current iteration value (in while loops it equals 'flow_input.iter.index')"), z.object({ "type": z.literal("ai") }).describe("Value resolved by the AI runtime for this input. The AI engine decides how to satisfy the parameter.")]).describe("Maps input parameters for a step. Can be a static value or a JavaScript expression that references previous results or flow inputs").describe("Integer. Maximum number of tokens the AI will generate in its response.\nRange: 1 to 4,294,967,295. Typical values: 256-4096 for most use cases.\n").optional(), "temperature": z.discriminatedUnion("type", [z.object({ "value": z.any().describe("The static value. For resources, use format '$res:path/to/resource'").optional(), "type": z.literal("static") }).describe("Static value passed directly to the step. Use for hardcoded values or resource references like '$res:path/to/resource'"), z.object({ "expr": z.string().describe("JavaScript expression returning the value. Available variables - results (object with all previous step results), flow_input (flow inputs), flow_input.iter (in loops)"), "type": z.literal("javascript") }).describe("JavaScript expression evaluated at runtime. Can reference previous step results via 'results.step_id' or flow inputs via 'flow_input.property'. Inside for loops, use 'flow_input.iter.value' for the current iteration value (in while loops it equals 'flow_input.iter.index')"), z.object({ "type": z.literal("ai") }).describe("Value resolved by the AI runtime for this input. The AI engine decides how to satisfy the parameter.")]).describe("Maps input parameters for a step. Can be a static value or a JavaScript expression that references previous results or flow inputs").describe("Float. Controls randomness/creativity of responses.\nRange: 0.0 to 2.0 (provider-dependent)\n- 0.0 = deterministic, focused responses\n- 0.7 = balanced (common default)\n- 1.0+ = more creative/random\n").optional(), "max_iterations": z.discriminatedUnion("type", [z.object({ "value": z.any().describe("The static value. For resources, use format '$res:path/to/resource'").optional(), "type": z.literal("static") }).describe("Static value passed directly to the step. Use for hardcoded values or resource references like '$res:path/to/resource'"), z.object({ "expr": z.string().describe("JavaScript expression returning the value. Available variables - results (object with all previous step results), flow_input (flow inputs), flow_input.iter (in loops)"), "type": z.literal("javascript") }).describe("JavaScript expression evaluated at runtime. Can reference previous step results via 'results.step_id' or flow inputs via 'flow_input.property'. Inside for loops, use 'flow_input.iter.value' for the current iteration value (in while loops it equals 'flow_input.iter.index')"), z.object({ "type": z.literal("ai") }).describe("Value resolved by the AI runtime for this input. The AI engine decides how to satisfy the parameter.")]).describe("Maps input parameters for a step. Can be a static value or a JavaScript expression that references previous results or flow inputs").describe("Number. Limits how many times the agent can loop through reasoning and tool use.\nRange: 1-1000.\n").optional(), "model": z.discriminatedUnion("type", [z.object({ "value": z.any().describe("The static value. For resources, use format '$res:path/to/resource'").optional(), "type": z.literal("static") }).describe("Static value passed directly to the step. Use for hardcoded values or resource references like '$res:path/to/resource'"), z.object({ "expr": z.string().describe("JavaScript expression returning the value. Available variables - results (object with all previous step results), flow_input (flow inputs), flow_input.iter (in loops)"), "type": z.literal("javascript") }).describe("JavaScript expression evaluated at runtime. Can reference previous step results via 'results.step_id' or flow inputs via 'flow_input.property'. Inside for loops, use 'flow_input.iter.value' for the current iteration value (in while loops it equals 'flow_input.iter.index')"), z.object({ "type": z.literal("ai") }).describe("Value resolved by the AI runtime for this input. The AI engine decides how to satisfy the parameter.")]).describe("Maps input parameters for a step. Can be a static value or a JavaScript expression that references previous results or flow inputs").describe("String. Only on a step linked to a saved agent (see `agent`): replaces the model\nsaved on the agent for this step's runs, on the agent's own provider resource. An\nempty value keeps the saved model. Set it to an expression such as\n`flow_input.model` to choose the model per run.\n").optional(), "reasoning_effort": z.discriminatedUnion("type", [z.object({ "value": z.any().describe("The static value. For resources, use format '$res:path/to/resource'").optional(), "type": z.literal("static") }).describe("Static value passed directly to the step. Use for hardcoded values or resource references like '$res:path/to/resource'"), z.object({ "expr": z.string().describe("JavaScript expression returning the value. Available variables - results (object with all previous step results), flow_input (flow inputs), flow_input.iter (in loops)"), "type": z.literal("javascript") }).describe("JavaScript expression evaluated at runtime. Can reference previous step results via 'results.step_id' or flow inputs via 'flow_input.property'. Inside for loops, use 'flow_input.iter.value' for the current iteration value (in while loops it equals 'flow_input.iter.index')"), z.object({ "type": z.literal("ai") }).describe("Value resolved by the AI runtime for this input. The AI engine decides how to satisfy the parameter.")]).describe("Maps input parameters for a step. Can be a static value or a JavaScript expression that references previous results or flow inputs").describe("String. Only on a step linked to a saved agent (see `agent`): replaces the reasoning\neffort saved on the agent for this step's runs, as a provider-native token (e.g.\n'low', 'high', 'none'). An empty value sends no effort, so the model runs at its\ndefault. Leave the input out to keep the saved effort, which holds only while the\nstep runs the saved model. A step that is not linked sets both inside `provider`.\n").optional() }).describe("Input parameters for the AI agent mapped to their values"), "tools": z.array(z.object({ "id": z.string().describe("Unique identifier for this tool. Cannot contain spaces - use underscores instead (e.g., 'get_user_data' not 'get user data')"), "summary": z.string().describe("The name the AI agent calls this tool by, not a human label. On a flowmodule tool it must match ^[a-zA-Z0-9_]+$ - letters, numbers and underscores only (e.g. 'search_documentation', not 'Search documentation') - and always be set; on an mcp or websearch tool it is a plain label. Put the human-readable explanation in 'description'.").optional(), "description": z.string().describe("Free-text description of the tool given to the AI to decide when and how to call it. Overrides the description auto-derived from the underlying script.").optional(), "job_token_scopes": z.array(z.string()).nullable().describe("Scopes the token of this tool's jobs is restricted to, on top of the agent step's own restriction: a tool can only narrow it.").optional(), "value": z.any().superRefine((x, ctx) => { - const schemas = [z.intersection(z.object({ "tool_type": z.literal("flowmodule") }), z.lazy(() => flowModuleValueSchema)).describe("A tool implemented as a flow module (script, flow, etc.). The AI can call this like any other flow module"), z.object({ "tool_type": z.literal("mcp"), "resource_path": z.string().describe("Path to the MCP resource/server configuration"), "include_tools": z.array(z.string()).describe("Whitelist of specific tools to include from this MCP server").optional(), "exclude_tools": z.array(z.string()).describe("Blacklist of tools to exclude from this MCP server").optional() }).describe("Reference to an external MCP (Model Context Protocol) tool. The AI can call tools from MCP servers"), z.object({ "tool_type": z.literal("websearch") }).describe("A tool implemented as a websearch tool. The AI can call this like any other websearch tool")]; +export const flowModuleValueSchema = z.discriminatedUnion("type", [z.object({ "input_transforms": z.record(z.string(), z.discriminatedUnion("type", [z.object({ "value": z.any().describe("The static value. For resources, use format '$res:path/to/resource'").optional(), "type": z.literal("static") }).describe("Static value passed directly to the step. Use for hardcoded values or resource references like '$res:path/to/resource'"), z.object({ "expr": z.string().describe("JavaScript expression returning the value. Available variables - results (object with all previous step results), flow_input (flow inputs), flow_input.iter (in loops)"), "type": z.literal("javascript") }).describe("JavaScript expression evaluated at runtime. Can reference previous step results via 'results.step_id' or flow inputs via 'flow_input.property'. Inside for loops, use 'flow_input.iter.value' for the current iteration value (in while loops it equals 'flow_input.iter.index')"), z.object({ "type": z.literal("ai") }).describe("Value resolved by the AI runtime for this input. The AI engine decides how to satisfy the parameter.")]).describe("Maps input parameters for a step. Can be a static value or a JavaScript expression that references previous results or flow inputs")).describe("Map of parameter names to their values (static or JavaScript expressions). These become the script's input arguments"), "content": z.string().describe("The script source code. Should export a 'main' function"), "language": z.enum(["deno","bun","bunnative","python3","go","bash","powershell","postgresql","mysql","bigquery","snowflake","mssql","oracledb","graphql","nativets","php","rust","ansible","csharp","nu","java","ruby","rlang","duckdb"]).describe("Programming language for this script"), "path": z.string().describe("Optional path for saving this script").optional(), "lock": z.string().describe("Lock file content for dependencies").optional(), "type": z.literal("rawscript"), "tag": z.string().describe("Worker group tag for execution routing").optional(), "concurrent_limit": z.number().describe("Maximum concurrent executions of this script").optional(), "concurrency_time_window_s": z.number().describe("Time window for concurrent_limit").optional(), "custom_concurrency_key": z.string().describe("Custom key for grouping concurrent executions").optional(), "is_trigger": z.boolean().describe("If true, this script is a trigger that can start the flow").optional(), "assets": z.array(z.object({ "path": z.string().describe("Path to the asset"), "kind": z.enum(["s3object","resource","ducklake","datatable","volume","dbt"]).describe("Type of asset"), "access_type": z.union([z.literal("r"), z.literal("w"), z.literal("rw"), z.literal(null)]).nullable().describe("Access level for this asset").optional(), "alt_access_type": z.union([z.literal("r"), z.literal("w"), z.literal("rw"), z.literal(null)]).nullable().describe("Alternative access level").optional() })).describe("External resources this script accesses (S3 objects, resources, etc.)").optional() }).describe("Inline script with code defined directly in the flow. Use 'bun' as default language if unspecified. The script receives arguments from input_transforms"), z.object({ "input_transforms": z.record(z.string(), z.discriminatedUnion("type", [z.object({ "value": z.any().describe("The static value. For resources, use format '$res:path/to/resource'").optional(), "type": z.literal("static") }).describe("Static value passed directly to the step. Use for hardcoded values or resource references like '$res:path/to/resource'"), z.object({ "expr": z.string().describe("JavaScript expression returning the value. Available variables - results (object with all previous step results), flow_input (flow inputs), flow_input.iter (in loops)"), "type": z.literal("javascript") }).describe("JavaScript expression evaluated at runtime. Can reference previous step results via 'results.step_id' or flow inputs via 'flow_input.property'. Inside for loops, use 'flow_input.iter.value' for the current iteration value (in while loops it equals 'flow_input.iter.index')"), z.object({ "type": z.literal("ai") }).describe("Value resolved by the AI runtime for this input. The AI engine decides how to satisfy the parameter.")]).describe("Maps input parameters for a step. Can be a static value or a JavaScript expression that references previous results or flow inputs")).describe("Map of parameter names to their values (static or JavaScript expressions). These become the script's input arguments"), "path": z.string().describe("Path to the script in the workspace (e.g., 'f/scripts/send_email')"), "hash": z.string().describe("Optional specific version hash of the script to use").optional(), "type": z.literal("script"), "tag_override": z.string().describe("Override the script's default worker group tag").optional(), "is_trigger": z.boolean().describe("If true, this script is a trigger that can start the flow").optional() }).describe("Reference to an existing script by path. Use this when calling a previously saved script instead of writing inline code"), z.object({ "input_transforms": z.record(z.string(), z.discriminatedUnion("type", [z.object({ "value": z.any().describe("The static value. For resources, use format '$res:path/to/resource'").optional(), "type": z.literal("static") }).describe("Static value passed directly to the step. Use for hardcoded values or resource references like '$res:path/to/resource'"), z.object({ "expr": z.string().describe("JavaScript expression returning the value. Available variables - results (object with all previous step results), flow_input (flow inputs), flow_input.iter (in loops)"), "type": z.literal("javascript") }).describe("JavaScript expression evaluated at runtime. Can reference previous step results via 'results.step_id' or flow inputs via 'flow_input.property'. Inside for loops, use 'flow_input.iter.value' for the current iteration value (in while loops it equals 'flow_input.iter.index')"), z.object({ "type": z.literal("ai") }).describe("Value resolved by the AI runtime for this input. The AI engine decides how to satisfy the parameter.")]).describe("Maps input parameters for a step. Can be a static value or a JavaScript expression that references previous results or flow inputs")).describe("Map of parameter names to their values (static or JavaScript expressions). 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If set to a non-empty string, the flow stops with this error. If empty string, a default error message is used. If null or omitted, no error is raised.").optional(), "error_include_result": z.boolean().describe("When stopping with an error (error_message set), embed the stopping step's own result inside the raised error object (as error.result) instead of discarding it. The top-level result stays { error }. Defaults to false.").optional() }).describe("Early termination condition for a module").optional(), "skip_if": z.object({ "expr": z.string().describe("JavaScript expression that returns true to skip. Can use 'flow_input' or 'results.<step_id>'") }).describe("Conditionally skip this step based on previous results or flow inputs").optional(), "sleep": z.discriminatedUnion("type", [z.object({ "value": z.any().describe("The static value. For resources, use format '$res:path/to/resource'").optional(), "type": z.literal("static") }).describe("Static value passed directly to the step. 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Can be a static value or a JavaScript expression that references previous results or flow inputs").optional(), "cache_ttl": z.number().describe("Cache duration in seconds for this step's results").optional(), "cache_ignore_s3_path": z.boolean().optional(), "timeout": z.discriminatedUnion("type", [z.object({ "value": z.any().describe("The static value. For resources, use format '$res:path/to/resource'").optional(), "type": z.literal("static") }).describe("Static value passed directly to the step. Use for hardcoded values or resource references like '$res:path/to/resource'"), z.object({ "expr": z.string().describe("JavaScript expression returning the value. Available variables - results (object with all previous step results), flow_input (flow inputs), flow_input.iter (in loops)"), "type": z.literal("javascript") }).describe("JavaScript expression evaluated at runtime. Can reference previous step results via 'results.step_id' or flow inputs via 'flow_input.property'. Inside for loops, use 'flow_input.iter.value' for the current iteration value (in while loops it equals 'flow_input.iter.index')"), z.object({ "type": z.literal("ai") }).describe("Value resolved by the AI runtime for this input. The AI engine decides how to satisfy the parameter.")]).describe("Maps input parameters for a step. Can be a static value or a JavaScript expression that references previous results or flow inputs").optional(), "delete_after_secs": z.number().int().describe("If set, delete the step's args, result and logs after this many seconds following job completion").optional(), "summary": z.string().describe("Short description of what this step does").optional(), "mock": z.object({ "enabled": z.boolean().describe("If true, return mock value instead of executing").optional(), "return_value": z.any().describe("Value to return when mocked").optional() }).describe("Mock configuration for testing without executing the actual step").optional(), "suspend": z.object({ "required_events": z.number().int().describe("Number of approvals required before continuing").optional(), "timeout": z.number().int().describe("Timeout in seconds before auto-continuing or canceling").optional(), "resume_form": z.object({ "schema": z.record(z.string(), z.any()).describe("JSON Schema for the resume form").optional() }).describe("Form schema for collecting input when resuming").optional(), "user_auth_required": z.boolean().describe("If true, only authenticated users can approve").optional(), "user_groups_required": z.discriminatedUnion("type", [z.object({ "value": z.any().describe("The static value. For resources, use format '$res:path/to/resource'").optional(), "type": z.literal("static") }).describe("Static value passed directly to the step. Use for hardcoded values or resource references like '$res:path/to/resource'"), z.object({ "expr": z.string().describe("JavaScript expression returning the value. Available variables - results (object with all previous step results), flow_input (flow inputs), flow_input.iter (in loops)"), "type": z.literal("javascript") }).describe("JavaScript expression evaluated at runtime. Can reference previous step results via 'results.step_id' or flow inputs via 'flow_input.property'. Inside for loops, use 'flow_input.iter.value' for the current iteration value (in while loops it equals 'flow_input.iter.index')"), z.object({ "type": z.literal("ai") }).describe("Value resolved by the AI runtime for this input. The AI engine decides how to satisfy the parameter.")]).describe("Maps input parameters for a step. Can be a static value or a JavaScript expression that references previous results or flow inputs").optional(), "self_approval_disabled": z.boolean().describe("If true, the user who started the flow cannot approve").optional(), "hide_cancel": z.boolean().describe("If true, hide the cancel button on the approval form").optional(), "continue_on_disapprove_timeout": z.boolean().describe("If true, continue flow on timeout instead of canceling").optional(), "skin": z.enum(["detailed","minimal"]).describe("How the approval request is presented, on the approval page and in Slack/Teams approval messages. 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Applies to everything the step runs (loop and branch bodies, AI agent tools).").optional(), "retry": z.object({ "constant": z.object({ "attempts": z.number().int().describe("Number of retry attempts").optional(), "seconds": z.number().int().describe("Seconds to wait between retries").optional() }).describe("Retry with constant delay between attempts").optional(), "exponential": z.object({ "attempts": z.number().int().describe("Number of retry attempts").optional(), "multiplier": z.number().int().describe("Multiplier for exponential backoff").optional(), "seconds": z.number().int().gte(1).describe("Base of the exponential (seconds); the n-th retry waits multiplier × seconds^n, where n counts constant retries too").optional(), "random_factor": z.number().int().gte(0).lte(100).describe("Random jitter percentage (0-100) to avoid thundering herd").optional() }).describe("Retry with exponential backoff: the n-th retry waits multiplier × seconds^n").optional(), "retry_if": z.object({ "expr": z.string().describe("JavaScript expression that returns true to retry. 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Applies to everything the step runs (loop and branch bodies, AI agent tools).").optional(), "retry": z.object({ "constant": z.object({ "attempts": z.number().int().describe("Number of retry attempts").optional(), "seconds": z.number().int().describe("Seconds to wait between retries").optional() }).describe("Retry with constant delay between attempts").optional(), "exponential": z.object({ "attempts": z.number().int().describe("Number of retry attempts").optional(), "multiplier": z.number().int().describe("Multiplier for exponential backoff").optional(), "seconds": z.number().int().gte(1).describe("Base of the exponential (seconds); the n-th retry waits multiplier × seconds^n, where n counts constant retries too").optional(), "random_factor": z.number().int().gte(0).lte(100).describe("Random jitter percentage (0-100) to avoid thundering herd").optional() }).describe("Retry with exponential backoff: the n-th retry waits multiplier × seconds^n").optional(), "retry_if": z.object({ "expr": z.string().describe("JavaScript expression that returns true to retry. 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To carry state across iterations, a step reads its own previous-iteration result via 'results.<its_own_id>' with a first-iteration fallback - the loop's stop_after_if must then be on that inner step (a plain single-step body with stop_after_if on the loop module does not resolve 'results' across iterations and never terminates); plain counters can instead be derived from 'flow_input.iter.index', which works in every configuration. stop_after_if is evaluated after each iteration - on the loop module 'result' is the last iteration's result"), z.object({ "branches": z.array(z.object({ "summary": z.string().describe("Short description of this branch condition").optional(), "expr": z.string().describe("JavaScript expression that returns boolean. Can use 'results.step_id' or 'flow_input'. First true expr wins"), "modules": z.array(z.object({ "id": z.string().describe("Unique identifier for this step. Used to reference results via 'results.step_id'. 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Optional; unset leaves the provider default.").optional() }).describe("Complete AI provider configuration with resource reference and model selection"), "type": z.literal("static") }).describe("Static provider configuration passed directly to the AI agent"), z.object({ "expr": z.string().describe("JavaScript expression returning the value. Available variables - results (object with all previous step results), flow_input (flow inputs), flow_input.iter (in loops)"), "type": z.literal("javascript") }).describe("JavaScript expression evaluated at runtime. Can reference previous step results via 'results.step_id' or flow inputs via 'flow_input.property'. Inside for loops, use 'flow_input.iter.value' for the current iteration value (in while loops it equals 'flow_input.iter.index')"), z.object({ "type": z.literal("ai") }).describe("Value resolved by the AI runtime for this input. The AI engine decides how to satisfy the parameter.")]).describe("Provider configuration - can be static (ProviderConfig), JavaScript expression, or AI-determined").optional(), "output_type": z.discriminatedUnion("type", [z.object({ "value": z.any().describe("The static value. For resources, use format '$res:path/to/resource'").optional(), "type": z.literal("static") }).describe("Static value passed directly to the step. Use for hardcoded values or resource references like '$res:path/to/resource'"), z.object({ "expr": z.string().describe("JavaScript expression returning the value. Available variables - results (object with all previous step results), flow_input (flow inputs), flow_input.iter (in loops)"), "type": z.literal("javascript") }).describe("JavaScript expression evaluated at runtime. Can reference previous step results via 'results.step_id' or flow inputs via 'flow_input.property'. Inside for loops, use 'flow_input.iter.value' for the current iteration value (in while loops it equals 'flow_input.iter.index')"), z.object({ "type": z.literal("ai") }).describe("Value resolved by the AI runtime for this input. The AI engine decides how to satisfy the parameter.")]).describe("Maps input parameters for a step. Can be a static value or a JavaScript expression that references previous results or flow inputs").describe("Output format type.\nValid values: 'text' (default) - plain text response, 'image' - image generation\n").optional(), "user_message": z.discriminatedUnion("type", [z.object({ "value": z.any().describe("The static value. For resources, use format '$res:path/to/resource'").optional(), "type": z.literal("static") }).describe("Static value passed directly to the step. Use for hardcoded values or resource references like '$res:path/to/resource'"), z.object({ "expr": z.string().describe("JavaScript expression returning the value. Available variables - results (object with all previous step results), flow_input (flow inputs), flow_input.iter (in loops)"), "type": z.literal("javascript") }).describe("JavaScript expression evaluated at runtime. Can reference previous step results via 'results.step_id' or flow inputs via 'flow_input.property'. Inside for loops, use 'flow_input.iter.value' for the current iteration value (in while loops it equals 'flow_input.iter.index')"), z.object({ "type": z.literal("ai") }).describe("Value resolved by the AI runtime for this input. The AI engine decides how to satisfy the parameter.")]).describe("Maps input parameters for a step. Can be a static value or a JavaScript expression that references previous results or flow inputs").describe("The user's prompt/message to the AI agent. Supports variable interpolation with\nflow.input syntax. Required unless memory is off and `previous_messages` supplies\nthe prompt; image output always needs it.\n").optional(), "system_prompt": z.discriminatedUnion("type", [z.object({ "value": z.any().describe("The static value. For resources, use format '$res:path/to/resource'").optional(), "type": z.literal("static") }).describe("Static value passed directly to the step. Use for hardcoded values or resource references like '$res:path/to/resource'"), z.object({ "expr": z.string().describe("JavaScript expression returning the value. Available variables - results (object with all previous step results), flow_input (flow inputs), flow_input.iter (in loops)"), "type": z.literal("javascript") }).describe("JavaScript expression evaluated at runtime. Can reference previous step results via 'results.step_id' or flow inputs via 'flow_input.property'. Inside for loops, use 'flow_input.iter.value' for the current iteration value (in while loops it equals 'flow_input.iter.index')"), z.object({ "type": z.literal("ai") }).describe("Value resolved by the AI runtime for this input. The AI engine decides how to satisfy the parameter.")]).describe("Maps input parameters for a step. Can be a static value or a JavaScript expression that references previous results or flow inputs").describe("System instructions that guide the AI's behavior, persona, and response style. Optional.").optional(), "streaming": z.discriminatedUnion("type", [z.object({ "value": z.any().describe("The static value. For resources, use format '$res:path/to/resource'").optional(), "type": z.literal("static") }).describe("Static value passed directly to the step. Use for hardcoded values or resource references like '$res:path/to/resource'"), z.object({ "expr": z.string().describe("JavaScript expression returning the value. Available variables - results (object with all previous step results), flow_input (flow inputs), flow_input.iter (in loops)"), "type": z.literal("javascript") }).describe("JavaScript expression evaluated at runtime. Can reference previous step results via 'results.step_id' or flow inputs via 'flow_input.property'. Inside for loops, use 'flow_input.iter.value' for the current iteration value (in while loops it equals 'flow_input.iter.index')"), z.object({ "type": z.literal("ai") }).describe("Value resolved by the AI runtime for this input. The AI engine decides how to satisfy the parameter.")]).describe("Maps input parameters for a step. Can be a static value or a JavaScript expression that references previous results or flow inputs").describe("Boolean. If true, stream the AI response incrementally.\nStreaming events include: token_delta, reasoning_token_delta, tool_call, tool_call_arguments, tool_execution, tool_result\n").optional(), "memory": z.discriminatedUnion("type", [z.object({ "value": z.discriminatedUnion("kind", [z.object({ "kind": z.literal("off") }).describe("No conversation memory/context"), z.object({ "kind": z.literal("window"), "context_length": z.number().int().describe("Number of most recent messages to load and store. 0 turns memory off.") }).describe("Keeps the most recent messages of the memory named by the run's memory id (or the step's\n`memory_id`). Without a memory id the agent runs without memory.\n"), z.object({ "kind": z.literal("compaction"), "context_window": z.number().int().describe("Overrides the context window looked up from the model, in tokens. Only a model\nWindmill does not know needs one; those fall back to 128000.\n").optional() }).describe("Keeps the whole memory named by the run's memory id (or the step's `memory_id`), replacing\nits older part with a summary as the conversation approaches the model's context window.\nWithout a memory id the agent runs without memory, and compaction bounds the run's own loop.\n"), z.object({ "kind": z.literal("auto"), "context_length": z.number().int().describe("Maximum number of messages to retain in context").optional(), "memory_id": z.string().describe("Identifier for persistent memory across agent invocations").optional() }).describe("Deprecated, still read as it was written: the run's memory id, else the `memory_id` here.\nThe step's own `memory_id` is not read while this kind is set; switch the kind to `window`\nto use it. Without a `context_length`, or with 0, it is `off` and reads `previous_messages`.\n"), z.object({ "kind": z.literal("manual"), "messages": z.array(z.object({ "role": z.enum(["user","assistant","system"]), "content": z.string() }).describe("A single message in conversation history")) }).describe("Deprecated, still read as it was written. Move the step to `off` with `previous_messages` instead.")]).describe("Managed memory, stored by Windmill and replayed with each request. The memory is named by a memory id, see `memory_id`. While it is off, a step can supply its history in `previous_messages`."), "type": z.literal("static") }).describe("Static memory configuration passed directly to the AI agent"), z.object({ "expr": z.string().describe("JavaScript expression returning the value. Available variables - results (object with all previous step results), flow_input (flow inputs), flow_input.iter (in loops)"), "type": z.literal("javascript") }).describe("JavaScript expression evaluated at runtime. Can reference previous step results via 'results.step_id' or flow inputs via 'flow_input.property'. Inside for loops, use 'flow_input.iter.value' for the current iteration value (in while loops it equals 'flow_input.iter.index')"), z.object({ "type": z.literal("ai") }).describe("Value resolved by the AI runtime for this input. The AI engine decides how to satisfy the parameter.")]).describe("Memory configuration - can be static (MemoryConfig), JavaScript expression, or AI-determined").optional(), "memory_id": z.discriminatedUnion("type", [z.object({ "value": z.any().describe("The static value. For resources, use format '$res:path/to/resource'").optional(), "type": z.literal("static") }).describe("Static value passed directly to the step. Use for hardcoded values or resource references like '$res:path/to/resource'"), z.object({ "expr": z.string().describe("JavaScript expression returning the value. Available variables - results (object with all previous step results), flow_input (flow inputs), flow_input.iter (in loops)"), "type": z.literal("javascript") }).describe("JavaScript expression evaluated at runtime. Can reference previous step results via 'results.step_id' or flow inputs via 'flow_input.property'. Inside for loops, use 'flow_input.iter.value' for the current iteration value (in while loops it equals 'flow_input.iter.index')"), z.object({ "type": z.literal("ai") }).describe("Value resolved by the AI runtime for this input. The AI engine decides how to satisfy the parameter.")]).describe("Maps input parameters for a step. Can be a static value or a JavaScript expression that references previous results or flow inputs").describe("String. Names the memory this step reads and writes, overriding the memory id the run\nwas started with (the chat conversation, an app chat session or the `memory_id` run\nparameter). Leave unset to use the run's memory id. A fixed value shares one memory\nacross every run; an expression such as `flow_input.customer_id` keeps one memory per\nkey. When it evaluates to an empty value the agent runs without memory. Read only\nwhile `memory` is `window` or `compaction`: it is ignored when memory is off, and an\nolder `auto` or `manual` memory reads neither history input.\n").optional(), "previous_messages": z.discriminatedUnion("type", [z.object({ "value": z.any().describe("The static value. For resources, use format '$res:path/to/resource'").optional(), "type": z.literal("static") }).describe("Static value passed directly to the step. Use for hardcoded values or resource references like '$res:path/to/resource'"), z.object({ "expr": z.string().describe("JavaScript expression returning the value. Available variables - results (object with all previous step results), flow_input (flow inputs), flow_input.iter (in loops)"), "type": z.literal("javascript") }).describe("JavaScript expression evaluated at runtime. Can reference previous step results via 'results.step_id' or flow inputs via 'flow_input.property'. Inside for loops, use 'flow_input.iter.value' for the current iteration value (in while loops it equals 'flow_input.iter.index')"), z.object({ "type": z.literal("ai") }).describe("Value resolved by the AI runtime for this input. The AI engine decides how to satisfy the parameter.")]).describe("Maps input parameters for a step. Can be a static value or a JavaScript expression that references previous results or flow inputs").describe("Array of MemoryMessage. History supplied by the flow, sent between the system prompt\nand the user message. Read only while `memory` is off or absent: managed memory\nignores it, and an older `auto` or `manual` memory reads neither history input.\n").optional(), "output_schema": z.discriminatedUnion("type", [z.object({ "value": z.any().describe("The static value. For resources, use format '$res:path/to/resource'").optional(), "type": z.literal("static") }).describe("Static value passed directly to the step. Use for hardcoded values or resource references like '$res:path/to/resource'"), z.object({ "expr": z.string().describe("JavaScript expression returning the value. Available variables - results (object with all previous step results), flow_input (flow inputs), flow_input.iter (in loops)"), "type": z.literal("javascript") }).describe("JavaScript expression evaluated at runtime. Can reference previous step results via 'results.step_id' or flow inputs via 'flow_input.property'. Inside for loops, use 'flow_input.iter.value' for the current iteration value (in while loops it equals 'flow_input.iter.index')"), z.object({ "type": z.literal("ai") }).describe("Value resolved by the AI runtime for this input. The AI engine decides how to satisfy the parameter.")]).describe("Maps input parameters for a step. Can be a static value or a JavaScript expression that references previous results or flow inputs").describe("JSON Schema object defining structured output format. Used when you need the AI to return data in a specific shape.\nSupports standard JSON Schema properties: type, properties, required, items, enum, pattern, minLength, maxLength, minimum, maximum, etc.\nExample: { type: 'object', properties: { name: { type: 'string' }, age: { type: 'integer' } }, required: ['name'] }\n").optional(), "user_attachments": z.discriminatedUnion("type", [z.object({ "value": z.any().describe("The static value. For resources, use format '$res:path/to/resource'").optional(), "type": z.literal("static") }).describe("Static value passed directly to the step. Use for hardcoded values or resource references like '$res:path/to/resource'"), z.object({ "expr": z.string().describe("JavaScript expression returning the value. Available variables - results (object with all previous step results), flow_input (flow inputs), flow_input.iter (in loops)"), "type": z.literal("javascript") }).describe("JavaScript expression evaluated at runtime. Can reference previous step results via 'results.step_id' or flow inputs via 'flow_input.property'. Inside for loops, use 'flow_input.iter.value' for the current iteration value (in while loops it equals 'flow_input.iter.index')"), z.object({ "type": z.literal("ai") }).describe("Value resolved by the AI runtime for this input. The AI engine decides how to satisfy the parameter.")]).describe("Maps input parameters for a step. Can be a static value or a JavaScript expression that references previous results or flow inputs").describe("Array of file references (images or PDFs) for the AI agent.\nFormat: Array<{ bucket: string, key: string }> - S3 object references\nExample: [{ bucket: 'my-bucket', key: 'documents/report.pdf' }]\n").optional(), "enabled_tools": z.discriminatedUnion("type", [z.object({ "value": z.any().describe("The static value. For resources, use format '$res:path/to/resource'").optional(), "type": z.literal("static") }).describe("Static value passed directly to the step. Use for hardcoded values or resource references like '$res:path/to/resource'"), z.object({ "expr": z.string().describe("JavaScript expression returning the value. Available variables - results (object with all previous step results), flow_input (flow inputs), flow_input.iter (in loops)"), "type": z.literal("javascript") }).describe("JavaScript expression evaluated at runtime. Can reference previous step results via 'results.step_id' or flow inputs via 'flow_input.property'. Inside for loops, use 'flow_input.iter.value' for the current iteration value (in while loops it equals 'flow_input.iter.index')"), z.object({ "type": z.literal("ai") }).describe("Value resolved by the AI runtime for this input. The AI engine decides how to satisfy the parameter.")]).describe("Maps input parameters for a step. Can be a static value or a JavaScript expression that references previous results or flow inputs").describe("Array of strings naming which of the tools configured in `tools` the agent may call\nthis run. Leaving it unset carries every one of them; an empty array carries none.\nA tool is named as the model is shown it. An entry the model is shown nothing of is\nnamed by what identifies it instead: an MCP server by its resource path, carrying\nevery tool it exposes (which of them stays that entry's include_tools/exclude_tools),\nand a websearch entry by the reserved name '__wm_web_search', whatever summary it carries\n(no tool may take that name).\nExample: ['get_user', 'u/admin/github_mcp', '__wm_web_search']\n").optional(), "max_completion_tokens": z.discriminatedUnion("type", [z.object({ "value": z.any().describe("The static value. For resources, use format '$res:path/to/resource'").optional(), "type": z.literal("static") }).describe("Static value passed directly to the step. Use for hardcoded values or resource references like '$res:path/to/resource'"), z.object({ "expr": z.string().describe("JavaScript expression returning the value. Available variables - results (object with all previous step results), flow_input (flow inputs), flow_input.iter (in loops)"), "type": z.literal("javascript") }).describe("JavaScript expression evaluated at runtime. Can reference previous step results via 'results.step_id' or flow inputs via 'flow_input.property'. Inside for loops, use 'flow_input.iter.value' for the current iteration value (in while loops it equals 'flow_input.iter.index')"), z.object({ "type": z.literal("ai") }).describe("Value resolved by the AI runtime for this input. The AI engine decides how to satisfy the parameter.")]).describe("Maps input parameters for a step. Can be a static value or a JavaScript expression that references previous results or flow inputs").describe("Integer. Maximum number of tokens the AI will generate in its response.\nRange: 1 to 4,294,967,295. Typical values: 256-4096 for most use cases.\n").optional(), "temperature": z.discriminatedUnion("type", [z.object({ "value": z.any().describe("The static value. For resources, use format '$res:path/to/resource'").optional(), "type": z.literal("static") }).describe("Static value passed directly to the step. Use for hardcoded values or resource references like '$res:path/to/resource'"), z.object({ "expr": z.string().describe("JavaScript expression returning the value. Available variables - results (object with all previous step results), flow_input (flow inputs), flow_input.iter (in loops)"), "type": z.literal("javascript") }).describe("JavaScript expression evaluated at runtime. Can reference previous step results via 'results.step_id' or flow inputs via 'flow_input.property'. Inside for loops, use 'flow_input.iter.value' for the current iteration value (in while loops it equals 'flow_input.iter.index')"), z.object({ "type": z.literal("ai") }).describe("Value resolved by the AI runtime for this input. The AI engine decides how to satisfy the parameter.")]).describe("Maps input parameters for a step. Can be a static value or a JavaScript expression that references previous results or flow inputs").describe("Float. Controls randomness/creativity of responses.\nRange: 0.0 to 2.0 (provider-dependent)\n- 0.0 = deterministic, focused responses\n- 0.7 = balanced (common default)\n- 1.0+ = more creative/random\n").optional(), "max_iterations": z.discriminatedUnion("type", [z.object({ "value": z.any().describe("The static value. For resources, use format '$res:path/to/resource'").optional(), "type": z.literal("static") }).describe("Static value passed directly to the step. Use for hardcoded values or resource references like '$res:path/to/resource'"), z.object({ "expr": z.string().describe("JavaScript expression returning the value. Available variables - results (object with all previous step results), flow_input (flow inputs), flow_input.iter (in loops)"), "type": z.literal("javascript") }).describe("JavaScript expression evaluated at runtime. Can reference previous step results via 'results.step_id' or flow inputs via 'flow_input.property'. Inside for loops, use 'flow_input.iter.value' for the current iteration value (in while loops it equals 'flow_input.iter.index')"), z.object({ "type": z.literal("ai") }).describe("Value resolved by the AI runtime for this input. The AI engine decides how to satisfy the parameter.")]).describe("Maps input parameters for a step. Can be a static value or a JavaScript expression that references previous results or flow inputs").describe("Number. Limits how many times the agent can loop through reasoning and tool use.\nRange: 1-1000.\n").optional(), "model": z.discriminatedUnion("type", [z.object({ "value": z.any().describe("The static value. For resources, use format '$res:path/to/resource'").optional(), "type": z.literal("static") }).describe("Static value passed directly to the step. Use for hardcoded values or resource references like '$res:path/to/resource'"), z.object({ "expr": z.string().describe("JavaScript expression returning the value. Available variables - results (object with all previous step results), flow_input (flow inputs), flow_input.iter (in loops)"), "type": z.literal("javascript") }).describe("JavaScript expression evaluated at runtime. Can reference previous step results via 'results.step_id' or flow inputs via 'flow_input.property'. Inside for loops, use 'flow_input.iter.value' for the current iteration value (in while loops it equals 'flow_input.iter.index')"), z.object({ "type": z.literal("ai") }).describe("Value resolved by the AI runtime for this input. The AI engine decides how to satisfy the parameter.")]).describe("Maps input parameters for a step. Can be a static value or a JavaScript expression that references previous results or flow inputs").describe("String. Only on a step linked to a saved agent (see `agent`): replaces the model\nsaved on the agent for this step's runs, on the agent's own provider resource. An\nempty value keeps the saved model. Set it to an expression such as\n`flow_input.model` to choose the model per run.\n").optional(), "reasoning_effort": z.discriminatedUnion("type", [z.object({ "value": z.any().describe("The static value. For resources, use format '$res:path/to/resource'").optional(), "type": z.literal("static") }).describe("Static value passed directly to the step. Use for hardcoded values or resource references like '$res:path/to/resource'"), z.object({ "expr": z.string().describe("JavaScript expression returning the value. Available variables - results (object with all previous step results), flow_input (flow inputs), flow_input.iter (in loops)"), "type": z.literal("javascript") }).describe("JavaScript expression evaluated at runtime. Can reference previous step results via 'results.step_id' or flow inputs via 'flow_input.property'. Inside for loops, use 'flow_input.iter.value' for the current iteration value (in while loops it equals 'flow_input.iter.index')"), z.object({ "type": z.literal("ai") }).describe("Value resolved by the AI runtime for this input. The AI engine decides how to satisfy the parameter.")]).describe("Maps input parameters for a step. Can be a static value or a JavaScript expression that references previous results or flow inputs").describe("String. Only on a step linked to a saved agent (see `agent`): replaces the reasoning\neffort saved on the agent for this step's runs, as a provider-native token (e.g.\n'low', 'high', 'none'). An empty value sends no effort, so the model runs at its\ndefault. Leave the input out to keep the saved effort, which holds only while the\nstep runs the saved model. A step that is not linked sets both inside `provider`.\n").optional() }).describe("Input parameters for the AI agent mapped to their values"), "tools": z.array(z.object({ "id": z.string().describe("Unique identifier for this tool. Cannot contain spaces - use underscores instead (e.g., 'get_user_data' not 'get user data')"), "summary": z.string().describe("The name the AI agent calls this tool by, not a human label. On a flowmodule tool it must match ^[a-zA-Z0-9_]+$ - letters, numbers and underscores only (e.g. 'search_documentation', not 'Search documentation') - and always be set; on an mcp, websearch or question tool it is a plain label. Put the human-readable explanation in 'description'.").optional(), "description": z.string().describe("Free-text description of the tool given to the AI to decide when and how to call it. Overrides the description auto-derived from the underlying script.").optional(), "job_token_scopes": z.array(z.string()).nullable().describe("Scopes the token of this tool's jobs is restricted to, on top of the agent step's own restriction: a tool can only narrow it.").optional(), "requires_approval": z.boolean().describe("Flowmodule and mcp tools only. Each call waits for a person to approve or reject it from the flow's run page or chat, without the agent holding a worker. Calls in the same turn that do not require approval run right away. A rejected call, or one nobody answers within 30 minutes, is reported to the AI as not run.").optional(), "value": z.any().superRefine((x, ctx) => { + const schemas = [z.intersection(z.object({ "tool_type": z.literal("flowmodule") }), z.lazy(() => flowModuleValueSchema)).describe("A tool implemented as a flow module (script, flow, etc.). The AI can call this like any other flow module"), z.object({ "tool_type": z.literal("mcp"), "resource_path": z.string().describe("Path to the MCP resource/server configuration"), "include_tools": z.array(z.string()).describe("Whitelist of specific tools to include from this MCP server").optional(), "exclude_tools": z.array(z.string()).describe("Blacklist of tools to exclude from this MCP server").optional() }).describe("Reference to an external MCP (Model Context Protocol) tool. The AI can call tools from MCP servers"), z.object({ "tool_type": z.literal("websearch") }).describe("A tool implemented as a websearch tool. The AI can call this like any other websearch tool"), z.object({ "tool_type": z.literal("question"), "timeout": z.number().int().describe("Seconds to wait for an answer before the question is reported to the AI as timed out. Defaults to 1800.").optional() }).describe("Built-in tool the AI calls as ask_question: the agent stops, releasing its worker, until someone answers from the flow's run page or chat or the question times out, then resumes with the answer as the tool result.")]; const errors = schemas.reduce<z.ZodError[]>( (errors, schema) => ((result) => @@ -20,8 +20,8 @@ export const flowModuleValueSchema = z.discriminatedUnion("type", [z.object({ "i }).describe("The implementation of a tool. Can be a flow module (script/flow) or an MCP tool reference") }).describe("A tool available to an AI agent. Can be a flow module or an external MCP (Model Context Protocol) tool")).describe("Array of tools the agent can use. The agent decides which tools to call based on the task").optional(), "type": z.literal("aiagent"), "tag": z.string().describe("Worker group tag for execution routing. If not set, the AI agent step runs on the flow's tag (default `flow`)").optional(), "omit_output_from_conversation": z.boolean().describe("If true, this AI agent step does not persist its assistant or tool messages to the flow conversation when chat mode is enabled.").default(false), "agent": z.string().describe("Path of a reusable `ai_agent` resource (hybrid linking). When set, the agent brain\nconfig (provider/model/system prompt/etc.) and tool set are resolved at runtime from\nthat resource; the module's input_transforms then only carry the flow-local inputs\n(user_message, user_attachments, enabled_tools and the history inputs memory_id and previous_messages)\nand, optionally, the `model` and `reasoning_effort` overrides of what the agent saved.\n").optional(), "tool_inputs": z.record(z.string(), z.record(z.string(), z.discriminatedUnion("type", [z.object({ "value": z.any().describe("The static value. For resources, use format '$res:path/to/resource'").optional(), "type": z.literal("static") }).describe("Static value passed directly to the step. Use for hardcoded values or resource references like '$res:path/to/resource'"), z.object({ "expr": z.string().describe("JavaScript expression returning the value. Available variables - results (object with all previous step results), flow_input (flow inputs), flow_input.iter (in loops)"), "type": z.literal("javascript") }).describe("JavaScript expression evaluated at runtime. Can reference previous step results via 'results.step_id' or flow inputs via 'flow_input.property'. Inside for loops, use 'flow_input.iter.value' for the current iteration value (in while loops it equals 'flow_input.iter.index')"), z.object({ "type": z.literal("ai") }).describe("Value resolved by the AI runtime for this input. The AI engine decides how to satisfy the parameter.")]).describe("Maps input parameters for a step. Can be a static value or a JavaScript expression that references previous results or flow inputs"))).describe("Host-local wiring for an agent's tool inputs, keyed by tool id then input key. Binds the\nreferenced agent's tools to this flow's context (flow_input/results) without mutating the\nshared resource; overlaid onto the tools' input_transforms at runtime — including when\n`agent` is unset, since a step forked for editing keeps these overrides until it is saved\nback or unlinked.\n").optional(), "parallel": z.boolean().describe("If true, the agent can execute multiple tool calls in parallel").optional() }).describe("AI agent step that can use tools to accomplish tasks. The agent receives inputs and can call any of its configured tools to complete the task"), z.object({ "input_transforms": z.object({ "provider": z.discriminatedUnion("type", [z.object({ "value": z.object({ "kind": z.enum(["openai","azure_openai","azure_foundry","anthropic","mistral","deepseek","googleai","groq","openrouter","togetherai","customai","aws_bedrock","typesafe","cloudflare"]).describe("Supported AI provider types"), "resource": z.string().describe("Resource reference in format '$res:{resource_path}' pointing to provider credentials"), "model": z.string().describe("Model identifier (e.g., 'gpt-4', 'claude-3-opus-20240229', 'gemini-pro')"), "reasoning_effort": z.string().describe("Provider-native reasoning effort token (e.g. 'low', 'high', 'none') for models that support extended thinking. Optional; unset leaves the provider default.").optional() }).describe("Complete AI provider configuration with resource reference and model selection"), "type": z.literal("static") }).describe("Static provider configuration passed directly to the AI agent"), z.object({ "expr": z.string().describe("JavaScript expression returning the value. Available variables - results (object with all previous step results), flow_input (flow inputs), flow_input.iter (in loops)"), "type": z.literal("javascript") }).describe("JavaScript expression evaluated at runtime. Can reference previous step results via 'results.step_id' or flow inputs via 'flow_input.property'. Inside for loops, use 'flow_input.iter.value' for the current iteration value (in while loops it equals 'flow_input.iter.index')"), z.object({ "type": z.literal("ai") }).describe("Value resolved by the AI runtime for this input. The AI engine decides how to satisfy the parameter.")]).describe("Provider configuration - can be static (ProviderConfig), JavaScript expression, or AI-determined"), "state": z.discriminatedUnion("type", [z.object({ "value": z.any().describe("The static value. For resources, use format '$res:path/to/resource'").optional(), "type": z.literal("static") }).describe("Static value passed directly to the step. Use for hardcoded values or resource references like '$res:path/to/resource'"), z.object({ "expr": z.string().describe("JavaScript expression returning the value. Available variables - results (object with all previous step results), flow_input (flow inputs), flow_input.iter (in loops)"), "type": z.literal("javascript") }).describe("JavaScript expression evaluated at runtime. Can reference previous step results via 'results.step_id' or flow inputs via 'flow_input.property'. Inside for loops, use 'flow_input.iter.value' for the current iteration value (in while loops it equals 'flow_input.iter.index')"), z.object({ "type": z.literal("ai") }).describe("Value resolved by the AI runtime for this input. The AI engine decides how to satisfy the parameter.")]).describe("Maps input parameters for a step. Can be a static value or a JavaScript expression that references previous results or flow inputs").describe("What the questions are asked about: a string, an object or an array of strings.\nAn object with descriptive keys holding only what the questions need works best.\nExample: { message: flow_input.message, plan: results.a.plan }\n"), "questions": z.discriminatedUnion("type", [z.object({ "value": z.any().describe("The static value. For resources, use format '$res:path/to/resource'").optional(), "type": z.literal("static") }).describe("Static value passed directly to the step. Use for hardcoded values or resource references like '$res:path/to/resource'"), z.object({ "expr": z.string().describe("JavaScript expression returning the value. Available variables - results (object with all previous step results), flow_input (flow inputs), flow_input.iter (in loops)"), "type": z.literal("javascript") }).describe("JavaScript expression evaluated at runtime. Can reference previous step results via 'results.step_id' or flow inputs via 'flow_input.property'. Inside for loops, use 'flow_input.iter.value' for the current iteration value (in while loops it equals 'flow_input.iter.index')"), z.object({ "type": z.literal("ai") }).describe("Value resolved by the AI runtime for this input. The AI engine decides how to satisfy the parameter.")]).describe("Maps input parameters for a step. Can be a static value or a JavaScript expression that references previous results or flow inputs").describe("Object mapping each question name to { type, instructions, criteria }, where type is:\n- 'choice': criteria maps each option to its description (up to 255); the answer\n has choice, probabilities and confidence\n- 'score': criteria is an ordered array of 2 to 10 level descriptions; the answer\n has score, legend, probabilities and confidence\n- 'noul': yes/no, criteria optionally { true, false } descriptions; the answer has\n noul, the probability of yes (0 to 1)\nExample: { intent: { type: 'choice', instructions: 'What does the customer want?',\ncriteria: { refund: 'Money back', bug: 'Something is broken' } } }\n") }).describe("Input parameters for the decision mapped to their values"), "type": z.literal("aidecision"), "tag": z.string().describe("Worker group tag for execution routing. If not set, the step runs on the flow's tag (default `flow`)").optional() }).describe("AI decision step: one call to a decision model (TypeSafe's Jev, Cloudflare's\nJev-compatible Clef, or OpenAI's Decisions API) that answers typed questions about a\nstate with calibrated probabilities, instead of generating text.\nPrefer it over an AI agent to classify, route, score or check something: it is fast,\ncheap and its answers are structured. Its result is { output: { <question name>: answer },\nmodel, usage }, so a later step reads e.g. results.<id>.output.intent.choice. To route on\nthe answers, follow it with a branchone whose branch exprs read\nresults.<id>.output.<question>.choice. Usable as an AI agent tool, where the calling agent\nsupplies the state.\n")]).describe("The actual implementation of a flow step. Can be a script (inline or referenced), subflow, loop, branch, or special module type") -export const flowModuleSchema = z.object({ "id": z.string().describe("Unique identifier for this step. Used to reference results via 'results.step_id'. Must be a valid identifier (alphanumeric, underscore, hyphen)"), "value": z.discriminatedUnion("type", [z.object({ "input_transforms": z.record(z.string(), z.discriminatedUnion("type", [z.object({ "value": z.any().describe("The static value. For resources, use format '$res:path/to/resource'").optional(), "type": z.literal("static") }).describe("Static value passed directly to the step. Use for hardcoded values or resource references like '$res:path/to/resource'"), z.object({ "expr": z.string().describe("JavaScript expression returning the value. Available variables - results (object with all previous step results), flow_input (flow inputs), flow_input.iter (in loops)"), "type": z.literal("javascript") }).describe("JavaScript expression evaluated at runtime. Can reference previous step results via 'results.step_id' or flow inputs via 'flow_input.property'. Inside for loops, use 'flow_input.iter.value' for the current iteration value (in while loops it equals 'flow_input.iter.index')"), z.object({ "type": z.literal("ai") }).describe("Value resolved by the AI runtime for this input. The AI engine decides how to satisfy the parameter.")]).describe("Maps input parameters for a step. Can be a static value or a JavaScript expression that references previous results or flow inputs")).describe("Map of parameter names to their values (static or JavaScript expressions). These become the script's input arguments"), "content": z.string().describe("The script source code. Should export a 'main' function"), "language": z.enum(["deno","bun","bunnative","python3","go","bash","powershell","postgresql","mysql","bigquery","snowflake","mssql","oracledb","graphql","nativets","php","rust","ansible","csharp","nu","java","ruby","rlang","duckdb"]).describe("Programming language for this script"), "path": z.string().describe("Optional path for saving this script").optional(), "lock": z.string().describe("Lock file content for dependencies").optional(), "type": z.literal("rawscript"), "tag": z.string().describe("Worker group tag for execution routing").optional(), "concurrent_limit": z.number().describe("Maximum concurrent executions of this script").optional(), "concurrency_time_window_s": z.number().describe("Time window for concurrent_limit").optional(), "custom_concurrency_key": z.string().describe("Custom key for grouping concurrent executions").optional(), "is_trigger": z.boolean().describe("If true, this script is a trigger that can start the flow").optional(), "assets": z.array(z.object({ "path": z.string().describe("Path to the asset"), "kind": z.enum(["s3object","resource","ducklake","datatable","volume","dbt"]).describe("Type of asset"), "access_type": z.union([z.literal("r"), z.literal("w"), z.literal("rw"), z.literal(null)]).nullable().describe("Access level for this asset").optional(), "alt_access_type": z.union([z.literal("r"), z.literal("w"), z.literal("rw"), z.literal(null)]).nullable().describe("Alternative access level").optional() })).describe("External resources this script accesses (S3 objects, resources, etc.)").optional() }).describe("Inline script with code defined directly in the flow. Use 'bun' as default language if unspecified. The script receives arguments from input_transforms"), z.object({ "input_transforms": z.record(z.string(), z.discriminatedUnion("type", [z.object({ "value": z.any().describe("The static value. For resources, use format '$res:path/to/resource'").optional(), "type": z.literal("static") }).describe("Static value passed directly to the step. Use for hardcoded values or resource references like '$res:path/to/resource'"), z.object({ "expr": z.string().describe("JavaScript expression returning the value. Available variables - results (object with all previous step results), flow_input (flow inputs), flow_input.iter (in loops)"), "type": z.literal("javascript") }).describe("JavaScript expression evaluated at runtime. Can reference previous step results via 'results.step_id' or flow inputs via 'flow_input.property'. Inside for loops, use 'flow_input.iter.value' for the current iteration value (in while loops it equals 'flow_input.iter.index')"), z.object({ "type": z.literal("ai") }).describe("Value resolved by the AI runtime for this input. The AI engine decides how to satisfy the parameter.")]).describe("Maps input parameters for a step. Can be a static value or a JavaScript expression that references previous results or flow inputs")).describe("Map of parameter names to their values (static or JavaScript expressions). These become the script's input arguments"), "path": z.string().describe("Path to the script in the workspace (e.g., 'f/scripts/send_email')"), "hash": z.string().describe("Optional specific version hash of the script to use").optional(), "type": z.literal("script"), "tag_override": z.string().describe("Override the script's default worker group tag").optional(), "is_trigger": z.boolean().describe("If true, this script is a trigger that can start the flow").optional() }).describe("Reference to an existing script by path. Use this when calling a previously saved script instead of writing inline code"), z.object({ "input_transforms": z.record(z.string(), z.discriminatedUnion("type", [z.object({ "value": z.any().describe("The static value. For resources, use format '$res:path/to/resource'").optional(), "type": z.literal("static") }).describe("Static value passed directly to the step. Use for hardcoded values or resource references like '$res:path/to/resource'"), z.object({ "expr": z.string().describe("JavaScript expression returning the value. Available variables - results (object with all previous step results), flow_input (flow inputs), flow_input.iter (in loops)"), "type": z.literal("javascript") }).describe("JavaScript expression evaluated at runtime. Can reference previous step results via 'results.step_id' or flow inputs via 'flow_input.property'. Inside for loops, use 'flow_input.iter.value' for the current iteration value (in while loops it equals 'flow_input.iter.index')"), z.object({ "type": z.literal("ai") }).describe("Value resolved by the AI runtime for this input. The AI engine decides how to satisfy the parameter.")]).describe("Maps input parameters for a step. Can be a static value or a JavaScript expression that references previous results or flow inputs")).describe("Map of parameter names to their values (static or JavaScript expressions). These become the subflow's input arguments"), "path": z.string().describe("Path to the flow in the workspace (e.g., 'f/flows/process_user')"), "type": z.literal("flow") }).describe("Reference to an existing flow by path. Use this to call another flow as a subflow"), z.object({ "modules": z.array(z.lazy(() => flowModuleSchema)).describe("Steps to execute for each iteration. These can reference the iteration value via 'flow_input.iter.value'"), "iterator": z.discriminatedUnion("type", [z.object({ "value": z.any().describe("The static value. For resources, use format '$res:path/to/resource'").optional(), "type": z.literal("static") }).describe("Static value passed directly to the step. Use for hardcoded values or resource references like '$res:path/to/resource'"), z.object({ "expr": z.string().describe("JavaScript expression returning the value. Available variables - results (object with all previous step results), flow_input (flow inputs), flow_input.iter (in loops)"), "type": z.literal("javascript") }).describe("JavaScript expression evaluated at runtime. Can reference previous step results via 'results.step_id' or flow inputs via 'flow_input.property'. Inside for loops, use 'flow_input.iter.value' for the current iteration value (in while loops it equals 'flow_input.iter.index')"), z.object({ "type": z.literal("ai") }).describe("Value resolved by the AI runtime for this input. The AI engine decides how to satisfy the parameter.")]).describe("Maps input parameters for a step. Can be a static value or a JavaScript expression that references previous results or flow inputs"), "skip_failures": z.boolean().describe("If true, iteration failures don't stop the loop. Failed iterations return null"), "type": z.literal("forloopflow"), "parallel": z.boolean().describe("If true, iterations run concurrently (faster for I/O-bound operations). Use with parallelism to control concurrency").optional(), "parallelism": z.discriminatedUnion("type", [z.object({ "value": z.any().describe("The static value. For resources, use format '$res:path/to/resource'").optional(), "type": z.literal("static") }).describe("Static value passed directly to the step. Use for hardcoded values or resource references like '$res:path/to/resource'"), z.object({ "expr": z.string().describe("JavaScript expression returning the value. Available variables - results (object with all previous step results), flow_input (flow inputs), flow_input.iter (in loops)"), "type": z.literal("javascript") }).describe("JavaScript expression evaluated at runtime. Can reference previous step results via 'results.step_id' or flow inputs via 'flow_input.property'. Inside for loops, use 'flow_input.iter.value' for the current iteration value (in while loops it equals 'flow_input.iter.index')"), z.object({ "type": z.literal("ai") }).describe("Value resolved by the AI runtime for this input. The AI engine decides how to satisfy the parameter.")]).describe("Maps input parameters for a step. Can be a static value or a JavaScript expression that references previous results or flow inputs").optional(), "squash": z.boolean().optional() }).describe("Executes nested modules in a loop over an iterator. Inside the loop, use 'flow_input.iter.value' to access the current iteration value, and 'flow_input.iter.index' for the index. Supports parallel execution for better performance on I/O-bound operations"), z.object({ "modules": z.array(z.lazy(() => flowModuleSchema)).describe("Steps to execute in each iteration"), "skip_failures": z.boolean().describe("If true, iteration failures don't stop the loop. Failed iterations return null"), "type": z.literal("whileloopflow"), "parallel": z.boolean().describe("If true, iterations run concurrently (use with caution in while loops)").optional(), "parallelism": z.discriminatedUnion("type", [z.object({ "value": z.any().describe("The static value. For resources, use format '$res:path/to/resource'").optional(), "type": z.literal("static") }).describe("Static value passed directly to the step. Use for hardcoded values or resource references like '$res:path/to/resource'"), z.object({ "expr": z.string().describe("JavaScript expression returning the value. Available variables - results (object with all previous step results), flow_input (flow inputs), flow_input.iter (in loops)"), "type": z.literal("javascript") }).describe("JavaScript expression evaluated at runtime. Can reference previous step results via 'results.step_id' or flow inputs via 'flow_input.property'. Inside for loops, use 'flow_input.iter.value' for the current iteration value (in while loops it equals 'flow_input.iter.index')"), z.object({ "type": z.literal("ai") }).describe("Value resolved by the AI runtime for this input. The AI engine decides how to satisfy the parameter.")]).describe("Maps input parameters for a step. Can be a static value or a JavaScript expression that references previous results or flow inputs").optional(), "squash": z.boolean().optional() }).describe("Executes nested modules repeatedly until stopped. The implicit iterator is the iteration counter, so 'flow_input.iter.value' equals 'flow_input.iter.index' (0, 1, 2, ...) and never carries state. To carry state across iterations, a step reads its own previous-iteration result via 'results.<its_own_id>' with a first-iteration fallback - the loop's stop_after_if must then be on that inner step (a plain single-step body with stop_after_if on the loop module does not resolve 'results' across iterations and never terminates); plain counters can instead be derived from 'flow_input.iter.index', which works in every configuration. stop_after_if is evaluated after each iteration - on the loop module 'result' is the last iteration's result"), z.object({ "branches": z.array(z.object({ "summary": z.string().describe("Short description of this branch condition").optional(), "expr": z.string().describe("JavaScript expression that returns boolean. Can use 'results.step_id' or 'flow_input'. First true expr wins"), "modules": z.array(z.lazy(() => flowModuleSchema)).describe("Steps to execute if this branch's expr is true") })).describe("Array of branches to evaluate in order. The first branch with expr evaluating to true executes"), "default": z.array(z.lazy(() => flowModuleSchema)).describe("Steps to execute if no branch expressions match"), "type": z.literal("branchone") }).describe("Conditional branching where only the first matching branch executes. Branches are evaluated in order, and the first one with a true expression runs. If no branches match, the default branch executes"), z.object({ "branches": z.array(z.object({ "summary": z.string().describe("Short description of this branch's purpose").optional(), "skip_failure": z.boolean().describe("If true, failure in this branch doesn't fail the entire flow").optional(), "modules": z.array(z.lazy(() => flowModuleSchema)).describe("Steps to execute in this branch") })).describe("Array of branches that all execute (either in parallel or sequentially)"), "type": z.literal("branchall"), "parallel": z.boolean().describe("If true, all branches execute concurrently. If false, they execute sequentially").optional() }).describe("Parallel branching where all branches execute simultaneously. Unlike BranchOne, all branches run regardless of conditions. Useful for executing independent tasks concurrently"), z.object({ "type": z.literal("identity"), "flow": z.boolean().describe("If true, marks this as a flow identity (special handling)").optional() }).describe("Pass-through module that returns its input unchanged. Useful for flow structure or as a placeholder"), z.object({ "input_transforms": z.object({ "provider": z.discriminatedUnion("type", [z.object({ "value": z.object({ "kind": z.enum(["openai","azure_openai","azure_foundry","anthropic","mistral","deepseek","googleai","groq","openrouter","togetherai","customai","aws_bedrock","typesafe","cloudflare"]).describe("Supported AI provider types"), "resource": z.string().describe("Resource reference in format '$res:{resource_path}' pointing to provider credentials"), "model": z.string().describe("Model identifier (e.g., 'gpt-4', 'claude-3-opus-20240229', 'gemini-pro')"), "reasoning_effort": z.string().describe("Provider-native reasoning effort token (e.g. 'low', 'high', 'none') for models that support extended thinking. Optional; unset leaves the provider default.").optional() }).describe("Complete AI provider configuration with resource reference and model selection"), "type": z.literal("static") }).describe("Static provider configuration passed directly to the AI agent"), z.object({ "expr": z.string().describe("JavaScript expression returning the value. Available variables - results (object with all previous step results), flow_input (flow inputs), flow_input.iter (in loops)"), "type": z.literal("javascript") }).describe("JavaScript expression evaluated at runtime. Can reference previous step results via 'results.step_id' or flow inputs via 'flow_input.property'. Inside for loops, use 'flow_input.iter.value' for the current iteration value (in while loops it equals 'flow_input.iter.index')"), z.object({ "type": z.literal("ai") }).describe("Value resolved by the AI runtime for this input. The AI engine decides how to satisfy the parameter.")]).describe("Provider configuration - can be static (ProviderConfig), JavaScript expression, or AI-determined").optional(), "output_type": z.discriminatedUnion("type", [z.object({ "value": z.any().describe("The static value. For resources, use format '$res:path/to/resource'").optional(), "type": z.literal("static") }).describe("Static value passed directly to the step. Use for hardcoded values or resource references like '$res:path/to/resource'"), z.object({ "expr": z.string().describe("JavaScript expression returning the value. Available variables - results (object with all previous step results), flow_input (flow inputs), flow_input.iter (in loops)"), "type": z.literal("javascript") }).describe("JavaScript expression evaluated at runtime. Can reference previous step results via 'results.step_id' or flow inputs via 'flow_input.property'. Inside for loops, use 'flow_input.iter.value' for the current iteration value (in while loops it equals 'flow_input.iter.index')"), z.object({ "type": z.literal("ai") }).describe("Value resolved by the AI runtime for this input. The AI engine decides how to satisfy the parameter.")]).describe("Maps input parameters for a step. Can be a static value or a JavaScript expression that references previous results or flow inputs").describe("Output format type.\nValid values: 'text' (default) - plain text response, 'image' - image generation\n").optional(), "user_message": z.discriminatedUnion("type", [z.object({ "value": z.any().describe("The static value. For resources, use format '$res:path/to/resource'").optional(), "type": z.literal("static") }).describe("Static value passed directly to the step. Use for hardcoded values or resource references like '$res:path/to/resource'"), z.object({ "expr": z.string().describe("JavaScript expression returning the value. Available variables - results (object with all previous step results), flow_input (flow inputs), flow_input.iter (in loops)"), "type": z.literal("javascript") }).describe("JavaScript expression evaluated at runtime. Can reference previous step results via 'results.step_id' or flow inputs via 'flow_input.property'. Inside for loops, use 'flow_input.iter.value' for the current iteration value (in while loops it equals 'flow_input.iter.index')"), z.object({ "type": z.literal("ai") }).describe("Value resolved by the AI runtime for this input. The AI engine decides how to satisfy the parameter.")]).describe("Maps input parameters for a step. Can be a static value or a JavaScript expression that references previous results or flow inputs").describe("The user's prompt/message to the AI agent. Supports variable interpolation with\nflow.input syntax. Required unless memory is off and `previous_messages` supplies\nthe prompt; image output always needs it.\n").optional(), "system_prompt": z.discriminatedUnion("type", [z.object({ "value": z.any().describe("The static value. For resources, use format '$res:path/to/resource'").optional(), "type": z.literal("static") }).describe("Static value passed directly to the step. Use for hardcoded values or resource references like '$res:path/to/resource'"), z.object({ "expr": z.string().describe("JavaScript expression returning the value. Available variables - results (object with all previous step results), flow_input (flow inputs), flow_input.iter (in loops)"), "type": z.literal("javascript") }).describe("JavaScript expression evaluated at runtime. Can reference previous step results via 'results.step_id' or flow inputs via 'flow_input.property'. Inside for loops, use 'flow_input.iter.value' for the current iteration value (in while loops it equals 'flow_input.iter.index')"), z.object({ "type": z.literal("ai") }).describe("Value resolved by the AI runtime for this input. The AI engine decides how to satisfy the parameter.")]).describe("Maps input parameters for a step. Can be a static value or a JavaScript expression that references previous results or flow inputs").describe("System instructions that guide the AI's behavior, persona, and response style. Optional.").optional(), "streaming": z.discriminatedUnion("type", [z.object({ "value": z.any().describe("The static value. For resources, use format '$res:path/to/resource'").optional(), "type": z.literal("static") }).describe("Static value passed directly to the step. Use for hardcoded values or resource references like '$res:path/to/resource'"), z.object({ "expr": z.string().describe("JavaScript expression returning the value. Available variables - results (object with all previous step results), flow_input (flow inputs), flow_input.iter (in loops)"), "type": z.literal("javascript") }).describe("JavaScript expression evaluated at runtime. Can reference previous step results via 'results.step_id' or flow inputs via 'flow_input.property'. Inside for loops, use 'flow_input.iter.value' for the current iteration value (in while loops it equals 'flow_input.iter.index')"), z.object({ "type": z.literal("ai") }).describe("Value resolved by the AI runtime for this input. The AI engine decides how to satisfy the parameter.")]).describe("Maps input parameters for a step. Can be a static value or a JavaScript expression that references previous results or flow inputs").describe("Boolean. If true, stream the AI response incrementally.\nStreaming events include: token_delta, reasoning_token_delta, tool_call, tool_call_arguments, tool_execution, tool_result\n").optional(), "memory": z.discriminatedUnion("type", [z.object({ "value": z.discriminatedUnion("kind", [z.object({ "kind": z.literal("off") }).describe("No conversation memory/context"), z.object({ "kind": z.literal("window"), "context_length": z.number().int().describe("Number of most recent messages to load and store. 0 turns memory off.") }).describe("Keeps the most recent messages of the memory named by the run's memory id (or the step's\n`memory_id`). Without a memory id the agent runs without memory.\n"), z.object({ "kind": z.literal("compaction"), "context_window": z.number().int().describe("Overrides the context window looked up from the model, in tokens. Only a model\nWindmill does not know needs one; those fall back to 128000.\n").optional() }).describe("Keeps the whole memory named by the run's memory id (or the step's `memory_id`), replacing\nits older part with a summary as the conversation approaches the model's context window.\nWithout a memory id the agent runs without memory, and compaction bounds the run's own loop.\n"), z.object({ "kind": z.literal("auto"), "context_length": z.number().int().describe("Maximum number of messages to retain in context").optional(), "memory_id": z.string().describe("Identifier for persistent memory across agent invocations").optional() }).describe("Deprecated, still read as it was written: the run's memory id, else the `memory_id` here.\nThe step's own `memory_id` is not read while this kind is set; switch the kind to `window`\nto use it. Without a `context_length`, or with 0, it is `off` and reads `previous_messages`.\n"), z.object({ "kind": z.literal("manual"), "messages": z.array(z.object({ "role": z.enum(["user","assistant","system"]), "content": z.string() }).describe("A single message in conversation history")) }).describe("Deprecated, still read as it was written. Move the step to `off` with `previous_messages` instead.")]).describe("Managed memory, stored by Windmill and replayed with each request. The memory is named by a memory id, see `memory_id`. While it is off, a step can supply its history in `previous_messages`."), "type": z.literal("static") }).describe("Static memory configuration passed directly to the AI agent"), z.object({ "expr": z.string().describe("JavaScript expression returning the value. Available variables - results (object with all previous step results), flow_input (flow inputs), flow_input.iter (in loops)"), "type": z.literal("javascript") }).describe("JavaScript expression evaluated at runtime. Can reference previous step results via 'results.step_id' or flow inputs via 'flow_input.property'. Inside for loops, use 'flow_input.iter.value' for the current iteration value (in while loops it equals 'flow_input.iter.index')"), z.object({ "type": z.literal("ai") }).describe("Value resolved by the AI runtime for this input. The AI engine decides how to satisfy the parameter.")]).describe("Memory configuration - can be static (MemoryConfig), JavaScript expression, or AI-determined").optional(), "memory_id": z.discriminatedUnion("type", [z.object({ "value": z.any().describe("The static value. For resources, use format '$res:path/to/resource'").optional(), "type": z.literal("static") }).describe("Static value passed directly to the step. Use for hardcoded values or resource references like '$res:path/to/resource'"), z.object({ "expr": z.string().describe("JavaScript expression returning the value. Available variables - results (object with all previous step results), flow_input (flow inputs), flow_input.iter (in loops)"), "type": z.literal("javascript") }).describe("JavaScript expression evaluated at runtime. Can reference previous step results via 'results.step_id' or flow inputs via 'flow_input.property'. Inside for loops, use 'flow_input.iter.value' for the current iteration value (in while loops it equals 'flow_input.iter.index')"), z.object({ "type": z.literal("ai") }).describe("Value resolved by the AI runtime for this input. The AI engine decides how to satisfy the parameter.")]).describe("Maps input parameters for a step. Can be a static value or a JavaScript expression that references previous results or flow inputs").describe("String. Names the memory this step reads and writes, overriding the memory id the run\nwas started with (the chat conversation, an app chat session or the `memory_id` run\nparameter). Leave unset to use the run's memory id. A fixed value shares one memory\nacross every run; an expression such as `flow_input.customer_id` keeps one memory per\nkey. When it evaluates to an empty value the agent runs without memory. Read only\nwhile `memory` is `window` or `compaction`: it is ignored when memory is off, and an\nolder `auto` or `manual` memory reads neither history input.\n").optional(), "previous_messages": z.discriminatedUnion("type", [z.object({ "value": z.any().describe("The static value. For resources, use format '$res:path/to/resource'").optional(), "type": z.literal("static") }).describe("Static value passed directly to the step. Use for hardcoded values or resource references like '$res:path/to/resource'"), z.object({ "expr": z.string().describe("JavaScript expression returning the value. Available variables - results (object with all previous step results), flow_input (flow inputs), flow_input.iter (in loops)"), "type": z.literal("javascript") }).describe("JavaScript expression evaluated at runtime. Can reference previous step results via 'results.step_id' or flow inputs via 'flow_input.property'. Inside for loops, use 'flow_input.iter.value' for the current iteration value (in while loops it equals 'flow_input.iter.index')"), z.object({ "type": z.literal("ai") }).describe("Value resolved by the AI runtime for this input. The AI engine decides how to satisfy the parameter.")]).describe("Maps input parameters for a step. Can be a static value or a JavaScript expression that references previous results or flow inputs").describe("Array of MemoryMessage. History supplied by the flow, sent between the system prompt\nand the user message. Read only while `memory` is off or absent: managed memory\nignores it, and an older `auto` or `manual` memory reads neither history input.\n").optional(), "output_schema": z.discriminatedUnion("type", [z.object({ "value": z.any().describe("The static value. For resources, use format '$res:path/to/resource'").optional(), "type": z.literal("static") }).describe("Static value passed directly to the step. Use for hardcoded values or resource references like '$res:path/to/resource'"), z.object({ "expr": z.string().describe("JavaScript expression returning the value. Available variables - results (object with all previous step results), flow_input (flow inputs), flow_input.iter (in loops)"), "type": z.literal("javascript") }).describe("JavaScript expression evaluated at runtime. Can reference previous step results via 'results.step_id' or flow inputs via 'flow_input.property'. Inside for loops, use 'flow_input.iter.value' for the current iteration value (in while loops it equals 'flow_input.iter.index')"), z.object({ "type": z.literal("ai") }).describe("Value resolved by the AI runtime for this input. The AI engine decides how to satisfy the parameter.")]).describe("Maps input parameters for a step. Can be a static value or a JavaScript expression that references previous results or flow inputs").describe("JSON Schema object defining structured output format. Used when you need the AI to return data in a specific shape.\nSupports standard JSON Schema properties: type, properties, required, items, enum, pattern, minLength, maxLength, minimum, maximum, etc.\nExample: { type: 'object', properties: { name: { type: 'string' }, age: { type: 'integer' } }, required: ['name'] }\n").optional(), "user_attachments": z.discriminatedUnion("type", [z.object({ "value": z.any().describe("The static value. For resources, use format '$res:path/to/resource'").optional(), "type": z.literal("static") }).describe("Static value passed directly to the step. Use for hardcoded values or resource references like '$res:path/to/resource'"), z.object({ "expr": z.string().describe("JavaScript expression returning the value. Available variables - results (object with all previous step results), flow_input (flow inputs), flow_input.iter (in loops)"), "type": z.literal("javascript") }).describe("JavaScript expression evaluated at runtime. Can reference previous step results via 'results.step_id' or flow inputs via 'flow_input.property'. Inside for loops, use 'flow_input.iter.value' for the current iteration value (in while loops it equals 'flow_input.iter.index')"), z.object({ "type": z.literal("ai") }).describe("Value resolved by the AI runtime for this input. The AI engine decides how to satisfy the parameter.")]).describe("Maps input parameters for a step. Can be a static value or a JavaScript expression that references previous results or flow inputs").describe("Array of file references (images or PDFs) for the AI agent.\nFormat: Array<{ bucket: string, key: string }> - S3 object references\nExample: [{ bucket: 'my-bucket', key: 'documents/report.pdf' }]\n").optional(), "enabled_tools": z.discriminatedUnion("type", [z.object({ "value": z.any().describe("The static value. For resources, use format '$res:path/to/resource'").optional(), "type": z.literal("static") }).describe("Static value passed directly to the step. Use for hardcoded values or resource references like '$res:path/to/resource'"), z.object({ "expr": z.string().describe("JavaScript expression returning the value. Available variables - results (object with all previous step results), flow_input (flow inputs), flow_input.iter (in loops)"), "type": z.literal("javascript") }).describe("JavaScript expression evaluated at runtime. Can reference previous step results via 'results.step_id' or flow inputs via 'flow_input.property'. Inside for loops, use 'flow_input.iter.value' for the current iteration value (in while loops it equals 'flow_input.iter.index')"), z.object({ "type": z.literal("ai") }).describe("Value resolved by the AI runtime for this input. The AI engine decides how to satisfy the parameter.")]).describe("Maps input parameters for a step. Can be a static value or a JavaScript expression that references previous results or flow inputs").describe("Array of strings naming which of the tools configured in `tools` the agent may call\nthis run. Leaving it unset carries every one of them; an empty array carries none.\nA tool is named as the model is shown it. An entry the model is shown nothing of is\nnamed by what identifies it instead: an MCP server by its resource path, carrying\nevery tool it exposes (which of them stays that entry's include_tools/exclude_tools),\nand a websearch entry by the reserved name '__wm_web_search', whatever summary it carries\n(no tool may take that name).\nExample: ['get_user', 'u/admin/github_mcp', '__wm_web_search']\n").optional(), "max_completion_tokens": z.discriminatedUnion("type", [z.object({ "value": z.any().describe("The static value. For resources, use format '$res:path/to/resource'").optional(), "type": z.literal("static") }).describe("Static value passed directly to the step. Use for hardcoded values or resource references like '$res:path/to/resource'"), z.object({ "expr": z.string().describe("JavaScript expression returning the value. Available variables - results (object with all previous step results), flow_input (flow inputs), flow_input.iter (in loops)"), "type": z.literal("javascript") }).describe("JavaScript expression evaluated at runtime. Can reference previous step results via 'results.step_id' or flow inputs via 'flow_input.property'. Inside for loops, use 'flow_input.iter.value' for the current iteration value (in while loops it equals 'flow_input.iter.index')"), z.object({ "type": z.literal("ai") }).describe("Value resolved by the AI runtime for this input. The AI engine decides how to satisfy the parameter.")]).describe("Maps input parameters for a step. Can be a static value or a JavaScript expression that references previous results or flow inputs").describe("Integer. Maximum number of tokens the AI will generate in its response.\nRange: 1 to 4,294,967,295. Typical values: 256-4096 for most use cases.\n").optional(), "temperature": z.discriminatedUnion("type", [z.object({ "value": z.any().describe("The static value. For resources, use format '$res:path/to/resource'").optional(), "type": z.literal("static") }).describe("Static value passed directly to the step. Use for hardcoded values or resource references like '$res:path/to/resource'"), z.object({ "expr": z.string().describe("JavaScript expression returning the value. Available variables - results (object with all previous step results), flow_input (flow inputs), flow_input.iter (in loops)"), "type": z.literal("javascript") }).describe("JavaScript expression evaluated at runtime. Can reference previous step results via 'results.step_id' or flow inputs via 'flow_input.property'. Inside for loops, use 'flow_input.iter.value' for the current iteration value (in while loops it equals 'flow_input.iter.index')"), z.object({ "type": z.literal("ai") }).describe("Value resolved by the AI runtime for this input. The AI engine decides how to satisfy the parameter.")]).describe("Maps input parameters for a step. Can be a static value or a JavaScript expression that references previous results or flow inputs").describe("Float. Controls randomness/creativity of responses.\nRange: 0.0 to 2.0 (provider-dependent)\n- 0.0 = deterministic, focused responses\n- 0.7 = balanced (common default)\n- 1.0+ = more creative/random\n").optional(), "max_iterations": z.discriminatedUnion("type", [z.object({ "value": z.any().describe("The static value. For resources, use format '$res:path/to/resource'").optional(), "type": z.literal("static") }).describe("Static value passed directly to the step. Use for hardcoded values or resource references like '$res:path/to/resource'"), z.object({ "expr": z.string().describe("JavaScript expression returning the value. Available variables - results (object with all previous step results), flow_input (flow inputs), flow_input.iter (in loops)"), "type": z.literal("javascript") }).describe("JavaScript expression evaluated at runtime. Can reference previous step results via 'results.step_id' or flow inputs via 'flow_input.property'. Inside for loops, use 'flow_input.iter.value' for the current iteration value (in while loops it equals 'flow_input.iter.index')"), z.object({ "type": z.literal("ai") }).describe("Value resolved by the AI runtime for this input. The AI engine decides how to satisfy the parameter.")]).describe("Maps input parameters for a step. Can be a static value or a JavaScript expression that references previous results or flow inputs").describe("Number. Limits how many times the agent can loop through reasoning and tool use.\nRange: 1-1000.\n").optional(), "model": z.discriminatedUnion("type", [z.object({ "value": z.any().describe("The static value. For resources, use format '$res:path/to/resource'").optional(), "type": z.literal("static") }).describe("Static value passed directly to the step. Use for hardcoded values or resource references like '$res:path/to/resource'"), z.object({ "expr": z.string().describe("JavaScript expression returning the value. Available variables - results (object with all previous step results), flow_input (flow inputs), flow_input.iter (in loops)"), "type": z.literal("javascript") }).describe("JavaScript expression evaluated at runtime. Can reference previous step results via 'results.step_id' or flow inputs via 'flow_input.property'. Inside for loops, use 'flow_input.iter.value' for the current iteration value (in while loops it equals 'flow_input.iter.index')"), z.object({ "type": z.literal("ai") }).describe("Value resolved by the AI runtime for this input. The AI engine decides how to satisfy the parameter.")]).describe("Maps input parameters for a step. Can be a static value or a JavaScript expression that references previous results or flow inputs").describe("String. Only on a step linked to a saved agent (see `agent`): replaces the model\nsaved on the agent for this step's runs, on the agent's own provider resource. An\nempty value keeps the saved model. Set it to an expression such as\n`flow_input.model` to choose the model per run.\n").optional(), "reasoning_effort": z.discriminatedUnion("type", [z.object({ "value": z.any().describe("The static value. For resources, use format '$res:path/to/resource'").optional(), "type": z.literal("static") }).describe("Static value passed directly to the step. Use for hardcoded values or resource references like '$res:path/to/resource'"), z.object({ "expr": z.string().describe("JavaScript expression returning the value. Available variables - results (object with all previous step results), flow_input (flow inputs), flow_input.iter (in loops)"), "type": z.literal("javascript") }).describe("JavaScript expression evaluated at runtime. Can reference previous step results via 'results.step_id' or flow inputs via 'flow_input.property'. Inside for loops, use 'flow_input.iter.value' for the current iteration value (in while loops it equals 'flow_input.iter.index')"), z.object({ "type": z.literal("ai") }).describe("Value resolved by the AI runtime for this input. The AI engine decides how to satisfy the parameter.")]).describe("Maps input parameters for a step. Can be a static value or a JavaScript expression that references previous results or flow inputs").describe("String. Only on a step linked to a saved agent (see `agent`): replaces the reasoning\neffort saved on the agent for this step's runs, as a provider-native token (e.g.\n'low', 'high', 'none'). An empty value sends no effort, so the model runs at its\ndefault. Leave the input out to keep the saved effort, which holds only while the\nstep runs the saved model. A step that is not linked sets both inside `provider`.\n").optional() }).describe("Input parameters for the AI agent mapped to their values"), "tools": z.array(z.object({ "id": z.string().describe("Unique identifier for this tool. Cannot contain spaces - use underscores instead (e.g., 'get_user_data' not 'get user data')"), "summary": z.string().describe("The name the AI agent calls this tool by, not a human label. On a flowmodule tool it must match ^[a-zA-Z0-9_]+$ - letters, numbers and underscores only (e.g. 'search_documentation', not 'Search documentation') - and always be set; on an mcp or websearch tool it is a plain label. Put the human-readable explanation in 'description'.").optional(), "description": z.string().describe("Free-text description of the tool given to the AI to decide when and how to call it. Overrides the description auto-derived from the underlying script.").optional(), "job_token_scopes": z.array(z.string()).nullable().describe("Scopes the token of this tool's jobs is restricted to, on top of the agent step's own restriction: a tool can only narrow it.").optional(), "value": z.any().superRefine((x, ctx) => { - const schemas = [z.intersection(z.object({ "tool_type": z.literal("flowmodule") }), z.lazy(() => flowModuleValueSchema)).describe("A tool implemented as a flow module (script, flow, etc.). The AI can call this like any other flow module"), z.object({ "tool_type": z.literal("mcp"), "resource_path": z.string().describe("Path to the MCP resource/server configuration"), "include_tools": z.array(z.string()).describe("Whitelist of specific tools to include from this MCP server").optional(), "exclude_tools": z.array(z.string()).describe("Blacklist of tools to exclude from this MCP server").optional() }).describe("Reference to an external MCP (Model Context Protocol) tool. The AI can call tools from MCP servers"), z.object({ "tool_type": z.literal("websearch") }).describe("A tool implemented as a websearch tool. The AI can call this like any other websearch tool")]; +export const flowModuleSchema = z.object({ "id": z.string().describe("Unique identifier for this step. Used to reference results via 'results.step_id'. Must be a valid identifier (alphanumeric, underscore, hyphen)"), "value": z.discriminatedUnion("type", [z.object({ "input_transforms": z.record(z.string(), z.discriminatedUnion("type", [z.object({ "value": z.any().describe("The static value. For resources, use format '$res:path/to/resource'").optional(), "type": z.literal("static") }).describe("Static value passed directly to the step. Use for hardcoded values or resource references like '$res:path/to/resource'"), z.object({ "expr": z.string().describe("JavaScript expression returning the value. Available variables - results (object with all previous step results), flow_input (flow inputs), flow_input.iter (in loops)"), "type": z.literal("javascript") }).describe("JavaScript expression evaluated at runtime. Can reference previous step results via 'results.step_id' or flow inputs via 'flow_input.property'. Inside for loops, use 'flow_input.iter.value' for the current iteration value (in while loops it equals 'flow_input.iter.index')"), z.object({ "type": z.literal("ai") }).describe("Value resolved by the AI runtime for this input. The AI engine decides how to satisfy the parameter.")]).describe("Maps input parameters for a step. Can be a static value or a JavaScript expression that references previous results or flow inputs")).describe("Map of parameter names to their values (static or JavaScript expressions). These become the script's input arguments"), "content": z.string().describe("The script source code. Should export a 'main' function"), "language": z.enum(["deno","bun","bunnative","python3","go","bash","powershell","postgresql","mysql","bigquery","snowflake","mssql","oracledb","graphql","nativets","php","rust","ansible","csharp","nu","java","ruby","rlang","duckdb"]).describe("Programming language for this script"), "path": z.string().describe("Optional path for saving this script").optional(), "lock": z.string().describe("Lock file content for dependencies").optional(), "type": z.literal("rawscript"), "tag": z.string().describe("Worker group tag for execution routing").optional(), "concurrent_limit": z.number().describe("Maximum concurrent executions of this script").optional(), "concurrency_time_window_s": z.number().describe("Time window for concurrent_limit").optional(), "custom_concurrency_key": z.string().describe("Custom key for grouping concurrent executions").optional(), "is_trigger": z.boolean().describe("If true, this script is a trigger that can start the flow").optional(), "assets": z.array(z.object({ "path": z.string().describe("Path to the asset"), "kind": z.enum(["s3object","resource","ducklake","datatable","volume","dbt"]).describe("Type of asset"), "access_type": z.union([z.literal("r"), z.literal("w"), z.literal("rw"), z.literal(null)]).nullable().describe("Access level for this asset").optional(), "alt_access_type": z.union([z.literal("r"), z.literal("w"), z.literal("rw"), z.literal(null)]).nullable().describe("Alternative access level").optional() })).describe("External resources this script accesses (S3 objects, resources, etc.)").optional() }).describe("Inline script with code defined directly in the flow. Use 'bun' as default language if unspecified. The script receives arguments from input_transforms"), z.object({ "input_transforms": z.record(z.string(), z.discriminatedUnion("type", [z.object({ "value": z.any().describe("The static value. For resources, use format '$res:path/to/resource'").optional(), "type": z.literal("static") }).describe("Static value passed directly to the step. Use for hardcoded values or resource references like '$res:path/to/resource'"), z.object({ "expr": z.string().describe("JavaScript expression returning the value. Available variables - results (object with all previous step results), flow_input (flow inputs), flow_input.iter (in loops)"), "type": z.literal("javascript") }).describe("JavaScript expression evaluated at runtime. Can reference previous step results via 'results.step_id' or flow inputs via 'flow_input.property'. Inside for loops, use 'flow_input.iter.value' for the current iteration value (in while loops it equals 'flow_input.iter.index')"), z.object({ "type": z.literal("ai") }).describe("Value resolved by the AI runtime for this input. The AI engine decides how to satisfy the parameter.")]).describe("Maps input parameters for a step. Can be a static value or a JavaScript expression that references previous results or flow inputs")).describe("Map of parameter names to their values (static or JavaScript expressions). These become the script's input arguments"), "path": z.string().describe("Path to the script in the workspace (e.g., 'f/scripts/send_email')"), "hash": z.string().describe("Optional specific version hash of the script to use").optional(), "type": z.literal("script"), "tag_override": z.string().describe("Override the script's default worker group tag").optional(), "is_trigger": z.boolean().describe("If true, this script is a trigger that can start the flow").optional() }).describe("Reference to an existing script by path. Use this when calling a previously saved script instead of writing inline code"), z.object({ "input_transforms": z.record(z.string(), z.discriminatedUnion("type", [z.object({ "value": z.any().describe("The static value. For resources, use format '$res:path/to/resource'").optional(), "type": z.literal("static") }).describe("Static value passed directly to the step. Use for hardcoded values or resource references like '$res:path/to/resource'"), z.object({ "expr": z.string().describe("JavaScript expression returning the value. Available variables - results (object with all previous step results), flow_input (flow inputs), flow_input.iter (in loops)"), "type": z.literal("javascript") }).describe("JavaScript expression evaluated at runtime. Can reference previous step results via 'results.step_id' or flow inputs via 'flow_input.property'. Inside for loops, use 'flow_input.iter.value' for the current iteration value (in while loops it equals 'flow_input.iter.index')"), z.object({ "type": z.literal("ai") }).describe("Value resolved by the AI runtime for this input. The AI engine decides how to satisfy the parameter.")]).describe("Maps input parameters for a step. Can be a static value or a JavaScript expression that references previous results or flow inputs")).describe("Map of parameter names to their values (static or JavaScript expressions). These become the subflow's input arguments"), "path": z.string().describe("Path to the flow in the workspace (e.g., 'f/flows/process_user')"), "type": z.literal("flow") }).describe("Reference to an existing flow by path. Use this to call another flow as a subflow"), z.object({ "modules": z.array(z.lazy(() => flowModuleSchema)).describe("Steps to execute for each iteration. These can reference the iteration value via 'flow_input.iter.value'"), "iterator": z.discriminatedUnion("type", [z.object({ "value": z.any().describe("The static value. For resources, use format '$res:path/to/resource'").optional(), "type": z.literal("static") }).describe("Static value passed directly to the step. Use for hardcoded values or resource references like '$res:path/to/resource'"), z.object({ "expr": z.string().describe("JavaScript expression returning the value. Available variables - results (object with all previous step results), flow_input (flow inputs), flow_input.iter (in loops)"), "type": z.literal("javascript") }).describe("JavaScript expression evaluated at runtime. Can reference previous step results via 'results.step_id' or flow inputs via 'flow_input.property'. Inside for loops, use 'flow_input.iter.value' for the current iteration value (in while loops it equals 'flow_input.iter.index')"), z.object({ "type": z.literal("ai") }).describe("Value resolved by the AI runtime for this input. The AI engine decides how to satisfy the parameter.")]).describe("Maps input parameters for a step. Can be a static value or a JavaScript expression that references previous results or flow inputs"), "skip_failures": z.boolean().describe("If true, iteration failures don't stop the loop. Failed iterations return null"), "type": z.literal("forloopflow"), "parallel": z.boolean().describe("If true, iterations run concurrently (faster for I/O-bound operations). Use with parallelism to control concurrency").optional(), "parallelism": z.discriminatedUnion("type", [z.object({ "value": z.any().describe("The static value. For resources, use format '$res:path/to/resource'").optional(), "type": z.literal("static") }).describe("Static value passed directly to the step. Use for hardcoded values or resource references like '$res:path/to/resource'"), z.object({ "expr": z.string().describe("JavaScript expression returning the value. Available variables - results (object with all previous step results), flow_input (flow inputs), flow_input.iter (in loops)"), "type": z.literal("javascript") }).describe("JavaScript expression evaluated at runtime. Can reference previous step results via 'results.step_id' or flow inputs via 'flow_input.property'. Inside for loops, use 'flow_input.iter.value' for the current iteration value (in while loops it equals 'flow_input.iter.index')"), z.object({ "type": z.literal("ai") }).describe("Value resolved by the AI runtime for this input. The AI engine decides how to satisfy the parameter.")]).describe("Maps input parameters for a step. Can be a static value or a JavaScript expression that references previous results or flow inputs").optional(), "squash": z.boolean().optional() }).describe("Executes nested modules in a loop over an iterator. Inside the loop, use 'flow_input.iter.value' to access the current iteration value, and 'flow_input.iter.index' for the index. Supports parallel execution for better performance on I/O-bound operations"), z.object({ "modules": z.array(z.lazy(() => flowModuleSchema)).describe("Steps to execute in each iteration"), "skip_failures": z.boolean().describe("If true, iteration failures don't stop the loop. Failed iterations return null"), "type": z.literal("whileloopflow"), "parallel": z.boolean().describe("If true, iterations run concurrently (use with caution in while loops)").optional(), "parallelism": z.discriminatedUnion("type", [z.object({ "value": z.any().describe("The static value. For resources, use format '$res:path/to/resource'").optional(), "type": z.literal("static") }).describe("Static value passed directly to the step. Use for hardcoded values or resource references like '$res:path/to/resource'"), z.object({ "expr": z.string().describe("JavaScript expression returning the value. Available variables - results (object with all previous step results), flow_input (flow inputs), flow_input.iter (in loops)"), "type": z.literal("javascript") }).describe("JavaScript expression evaluated at runtime. Can reference previous step results via 'results.step_id' or flow inputs via 'flow_input.property'. Inside for loops, use 'flow_input.iter.value' for the current iteration value (in while loops it equals 'flow_input.iter.index')"), z.object({ "type": z.literal("ai") }).describe("Value resolved by the AI runtime for this input. The AI engine decides how to satisfy the parameter.")]).describe("Maps input parameters for a step. Can be a static value or a JavaScript expression that references previous results or flow inputs").optional(), "squash": z.boolean().optional() }).describe("Executes nested modules repeatedly until stopped. The implicit iterator is the iteration counter, so 'flow_input.iter.value' equals 'flow_input.iter.index' (0, 1, 2, ...) and never carries state. To carry state across iterations, a step reads its own previous-iteration result via 'results.<its_own_id>' with a first-iteration fallback - the loop's stop_after_if must then be on that inner step (a plain single-step body with stop_after_if on the loop module does not resolve 'results' across iterations and never terminates); plain counters can instead be derived from 'flow_input.iter.index', which works in every configuration. stop_after_if is evaluated after each iteration - on the loop module 'result' is the last iteration's result"), z.object({ "branches": z.array(z.object({ "summary": z.string().describe("Short description of this branch condition").optional(), "expr": z.string().describe("JavaScript expression that returns boolean. Can use 'results.step_id' or 'flow_input'. First true expr wins"), "modules": z.array(z.lazy(() => flowModuleSchema)).describe("Steps to execute if this branch's expr is true") })).describe("Array of branches to evaluate in order. The first branch with expr evaluating to true executes"), "default": z.array(z.lazy(() => flowModuleSchema)).describe("Steps to execute if no branch expressions match"), "type": z.literal("branchone") }).describe("Conditional branching where only the first matching branch executes. Branches are evaluated in order, and the first one with a true expression runs. If no branches match, the default branch executes"), z.object({ "branches": z.array(z.object({ "summary": z.string().describe("Short description of this branch's purpose").optional(), "skip_failure": z.boolean().describe("If true, failure in this branch doesn't fail the entire flow").optional(), "modules": z.array(z.lazy(() => flowModuleSchema)).describe("Steps to execute in this branch") })).describe("Array of branches that all execute (either in parallel or sequentially)"), "type": z.literal("branchall"), "parallel": z.boolean().describe("If true, all branches execute concurrently. If false, they execute sequentially").optional() }).describe("Parallel branching where all branches execute simultaneously. Unlike BranchOne, all branches run regardless of conditions. Useful for executing independent tasks concurrently"), z.object({ "type": z.literal("identity"), "flow": z.boolean().describe("If true, marks this as a flow identity (special handling)").optional() }).describe("Pass-through module that returns its input unchanged. Useful for flow structure or as a placeholder"), z.object({ "input_transforms": z.object({ "provider": z.discriminatedUnion("type", [z.object({ "value": z.object({ "kind": z.enum(["openai","azure_openai","azure_foundry","anthropic","mistral","deepseek","googleai","groq","openrouter","togetherai","customai","aws_bedrock","typesafe","cloudflare"]).describe("Supported AI provider types"), "resource": z.string().describe("Resource reference in format '$res:{resource_path}' pointing to provider credentials"), "model": z.string().describe("Model identifier (e.g., 'gpt-4', 'claude-3-opus-20240229', 'gemini-pro')"), "reasoning_effort": z.string().describe("Provider-native reasoning effort token (e.g. 'low', 'high', 'none') for models that support extended thinking. Optional; unset leaves the provider default.").optional() }).describe("Complete AI provider configuration with resource reference and model selection"), "type": z.literal("static") }).describe("Static provider configuration passed directly to the AI agent"), z.object({ "expr": z.string().describe("JavaScript expression returning the value. Available variables - results (object with all previous step results), flow_input (flow inputs), flow_input.iter (in loops)"), "type": z.literal("javascript") }).describe("JavaScript expression evaluated at runtime. Can reference previous step results via 'results.step_id' or flow inputs via 'flow_input.property'. Inside for loops, use 'flow_input.iter.value' for the current iteration value (in while loops it equals 'flow_input.iter.index')"), z.object({ "type": z.literal("ai") }).describe("Value resolved by the AI runtime for this input. The AI engine decides how to satisfy the parameter.")]).describe("Provider configuration - can be static (ProviderConfig), JavaScript expression, or AI-determined").optional(), "output_type": z.discriminatedUnion("type", [z.object({ "value": z.any().describe("The static value. For resources, use format '$res:path/to/resource'").optional(), "type": z.literal("static") }).describe("Static value passed directly to the step. Use for hardcoded values or resource references like '$res:path/to/resource'"), z.object({ "expr": z.string().describe("JavaScript expression returning the value. Available variables - results (object with all previous step results), flow_input (flow inputs), flow_input.iter (in loops)"), "type": z.literal("javascript") }).describe("JavaScript expression evaluated at runtime. Can reference previous step results via 'results.step_id' or flow inputs via 'flow_input.property'. Inside for loops, use 'flow_input.iter.value' for the current iteration value (in while loops it equals 'flow_input.iter.index')"), z.object({ "type": z.literal("ai") }).describe("Value resolved by the AI runtime for this input. The AI engine decides how to satisfy the parameter.")]).describe("Maps input parameters for a step. Can be a static value or a JavaScript expression that references previous results or flow inputs").describe("Output format type.\nValid values: 'text' (default) - plain text response, 'image' - image generation\n").optional(), "user_message": z.discriminatedUnion("type", [z.object({ "value": z.any().describe("The static value. For resources, use format '$res:path/to/resource'").optional(), "type": z.literal("static") }).describe("Static value passed directly to the step. Use for hardcoded values or resource references like '$res:path/to/resource'"), z.object({ "expr": z.string().describe("JavaScript expression returning the value. Available variables - results (object with all previous step results), flow_input (flow inputs), flow_input.iter (in loops)"), "type": z.literal("javascript") }).describe("JavaScript expression evaluated at runtime. Can reference previous step results via 'results.step_id' or flow inputs via 'flow_input.property'. Inside for loops, use 'flow_input.iter.value' for the current iteration value (in while loops it equals 'flow_input.iter.index')"), z.object({ "type": z.literal("ai") }).describe("Value resolved by the AI runtime for this input. The AI engine decides how to satisfy the parameter.")]).describe("Maps input parameters for a step. Can be a static value or a JavaScript expression that references previous results or flow inputs").describe("The user's prompt/message to the AI agent. Supports variable interpolation with\nflow.input syntax. Required unless memory is off and `previous_messages` supplies\nthe prompt; image output always needs it.\n").optional(), "system_prompt": z.discriminatedUnion("type", [z.object({ "value": z.any().describe("The static value. For resources, use format '$res:path/to/resource'").optional(), "type": z.literal("static") }).describe("Static value passed directly to the step. Use for hardcoded values or resource references like '$res:path/to/resource'"), z.object({ "expr": z.string().describe("JavaScript expression returning the value. Available variables - results (object with all previous step results), flow_input (flow inputs), flow_input.iter (in loops)"), "type": z.literal("javascript") }).describe("JavaScript expression evaluated at runtime. Can reference previous step results via 'results.step_id' or flow inputs via 'flow_input.property'. Inside for loops, use 'flow_input.iter.value' for the current iteration value (in while loops it equals 'flow_input.iter.index')"), z.object({ "type": z.literal("ai") }).describe("Value resolved by the AI runtime for this input. The AI engine decides how to satisfy the parameter.")]).describe("Maps input parameters for a step. Can be a static value or a JavaScript expression that references previous results or flow inputs").describe("System instructions that guide the AI's behavior, persona, and response style. Optional.").optional(), "streaming": z.discriminatedUnion("type", [z.object({ "value": z.any().describe("The static value. For resources, use format '$res:path/to/resource'").optional(), "type": z.literal("static") }).describe("Static value passed directly to the step. Use for hardcoded values or resource references like '$res:path/to/resource'"), z.object({ "expr": z.string().describe("JavaScript expression returning the value. Available variables - results (object with all previous step results), flow_input (flow inputs), flow_input.iter (in loops)"), "type": z.literal("javascript") }).describe("JavaScript expression evaluated at runtime. Can reference previous step results via 'results.step_id' or flow inputs via 'flow_input.property'. Inside for loops, use 'flow_input.iter.value' for the current iteration value (in while loops it equals 'flow_input.iter.index')"), z.object({ "type": z.literal("ai") }).describe("Value resolved by the AI runtime for this input. The AI engine decides how to satisfy the parameter.")]).describe("Maps input parameters for a step. Can be a static value or a JavaScript expression that references previous results or flow inputs").describe("Boolean. If true, stream the AI response incrementally.\nStreaming events include: token_delta, reasoning_token_delta, tool_call, tool_call_arguments, tool_execution, tool_result\n").optional(), "memory": z.discriminatedUnion("type", [z.object({ "value": z.discriminatedUnion("kind", [z.object({ "kind": z.literal("off") }).describe("No conversation memory/context"), z.object({ "kind": z.literal("window"), "context_length": z.number().int().describe("Number of most recent messages to load and store. 0 turns memory off.") }).describe("Keeps the most recent messages of the memory named by the run's memory id (or the step's\n`memory_id`). Without a memory id the agent runs without memory.\n"), z.object({ "kind": z.literal("compaction"), "context_window": z.number().int().describe("Overrides the context window looked up from the model, in tokens. Only a model\nWindmill does not know needs one; those fall back to 128000.\n").optional() }).describe("Keeps the whole memory named by the run's memory id (or the step's `memory_id`), replacing\nits older part with a summary as the conversation approaches the model's context window.\nWithout a memory id the agent runs without memory, and compaction bounds the run's own loop.\n"), z.object({ "kind": z.literal("auto"), "context_length": z.number().int().describe("Maximum number of messages to retain in context").optional(), "memory_id": z.string().describe("Identifier for persistent memory across agent invocations").optional() }).describe("Deprecated, still read as it was written: the run's memory id, else the `memory_id` here.\nThe step's own `memory_id` is not read while this kind is set; switch the kind to `window`\nto use it. Without a `context_length`, or with 0, it is `off` and reads `previous_messages`.\n"), z.object({ "kind": z.literal("manual"), "messages": z.array(z.object({ "role": z.enum(["user","assistant","system"]), "content": z.string() }).describe("A single message in conversation history")) }).describe("Deprecated, still read as it was written. Move the step to `off` with `previous_messages` instead.")]).describe("Managed memory, stored by Windmill and replayed with each request. The memory is named by a memory id, see `memory_id`. While it is off, a step can supply its history in `previous_messages`."), "type": z.literal("static") }).describe("Static memory configuration passed directly to the AI agent"), z.object({ "expr": z.string().describe("JavaScript expression returning the value. Available variables - results (object with all previous step results), flow_input (flow inputs), flow_input.iter (in loops)"), "type": z.literal("javascript") }).describe("JavaScript expression evaluated at runtime. Can reference previous step results via 'results.step_id' or flow inputs via 'flow_input.property'. Inside for loops, use 'flow_input.iter.value' for the current iteration value (in while loops it equals 'flow_input.iter.index')"), z.object({ "type": z.literal("ai") }).describe("Value resolved by the AI runtime for this input. The AI engine decides how to satisfy the parameter.")]).describe("Memory configuration - can be static (MemoryConfig), JavaScript expression, or AI-determined").optional(), "memory_id": z.discriminatedUnion("type", [z.object({ "value": z.any().describe("The static value. For resources, use format '$res:path/to/resource'").optional(), "type": z.literal("static") }).describe("Static value passed directly to the step. Use for hardcoded values or resource references like '$res:path/to/resource'"), z.object({ "expr": z.string().describe("JavaScript expression returning the value. Available variables - results (object with all previous step results), flow_input (flow inputs), flow_input.iter (in loops)"), "type": z.literal("javascript") }).describe("JavaScript expression evaluated at runtime. Can reference previous step results via 'results.step_id' or flow inputs via 'flow_input.property'. Inside for loops, use 'flow_input.iter.value' for the current iteration value (in while loops it equals 'flow_input.iter.index')"), z.object({ "type": z.literal("ai") }).describe("Value resolved by the AI runtime for this input. The AI engine decides how to satisfy the parameter.")]).describe("Maps input parameters for a step. Can be a static value or a JavaScript expression that references previous results or flow inputs").describe("String. Names the memory this step reads and writes, overriding the memory id the run\nwas started with (the chat conversation, an app chat session or the `memory_id` run\nparameter). Leave unset to use the run's memory id. A fixed value shares one memory\nacross every run; an expression such as `flow_input.customer_id` keeps one memory per\nkey. When it evaluates to an empty value the agent runs without memory. Read only\nwhile `memory` is `window` or `compaction`: it is ignored when memory is off, and an\nolder `auto` or `manual` memory reads neither history input.\n").optional(), "previous_messages": z.discriminatedUnion("type", [z.object({ "value": z.any().describe("The static value. For resources, use format '$res:path/to/resource'").optional(), "type": z.literal("static") }).describe("Static value passed directly to the step. Use for hardcoded values or resource references like '$res:path/to/resource'"), z.object({ "expr": z.string().describe("JavaScript expression returning the value. Available variables - results (object with all previous step results), flow_input (flow inputs), flow_input.iter (in loops)"), "type": z.literal("javascript") }).describe("JavaScript expression evaluated at runtime. Can reference previous step results via 'results.step_id' or flow inputs via 'flow_input.property'. Inside for loops, use 'flow_input.iter.value' for the current iteration value (in while loops it equals 'flow_input.iter.index')"), z.object({ "type": z.literal("ai") }).describe("Value resolved by the AI runtime for this input. The AI engine decides how to satisfy the parameter.")]).describe("Maps input parameters for a step. Can be a static value or a JavaScript expression that references previous results or flow inputs").describe("Array of MemoryMessage. History supplied by the flow, sent between the system prompt\nand the user message. Read only while `memory` is off or absent: managed memory\nignores it, and an older `auto` or `manual` memory reads neither history input.\n").optional(), "output_schema": z.discriminatedUnion("type", [z.object({ "value": z.any().describe("The static value. For resources, use format '$res:path/to/resource'").optional(), "type": z.literal("static") }).describe("Static value passed directly to the step. Use for hardcoded values or resource references like '$res:path/to/resource'"), z.object({ "expr": z.string().describe("JavaScript expression returning the value. Available variables - results (object with all previous step results), flow_input (flow inputs), flow_input.iter (in loops)"), "type": z.literal("javascript") }).describe("JavaScript expression evaluated at runtime. Can reference previous step results via 'results.step_id' or flow inputs via 'flow_input.property'. Inside for loops, use 'flow_input.iter.value' for the current iteration value (in while loops it equals 'flow_input.iter.index')"), z.object({ "type": z.literal("ai") }).describe("Value resolved by the AI runtime for this input. The AI engine decides how to satisfy the parameter.")]).describe("Maps input parameters for a step. Can be a static value or a JavaScript expression that references previous results or flow inputs").describe("JSON Schema object defining structured output format. Used when you need the AI to return data in a specific shape.\nSupports standard JSON Schema properties: type, properties, required, items, enum, pattern, minLength, maxLength, minimum, maximum, etc.\nExample: { type: 'object', properties: { name: { type: 'string' }, age: { type: 'integer' } }, required: ['name'] }\n").optional(), "user_attachments": z.discriminatedUnion("type", [z.object({ "value": z.any().describe("The static value. For resources, use format '$res:path/to/resource'").optional(), "type": z.literal("static") }).describe("Static value passed directly to the step. Use for hardcoded values or resource references like '$res:path/to/resource'"), z.object({ "expr": z.string().describe("JavaScript expression returning the value. Available variables - results (object with all previous step results), flow_input (flow inputs), flow_input.iter (in loops)"), "type": z.literal("javascript") }).describe("JavaScript expression evaluated at runtime. Can reference previous step results via 'results.step_id' or flow inputs via 'flow_input.property'. Inside for loops, use 'flow_input.iter.value' for the current iteration value (in while loops it equals 'flow_input.iter.index')"), z.object({ "type": z.literal("ai") }).describe("Value resolved by the AI runtime for this input. The AI engine decides how to satisfy the parameter.")]).describe("Maps input parameters for a step. Can be a static value or a JavaScript expression that references previous results or flow inputs").describe("Array of file references (images or PDFs) for the AI agent.\nFormat: Array<{ bucket: string, key: string }> - S3 object references\nExample: [{ bucket: 'my-bucket', key: 'documents/report.pdf' }]\n").optional(), "enabled_tools": z.discriminatedUnion("type", [z.object({ "value": z.any().describe("The static value. For resources, use format '$res:path/to/resource'").optional(), "type": z.literal("static") }).describe("Static value passed directly to the step. Use for hardcoded values or resource references like '$res:path/to/resource'"), z.object({ "expr": z.string().describe("JavaScript expression returning the value. Available variables - results (object with all previous step results), flow_input (flow inputs), flow_input.iter (in loops)"), "type": z.literal("javascript") }).describe("JavaScript expression evaluated at runtime. Can reference previous step results via 'results.step_id' or flow inputs via 'flow_input.property'. Inside for loops, use 'flow_input.iter.value' for the current iteration value (in while loops it equals 'flow_input.iter.index')"), z.object({ "type": z.literal("ai") }).describe("Value resolved by the AI runtime for this input. The AI engine decides how to satisfy the parameter.")]).describe("Maps input parameters for a step. Can be a static value or a JavaScript expression that references previous results or flow inputs").describe("Array of strings naming which of the tools configured in `tools` the agent may call\nthis run. Leaving it unset carries every one of them; an empty array carries none.\nA tool is named as the model is shown it. An entry the model is shown nothing of is\nnamed by what identifies it instead: an MCP server by its resource path, carrying\nevery tool it exposes (which of them stays that entry's include_tools/exclude_tools),\nand a websearch entry by the reserved name '__wm_web_search', whatever summary it carries\n(no tool may take that name).\nExample: ['get_user', 'u/admin/github_mcp', '__wm_web_search']\n").optional(), "max_completion_tokens": z.discriminatedUnion("type", [z.object({ "value": z.any().describe("The static value. For resources, use format '$res:path/to/resource'").optional(), "type": z.literal("static") }).describe("Static value passed directly to the step. Use for hardcoded values or resource references like '$res:path/to/resource'"), z.object({ "expr": z.string().describe("JavaScript expression returning the value. Available variables - results (object with all previous step results), flow_input (flow inputs), flow_input.iter (in loops)"), "type": z.literal("javascript") }).describe("JavaScript expression evaluated at runtime. Can reference previous step results via 'results.step_id' or flow inputs via 'flow_input.property'. Inside for loops, use 'flow_input.iter.value' for the current iteration value (in while loops it equals 'flow_input.iter.index')"), z.object({ "type": z.literal("ai") }).describe("Value resolved by the AI runtime for this input. The AI engine decides how to satisfy the parameter.")]).describe("Maps input parameters for a step. Can be a static value or a JavaScript expression that references previous results or flow inputs").describe("Integer. Maximum number of tokens the AI will generate in its response.\nRange: 1 to 4,294,967,295. Typical values: 256-4096 for most use cases.\n").optional(), "temperature": z.discriminatedUnion("type", [z.object({ "value": z.any().describe("The static value. For resources, use format '$res:path/to/resource'").optional(), "type": z.literal("static") }).describe("Static value passed directly to the step. Use for hardcoded values or resource references like '$res:path/to/resource'"), z.object({ "expr": z.string().describe("JavaScript expression returning the value. Available variables - results (object with all previous step results), flow_input (flow inputs), flow_input.iter (in loops)"), "type": z.literal("javascript") }).describe("JavaScript expression evaluated at runtime. Can reference previous step results via 'results.step_id' or flow inputs via 'flow_input.property'. Inside for loops, use 'flow_input.iter.value' for the current iteration value (in while loops it equals 'flow_input.iter.index')"), z.object({ "type": z.literal("ai") }).describe("Value resolved by the AI runtime for this input. The AI engine decides how to satisfy the parameter.")]).describe("Maps input parameters for a step. Can be a static value or a JavaScript expression that references previous results or flow inputs").describe("Float. Controls randomness/creativity of responses.\nRange: 0.0 to 2.0 (provider-dependent)\n- 0.0 = deterministic, focused responses\n- 0.7 = balanced (common default)\n- 1.0+ = more creative/random\n").optional(), "max_iterations": z.discriminatedUnion("type", [z.object({ "value": z.any().describe("The static value. For resources, use format '$res:path/to/resource'").optional(), "type": z.literal("static") }).describe("Static value passed directly to the step. Use for hardcoded values or resource references like '$res:path/to/resource'"), z.object({ "expr": z.string().describe("JavaScript expression returning the value. Available variables - results (object with all previous step results), flow_input (flow inputs), flow_input.iter (in loops)"), "type": z.literal("javascript") }).describe("JavaScript expression evaluated at runtime. Can reference previous step results via 'results.step_id' or flow inputs via 'flow_input.property'. Inside for loops, use 'flow_input.iter.value' for the current iteration value (in while loops it equals 'flow_input.iter.index')"), z.object({ "type": z.literal("ai") }).describe("Value resolved by the AI runtime for this input. The AI engine decides how to satisfy the parameter.")]).describe("Maps input parameters for a step. Can be a static value or a JavaScript expression that references previous results or flow inputs").describe("Number. Limits how many times the agent can loop through reasoning and tool use.\nRange: 1-1000.\n").optional(), "model": z.discriminatedUnion("type", [z.object({ "value": z.any().describe("The static value. For resources, use format '$res:path/to/resource'").optional(), "type": z.literal("static") }).describe("Static value passed directly to the step. Use for hardcoded values or resource references like '$res:path/to/resource'"), z.object({ "expr": z.string().describe("JavaScript expression returning the value. Available variables - results (object with all previous step results), flow_input (flow inputs), flow_input.iter (in loops)"), "type": z.literal("javascript") }).describe("JavaScript expression evaluated at runtime. Can reference previous step results via 'results.step_id' or flow inputs via 'flow_input.property'. Inside for loops, use 'flow_input.iter.value' for the current iteration value (in while loops it equals 'flow_input.iter.index')"), z.object({ "type": z.literal("ai") }).describe("Value resolved by the AI runtime for this input. The AI engine decides how to satisfy the parameter.")]).describe("Maps input parameters for a step. Can be a static value or a JavaScript expression that references previous results or flow inputs").describe("String. Only on a step linked to a saved agent (see `agent`): replaces the model\nsaved on the agent for this step's runs, on the agent's own provider resource. An\nempty value keeps the saved model. Set it to an expression such as\n`flow_input.model` to choose the model per run.\n").optional(), "reasoning_effort": z.discriminatedUnion("type", [z.object({ "value": z.any().describe("The static value. For resources, use format '$res:path/to/resource'").optional(), "type": z.literal("static") }).describe("Static value passed directly to the step. Use for hardcoded values or resource references like '$res:path/to/resource'"), z.object({ "expr": z.string().describe("JavaScript expression returning the value. Available variables - results (object with all previous step results), flow_input (flow inputs), flow_input.iter (in loops)"), "type": z.literal("javascript") }).describe("JavaScript expression evaluated at runtime. Can reference previous step results via 'results.step_id' or flow inputs via 'flow_input.property'. Inside for loops, use 'flow_input.iter.value' for the current iteration value (in while loops it equals 'flow_input.iter.index')"), z.object({ "type": z.literal("ai") }).describe("Value resolved by the AI runtime for this input. The AI engine decides how to satisfy the parameter.")]).describe("Maps input parameters for a step. Can be a static value or a JavaScript expression that references previous results or flow inputs").describe("String. Only on a step linked to a saved agent (see `agent`): replaces the reasoning\neffort saved on the agent for this step's runs, as a provider-native token (e.g.\n'low', 'high', 'none'). An empty value sends no effort, so the model runs at its\ndefault. Leave the input out to keep the saved effort, which holds only while the\nstep runs the saved model. A step that is not linked sets both inside `provider`.\n").optional() }).describe("Input parameters for the AI agent mapped to their values"), "tools": z.array(z.object({ "id": z.string().describe("Unique identifier for this tool. Cannot contain spaces - use underscores instead (e.g., 'get_user_data' not 'get user data')"), "summary": z.string().describe("The name the AI agent calls this tool by, not a human label. On a flowmodule tool it must match ^[a-zA-Z0-9_]+$ - letters, numbers and underscores only (e.g. 'search_documentation', not 'Search documentation') - and always be set; on an mcp, websearch or question tool it is a plain label. Put the human-readable explanation in 'description'.").optional(), "description": z.string().describe("Free-text description of the tool given to the AI to decide when and how to call it. Overrides the description auto-derived from the underlying script.").optional(), "job_token_scopes": z.array(z.string()).nullable().describe("Scopes the token of this tool's jobs is restricted to, on top of the agent step's own restriction: a tool can only narrow it.").optional(), "requires_approval": z.boolean().describe("Flowmodule and mcp tools only. Each call waits for a person to approve or reject it from the flow's run page or chat, without the agent holding a worker. Calls in the same turn that do not require approval run right away. A rejected call, or one nobody answers within 30 minutes, is reported to the AI as not run.").optional(), "value": z.any().superRefine((x, ctx) => { + const schemas = [z.intersection(z.object({ "tool_type": z.literal("flowmodule") }), z.lazy(() => flowModuleValueSchema)).describe("A tool implemented as a flow module (script, flow, etc.). The AI can call this like any other flow module"), z.object({ "tool_type": z.literal("mcp"), "resource_path": z.string().describe("Path to the MCP resource/server configuration"), "include_tools": z.array(z.string()).describe("Whitelist of specific tools to include from this MCP server").optional(), "exclude_tools": z.array(z.string()).describe("Blacklist of tools to exclude from this MCP server").optional() }).describe("Reference to an external MCP (Model Context Protocol) tool. The AI can call tools from MCP servers"), z.object({ "tool_type": z.literal("websearch") }).describe("A tool implemented as a websearch tool. The AI can call this like any other websearch tool"), z.object({ "tool_type": z.literal("question"), "timeout": z.number().int().describe("Seconds to wait for an answer before the question is reported to the AI as timed out. Defaults to 1800.").optional() }).describe("Built-in tool the AI calls as ask_question: the agent stops, releasing its worker, until someone answers from the flow's run page or chat or the question times out, then resumes with the answer as the tool result.")]; const errors = schemas.reduce<z.ZodError[]>( (errors, schema) => ((result) => diff --git a/frontend/src/lib/components/flows/FlowProgressBar.svelte b/frontend/src/lib/components/flows/FlowProgressBar.svelte index 5edf55b5de..8b3a966d57 100644 --- a/frontend/src/lib/components/flows/FlowProgressBar.svelte +++ b/frontend/src/lib/components/flows/FlowProgressBar.svelte @@ -2,6 +2,7 @@ import { type Job } from '$lib/gen' import ProgressBar from '../progressBar/ProgressBar.svelte' import { forLater } from '$lib/forLater' + import { waitingRequest } from '../agentRequest' import type { Snippet } from 'svelte' interface Props { @@ -79,7 +80,13 @@ if (modules.length > maxDone) { const nextModule = modules[maxDone] - if (nextModule.type === 'InProgress') { + if (nextModule.type === 'InProgress' && waitingRequest(nextModule)) { + // An agent waiting on a person reads like an approval step. + newIsWaitingForEvents = true + if (nextModule.id) { + newCurrentStepId = nextModule.id + } + } else if (nextModule.type === 'InProgress') { newNextInProgress = true // Get the step ID if available if (nextModule.id) { diff --git a/frontend/src/lib/components/flows/agentDraft.svelte.ts b/frontend/src/lib/components/flows/agentDraft.svelte.ts index aef204784d..5412c8728f 100644 --- a/frontend/src/lib/components/flows/agentDraft.svelte.ts +++ b/frontend/src/lib/components/flows/agentDraft.svelte.ts @@ -24,7 +24,7 @@ import { // Lives here rather than beside the other config helpers: `agentResourceUtils` is a leaf, and // importing tool-name validation into it would cycle back through `flowInfers` and pull the whole // editor into every module that reads a brain key. -import { getToolNameError } from './agentToolUtils' +import { getToolNameError, isNamedTool, type AgentTool } from './agentToolUtils' /** * Why a run of this config would fail before it started, if it would. Only the conditions the @@ -49,12 +49,10 @@ function agentConfigRunError(args: Record<string, any> | undefined): string | un return 'Tools must be a list. Fix it in the resource editor before deploying.' } // Only a flowmodule tool's summary is a callable name: the worker never reads an mcp or - // websearch summary, so a blank one there is not an error and must not count as a sibling. - // Same filter as `collectInvalidAgentToolNames`, which is the rule the graph enforces. + // built-in tool's summary, so a blank one there is not an error and must not count as a + // sibling. Same filter as `collectInvalidAgentToolNames`, which is the rule the graph enforces. const tools = (args?.tools ?? []) as Record<string, any>[] - const named = tools.filter( - (t) => t?.value?.tool_type !== 'mcp' && t?.value?.tool_type !== 'websearch' - ) + const named = tools.filter((t) => isNamedTool(t as AgentTool)) const siblingNames = named.map((t) => t?.summary ?? '') for (const tool of named) { const err = getToolNameError(tool?.summary ?? '', tool?.value?.tool_type, siblingNames) diff --git a/frontend/src/lib/components/flows/agentToolTree.ts b/frontend/src/lib/components/flows/agentToolTree.ts index 081eeed467..45fefbe194 100644 --- a/frontend/src/lib/components/flows/agentToolTree.ts +++ b/frontend/src/lib/components/flows/agentToolTree.ts @@ -2,6 +2,7 @@ import type { FlowModule } from '$lib/gen' import { getToolNameError, isFlowModuleTool, + isNamedTool, type AgentTool, type FlowModuleTool } from './agentToolUtils' @@ -195,10 +196,8 @@ export function collectInvalidAgentToolNames(modules: unknown): InvalidAgentTool forEachAiAgentModule(modules, (mod, v) => { const tools: AgentTool[] = Array.isArray(v.tools) ? v.tools : [] // Only a flowmodule tool's summary is a callable name: the worker never reads an mcp or - // websearch summary, so a blank one there must stay writable (both default to ''). - const named = tools.filter( - (tool) => tool.value?.tool_type !== 'mcp' && tool.value?.tool_type !== 'websearch' - ) + // built-in tool's summary, so a blank one there must stay writable. + const named = tools.filter(isNamedTool) const siblingNames = named.map((tool) => tool.summary ?? '') for (const tool of named) { const name = tool.summary ?? '' diff --git a/frontend/src/lib/components/flows/agentToolUtils.test.ts b/frontend/src/lib/components/flows/agentToolUtils.test.ts index 6ff47db176..6a7ec84568 100644 --- a/frontend/src/lib/components/flows/agentToolUtils.test.ts +++ b/frontend/src/lib/components/flows/agentToolUtils.test.ts @@ -49,4 +49,11 @@ describe('toolEnabledName', () => { `'${WEBSEARCH_ENABLED_NAME}' is a reserved name` ) }) + + it("names the question tool by the worker's reserved name", () => { + expect( + toolEnabledName({ id: 't', summary: 'label', value: { tool_type: 'question' } } as any) + ).toBe('__wm_question') + expect(getToolNameError('__wm_question')).toBe(`'__wm_question' is a reserved name`) + }) }) diff --git a/frontend/src/lib/components/flows/agentToolUtils.ts b/frontend/src/lib/components/flows/agentToolUtils.ts index 74813cd0a4..643d5d05cd 100644 --- a/frontend/src/lib/components/flows/agentToolUtils.ts +++ b/frontend/src/lib/components/flows/agentToolUtils.ts @@ -10,6 +10,26 @@ import { forbiddenIds } from './idUtils' * search. */ export const WEBSEARCH_ENABLED_NAME = '__wm_web_search' +/** Tools the worker answers itself rather than by running a module. None is named by its + * `summary`: each has a reserved `enabledName` (mirroring the `*_ENABLED_NAME`s in the worker), + * and the model sees a fixed name the worker picks. `question` parks the agent until someone + * answers (`windmill-worker/src/ai/pause.rs`). */ +export const BUILTIN_TOOLS = { + websearch: { label: 'Web search', enabledName: WEBSEARCH_ENABLED_NAME }, + question: { label: 'Ask a question', enabledName: '__wm_question' } +} as const +export type BuiltinToolType = keyof typeof BUILTIN_TOOLS + +export function builtinToolType(tool: AgentTool | undefined): BuiltinToolType | undefined { + const type = tool?.value?.tool_type + return type && type in BUILTIN_TOOLS ? (type as BuiltinToolType) : undefined +} + +/** Whether a tool is named by its `summary`, which only the model-facing kinds are. */ +export function isNamedTool(tool: AgentTool | undefined): boolean { + return tool?.value?.tool_type !== 'mcp' && builtinToolType(tool) === undefined +} + /** * A tool's `summary` is the name the LLM sees, and the worker rejects any name that does not match * `^[a-zA-Z0-9_]+$` (`ai_executor.rs`), so an unvalidated name fails on every run of the flow. @@ -21,10 +41,10 @@ export const WEBSEARCH_ENABLED_NAME = '__wm_web_search' */ export function getToolNameError( name: string, - kind?: 'mcp' | 'websearch' | (string & {}), + kind?: 'mcp' | BuiltinToolType | (string & {}), siblingNames?: string[] ): string | undefined { - if (kind === 'websearch') return undefined + if (kind && kind in BUILTIN_TOOLS) return undefined if (kind === 'mcp') { return name.length > 0 ? undefined : 'Tool name must not be empty' } @@ -36,7 +56,10 @@ export function getToolNameError( if (!/^[a-zA-Z0-9_]+$/.test(name)) { return 'Tool name must only contain letters, numbers and underscores' } - if (forbiddenIds.includes(name) || name === WEBSEARCH_ENABLED_NAME) { + if ( + forbiddenIds.includes(name) || + Object.values(BUILTIN_TOOLS).some((builtin) => builtin.enabledName === name) + ) { return `'${name}' is a reserved name` } if (siblingNames && siblingNames.filter((n) => n === name).length > 1) { @@ -48,6 +71,7 @@ export function getToolNameError( export const SPECIAL_TOOL_KINDS = [ 'mcpTool', 'websearchTool', + 'questionTool', 'aiAgentTool', 'aiDecisionTool' ] as const @@ -154,8 +178,9 @@ export function toolEnabledName(tool: AgentTool): string | undefined { if (value?.tool_type === 'mcp') { return (value?.resource_path as string | undefined)?.replace(/^\$res:/, '') || undefined } - if (value?.tool_type === 'websearch') { - return WEBSEARCH_ENABLED_NAME + const builtin = builtinToolType(tool) + if (builtin) { + return BUILTIN_TOOLS[builtin].enabledName } return toolDisplayName(tool) } @@ -233,13 +258,17 @@ export function createMcpTool(id: string): McpTool { export function createWebsearchTool(id: string): WebsearchTool { return { id, - summary: 'Web Search', + summary: 'Web search', value: { tool_type: 'websearch' } } } +export function createQuestionTool(id: string): AgentTool { + return { id, summary: BUILTIN_TOOLS.question.label, value: { tool_type: 'question' } } +} + /** * Convert a FlowModuleTool to a FlowModule for use with loadFlowModuleState etc. * Strips the extra `tool_type` field and maps AgentTool fields to FlowModule fields. diff --git a/frontend/src/lib/components/flows/content/AgentConfigModal.svelte b/frontend/src/lib/components/flows/content/AgentConfigModal.svelte index 5fe009b57b..fa052d00ac 100644 --- a/frontend/src/lib/components/flows/content/AgentConfigModal.svelte +++ b/frontend/src/lib/components/flows/content/AgentConfigModal.svelte @@ -15,7 +15,12 @@ is that one, since both answer the same question about what an assistant can see summarizeAgentBrain, type AIAgentConfig } from '../agentResourceUtils' - import { toolDisplayName, type AgentTool } from '../agentToolUtils' + import { + BUILTIN_TOOLS, + builtinToolType, + toolDisplayName, + type AgentTool + } from '../agentToolUtils' type Section = 'model' | 'instructions' | 'tools' @@ -71,7 +76,8 @@ is that one, since both answer the same question about what an assistant can see function toolKind(tool: AgentTool): string { const value = tool?.value as Record<string, any> | undefined if (value?.tool_type === 'mcp') return 'MCP server' - if (value?.tool_type === 'websearch') return 'Web search' + const builtin = builtinToolType(tool) + if (builtin) return BUILTIN_TOOLS[builtin].label switch (value?.type) { case 'script': return `Script ${value.path ?? ''}`.trim() diff --git a/frontend/src/lib/components/flows/content/AgentToolRoster.svelte b/frontend/src/lib/components/flows/content/AgentToolRoster.svelte index 7851385465..80b36af3e9 100644 --- a/frontend/src/lib/components/flows/content/AgentToolRoster.svelte +++ b/frontend/src/lib/components/flows/content/AgentToolRoster.svelte @@ -1,7 +1,13 @@ <script lang="ts"> import { ChevronRight, Plus, Wrench, X } from 'lucide-svelte' import { twMerge } from 'tailwind-merge' - import { getToolNameError, toolDisplayName } from '../agentToolUtils' + import { + BUILTIN_TOOLS, + builtinToolType, + getToolNameError, + isNamedTool, + toolDisplayName + } from '../agentToolUtils' import type { AgentTool } from '../agentToolUtils' import { Button } from '$lib/components/common' import Popover from '$lib/components/meltComponents/Popover.svelte' @@ -42,15 +48,14 @@ if (value?.type === 'aiagent') return 'agent' if (value?.type === 'aidecision') return 'decision' if (value?.tool_type === 'mcp') return 'MCP' - if (value?.tool_type === 'websearch') return 'web search' + const builtin = builtinToolType(tool) + if (builtin) return BUILTIN_TOOLS[builtin].label.toLowerCase() return undefined } - /** Only a flow module tool's summary is the name the model is given; an mcp or websearch + /** Only a flow module tool's summary is the name the model is given; an mcp or built-in tool's * summary is never sent, so a blank one there is not an error. Same rule as `agentToolTree`. */ - function isNamed(tool: AgentTool): boolean { - return tool?.value?.tool_type !== 'mcp' && tool?.value?.tool_type !== 'websearch' - } + const isNamed = isNamedTool let siblingNames = $derived(tools.filter(isNamed).map((tool) => tool?.summary ?? '')) @@ -103,6 +108,7 @@ )} on:pickMcpTool={() => (onAddTool?.({ kind: 'mcpTool' }), close())} on:pickWebsearchTool={() => (onAddTool?.({ kind: 'websearchTool' }), close())} + on:pickQuestionTool={() => (onAddTool?.({ kind: 'questionTool' }), close())} on:pickAiAgentTool={() => (onAddTool?.({ kind: 'aiAgentTool' }), close())} on:pickAiDecisionTool={() => (onAddTool?.({ kind: 'aiDecisionTool' }), close())} /> diff --git a/frontend/src/lib/components/flows/content/AgentToolWrapper.svelte b/frontend/src/lib/components/flows/content/AgentToolWrapper.svelte index 69a4acf74e..594ab97f34 100644 --- a/frontend/src/lib/components/flows/content/AgentToolWrapper.svelte +++ b/frontend/src/lib/components/flows/content/AgentToolWrapper.svelte @@ -5,6 +5,7 @@ import FlowModuleComponent from './FlowModuleComponent.svelte' import McpToolEditor from './McpToolEditor.svelte' import WebsearchToolDisplay from './WebsearchToolDisplay.svelte' + import QuestionToolDisplay from './QuestionToolDisplay.svelte' interface Props { tool: AgentTool @@ -62,6 +63,9 @@ isAgentTool={true} {staticOnly} bind:toolDescription={tool.description} + bind:toolRequiresApproval={ + () => tool.requires_approval, (v) => (tool.requires_approval = v || undefined) + } {siblingToolNames} /> {:else if isMcpTool(tool)} @@ -69,4 +73,6 @@ <McpToolEditor bind:tool {noEditor} /> {:else if isWebsearchTool(tool)} <WebsearchToolDisplay {noEditor} /> +{:else if tool.value?.tool_type === 'question'} + <QuestionToolDisplay bind:tool {noEditor} /> {/if} diff --git a/frontend/src/lib/components/flows/content/FlowModuleComponent.svelte b/frontend/src/lib/components/flows/content/FlowModuleComponent.svelte index fa64fad44d..fb2e0bcb1f 100644 --- a/frontend/src/lib/components/flows/content/FlowModuleComponent.svelte +++ b/frontend/src/lib/components/flows/content/FlowModuleComponent.svelte @@ -71,7 +71,8 @@ signDebugRequest, getDebugErrorMessage } from '$lib/components/debug' - import { Bug, Terminal } from 'lucide-svelte' + import { Bug, Hand, Terminal } from 'lucide-svelte' + import Popover from '$lib/components/Popover.svelte' import { sendUserToast } from '$lib/utils' import { useOperatingWorkspace } from '$lib/components/operatingWorkspace.svelte' @@ -133,6 +134,8 @@ /** Lets the agent's Tools section add a tool through the graph's own insert path. */ flowModuleSchemaMap?: import('../map/FlowModuleSchemaMap.svelte').default toolDescription?: string | undefined + /** The tool's `requires_approval` setting; only an agent tool has one. */ + toolRequiresApproval?: boolean siblingToolNames?: string[] } @@ -153,6 +156,7 @@ staticOnly = false, flowModuleSchemaMap = undefined, toolDescription = $bindable(undefined), + toolRequiresApproval = $bindable(), siblingToolNames = undefined }: Props = $props() @@ -1149,6 +1153,20 @@ label="Chat" /> {/if} + {#if isAgentTool} + <Tab value="tool_settings" label="Tool settings"> + {#snippet extra()} + {#if toolRequiresApproval} + <div class="flex flex-row items-center gap-1 text-secondary"> + <Popover notClickable> + <Hand size={12} /> + {#snippet text()}Require approval · On{/snippet} + </Popover> + </div> + {/if} + {/snippet} + </Tab> + {/if} {#if !preprocessorModule && !isAgentTool} <Tab value="advanced" label="Run settings"> {#snippet extra()} @@ -1395,6 +1413,24 @@ /> </Section> </div> + {:else if visibleSelected === 'tool_settings' && isAgentTool} + <div class="flex-1 overflow-auto p-4"> + <Section label="Approval"> + <Toggle + size="xs" + textClass="text-xs font-normal text-primary" + disabled={noEditor} + bind:checked={ + () => toolRequiresApproval ?? false, (v) => (toolRequiresApproval = v) + } + options={{ + right: 'Require approval', + rightTooltip: + 'Each call waits for someone to approve or reject it from the run page or the chat, without holding a worker. Other calls in the same turn run right away. A rejected call is reported to the agent as not run. An agent used as a tool of another agent cannot wait, so it leaves such tools out.' + }} + /> + </Section> + </div> {:else if visibleSelected === 'advanced'} <FlowRunSettings bind:this={runSettings} diff --git a/frontend/src/lib/components/flows/content/McpToolEditor.svelte b/frontend/src/lib/components/flows/content/McpToolEditor.svelte index f69aa25d1d..18d69dcb63 100644 --- a/frontend/src/lib/components/flows/content/McpToolEditor.svelte +++ b/frontend/src/lib/components/flows/content/McpToolEditor.svelte @@ -31,6 +31,7 @@ import McpConnect from '$lib/components/mcp/McpConnect.svelte' import type { FlowEditorContext } from '../types' import { useOperatingWorkspace } from '$lib/components/operatingWorkspace.svelte' + import Toggle from '$lib/components/Toggle.svelte' const operatingWorkspace = useOperatingWorkspace() @@ -126,6 +127,19 @@ /> </Label> </div> + <Toggle + size="xs" + textClass="text-xs font-normal text-primary" + disabled={noEditor} + bind:checked={ + () => tool.requires_approval ?? false, (v) => (tool.requires_approval = v || undefined) + } + options={{ + right: 'Require approval', + rightTooltip: + 'Each call waits for someone to approve or reject it from the run page or the chat, without holding a worker. Other calls in the same turn run right away. A rejected call is reported to the agent as not run. An agent used as a tool of another agent cannot wait, so it leaves such tools out.' + }} + /> <Section label="Available Tools"> {#snippet action()} diff --git a/frontend/src/lib/components/flows/content/QuestionToolDisplay.svelte b/frontend/src/lib/components/flows/content/QuestionToolDisplay.svelte new file mode 100644 index 0000000000..c07033b264 --- /dev/null +++ b/frontend/src/lib/components/flows/content/QuestionToolDisplay.svelte @@ -0,0 +1,32 @@ +<script lang="ts"> + import { SecondsInput } from '$lib/components/common' + import Label from '$lib/components/Label.svelte' + import FlowCard from '../common/FlowCard.svelte' + import { BUILTIN_TOOLS, type AgentTool } from '../agentToolUtils' + + /** Matches `DEFAULT_TIMEOUT_SECS` in `windmill-worker/src/ai/pause.rs`. */ + const DEFAULT_QUESTION_TIMEOUT_SECS = 1800 + + let { tool = $bindable(), noEditor = false }: { tool: AgentTool; noEditor?: boolean } = $props() + + let value = $derived(tool.value as { tool_type: 'question'; timeout?: number }) +</script> + +<FlowCard + {noEditor} + title={BUILTIN_TOOLS.question.label} + subtitle="Lets the agent ask a person and wait for their answer, from the run page or the chat." + subtitleDocLink="https://www.windmill.dev/docs/core_concepts/ai_agents" +> + <div class="flex flex-col gap-4 overflow-auto p-4" style="scrollbar-gutter: stable"> + <Label label="Timeout"> + <p class="text-xs font-normal text-secondary">Past it, the agent is told nobody answered</p> + <SecondsInput + disabled={noEditor} + bind:seconds={ + () => value.timeout ?? DEFAULT_QUESTION_TIMEOUT_SECS, (v) => (value.timeout = v) + } + /> + </Label> + </div> +</FlowCard> diff --git a/frontend/src/lib/components/flows/content/WebsearchToolDisplay.svelte b/frontend/src/lib/components/flows/content/WebsearchToolDisplay.svelte index 2d679ff665..13d229ca97 100644 --- a/frontend/src/lib/components/flows/content/WebsearchToolDisplay.svelte +++ b/frontend/src/lib/components/flows/content/WebsearchToolDisplay.svelte @@ -1,15 +1,12 @@ <script lang="ts"> - import Alert from '$lib/components/common/alert/Alert.svelte' import FlowCard from '../common/FlowCard.svelte' let { noEditor = false }: { noEditor?: boolean } = $props() </script> -<FlowCard {noEditor} title="Web search"> - <div class="flex flex-col gap-4 overflow-auto p-4" style="scrollbar-gutter: stable"> - <Alert title="Web search tool" type="info"> - Gives the AI Agent the ability to search the web. Only works for openai, anthropic and google - models for now. - </Alert> - </div> -</FlowCard> +<FlowCard + {noEditor} + title="Web search" + subtitle="Works with OpenAI, Anthropic and Google models." + subtitleDocLink="https://www.windmill.dev/docs/core_concepts/ai_agents" +/> diff --git a/frontend/src/lib/components/flows/conversations/FlowChatInterface.svelte b/frontend/src/lib/components/flows/conversations/FlowChatInterface.svelte index 52098d33ee..15f9f97831 100644 --- a/frontend/src/lib/components/flows/conversations/FlowChatInterface.svelte +++ b/frontend/src/lib/components/flows/conversations/FlowChatInterface.svelte @@ -12,7 +12,7 @@ import { tick, untrack } from 'svelte' import type { Chat } from 'windmill-chat' import { saveFlowChatInputs } from './flowChatProps' - import { ResourceService, type FlowModule } from '$lib/gen' + import { JobService, ResourceService, type FlowModule } from '$lib/gen' import { resource } from 'runed' import { useWorkspaceStorageConfigured } from '$lib/components/inputTransformEnv.svelte' import { @@ -22,6 +22,10 @@ } from './agentAttachmentInput' import { deepEqual } from 'fast-equals' import FlowChatModelSettings from './FlowChatModelSettings.svelte' + import { + pendingAgentApproval, + type PendingAgentRequest + } from '$lib/components/agentRequest' import { agentModelGap, chatLinkedAgentPaths, @@ -202,7 +206,8 @@ sendDisabled: () => deploymentInProgress || !!modelGap || !!wrongKindReason, // The model controls only: a retry changes model when the reader did, but replays // the run's own attachments rather than whatever the composer holds now. - inputsShownInComposer: () => composerOwnedInputs(modelWiring, undefined) + inputsShownInComposer: () => composerOwnedInputs(modelWiring, undefined), + agentRequest: () => agentRequest }) setChatViewHost(chatHost) @@ -248,6 +253,49 @@ }) }) + // Only a flow that can ask a person something reads its running turn's status. Read off the + // flow, not the stream: an agent that does not stream sends no tool call. A linked agent's + // tools are not loaded here, so it counts; only a top-level step's request is answered from + // the chat. + const mayRequestApproval = $derived( + (flowModules ?? []).some((module) => { + const value = module.value as any + return ( + value?.type === 'aiagent' && + (!!value.agent || + value.tools?.some( + (tool: any) => tool?.requires_approval || tool?.value?.tool_type === 'question' + )) + ) + }) + ) + const approvalJobId = $derived(mayRequestApproval ? chatHost.state.runningJobId : undefined) + + // The stream only says a call is running; the request to answer, and the job that answers + // it, are on the flow's status. + let agentRequest = $state<PendingAgentRequest | undefined>(undefined) + $effect(() => { + const id = approvalJobId + agentRequest = undefined + if (!id || !workspace) return + const args = { workspace, id, noLogs: true } + let stopped = false + const load = async () => { + try { + const job = await JobService.getJob(args) + if (!stopped) agentRequest = pendingAgentApproval(job) + } catch { + // transient; the next poll reads it again + } + } + void load() + const interval = setInterval(load, 2000) + return () => { + stopped = true + clearInterval(interval) + } + }) + // Older pages load when the reader reaches the top; the viewport stays where it was. let scrollElement = $state<HTMLDivElement | undefined>(undefined) let loadingOlder = false diff --git a/frontend/src/lib/components/flows/conversations/flowChatViewHost.svelte.ts b/frontend/src/lib/components/flows/conversations/flowChatViewHost.svelte.ts index 6009d73ccd..d9ff62d8e3 100644 --- a/frontend/src/lib/components/flows/conversations/flowChatViewHost.svelte.ts +++ b/frontend/src/lib/components/flows/conversations/flowChatViewHost.svelte.ts @@ -18,7 +18,11 @@ import type { ChatSendRequestOptions, ChatViewHost } from '$lib/components/copilot/chat/chatViewHost' -import type { DisplayMessage, WebSearchResult } from '$lib/components/copilot/chat/shared' +import type { + DisplayMessage, + ToolDisplayMessage, + WebSearchResult +} from '$lib/components/copilot/chat/shared' import type { AIAutonomyMode } from '$lib/components/copilot/chat/AIChatManager.svelte' import { AIWorkMode } from '$lib/components/copilot/chat/workMode' import { isPlanCardTool } from '$lib/components/copilot/chat/planMode' @@ -36,6 +40,11 @@ import { JobService } from '$lib/gen' import { sendUserToast } from '$lib/toast' import { attachmentLanes } from './messageAttachments' import type { AttachmentsTarget } from './agentAttachmentInput' +import { + answerAgentRequest, + type AgentRequest, + type PendingAgentRequest +} from '$lib/components/agentRequest' export type FlowChatViewHostOptions = { /** The flow inputs sent next to `user_message` with every turn. */ @@ -55,6 +64,8 @@ export type FlowChatViewHostOptions = { /** Flow inputs edited by a control beside the composer, such as the model button. A retry * takes their current value rather than the failed turn's. */ inputsShownInComposer?: () => string[] + /** The approval or question the running turn's agent step waits on. */ + agentRequest?: () => PendingAgentRequest | undefined /** Injectables for tests: the clock and scheduler behind the typewriter pacing. */ revealOptions?: Pick<TypewriterRevealOptions, 'instant' | 'now' | 'schedule' | 'cancel'> } @@ -133,6 +144,57 @@ export type DisplayLookups = { workspace?: string /** How much of a pending assistant row the pacing has put on screen. */ revealed?: (message: ChatMessage) => Revealed | undefined + /** The approval or question the running turn's agent waits on. */ + request?: AgentRequest +} + +const QUESTION_CALL = /^ask_question(_\d+)?$/ + +/** The calls a request holds, as the cards the copilot shows for a confirmation or a question. + * `row` is the streamed card of that call, if any: an agent that does not stream sends none. */ +function requestCard( + request: AgentRequest, + toolName: string, + row: ToolDisplayMessage +): ToolDisplayMessage { + if (request.type === 'question') { + return { + ...row, + content: 'Waiting for your answer', + isLoading: true, + userQuestion: { + question: request.question, + choices: request.choices ?? [], + multiSelect: request.multi_select + } + } + } + const call = request.calls.find((c) => c.function_name === toolName) + const others = request.calls.length - 1 + return { + ...row, + content: + `Waiting for approval to run ${toolName}` + + (others > 0 ? `, answered together with ${others} other call${others > 1 ? 's' : ''}` : ''), + parameters: row.parameters ?? call?.arguments, + showDetails: true, + isLoading: true, + needsConfirmation: true, + confirmAction: 'run' + } +} + +function requestKey({ agentJobId, action }: PendingAgentRequest): string { + return `${agentJobId}:${action.call_id}` +} + +function holds(request: AgentRequest, toolName: string | undefined): toolName is string { + return ( + !!toolName && + (request.type === 'question' + ? QUESTION_CALL.test(toolName) + : request.calls.some((c) => c.function_name === toolName)) + ) } /** @@ -196,7 +258,9 @@ export function toDisplayMessages( for (let i = messages.length - 1; i >= 0 && latestUser < 0; i--) { if (messages[i].role === 'user') latestUser = i } - return messages.flatMap((message, i): DisplayMessage[] => { + const request = lookups.request + let requestShown = false + const shown = messages.flatMap((message, i): DisplayMessage[] => { switch (message.role) { case 'user': { const index = userIndex++ @@ -253,7 +317,7 @@ export function toDisplayMessages( !STRUCTURED_OUTPUT_CALL.test(message.tool.name) ? `${message.tool.name} did not finish` : undefined - const call: DisplayMessage = { + let call: ToolDisplayMessage = { role: 'tool', tool_call_id: message.id, // The card's header is the row's text, which the server only words once the @@ -270,6 +334,10 @@ export function toDisplayMessages( isLoading: message.pending && message.tool?.status === 'running', jobId: message.jobId } + if (request && i > latestUser && call.isLoading && holds(request, toolName)) { + call = requestCard(request, toolName, call) + requestShown = true + } // The tool card has no thinking section: the thinking that led to the call reads // as a card of its own, just before it. return message.reasoning @@ -308,6 +376,25 @@ export function toDisplayMessages( } } }) + if (!request || requestShown) return shown + // No streamed card to put it on: the agent does not stream, or the page was opened after + // the call was made. + const calls = + request.type === 'question' + ? [{ function_name: 'ask_question', arguments: undefined }] + : request.calls + return [ + ...shown, + ...calls.map((call, n) => + requestCard(request, call.function_name, { + role: 'tool', + tool_call_id: `${request.call_id}:${n}`, + content: '', + toolName: call.function_name, + parameters: call.arguments + }) + ) + ] } /** The two paced lanes of one streaming message, and how much of each has been fed in. */ @@ -450,9 +537,30 @@ export class FlowChatViewHost implements ChatViewHost, DraftSender<ComposerAttac displayMessages = $derived.by(() => toDisplayMessages(this.#state.messages, isBusy(this.#state.status), this.#stoppedTurns, { workspace: this.#options.workspace?.(), - revealed: (message) => this.#revealed[message.id] + revealed: (message) => this.#revealed[message.id], + request: this.#agentRequest?.action }) ) + + /** The request answered here, by agent job and call id: its cards drop their buttons until + * the flow's status catches up. */ + #answeredRequest = $state<string | undefined>(undefined) + get #agentRequest(): PendingAgentRequest | undefined { + const request = this.#options.agentRequest?.() + return request && requestKey(request) === this.#answeredRequest ? undefined : request + } + + #answer(approved: boolean, answer?: string | string[]): boolean { + const request = this.#agentRequest + const workspace = this.#options.workspace?.() + if (!request || !workspace) return false + this.#answeredRequest = requestKey(request) + answerAgentRequest(workspace, request, approved, answer).catch((e: any) => { + this.#answeredRequest = undefined + sendUserToast(e?.body ?? e?.message ?? 'Failed to answer the request', true) + }) + return true + } /** The user message of each turn stopped in this view, by message id and, once the chat has * read its row, row id: a reopened conversation or an older page rebuilds messages from rows, * so a turn left before its row was read is not recognised there. Only this session knows; @@ -698,8 +806,16 @@ export class FlowChatViewHost implements ChatViewHost, DraftSender<ComposerAttac void this.#turns.send(composerDraft(message.content), replayInputs) } restartGeneration = () => {} - handleUserQuestionAnswer = () => false - handleToolConfirmation = () => {} + handleUserQuestionAnswer = (_toolId: string, choices: string[]) => + this.#answer( + true, + this.#agentRequest?.action.type === 'question' && this.#agentRequest.action.multi_select + ? choices + : choices[0] + ) + handleToolConfirmation = (_toolId: string, confirmed: boolean) => { + this.#answer(confirmed) + } hasPendingRunForm = false isRunFormPending = () => false diff --git a/frontend/src/lib/components/flows/conversations/flowChatViewHost.test.ts b/frontend/src/lib/components/flows/conversations/flowChatViewHost.test.ts index 1c1a62dab8..617f3c7ffe 100644 --- a/frontend/src/lib/components/flows/conversations/flowChatViewHost.test.ts +++ b/frontend/src/lib/components/flows/conversations/flowChatViewHost.test.ts @@ -177,6 +177,51 @@ describe('toDisplayMessages', () => { expect(notCitations).toMatchObject({ toolName: 'websearch', result: { hits: 3 } }) }) + it('puts a pending request on the card of the call it holds, or adds one when none streamed', () => { + const approval = { + type: 'approval' as const, + call_id: 'c1', + calls: [{ function_name: 'delete_database', arguments: { name: 'staging' } }], + expires_at: '2026-09-16T10:30:00Z' + } + const turn = [ + message({ role: 'user', content: 'delete staging' }), + message({ role: 'tool', pending: true, tool: { name: 'list_databases', status: 'success' } }), + message({ role: 'tool', pending: true, tool: { name: 'delete_database', status: 'running' } }) + ] + const held = toDisplayMessages(turn, true, new Set(), { request: approval }) + expect(held).toHaveLength(3) + expect(held[1]).not.toHaveProperty('needsConfirmation') + expect(held[2]).toMatchObject({ + needsConfirmation: true, + isLoading: true, + parameters: { name: 'staging' } + }) + + const twice = { + ...approval, + calls: [...approval.calls, { function_name: 'delete_database', arguments: { name: 'prod' } }] + } + const added = toDisplayMessages(turn.slice(0, 1), true, new Set(), { request: twice }) + expect(added.slice(1).map((m) => (m as { parameters?: unknown }).parameters)).toEqual([ + { name: 'staging' }, + { name: 'prod' } + ]) + + const question = { + type: 'question' as const, + call_id: 'c2', + question: 'Which one?', + expires_at: '2026-09-16T10:30:00Z' + } + const unstreamed = toDisplayMessages(turn.slice(0, 1), true, new Set(), { request: question }) + expect(unstreamed[1]).toMatchObject({ + role: 'tool', + isLoading: true, + userQuestion: { question: 'Which one?', choices: [] } + }) + }) + it('shows a call the turn finished without as an error, not as still running', () => { const display = toDisplayMessages([ message({ role: 'user', content: 'hi' }), diff --git a/frontend/src/lib/components/flows/flowStateUtils.svelte.ts b/frontend/src/lib/components/flows/flowStateUtils.svelte.ts index 030897a63b..955d94bf52 100644 --- a/frontend/src/lib/components/flows/flowStateUtils.svelte.ts +++ b/frontend/src/lib/components/flows/flowStateUtils.svelte.ts @@ -32,6 +32,7 @@ import { createAiDecisionTool, createMcpTool, createWebsearchTool, + createQuestionTool, newAiDecisionInputTransforms, newFlowModuleAgentTool, SPECIAL_TOOL_KINDS, @@ -587,6 +588,9 @@ export async function insertNewModuleAtIndex( const websearchTool = createWebsearchTool(module.id) ;(modules as AgentTool[]).splice(index, 0, websearchTool) return modules as AgentTool[] + } else if (toolKind === 'questionTool') { + ;(modules as AgentTool[]).splice(index, 0, createQuestionTool(module.id)) + return modules as AgentTool[] } else if (toolKind === 'aiAgentTool') { // Create AI Agent tool (nested agent) const aiAgentTool = createAiAgentTool(module.id) diff --git a/frontend/src/lib/components/flows/map/InsertModuleInner.svelte b/frontend/src/lib/components/flows/map/InsertModuleInner.svelte index b4228ea0a3..5bb48febd2 100644 --- a/frontend/src/lib/components/flows/map/InsertModuleInner.svelte +++ b/frontend/src/lib/components/flows/map/InsertModuleInner.svelte @@ -243,12 +243,22 @@ }} /> <TopLevelNode - label="Web Search" + label="Web search" onSelect={() => { dispatch('pickWebsearchTool') dispatch('close') }} /> + <!-- A nested agent cannot park, so the worker drops it from its roster. --> + {#if !nestedAgent} + <TopLevelNode + label="Ask a question" + onSelect={() => { + dispatch('pickQuestionTool') + dispatch('close') + }} + /> + {/if} <TopLevelNode label="AI Agent" chevron={false} diff --git a/frontend/src/lib/components/flows/pickers/TopLevelNode.svelte b/frontend/src/lib/components/flows/pickers/TopLevelNode.svelte index a8f3e040c4..69ce0e4848 100644 --- a/frontend/src/lib/components/flows/pickers/TopLevelNode.svelte +++ b/frontend/src/lib/components/flows/pickers/TopLevelNode.svelte @@ -11,6 +11,7 @@ Repeat, Scale, Square, + MessageCircleQuestion, Zap } from 'lucide-svelte' import type { ComponentType } from 'svelte' @@ -54,7 +55,8 @@ 'Claude Code': { icon: BotIcon, iconClass: 'text-ai' }, Pi: { icon: BotIcon, iconClass: 'text-ai' }, MCP: { icon: Plug }, - 'Web Search': { icon: Globe } + 'Web search': { icon: Globe }, + 'Ask a question': { icon: MessageCircleQuestion } } const config = $derived(iconMap[label]) diff --git a/frontend/src/lib/components/graph/graphBuilder.svelte.ts b/frontend/src/lib/components/graph/graphBuilder.svelte.ts index 98a03f8c0f..8fc8e664f0 100644 --- a/frontend/src/lib/components/graph/graphBuilder.svelte.ts +++ b/frontend/src/lib/components/graph/graphBuilder.svelte.ts @@ -32,6 +32,7 @@ export type InsertKind = | 'aidecision' | 'mcpTool' | 'websearchTool' + | 'questionTool' | 'aiAgentTool' | 'aiDecisionTool' diff --git a/frontend/src/lib/components/graph/renderers/nodes/AIToolNode.svelte b/frontend/src/lib/components/graph/renderers/nodes/AIToolNode.svelte index a8880334ca..4f91b87a95 100644 --- a/frontend/src/lib/components/graph/renderers/nodes/AIToolNode.svelte +++ b/frontend/src/lib/components/graph/renderers/nodes/AIToolNode.svelte @@ -1,5 +1,10 @@ <script module lang="ts"> - import { getToolNameError, type AgentTool } from '$lib/components/flows/agentToolUtils' + import { + BUILTIN_TOOLS, + builtinToolType, + getToolNameError, + type AgentTool + } from '$lib/components/flows/agentToolUtils' export const AI_TOOL_BASE_OFFSET = 5 export const AI_TOOL_ROW_OFFSET = 30 @@ -9,6 +14,8 @@ export const AI_MCP_TOOL_CALL_PREFIX = '_wm_ai_mcp_tool_call' export const AI_TOOL_MESSAGE_PREFIX = '_wm_ai_agent_message' export const AI_WEBSEARCH_PREFIX = '_wm_ai_websearch' + export const AI_APPROVAL_PREFIX = '_wm_ai_approval' + export const AI_QUESTION_PREFIX = '_wm_ai_question' const ROW_WIDTH = 275 const NEW_TOOL_NODE_WIDTH = 50 @@ -48,6 +55,8 @@ return action.module_id === tool.moduleId case 'web_search': return tool.type === 'websearch' + case 'question': + return tool.type === 'question' case 'mcp_tool_call': // One MCP node stands for a whole server and many function names, so the server path // is the only join that holds. The worker strips `$res:` before building the action, @@ -56,6 +65,8 @@ tool.type === 'mcp' && bareResourcePath(action.resource_path) === bareResourcePath(tool.resourcePath) ) + // The calls it holds are decorated by their own actions once they run. + case 'approval': case 'message': return false } @@ -76,6 +87,10 @@ return AI_MCP_TOOL_CALL_PREFIX + '-' + agentModuleId + '-' + idx case 'web_search': return AI_WEBSEARCH_PREFIX + '-' + agentModuleId + '-' + idx + case 'approval': + return AI_APPROVAL_PREFIX + '-' + agentModuleId + '-' + idx + case 'question': + return AI_QUESTION_PREFIX + '-' + agentModuleId + '-' + idx case 'message': return getToolCallId(idx, agentModuleId) } @@ -156,15 +171,13 @@ stateType?: GraphModuleState['type'] resourcePath?: string }[] = sourceTools.map((t, idx) => { - // Handle FlowModule, MCP, and Websearch tools + // Handle FlowModule, MCP, and built-in tools const toolType = - t.value.tool_type === 'mcp' - ? 'mcp' - : t.value.tool_type === 'websearch' - ? 'websearch' - : t.value.tool_type === 'flowmodule' - ? t.value.type - : undefined + t.value.tool_type === 'mcp' || builtinToolType(t) + ? t.value.tool_type + : t.value.tool_type === 'flowmodule' + ? t.value.type + : undefined return { id: t.id, name: t.summary ?? '', @@ -183,7 +196,12 @@ if (a.type === 'tool_call' || a.type === 'mcp_tool_call') { return { id, name: a.function_name } } else if (a.type === 'web_search') { - return { id, name: 'Web Search', type: 'websearch' } + return { id, name: 'Web search', type: 'websearch' } + } else if (a.type === 'approval') { + const names = a.calls.map((call) => call.function_name).join(', ') + return { id, name: `Approval: ${names}`, type: 'approval' } + } else if (a.type === 'question') { + return { id, name: BUILTIN_TOOLS.question.label, type: 'question' } } else { return { id, name: 'Message' } } @@ -304,7 +322,18 @@ NewAiToolN, NodeLayout } from '../../graphBuilder.svelte' - import { Bot, Globe, MessageCircle, Play, Plug, Scale, Wrench, X } from 'lucide-svelte' + import { + Bot, + Globe, + MessageCircle, + MessageCircleQuestion, + Play, + Plug, + Scale, + UserCheck, + Wrench, + X + } from 'lucide-svelte' import { twMerge } from 'tailwind-merge' import type { Edge, Node } from '@xyflow/svelte' @@ -403,6 +432,10 @@ <Play size={16} class="ml-1 shrink-0" /> {:else if data.type === 'websearch'} <Globe size={16} class="ml-1 shrink-0" /> + {:else if data.type === 'approval'} + <UserCheck size={16} class="ml-1 shrink-0" /> + {:else if data.type === 'question'} + <MessageCircleQuestion size={16} class="ml-1 shrink-0" /> {:else if data.type === 'mcp'} <Plug size={16} class="ml-1 shrink-0" /> {:else if data.type === 'aiagent'} diff --git a/frontend/src/lib/components/graph/renderers/nodes/ModuleNode.svelte b/frontend/src/lib/components/graph/renderers/nodes/ModuleNode.svelte index 53679a0de1..0234c09beb 100644 --- a/frontend/src/lib/components/graph/renderers/nodes/ModuleNode.svelte +++ b/frontend/src/lib/components/graph/renderers/nodes/ModuleNode.svelte @@ -10,6 +10,7 @@ import { getContext } from 'svelte' import { getGraphContext } from '../../graphContext' import { getFlowRunStatusContext } from '../../flowRunStatus.svelte' + import { waitingRequest } from '$lib/components/agentRequest' interface Props { data: ModuleN['data'] @@ -22,9 +23,13 @@ const flowRunStatus = getFlowRunStatusContext() let state = $derived.by(() => { - return data.testModuleState + const state = data.testModuleState ? (jobToGraphModuleState(data.testModuleState) ?? flowRunStatus?.getModuleState(data.id)) : flowRunStatus?.getModuleState(data.id) + // An agent waiting on a person reads like an approval step, though its job is running. + return state?.type === 'InProgress' && waitingRequest(state) + ? { ...state, type: 'WaitingForEvents' as const } + : state }) // A `message` is the one action with no tool node of its own, so the annotation is the only @@ -33,6 +38,8 @@ { type: 'tool_call', singular: 'tool call', plural: 'tool calls' }, { type: 'mcp_tool_call', singular: 'MCP call', plural: 'MCP calls' }, { type: 'web_search', singular: 'web search', plural: 'web searches' }, + { type: 'approval', singular: 'approval request', plural: 'approval requests' }, + { type: 'question', singular: 'question', plural: 'questions' }, { type: 'message', singular: 'message', plural: 'messages' } ] as const diff --git a/frontend/src/lib/components/graph/renderers/nodes/NewAIToolNode.svelte b/frontend/src/lib/components/graph/renderers/nodes/NewAIToolNode.svelte index 7c088c119a..3cfa3f64f9 100644 --- a/frontend/src/lib/components/graph/renderers/nodes/NewAIToolNode.svelte +++ b/frontend/src/lib/components/graph/renderers/nodes/NewAIToolNode.svelte @@ -106,6 +106,14 @@ }) close() }} + on:pickQuestionTool={() => { + data.eventHandlers.insert({ + index: -1, + agentId: data.agentModuleId, + kind: 'questionTool' + }) + close() + }} on:pickAiAgentTool={(e) => { data.eventHandlers.insert({ index: -1, diff --git a/frontend/src/lib/components/runs/FlowExecutionStatus.svelte b/frontend/src/lib/components/runs/FlowExecutionStatus.svelte index 67b6520ffb..d3bed5d562 100644 --- a/frontend/src/lib/components/runs/FlowExecutionStatus.svelte +++ b/frontend/src/lib/components/runs/FlowExecutionStatus.svelte @@ -1,5 +1,7 @@ <script lang="ts"> import FlowStatusWaitingForEvents from '../FlowStatusWaitingForEvents.svelte' + import AgentApprovalRequest from '../AgentApprovalRequest.svelte' + import { pendingAgentApproval } from '../agentRequest' import type { FlowStatusModule, Job } from '$lib/gen' import { type StateStore } from '$lib/utils' import { fade, slide } from 'svelte/transition' @@ -18,7 +20,9 @@ ) const isSuspended = $derived(suspendStatus.val && Object.keys(suspendStatus.val).length > 0) - const anyStatusActive = $derived(isWaitingForEvents || isSuspended) + const pendingApproval = $derived(pendingAgentApproval(job)) + + const anyStatusActive = $derived(isWaitingForEvents || isSuspended || !!pendingApproval) </script> {#if job && anyStatusActive} @@ -28,6 +32,15 @@ > {#if isWaitingForEvents} <FlowStatusWaitingForEvents workspaceId={job.workspace_id} {job} {isOwner} /> + {:else if pendingApproval} + {#key pendingApproval.action.call_id} + <AgentApprovalRequest + workspaceId={job.workspace_id ?? ''} + agentJobId={pendingApproval.agentJobId} + request={pendingApproval.action} + pending + /> + {/key} {:else if isSuspended} <div class="flex gap-2 flex-col" in:fade={{ duration: 150 }}> {#each Object.values(suspendStatus.val) as suspendCount (suspendCount.job.id)} diff --git a/frontend/src/lib/components/runs/JobStatusIcon.svelte b/frontend/src/lib/components/runs/JobStatusIcon.svelte index 358ab1edeb..c37791310e 100644 --- a/frontend/src/lib/components/runs/JobStatusIcon.svelte +++ b/frontend/src/lib/components/runs/JobStatusIcon.svelte @@ -13,6 +13,7 @@ X } from 'lucide-svelte' import type { Job } from '$lib/gen' + import { isSuspended } from '../agentRequest' interface Props { job: Job @@ -60,7 +61,7 @@ <Badge color="red" {roundedFull} baseClass={roundedFull ? '' : '!px-1.5'}> <X size={14} /> </Badge> - {:else if 'running' in job && job.running && job.suspend} + {:else if 'running' in job && job.running && isSuspended(job)} <Badge color="violet" {roundedFull} baseClass={roundedFull ? '' : '!px-1.5'} title="Suspended"> <Hourglass size={14} /> </Badge> diff --git a/openflow.openapi.yaml b/openflow.openapi.yaml index 91a2d4b79e..1d3ee7db95 100644 --- a/openflow.openapi.yaml +++ b/openflow.openapi.yaml @@ -1008,7 +1008,7 @@ components: description: Unique identifier for this tool. Cannot contain spaces - use underscores instead (e.g., 'get_user_data' not 'get user data') summary: type: string - description: "The name the AI agent calls this tool by, not a human label. On a flowmodule tool it must match ^[a-zA-Z0-9_]+$ - letters, numbers and underscores only (e.g. 'search_documentation', not 'Search documentation') - and always be set; on an mcp or websearch tool it is a plain label. Put the human-readable explanation in 'description'." + description: "The name the AI agent calls this tool by, not a human label. On a flowmodule tool it must match ^[a-zA-Z0-9_]+$ - letters, numbers and underscores only (e.g. 'search_documentation', not 'Search documentation') - and always be set; on an mcp, websearch or question tool it is a plain label. Put the human-readable explanation in 'description'." description: type: string description: Free-text description of the tool given to the AI to decide when and how to call it. Overrides the description auto-derived from the underlying script. @@ -1018,6 +1018,9 @@ components: items: type: string description: "Scopes the token of this tool's jobs is restricted to, on top of the agent step's own restriction: a tool can only narrow it." + requires_approval: + type: boolean + description: "Flowmodule and mcp tools only. Each call waits for a person to approve or reject it from the flow's run page or chat, without the agent holding a worker. Calls in the same turn that do not require approval run right away. A rejected call, or one nobody answers within 30 minutes, is reported to the AI as not run." value: $ref: '#/components/schemas/ToolValue' required: @@ -1030,12 +1033,14 @@ components: - $ref: '#/components/schemas/FlowModuleTool' - $ref: '#/components/schemas/McpToolValue' - $ref: '#/components/schemas/WebsearchToolValue' + - $ref: '#/components/schemas/QuestionToolValue' discriminator: propertyName: tool_type mapping: flowmodule: '#/components/schemas/FlowModuleTool' mcp: '#/components/schemas/McpToolValue' websearch: '#/components/schemas/WebsearchToolValue' + question: '#/components/schemas/QuestionToolValue' FlowModuleTool: description: A tool implemented as a flow module (script, flow, etc.). The AI can call this like any other flow module @@ -1061,6 +1066,20 @@ components: required: - tool_type + QuestionToolValue: + type: object + description: "Built-in tool the AI calls as ask_question: the agent stops, releasing its worker, until someone answers from the flow's run page or chat or the question times out, then resumes with the answer as the tool result." + properties: + tool_type: + type: string + enum: + - question + timeout: + type: integer + description: Seconds to wait for an answer before the question is reported to the AI as timed out. Defaults to 1800. + required: + - tool_type + McpToolValue: type: object description: Reference to an external MCP (Model Context Protocol) tool. The AI can call tools from MCP servers @@ -1494,6 +1513,57 @@ components: enum: [web_search] required: - type + - type: object + properties: + type: + type: string + enum: [approval] + call_id: + type: string + calls: + type: array + items: + type: object + properties: + function_name: + type: string + arguments: {} + required: + - function_name + - arguments + expires_at: + type: string + format: date-time + required: + - type + - call_id + - calls + - expires_at + - type: object + properties: + type: + type: string + enum: [question] + call_id: + type: string + question: + type: string + choices: + type: array + items: + type: string + description: answers the model proposes; a free-text answer is always possible + multi_select: + type: boolean + description: whether several choices can be picked together + expires_at: + type: string + format: date-time + required: + - type + - call_id + - question + - expires_at - type: object properties: type: diff --git a/system_prompts/auto-generated/flow.md b/system_prompts/auto-generated/flow.md index b6ba8de664..4ddf084d34 100644 --- a/system_prompts/auto-generated/flow.md +++ b/system_prompts/auto-generated/flow.md @@ -68,7 +68,10 @@ value: An `aiagent` module runs an LLM that can call tools. Each entry of `value.tools` is a module-shaped object with an extra `value.tool_type`: `flowmodule` for a script/flow tool, `mcp` for an MCP server -tool, `websearch` for web search. +tool, `websearch` for web search, `question` for a built-in `ask_question` tool (the agent stops, +without holding a worker, until someone answers from the run page or the chat; optional +`value.timeout` in seconds, default 1800). Set `requires_approval: true` on a `flowmodule` or `mcp` +tool to have a person approve or reject each of its calls before it runs. ```json { @@ -164,9 +167,9 @@ needs becomes unreachable. ### Tool Naming Rules -These rules cover `flowmodule` tools, the ones the agent calls by name. A `websearch` tool's -`summary` is a plain label (`Web Search`), and an `mcp` tool exposes the MCP server's own tool -names, so neither is name-checked at all — leave those summaries as they are. +These rules cover `flowmodule` tools, the ones the agent calls by name. A `websearch` or `question` +tool's `summary` is a plain label (`Web Search`), and an `mcp` tool exposes the MCP +server's own tool names, so none is name-checked at all — leave those summaries as they are. - A flowmodule tool's `summary` is the **name the agent calls it by**, not a human label. Put the human-readable explanation in `description` @@ -610,4 +613,4 @@ Reference a specific resource using `$res:` prefix: ## OpenFlow Schema -{"OpenFlow":{"type":"object","description":"Top-level flow definition containing metadata, configuration, and the flow structure","properties":{"summary":{"type":"string","description":"Short description of what this flow does"},"description":{"type":"string","description":"Detailed documentation for this flow"},"value":{"$ref":"#/components/schemas/FlowValue"},"schema":{"type":"object","description":"JSON Schema for flow inputs. Use this to define input parameters, their types, defaults, and validation. For resource inputs, set type to 'object' and format to 'resource-<type>' (e.g., 'resource-stripe')"},"on_behalf_of_email":{"type":"string","description":"Address of the account the flow runs on behalf of. Derived from on_behalf_of on read; accepted on write, where it is resolved to the account it names."},"on_behalf_of":{"type":"string","description":"The flow runs with the permissions of this identity: u/{username}, g/{group}, or a bare email when the username is itself email-shaped. The only stored half of the identity; on_behalf_of_email is derived from it. Omit it when writing and it is resolved from that address instead."}},"required":["summary","value"]},"FlowValue":{"type":"object","description":"The flow structure containing modules and optional preprocessor/failure handlers","properties":{"modules":{"type":"array","description":"Array of steps that execute in sequence. Each step can be a script, subflow, loop, or branch","items":{"$ref":"#/components/schemas/FlowModule"}},"failure_module":{"description":"Special module that executes when the flow fails. Receives error object with message, name, stack, and step_id. Must have id 'failure'. Only supports script/rawscript types","$ref":"#/components/schemas/FlowModule"},"preprocessor_module":{"description":"Special module that runs before the first step on external triggers. Must have id 'preprocessor'. Only supports script/rawscript types. Cannot reference other step results","$ref":"#/components/schemas/FlowModule"},"same_worker":{"type":"boolean","description":"If true, all steps run on the same worker for better performance"},"preserve_step_tags":{"type":"boolean","description":"If true and the flow runs on a custom worker tag, steps that declare their own non-empty tag run on it instead of inheriting the flow tag. Steps without their own tag still inherit the flow tag."},"concurrent_limit":{"type":"number","description":"Maximum number of concurrent executions of this flow"},"concurrency_key":{"type":"string","description":"Expression to group concurrent executions (e.g., by user ID)"},"concurrency_time_window_s":{"type":"number","description":"Time window in seconds for concurrent_limit"},"debounce_delay_s":{"type":"integer","description":"Delay in seconds to debounce flow executions"},"debounce_key":{"type":"string","description":"Expression to group debounced executions"},"debounce_args_to_accumulate":{"type":"array","description":"Arguments to accumulate across debounced executions","items":{"type":"string"}},"max_total_debouncing_time":{"type":"integer","description":"Maximum total time in seconds that a job can be debounced"},"max_total_debounces_amount":{"type":"integer","description":"Maximum number of times a job can be debounced"},"skip_expr":{"type":"string","description":"JavaScript expression to conditionally skip the entire flow"},"cache_ttl":{"type":"number","description":"Cache duration in seconds for flow results"},"cache_ignore_s3_path":{"type":"boolean"},"delete_after_secs":{"type":"integer","description":"If set, delete the flow job's args, result and logs after this many seconds following job completion"},"flow_env":{"type":"object","description":"Environment variables available to all steps. Values can be strings, JSON values, or special references: '$var:path' (workspace variable) or '$res:path' (resource).","additionalProperties":{}},"priority":{"type":"number","description":"Execution priority (higher numbers run first)"},"early_return":{"type":"string","description":"Id of the step whose result a sync webhook returns as soon as that step completes, while the rest of the flow keeps running. When the step does not run, or fails while the flow has a failure module, the flow's final result is returned instead."},"chat_input_enabled":{"type":"boolean","description":"Whether this flow accepts chat-style input"},"notes":{"type":"array","description":"Sticky notes attached to the flow","items":{"$ref":"#/components/schemas/FlowNote"}},"groups":{"type":"array","description":"Semantic groups of modules for organizational purposes","items":{"$ref":"#/components/schemas/FlowGroup"}}},"required":["modules"]},"Retry":{"type":"object","description":"Retry configuration for failed module executions","properties":{"constant":{"type":"object","description":"Retry with constant delay between attempts","properties":{"attempts":{"type":"integer","description":"Number of retry attempts"},"seconds":{"type":"integer","description":"Seconds to wait between retries"}}},"exponential":{"type":"object","description":"Retry with exponential backoff: the n-th retry waits multiplier \u00d7 seconds^n","properties":{"attempts":{"type":"integer","description":"Number of retry attempts"},"multiplier":{"type":"integer","description":"Multiplier for exponential backoff"},"seconds":{"type":"integer","minimum":1,"description":"Base of the exponential (seconds); the n-th retry waits multiplier \u00d7 seconds^n, where n counts constant retries too"},"random_factor":{"type":"integer","minimum":0,"maximum":100,"description":"Random jitter percentage (0-100) to avoid thundering herd"}}},"retry_if":{"$ref":"#/components/schemas/RetryIf"}}},"FlowNote":{"type":"object","description":"A sticky note attached to a flow for documentation and annotation","properties":{"id":{"type":"string","description":"Unique identifier for the note"},"text":{"type":"string","description":"Content of the note"},"position":{"type":"object","description":"Position of the note in the flow editor","properties":{"x":{"type":"number","description":"X coordinate"},"y":{"type":"number","description":"Y coordinate"}},"required":["x","y"]},"size":{"type":"object","description":"Size of the note in the flow editor","properties":{"width":{"type":"number","description":"Width in pixels"},"height":{"type":"number","description":"Height in pixels"}},"required":["width","height"]},"color":{"type":"string","description":"Color of the note, one of: yellow, blue, green, purple, pink, orange, red, cyan, lime, gray. Any other value renders unstyled."},"type":{"type":"string","enum":["free","group"],"description":"Type of note - 'free' for standalone notes. 'group' notes are deprecated; segment a flow with FlowValue.groups instead."},"locked":{"type":"boolean","default":false,"description":"Whether the note is locked and cannot be edited or moved"},"contained_node_ids":{"type":"array","items":{"type":"string"},"description":"For group notes, the IDs of nodes contained within this group"}},"required":["id","text","color","type"]},"FlowGroup":{"type":"object","description":"A semantic group of flow modules for organizational purposes. Does not affect execution \u2014 modules remain in their original position in the flow. Groups provide naming and collapsibility in the editor. Members are computed dynamically from all nodes on paths between start_id and end_id.","properties":{"summary":{"type":"string","description":"Display name for this group"},"note":{"type":"string","description":"Markdown note shown below the group header"},"autocollapse":{"type":"boolean","default":false,"description":"If true, this group is collapsed by default in the flow editor. UI hint only."},"start_id":{"type":"string","description":"ID of the first flow module in this group (topological entry point)"},"end_id":{"type":"string","description":"ID of the last flow module in this group (topological exit point)"},"color":{"type":"string","description":"Color for the group in the flow editor, one of: yellow, blue, green, purple, pink, orange, red, cyan, lime, gray. Omit it to let the editor pick one."}},"required":["start_id","end_id"]},"RetryIf":{"type":"object","description":"Conditional retry based on error or result","properties":{"expr":{"type":"string","description":"JavaScript expression that returns true to retry. Has access to 'result' and 'error' variables"}},"required":["expr"]},"StopAfterIf":{"type":"object","description":"Early termination condition for a module","properties":{"skip_if_stopped":{"type":"boolean","description":"If true, following steps are skipped when this condition triggers"},"expr":{"type":"string","description":"JavaScript expression evaluated after the module runs. Can use 'result' (step's result) or 'flow_input'. Return true to stop"},"error_message":{"type":"string","nullable":true,"description":"Custom error message when stopping with an error. Mutually exclusive with skip_if_stopped. If set to a non-empty string, the flow stops with this error. If empty string, a default error message is used. If null or omitted, no error is raised."},"error_include_result":{"type":"boolean","description":"When stopping with an error (error_message set), embed the stopping step's own result inside the raised error object (as error.result) instead of discarding it. The top-level result stays { error }. Defaults to false."}},"required":["expr"]},"FlowModule":{"type":"object","description":"A single step in a flow. Can be a script, subflow, loop, or branch","properties":{"id":{"type":"string","description":"Unique identifier for this step. Used to reference results via 'results.step_id'. Must be a valid identifier (alphanumeric, underscore, hyphen)"},"value":{"$ref":"#/components/schemas/FlowModuleValue"},"stop_after_if":{"description":"Early termination condition evaluated after this step completes","$ref":"#/components/schemas/StopAfterIf"},"stop_after_all_iters_if":{"description":"For loops only - early termination condition evaluated after all iterations complete","$ref":"#/components/schemas/StopAfterIf"},"skip_if":{"type":"object","description":"Conditionally skip this step based on previous results or flow inputs","properties":{"expr":{"type":"string","description":"JavaScript expression that returns true to skip. Can use 'flow_input' or 'results.<step_id>'"}},"required":["expr"]},"sleep":{"description":"Delay before executing this step (in seconds or as expression)","$ref":"#/components/schemas/InputTransform"},"cache_ttl":{"type":"number","description":"Cache duration in seconds for this step's results"},"cache_ignore_s3_path":{"type":"boolean"},"timeout":{"description":"Maximum execution time in seconds (static value or expression)","$ref":"#/components/schemas/InputTransform"},"delete_after_secs":{"type":"integer","description":"If set, delete the step's args, result and logs after this many seconds following job completion"},"summary":{"type":"string","description":"Short description of what this step does"},"mock":{"type":"object","description":"Mock configuration for testing without executing the actual step","properties":{"enabled":{"type":"boolean","description":"If true, return mock value instead of executing"},"return_value":{"description":"Value to return when mocked"}}},"suspend":{"type":"object","description":"Configuration for approval/resume steps that wait for user input","properties":{"required_events":{"type":"integer","description":"Number of approvals required before continuing"},"timeout":{"type":"integer","description":"Timeout in seconds before auto-continuing or canceling"},"resume_form":{"type":"object","description":"Form schema for collecting input when resuming","properties":{"schema":{"type":"object","description":"JSON Schema for the resume form"}}},"user_auth_required":{"type":"boolean","description":"If true, only authenticated users can approve"},"user_groups_required":{"description":"Expression or list of groups that can approve","$ref":"#/components/schemas/InputTransform"},"self_approval_disabled":{"type":"boolean","description":"If true, the user who started the flow cannot approve"},"hide_cancel":{"type":"boolean","description":"If true, hide the cancel button on the approval form"},"continue_on_disapprove_timeout":{"type":"boolean","description":"If true, continue flow on timeout instead of canceling"},"skin":{"type":"string","enum":["detailed","minimal"],"description":"How the approval request is presented, on the approval page and in Slack/Teams approval messages. 'detailed' (used when unset) shows the flow details (arguments, graph, approvers); 'minimal' shows only the request: the step description, form and approve/reject actions"}}},"priority":{"type":"number","description":"Execution priority for this step (higher numbers run first)"},"continue_on_error":{"type":"boolean","description":"If true, flow continues even if this step fails"},"job_token_scopes":{"type":"array","nullable":true,"items":{"type":"string"},"description":"Scopes the token of this step's jobs is restricted to (domain:action[:resource], e.g. oidc:write), on top of the flow's own restriction: a step can only narrow it. Applies to everything the step runs (loop and branch bodies, AI agent tools)."},"retry":{"description":"Retry configuration if this step fails","$ref":"#/components/schemas/Retry"},"debouncing":{"description":"Debounce configuration for this step (EE only)","type":"object","properties":{"debounce_delay_s":{"type":"integer","description":"Delay in seconds to debounce this step's executions across flow runs"},"debounce_key":{"type":"string","description":"Expression to group debounced executions. Supports $workspace and $args[name]. Default: $workspace/flow/<flow_path>-<step_id>"},"debounce_args_to_accumulate":{"type":"array","description":"Array-type arguments to accumulate across debounced executions","items":{"type":"string"}},"max_total_debouncing_time":{"type":"integer","description":"Maximum total time in seconds before forced execution"},"max_total_debounces_amount":{"type":"integer","description":"Maximum number of debounces before forced execution"}}}},"required":["value","id"]},"InputTransform":{"description":"Maps input parameters for a step. Can be a static value or a JavaScript expression that references previous results or flow inputs","oneOf":[{"$ref":"#/components/schemas/StaticTransform"},{"$ref":"#/components/schemas/JavascriptTransform"},{"$ref":"#/components/schemas/AiTransform"}],"discriminator":{"propertyName":"type","mapping":{"static":"#/components/schemas/StaticTransform","javascript":"#/components/schemas/JavascriptTransform","ai":"#/components/schemas/AiTransform"}}},"StaticTransform":{"type":"object","description":"Static value passed directly to the step. Use for hardcoded values or resource references like '$res:path/to/resource'","properties":{"value":{"description":"The static value. For resources, use format '$res:path/to/resource'"},"type":{"type":"string","enum":["static"]}},"required":["type"]},"JavascriptTransform":{"type":"object","description":"JavaScript expression evaluated at runtime. Can reference previous step results via 'results.step_id' or flow inputs via 'flow_input.property'. Inside for loops, use 'flow_input.iter.value' for the current iteration value (in while loops it equals 'flow_input.iter.index')","properties":{"expr":{"type":"string","description":"JavaScript expression returning the value. Available variables - results (object with all previous step results), flow_input (flow inputs), flow_input.iter (in loops)"},"type":{"type":"string","enum":["javascript"]}},"required":["expr","type"]},"AiTransform":{"type":"object","description":"Value resolved by the AI runtime for this input. The AI engine decides how to satisfy the parameter.","properties":{"type":{"type":"string","enum":["ai"]}},"required":["type"]},"AIProviderKind":{"type":"string","description":"Supported AI provider types","enum":["openai","azure_openai","azure_foundry","anthropic","mistral","deepseek","googleai","groq","openrouter","togetherai","customai","aws_bedrock","typesafe","cloudflare"]},"ProviderConfig":{"type":"object","description":"Complete AI provider configuration with resource reference and model selection","properties":{"kind":{"$ref":"#/components/schemas/AIProviderKind"},"resource":{"type":"string","description":"Resource reference in format '$res:{resource_path}' pointing to provider credentials"},"model":{"type":"string","description":"Model identifier (e.g., 'gpt-4', 'claude-3-opus-20240229', 'gemini-pro')"},"reasoning_effort":{"type":"string","description":"Provider-native reasoning effort token (e.g. 'low', 'high', 'none') for models that support extended thinking. Optional; unset leaves the provider default."}},"required":["kind","resource","model"]},"StaticProviderTransform":{"type":"object","description":"Static provider configuration passed directly to the AI agent","properties":{"value":{"$ref":"#/components/schemas/ProviderConfig"},"type":{"type":"string","enum":["static"]}},"required":["type","value"]},"ProviderTransform":{"description":"Provider configuration - can be static (ProviderConfig), JavaScript expression, or AI-determined","oneOf":[{"$ref":"#/components/schemas/StaticProviderTransform"},{"$ref":"#/components/schemas/JavascriptTransform"},{"$ref":"#/components/schemas/AiTransform"}],"discriminator":{"propertyName":"type","mapping":{"static":"#/components/schemas/StaticProviderTransform","javascript":"#/components/schemas/JavascriptTransform","ai":"#/components/schemas/AiTransform"}}},"MemoryOff":{"type":"object","description":"No conversation memory/context","properties":{"kind":{"type":"string","enum":["off"]}},"required":["kind"]},"MemoryWindow":{"type":"object","description":"Keeps the most recent messages of the memory named by the run's memory id (or the step's\n`memory_id`). Without a memory id the agent runs without memory.\n","properties":{"kind":{"type":"string","enum":["window"]},"context_length":{"type":"integer","description":"Number of most recent messages to load and store. 0 turns memory off."}},"required":["kind","context_length"]},"MemoryAuto":{"type":"object","deprecated":true,"description":"Deprecated, still read as it was written: the run's memory id, else the `memory_id` here.\nThe step's own `memory_id` is not read while this kind is set; switch the kind to `window`\nto use it. Without a `context_length`, or with 0, it is `off` and reads `previous_messages`.\n","properties":{"kind":{"type":"string","enum":["auto"]},"context_length":{"type":"integer","description":"Maximum number of messages to retain in context"},"memory_id":{"type":"string","description":"Identifier for persistent memory across agent invocations"}},"required":["kind"]},"MemoryCompaction":{"type":"object","description":"Keeps the whole memory named by the run's memory id (or the step's `memory_id`), replacing\nits older part with a summary as the conversation approaches the model's context window.\nWithout a memory id the agent runs without memory, and compaction bounds the run's own loop.\n","properties":{"kind":{"type":"string","enum":["compaction"]},"context_window":{"type":"integer","description":"Overrides the context window looked up from the model, in tokens. Only a model\nWindmill does not know needs one; those fall back to 128000.\n"}},"required":["kind"]},"MemoryMessage":{"type":"object","description":"A single message in conversation history","properties":{"role":{"type":"string","enum":["user","assistant","system"]},"content":{"type":"string"}},"required":["role","content"]},"MemoryManual":{"type":"object","deprecated":true,"description":"Deprecated, still read as it was written. Move the step to `off` with `previous_messages` instead.","properties":{"kind":{"type":"string","enum":["manual"]},"messages":{"type":"array","items":{"$ref":"#/components/schemas/MemoryMessage"}}},"required":["kind","messages"]},"MemoryConfig":{"description":"Managed memory, stored by Windmill and replayed with each request. The memory is named by a memory id, see `memory_id`. While it is off, a step can supply its history in `previous_messages`.","oneOf":[{"$ref":"#/components/schemas/MemoryOff"},{"$ref":"#/components/schemas/MemoryWindow"},{"$ref":"#/components/schemas/MemoryCompaction"},{"$ref":"#/components/schemas/MemoryAuto"},{"$ref":"#/components/schemas/MemoryManual"}],"discriminator":{"propertyName":"kind","mapping":{"off":"#/components/schemas/MemoryOff","window":"#/components/schemas/MemoryWindow","compaction":"#/components/schemas/MemoryCompaction","auto":"#/components/schemas/MemoryAuto","manual":"#/components/schemas/MemoryManual"}}},"StaticMemoryTransform":{"type":"object","description":"Static memory configuration passed directly to the AI agent","properties":{"value":{"$ref":"#/components/schemas/MemoryConfig"},"type":{"type":"string","enum":["static"]}},"required":["type","value"]},"MemoryTransform":{"description":"Memory configuration - can be static (MemoryConfig), JavaScript expression, or AI-determined","oneOf":[{"$ref":"#/components/schemas/StaticMemoryTransform"},{"$ref":"#/components/schemas/JavascriptTransform"},{"$ref":"#/components/schemas/AiTransform"}],"discriminator":{"propertyName":"type","mapping":{"static":"#/components/schemas/StaticMemoryTransform","javascript":"#/components/schemas/JavascriptTransform","ai":"#/components/schemas/AiTransform"}}},"FlowModuleValue":{"description":"The actual implementation of a flow step. Can be a script (inline or referenced), subflow, loop, branch, or special module type","oneOf":[{"$ref":"#/components/schemas/RawScript"},{"$ref":"#/components/schemas/PathScript"},{"$ref":"#/components/schemas/PathFlow"},{"$ref":"#/components/schemas/ForloopFlow"},{"$ref":"#/components/schemas/WhileloopFlow"},{"$ref":"#/components/schemas/BranchOne"},{"$ref":"#/components/schemas/BranchAll"},{"$ref":"#/components/schemas/Identity"},{"$ref":"#/components/schemas/AiAgent"},{"$ref":"#/components/schemas/AiDecision"}],"discriminator":{"propertyName":"type","mapping":{"rawscript":"#/components/schemas/RawScript","script":"#/components/schemas/PathScript","flow":"#/components/schemas/PathFlow","forloopflow":"#/components/schemas/ForloopFlow","whileloopflow":"#/components/schemas/WhileloopFlow","branchone":"#/components/schemas/BranchOne","branchall":"#/components/schemas/BranchAll","identity":"#/components/schemas/Identity","aiagent":"#/components/schemas/AiAgent","aidecision":"#/components/schemas/AiDecision"}}},"RawScript":{"type":"object","description":"Inline script with code defined directly in the flow. Use 'bun' as default language if unspecified. The script receives arguments from input_transforms","properties":{"input_transforms":{"type":"object","description":"Map of parameter names to their values (static or JavaScript expressions). These become the script's input arguments","additionalProperties":{"$ref":"#/components/schemas/InputTransform"}},"content":{"type":"string","description":"The script source code. Should export a 'main' function"},"language":{"type":"string","description":"Programming language for this script","enum":["deno","bun","bunnative","python3","go","bash","powershell","postgresql","mysql","bigquery","snowflake","mssql","oracledb","graphql","nativets","php","rust","ansible","csharp","nu","java","ruby","rlang","duckdb"]},"path":{"type":"string","description":"Optional path for saving this script"},"lock":{"type":"string","description":"Lock file content for dependencies"},"type":{"type":"string","enum":["rawscript"]},"tag":{"type":"string","description":"Worker group tag for execution routing"},"concurrent_limit":{"type":"number","description":"Maximum concurrent executions of this script"},"concurrency_time_window_s":{"type":"number","description":"Time window for concurrent_limit"},"custom_concurrency_key":{"type":"string","description":"Custom key for grouping concurrent executions"},"is_trigger":{"type":"boolean","description":"If true, this script is a trigger that can start the flow"},"assets":{"type":"array","description":"External resources this script accesses (S3 objects, resources, etc.)","items":{"type":"object","required":["path","kind"],"properties":{"path":{"type":"string","description":"Path to the asset"},"kind":{"type":"string","description":"Type of asset","enum":["s3object","resource","ducklake","datatable","volume","dbt"]},"access_type":{"type":"string","nullable":true,"description":"Access level for this asset","enum":["r","w","rw"]},"alt_access_type":{"type":"string","nullable":true,"description":"Alternative access level","enum":["r","w","rw"]}}}}},"required":["type","content","language","input_transforms"]},"PathScript":{"type":"object","description":"Reference to an existing script by path. Use this when calling a previously saved script instead of writing inline code","properties":{"input_transforms":{"type":"object","description":"Map of parameter names to their values (static or JavaScript expressions). These become the script's input arguments","additionalProperties":{"$ref":"#/components/schemas/InputTransform"}},"path":{"type":"string","description":"Path to the script in the workspace (e.g., 'f/scripts/send_email')"},"hash":{"type":"string","description":"Optional specific version hash of the script to use"},"type":{"type":"string","enum":["script"]},"tag_override":{"type":"string","description":"Override the script's default worker group tag"},"is_trigger":{"type":"boolean","description":"If true, this script is a trigger that can start the flow"}},"required":["type","path","input_transforms"]},"PathFlow":{"type":"object","description":"Reference to an existing flow by path. Use this to call another flow as a subflow","properties":{"input_transforms":{"type":"object","description":"Map of parameter names to their values (static or JavaScript expressions). These become the subflow's input arguments","additionalProperties":{"$ref":"#/components/schemas/InputTransform"}},"path":{"type":"string","description":"Path to the flow in the workspace (e.g., 'f/flows/process_user')"},"type":{"type":"string","enum":["flow"]}},"required":["type","path","input_transforms"]},"ForloopFlow":{"type":"object","description":"Executes nested modules in a loop over an iterator. Inside the loop, use 'flow_input.iter.value' to access the current iteration value, and 'flow_input.iter.index' for the index. Supports parallel execution for better performance on I/O-bound operations","properties":{"modules":{"type":"array","description":"Steps to execute for each iteration. These can reference the iteration value via 'flow_input.iter.value'","items":{"$ref":"#/components/schemas/FlowModule"}},"iterator":{"description":"JavaScript expression that returns an array to iterate over. Can reference 'results.step_id' or 'flow_input'","$ref":"#/components/schemas/InputTransform"},"skip_failures":{"type":"boolean","description":"If true, iteration failures don't stop the loop. Failed iterations return null"},"type":{"type":"string","enum":["forloopflow"]},"parallel":{"type":"boolean","description":"If true, iterations run concurrently (faster for I/O-bound operations). Use with parallelism to control concurrency"},"parallelism":{"description":"Maximum number of concurrent iterations when parallel=true. Limits resource usage. Can be static number or expression","$ref":"#/components/schemas/InputTransform"},"squash":{"type":"boolean"}},"required":["modules","iterator","skip_failures","type"]},"WhileloopFlow":{"type":"object","description":"Executes nested modules repeatedly until stopped. The implicit iterator is the iteration counter, so 'flow_input.iter.value' equals 'flow_input.iter.index' (0, 1, 2, ...) and never carries state. To carry state across iterations, a step reads its own previous-iteration result via 'results.<its_own_id>' with a first-iteration fallback - the loop's stop_after_if must then be on that inner step (a plain single-step body with stop_after_if on the loop module does not resolve 'results' across iterations and never terminates); plain counters can instead be derived from 'flow_input.iter.index', which works in every configuration. stop_after_if is evaluated after each iteration - on the loop module 'result' is the last iteration's result","properties":{"modules":{"type":"array","description":"Steps to execute in each iteration","items":{"$ref":"#/components/schemas/FlowModule"}},"skip_failures":{"type":"boolean","description":"If true, iteration failures don't stop the loop. Failed iterations return null"},"type":{"type":"string","enum":["whileloopflow"]},"parallel":{"type":"boolean","description":"If true, iterations run concurrently (use with caution in while loops)"},"parallelism":{"description":"Maximum number of concurrent iterations when parallel=true","$ref":"#/components/schemas/InputTransform"},"squash":{"type":"boolean"}},"required":["modules","skip_failures","type"]},"BranchOne":{"type":"object","description":"Conditional branching where only the first matching branch executes. Branches are evaluated in order, and the first one with a true expression runs. If no branches match, the default branch executes","properties":{"branches":{"type":"array","description":"Array of branches to evaluate in order. The first branch with expr evaluating to true executes","items":{"type":"object","properties":{"summary":{"type":"string","description":"Short description of this branch condition"},"expr":{"type":"string","description":"JavaScript expression that returns boolean. Can use 'results.step_id' or 'flow_input'. First true expr wins"},"modules":{"type":"array","description":"Steps to execute if this branch's expr is true","items":{"$ref":"#/components/schemas/FlowModule"}}},"required":["modules","expr"]}},"default":{"type":"array","description":"Steps to execute if no branch expressions match","items":{"$ref":"#/components/schemas/FlowModule"}},"type":{"type":"string","enum":["branchone"]}},"required":["branches","default","type"]},"BranchAll":{"type":"object","description":"Parallel branching where all branches execute simultaneously. Unlike BranchOne, all branches run regardless of conditions. Useful for executing independent tasks concurrently","properties":{"branches":{"type":"array","description":"Array of branches that all execute (either in parallel or sequentially)","items":{"type":"object","properties":{"summary":{"type":"string","description":"Short description of this branch's purpose"},"skip_failure":{"type":"boolean","description":"If true, failure in this branch doesn't fail the entire flow"},"modules":{"type":"array","description":"Steps to execute in this branch","items":{"$ref":"#/components/schemas/FlowModule"}}},"required":["modules"]}},"type":{"type":"string","enum":["branchall"]},"parallel":{"type":"boolean","description":"If true, all branches execute concurrently. If false, they execute sequentially"}},"required":["branches","type"]},"AgentTool":{"type":"object","description":"A tool available to an AI agent. Can be a flow module or an external MCP (Model Context Protocol) tool","properties":{"id":{"type":"string","description":"Unique identifier for this tool. Cannot contain spaces - use underscores instead (e.g., 'get_user_data' not 'get user data')"},"summary":{"type":"string","description":"The name the AI agent calls this tool by, not a human label. On a flowmodule tool it must match ^[a-zA-Z0-9_]+$ - letters, numbers and underscores only (e.g. 'search_documentation', not 'Search documentation') - and always be set; on an mcp or websearch tool it is a plain label. Put the human-readable explanation in 'description'."},"description":{"type":"string","description":"Free-text description of the tool given to the AI to decide when and how to call it. Overrides the description auto-derived from the underlying script."},"job_token_scopes":{"type":"array","nullable":true,"items":{"type":"string"},"description":"Scopes the token of this tool's jobs is restricted to, on top of the agent step's own restriction: a tool can only narrow it."},"value":{"$ref":"#/components/schemas/ToolValue"}},"required":["id","value"]},"ToolValue":{"description":"The implementation of a tool. Can be a flow module (script/flow) or an MCP tool reference","oneOf":[{"$ref":"#/components/schemas/FlowModuleTool"},{"$ref":"#/components/schemas/McpToolValue"},{"$ref":"#/components/schemas/WebsearchToolValue"}],"discriminator":{"propertyName":"tool_type","mapping":{"flowmodule":"#/components/schemas/FlowModuleTool","mcp":"#/components/schemas/McpToolValue","websearch":"#/components/schemas/WebsearchToolValue"}}},"FlowModuleTool":{"description":"A tool implemented as a flow module (script, flow, etc.). The AI can call this like any other flow module","allOf":[{"type":"object","properties":{"tool_type":{"type":"string","enum":["flowmodule"]}},"required":["tool_type"]},{"$ref":"#/components/schemas/FlowModuleValue"}]},"WebsearchToolValue":{"type":"object","description":"A tool implemented as a websearch tool. The AI can call this like any other websearch tool","properties":{"tool_type":{"type":"string","enum":["websearch"]}},"required":["tool_type"]},"McpToolValue":{"type":"object","description":"Reference to an external MCP (Model Context Protocol) tool. The AI can call tools from MCP servers","properties":{"tool_type":{"type":"string","enum":["mcp"]},"resource_path":{"type":"string","description":"Path to the MCP resource/server configuration"},"include_tools":{"type":"array","description":"Whitelist of specific tools to include from this MCP server","items":{"type":"string"}},"exclude_tools":{"type":"array","description":"Blacklist of tools to exclude from this MCP server","items":{"type":"string"}}},"required":["tool_type","resource_path"]},"AiAgent":{"type":"object","description":"AI agent step that can use tools to accomplish tasks. The agent receives inputs and can call any of its configured tools to complete the task","properties":{"input_transforms":{"type":"object","description":"Input parameters for the AI agent mapped to their values","properties":{"provider":{"$ref":"#/components/schemas/ProviderTransform"},"output_type":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"Output format type.\nValid values: 'text' (default) - plain text response, 'image' - image generation\n"},"user_message":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"The user's prompt/message to the AI agent. Supports variable interpolation with\nflow.input syntax. Required unless memory is off and `previous_messages` supplies\nthe prompt; image output always needs it.\n"},"system_prompt":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"System instructions that guide the AI's behavior, persona, and response style. Optional."},"streaming":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"Boolean. If true, stream the AI response incrementally.\nStreaming events include: token_delta, reasoning_token_delta, tool_call, tool_call_arguments, tool_execution, tool_result\n"},"memory":{"$ref":"#/components/schemas/MemoryTransform"},"memory_id":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"String. Names the memory this step reads and writes, overriding the memory id the run\nwas started with (the chat conversation, an app chat session or the `memory_id` run\nparameter). Leave unset to use the run's memory id. A fixed value shares one memory\nacross every run; an expression such as `flow_input.customer_id` keeps one memory per\nkey. When it evaluates to an empty value the agent runs without memory. Read only\nwhile `memory` is `window` or `compaction`: it is ignored when memory is off, and an\nolder `auto` or `manual` memory reads neither history input.\n"},"previous_messages":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"Array of MemoryMessage. History supplied by the flow, sent between the system prompt\nand the user message. Read only while `memory` is off or absent: managed memory\nignores it, and an older `auto` or `manual` memory reads neither history input.\n"},"output_schema":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"JSON Schema object defining structured output format. Used when you need the AI to return data in a specific shape.\nSupports standard JSON Schema properties: type, properties, required, items, enum, pattern, minLength, maxLength, minimum, maximum, etc.\nExample: { type: 'object', properties: { name: { type: 'string' }, age: { type: 'integer' } }, required: ['name'] }\n"},"user_attachments":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"Array of file references (images or PDFs) for the AI agent.\nFormat: Array<{ bucket: string, key: string }> - S3 object references\nExample: [{ bucket: 'my-bucket', key: 'documents/report.pdf' }]\n"},"enabled_tools":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"Array of strings naming which of the tools configured in `tools` the agent may call\nthis run. Leaving it unset carries every one of them; an empty array carries none.\nA tool is named as the model is shown it. An entry the model is shown nothing of is\nnamed by what identifies it instead: an MCP server by its resource path, carrying\nevery tool it exposes (which of them stays that entry's include_tools/exclude_tools),\nand a websearch entry by the reserved name '__wm_web_search', whatever summary it carries\n(no tool may take that name).\nExample: ['get_user', 'u/admin/github_mcp', '__wm_web_search']\n"},"max_completion_tokens":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"Integer. Maximum number of tokens the AI will generate in its response.\nRange: 1 to 4,294,967,295. Typical values: 256-4096 for most use cases.\n"},"temperature":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"Float. Controls randomness/creativity of responses.\nRange: 0.0 to 2.0 (provider-dependent)\n- 0.0 = deterministic, focused responses\n- 0.7 = balanced (common default)\n- 1.0+ = more creative/random\n"},"max_iterations":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"Number. Limits how many times the agent can loop through reasoning and tool use.\nRange: 1-1000.\n"},"model":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"String. Only on a step linked to a saved agent (see `agent`): replaces the model\nsaved on the agent for this step's runs, on the agent's own provider resource. An\nempty value keeps the saved model. Set it to an expression such as\n`flow_input.model` to choose the model per run.\n"},"reasoning_effort":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"String. Only on a step linked to a saved agent (see `agent`): replaces the reasoning\neffort saved on the agent for this step's runs, as a provider-native token (e.g.\n'low', 'high', 'none'). An empty value sends no effort, so the model runs at its\ndefault. Leave the input out to keep the saved effort, which holds only while the\nstep runs the saved model. A step that is not linked sets both inside `provider`.\n"}}},"tools":{"type":"array","description":"Array of tools the agent can use. The agent decides which tools to call based on the task","items":{"$ref":"#/components/schemas/AgentTool"}},"type":{"type":"string","enum":["aiagent"]},"tag":{"type":"string","description":"Worker group tag for execution routing. If not set, the AI agent step runs on the flow's tag (default `flow`)"},"omit_output_from_conversation":{"type":"boolean","default":false,"description":"If true, this AI agent step does not persist its assistant or tool messages to the flow conversation when chat mode is enabled."},"agent":{"type":"string","description":"Path of a reusable `ai_agent` resource (hybrid linking). When set, the agent brain\nconfig (provider/model/system prompt/etc.) and tool set are resolved at runtime from\nthat resource; the module's input_transforms then only carry the flow-local inputs\n(user_message, user_attachments, enabled_tools and the history inputs memory_id and previous_messages)\nand, optionally, the `model` and `reasoning_effort` overrides of what the agent saved.\n"},"tool_inputs":{"type":"object","description":"Host-local wiring for an agent's tool inputs, keyed by tool id then input key. Binds the\nreferenced agent's tools to this flow's context (flow_input/results) without mutating the\nshared resource; overlaid onto the tools' input_transforms at runtime \u2014 including when\n`agent` is unset, since a step forked for editing keeps these overrides until it is saved\nback or unlinked.\n","additionalProperties":{"type":"object","additionalProperties":{"$ref":"#/components/schemas/InputTransform"}}},"parallel":{"type":"boolean","description":"If true, the agent can execute multiple tool calls in parallel"}},"required":["type","input_transforms"]},"AiDecision":{"type":"object","description":"AI decision step: one call to a decision model (TypeSafe's Jev, Cloudflare's\nJev-compatible Clef, or OpenAI's Decisions API) that answers typed questions about a\nstate with calibrated probabilities, instead of generating text.\nPrefer it over an AI agent to classify, route, score or check something: it is fast,\ncheap and its answers are structured. Its result is { output: { <question name>: answer },\nmodel, usage }, so a later step reads e.g. results.<id>.output.intent.choice. To route on\nthe answers, follow it with a branchone whose branch exprs read\nresults.<id>.output.<question>.choice. Usable as an AI agent tool, where the calling agent\nsupplies the state.\n","properties":{"input_transforms":{"type":"object","description":"Input parameters for the decision mapped to their values","properties":{"provider":{"$ref":"#/components/schemas/ProviderTransform"},"state":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"What the questions are asked about: a string, an object or an array of strings.\nAn object with descriptive keys holding only what the questions need works best.\nExample: { message: flow_input.message, plan: results.a.plan }\n"},"questions":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"Object mapping each question name to { type, instructions, criteria }, where type is:\n- 'choice': criteria maps each option to its description (up to 255); the answer\n has choice, probabilities and confidence\n- 'score': criteria is an ordered array of 2 to 10 level descriptions; the answer\n has score, legend, probabilities and confidence\n- 'noul': yes/no, criteria optionally { true, false } descriptions; the answer has\n noul, the probability of yes (0 to 1)\nExample: { intent: { type: 'choice', instructions: 'What does the customer want?',\ncriteria: { refund: 'Money back', bug: 'Something is broken' } } }\n"}},"required":["provider","state","questions"]},"type":{"type":"string","enum":["aidecision"]},"tag":{"type":"string","description":"Worker group tag for execution routing. If not set, the step runs on the flow's tag (default `flow`)"}},"required":["type","input_transforms"]},"Identity":{"type":"object","description":"Pass-through module that returns its input unchanged. Useful for flow structure or as a placeholder","properties":{"type":{"type":"string","enum":["identity"]},"flow":{"type":"boolean","description":"If true, marks this as a flow identity (special handling)"}},"required":["type"]},"FlowStatus":{"type":"object","properties":{"step":{"type":"integer"},"modules":{"type":"array","items":{"$ref":"#/components/schemas/FlowStatusModule"}},"user_states":{"additionalProperties":true},"preprocessor_module":{"allOf":[{"$ref":"#/components/schemas/FlowStatusModule"}]},"failure_module":{"allOf":[{"$ref":"#/components/schemas/FlowStatusModule"},{"type":"object","properties":{"parent_module":{"type":"string"}}}]},"retry":{"type":"object","properties":{"fail_count":{"type":"integer"},"failed_jobs":{"type":"array","items":{"type":"string","format":"uuid"}}}}},"required":["step","modules","failure_module"]},"FlowStatusModule":{"type":"object","properties":{"type":{"type":"string","enum":["WaitingForPriorSteps","WaitingForEvents","WaitingForExecutor","InProgress","Success","Failure"]},"id":{"type":"string"},"job":{"type":"string","format":"uuid"},"count":{"type":"integer"},"progress":{"type":"integer"},"iterator":{"type":"object","properties":{"index":{"type":"integer"},"itered":{"type":"array","items":{}},"itered_len":{"type":"integer"},"args":{}}},"flow_jobs":{"type":"array","items":{"type":"string"}},"flow_jobs_success":{"type":"array","items":{"type":"boolean"}},"flow_jobs_duration":{"type":"object","properties":{"started_at":{"type":"array","items":{"type":"string"}},"duration_ms":{"type":"array","items":{"type":"integer"}}}},"branch_chosen":{"type":"object","properties":{"type":{"type":"string","enum":["branch","default"]},"branch":{"type":"integer"}},"required":["type"]},"branchall":{"type":"object","properties":{"branch":{"type":"integer"},"len":{"type":"integer"}},"required":["branch","len"]},"approvers":{"type":"array","items":{"type":"object","properties":{"resume_id":{"type":"integer"},"approver":{"type":"string"}},"required":["resume_id","approver"]}},"failed_retries":{"type":"array","items":{"type":"string","format":"uuid"}},"skipped":{"type":"boolean"},"agent_actions":{"type":"array","items":{"type":"object","oneOf":[{"type":"object","properties":{"job_id":{"type":"string","format":"uuid"},"function_name":{"type":"string"},"type":{"type":"string","enum":["tool_call"]},"module_id":{"type":"string"}},"required":["job_id","function_name","type","module_id"]},{"type":"object","properties":{"call_id":{"type":"string","format":"uuid"},"function_name":{"type":"string"},"resource_path":{"type":"string"},"type":{"type":"string","enum":["mcp_tool_call"]},"arguments":{"type":"object"}},"required":["call_id","function_name","resource_path","type"]},{"type":"object","properties":{"type":{"type":"string","enum":["web_search"]}},"required":["type"]},{"type":"object","properties":{"type":{"type":"string","enum":["message"]}},"required":["content","type"]}]}},"agent_actions_success":{"type":"array","items":{"type":"boolean"}}},"required":["type"]}} \ No newline at end of file +{"OpenFlow":{"type":"object","description":"Top-level flow definition containing metadata, configuration, and the flow structure","properties":{"summary":{"type":"string","description":"Short description of what this flow does"},"description":{"type":"string","description":"Detailed documentation for this flow"},"value":{"$ref":"#/components/schemas/FlowValue"},"schema":{"type":"object","description":"JSON Schema for flow inputs. Use this to define input parameters, their types, defaults, and validation. For resource inputs, set type to 'object' and format to 'resource-<type>' (e.g., 'resource-stripe')"},"on_behalf_of_email":{"type":"string","description":"Address of the account the flow runs on behalf of. Derived from on_behalf_of on read; accepted on write, where it is resolved to the account it names."},"on_behalf_of":{"type":"string","description":"The flow runs with the permissions of this identity: u/{username}, g/{group}, or a bare email when the username is itself email-shaped. The only stored half of the identity; on_behalf_of_email is derived from it. Omit it when writing and it is resolved from that address instead."}},"required":["summary","value"]},"FlowValue":{"type":"object","description":"The flow structure containing modules and optional preprocessor/failure handlers","properties":{"modules":{"type":"array","description":"Array of steps that execute in sequence. Each step can be a script, subflow, loop, or branch","items":{"$ref":"#/components/schemas/FlowModule"}},"failure_module":{"description":"Special module that executes when the flow fails. Receives error object with message, name, stack, and step_id. Must have id 'failure'. Only supports script/rawscript types","$ref":"#/components/schemas/FlowModule"},"preprocessor_module":{"description":"Special module that runs before the first step on external triggers. Must have id 'preprocessor'. Only supports script/rawscript types. Cannot reference other step results","$ref":"#/components/schemas/FlowModule"},"same_worker":{"type":"boolean","description":"If true, all steps run on the same worker for better performance"},"preserve_step_tags":{"type":"boolean","description":"If true and the flow runs on a custom worker tag, steps that declare their own non-empty tag run on it instead of inheriting the flow tag. Steps without their own tag still inherit the flow tag."},"concurrent_limit":{"type":"number","description":"Maximum number of concurrent executions of this flow"},"concurrency_key":{"type":"string","description":"Expression to group concurrent executions (e.g., by user ID)"},"concurrency_time_window_s":{"type":"number","description":"Time window in seconds for concurrent_limit"},"debounce_delay_s":{"type":"integer","description":"Delay in seconds to debounce flow executions"},"debounce_key":{"type":"string","description":"Expression to group debounced executions"},"debounce_args_to_accumulate":{"type":"array","description":"Arguments to accumulate across debounced executions","items":{"type":"string"}},"max_total_debouncing_time":{"type":"integer","description":"Maximum total time in seconds that a job can be debounced"},"max_total_debounces_amount":{"type":"integer","description":"Maximum number of times a job can be debounced"},"skip_expr":{"type":"string","description":"JavaScript expression to conditionally skip the entire flow"},"cache_ttl":{"type":"number","description":"Cache duration in seconds for flow results"},"cache_ignore_s3_path":{"type":"boolean"},"delete_after_secs":{"type":"integer","description":"If set, delete the flow job's args, result and logs after this many seconds following job completion"},"flow_env":{"type":"object","description":"Environment variables available to all steps. Values can be strings, JSON values, or special references: '$var:path' (workspace variable) or '$res:path' (resource).","additionalProperties":{}},"priority":{"type":"number","description":"Execution priority (higher numbers run first)"},"early_return":{"type":"string","description":"Id of the step whose result a sync webhook returns as soon as that step completes, while the rest of the flow keeps running. When the step does not run, or fails while the flow has a failure module, the flow's final result is returned instead."},"chat_input_enabled":{"type":"boolean","description":"Whether this flow accepts chat-style input"},"notes":{"type":"array","description":"Sticky notes attached to the flow","items":{"$ref":"#/components/schemas/FlowNote"}},"groups":{"type":"array","description":"Semantic groups of modules for organizational purposes","items":{"$ref":"#/components/schemas/FlowGroup"}}},"required":["modules"]},"Retry":{"type":"object","description":"Retry configuration for failed module executions","properties":{"constant":{"type":"object","description":"Retry with constant delay between attempts","properties":{"attempts":{"type":"integer","description":"Number of retry attempts"},"seconds":{"type":"integer","description":"Seconds to wait between retries"}}},"exponential":{"type":"object","description":"Retry with exponential backoff: the n-th retry waits multiplier \u00d7 seconds^n","properties":{"attempts":{"type":"integer","description":"Number of retry attempts"},"multiplier":{"type":"integer","description":"Multiplier for exponential backoff"},"seconds":{"type":"integer","minimum":1,"description":"Base of the exponential (seconds); the n-th retry waits multiplier \u00d7 seconds^n, where n counts constant retries too"},"random_factor":{"type":"integer","minimum":0,"maximum":100,"description":"Random jitter percentage (0-100) to avoid thundering herd"}}},"retry_if":{"$ref":"#/components/schemas/RetryIf"}}},"FlowNote":{"type":"object","description":"A sticky note attached to a flow for documentation and annotation","properties":{"id":{"type":"string","description":"Unique identifier for the note"},"text":{"type":"string","description":"Content of the note"},"position":{"type":"object","description":"Position of the note in the flow editor","properties":{"x":{"type":"number","description":"X coordinate"},"y":{"type":"number","description":"Y coordinate"}},"required":["x","y"]},"size":{"type":"object","description":"Size of the note in the flow editor","properties":{"width":{"type":"number","description":"Width in pixels"},"height":{"type":"number","description":"Height in pixels"}},"required":["width","height"]},"color":{"type":"string","description":"Color of the note, one of: yellow, blue, green, purple, pink, orange, red, cyan, lime, gray. Any other value renders unstyled."},"type":{"type":"string","enum":["free","group"],"description":"Type of note - 'free' for standalone notes. 'group' notes are deprecated; segment a flow with FlowValue.groups instead."},"locked":{"type":"boolean","default":false,"description":"Whether the note is locked and cannot be edited or moved"},"contained_node_ids":{"type":"array","items":{"type":"string"},"description":"For group notes, the IDs of nodes contained within this group"}},"required":["id","text","color","type"]},"FlowGroup":{"type":"object","description":"A semantic group of flow modules for organizational purposes. Does not affect execution \u2014 modules remain in their original position in the flow. Groups provide naming and collapsibility in the editor. Members are computed dynamically from all nodes on paths between start_id and end_id.","properties":{"summary":{"type":"string","description":"Display name for this group"},"note":{"type":"string","description":"Markdown note shown below the group header"},"autocollapse":{"type":"boolean","default":false,"description":"If true, this group is collapsed by default in the flow editor. UI hint only."},"start_id":{"type":"string","description":"ID of the first flow module in this group (topological entry point)"},"end_id":{"type":"string","description":"ID of the last flow module in this group (topological exit point)"},"color":{"type":"string","description":"Color for the group in the flow editor, one of: yellow, blue, green, purple, pink, orange, red, cyan, lime, gray. Omit it to let the editor pick one."}},"required":["start_id","end_id"]},"RetryIf":{"type":"object","description":"Conditional retry based on error or result","properties":{"expr":{"type":"string","description":"JavaScript expression that returns true to retry. Has access to 'result' and 'error' variables"}},"required":["expr"]},"StopAfterIf":{"type":"object","description":"Early termination condition for a module","properties":{"skip_if_stopped":{"type":"boolean","description":"If true, following steps are skipped when this condition triggers"},"expr":{"type":"string","description":"JavaScript expression evaluated after the module runs. Can use 'result' (step's result) or 'flow_input'. Return true to stop"},"error_message":{"type":"string","nullable":true,"description":"Custom error message when stopping with an error. Mutually exclusive with skip_if_stopped. If set to a non-empty string, the flow stops with this error. If empty string, a default error message is used. If null or omitted, no error is raised."},"error_include_result":{"type":"boolean","description":"When stopping with an error (error_message set), embed the stopping step's own result inside the raised error object (as error.result) instead of discarding it. The top-level result stays { error }. Defaults to false."}},"required":["expr"]},"FlowModule":{"type":"object","description":"A single step in a flow. Can be a script, subflow, loop, or branch","properties":{"id":{"type":"string","description":"Unique identifier for this step. Used to reference results via 'results.step_id'. Must be a valid identifier (alphanumeric, underscore, hyphen)"},"value":{"$ref":"#/components/schemas/FlowModuleValue"},"stop_after_if":{"description":"Early termination condition evaluated after this step completes","$ref":"#/components/schemas/StopAfterIf"},"stop_after_all_iters_if":{"description":"For loops only - early termination condition evaluated after all iterations complete","$ref":"#/components/schemas/StopAfterIf"},"skip_if":{"type":"object","description":"Conditionally skip this step based on previous results or flow inputs","properties":{"expr":{"type":"string","description":"JavaScript expression that returns true to skip. Can use 'flow_input' or 'results.<step_id>'"}},"required":["expr"]},"sleep":{"description":"Delay before executing this step (in seconds or as expression)","$ref":"#/components/schemas/InputTransform"},"cache_ttl":{"type":"number","description":"Cache duration in seconds for this step's results"},"cache_ignore_s3_path":{"type":"boolean"},"timeout":{"description":"Maximum execution time in seconds (static value or expression)","$ref":"#/components/schemas/InputTransform"},"delete_after_secs":{"type":"integer","description":"If set, delete the step's args, result and logs after this many seconds following job completion"},"summary":{"type":"string","description":"Short description of what this step does"},"mock":{"type":"object","description":"Mock configuration for testing without executing the actual step","properties":{"enabled":{"type":"boolean","description":"If true, return mock value instead of executing"},"return_value":{"description":"Value to return when mocked"}}},"suspend":{"type":"object","description":"Configuration for approval/resume steps that wait for user input","properties":{"required_events":{"type":"integer","description":"Number of approvals required before continuing"},"timeout":{"type":"integer","description":"Timeout in seconds before auto-continuing or canceling"},"resume_form":{"type":"object","description":"Form schema for collecting input when resuming","properties":{"schema":{"type":"object","description":"JSON Schema for the resume form"}}},"user_auth_required":{"type":"boolean","description":"If true, only authenticated users can approve"},"user_groups_required":{"description":"Expression or list of groups that can approve","$ref":"#/components/schemas/InputTransform"},"self_approval_disabled":{"type":"boolean","description":"If true, the user who started the flow cannot approve"},"hide_cancel":{"type":"boolean","description":"If true, hide the cancel button on the approval form"},"continue_on_disapprove_timeout":{"type":"boolean","description":"If true, continue flow on timeout instead of canceling"},"skin":{"type":"string","enum":["detailed","minimal"],"description":"How the approval request is presented, on the approval page and in Slack/Teams approval messages. 'detailed' (used when unset) shows the flow details (arguments, graph, approvers); 'minimal' shows only the request: the step description, form and approve/reject actions"}}},"priority":{"type":"number","description":"Execution priority for this step (higher numbers run first)"},"continue_on_error":{"type":"boolean","description":"If true, flow continues even if this step fails"},"job_token_scopes":{"type":"array","nullable":true,"items":{"type":"string"},"description":"Scopes the token of this step's jobs is restricted to (domain:action[:resource], e.g. oidc:write), on top of the flow's own restriction: a step can only narrow it. Applies to everything the step runs (loop and branch bodies, AI agent tools)."},"retry":{"description":"Retry configuration if this step fails","$ref":"#/components/schemas/Retry"},"debouncing":{"description":"Debounce configuration for this step (EE only)","type":"object","properties":{"debounce_delay_s":{"type":"integer","description":"Delay in seconds to debounce this step's executions across flow runs"},"debounce_key":{"type":"string","description":"Expression to group debounced executions. Supports $workspace and $args[name]. Default: $workspace/flow/<flow_path>-<step_id>"},"debounce_args_to_accumulate":{"type":"array","description":"Array-type arguments to accumulate across debounced executions","items":{"type":"string"}},"max_total_debouncing_time":{"type":"integer","description":"Maximum total time in seconds before forced execution"},"max_total_debounces_amount":{"type":"integer","description":"Maximum number of debounces before forced execution"}}}},"required":["value","id"]},"InputTransform":{"description":"Maps input parameters for a step. Can be a static value or a JavaScript expression that references previous results or flow inputs","oneOf":[{"$ref":"#/components/schemas/StaticTransform"},{"$ref":"#/components/schemas/JavascriptTransform"},{"$ref":"#/components/schemas/AiTransform"}],"discriminator":{"propertyName":"type","mapping":{"static":"#/components/schemas/StaticTransform","javascript":"#/components/schemas/JavascriptTransform","ai":"#/components/schemas/AiTransform"}}},"StaticTransform":{"type":"object","description":"Static value passed directly to the step. Use for hardcoded values or resource references like '$res:path/to/resource'","properties":{"value":{"description":"The static value. For resources, use format '$res:path/to/resource'"},"type":{"type":"string","enum":["static"]}},"required":["type"]},"JavascriptTransform":{"type":"object","description":"JavaScript expression evaluated at runtime. Can reference previous step results via 'results.step_id' or flow inputs via 'flow_input.property'. Inside for loops, use 'flow_input.iter.value' for the current iteration value (in while loops it equals 'flow_input.iter.index')","properties":{"expr":{"type":"string","description":"JavaScript expression returning the value. Available variables - results (object with all previous step results), flow_input (flow inputs), flow_input.iter (in loops)"},"type":{"type":"string","enum":["javascript"]}},"required":["expr","type"]},"AiTransform":{"type":"object","description":"Value resolved by the AI runtime for this input. The AI engine decides how to satisfy the parameter.","properties":{"type":{"type":"string","enum":["ai"]}},"required":["type"]},"AIProviderKind":{"type":"string","description":"Supported AI provider types","enum":["openai","azure_openai","azure_foundry","anthropic","mistral","deepseek","googleai","groq","openrouter","togetherai","customai","aws_bedrock","typesafe","cloudflare"]},"ProviderConfig":{"type":"object","description":"Complete AI provider configuration with resource reference and model selection","properties":{"kind":{"$ref":"#/components/schemas/AIProviderKind"},"resource":{"type":"string","description":"Resource reference in format '$res:{resource_path}' pointing to provider credentials"},"model":{"type":"string","description":"Model identifier (e.g., 'gpt-4', 'claude-3-opus-20240229', 'gemini-pro')"},"reasoning_effort":{"type":"string","description":"Provider-native reasoning effort token (e.g. 'low', 'high', 'none') for models that support extended thinking. Optional; unset leaves the provider default."}},"required":["kind","resource","model"]},"StaticProviderTransform":{"type":"object","description":"Static provider configuration passed directly to the AI agent","properties":{"value":{"$ref":"#/components/schemas/ProviderConfig"},"type":{"type":"string","enum":["static"]}},"required":["type","value"]},"ProviderTransform":{"description":"Provider configuration - can be static (ProviderConfig), JavaScript expression, or AI-determined","oneOf":[{"$ref":"#/components/schemas/StaticProviderTransform"},{"$ref":"#/components/schemas/JavascriptTransform"},{"$ref":"#/components/schemas/AiTransform"}],"discriminator":{"propertyName":"type","mapping":{"static":"#/components/schemas/StaticProviderTransform","javascript":"#/components/schemas/JavascriptTransform","ai":"#/components/schemas/AiTransform"}}},"MemoryOff":{"type":"object","description":"No conversation memory/context","properties":{"kind":{"type":"string","enum":["off"]}},"required":["kind"]},"MemoryWindow":{"type":"object","description":"Keeps the most recent messages of the memory named by the run's memory id (or the step's\n`memory_id`). Without a memory id the agent runs without memory.\n","properties":{"kind":{"type":"string","enum":["window"]},"context_length":{"type":"integer","description":"Number of most recent messages to load and store. 0 turns memory off."}},"required":["kind","context_length"]},"MemoryAuto":{"type":"object","deprecated":true,"description":"Deprecated, still read as it was written: the run's memory id, else the `memory_id` here.\nThe step's own `memory_id` is not read while this kind is set; switch the kind to `window`\nto use it. Without a `context_length`, or with 0, it is `off` and reads `previous_messages`.\n","properties":{"kind":{"type":"string","enum":["auto"]},"context_length":{"type":"integer","description":"Maximum number of messages to retain in context"},"memory_id":{"type":"string","description":"Identifier for persistent memory across agent invocations"}},"required":["kind"]},"MemoryCompaction":{"type":"object","description":"Keeps the whole memory named by the run's memory id (or the step's `memory_id`), replacing\nits older part with a summary as the conversation approaches the model's context window.\nWithout a memory id the agent runs without memory, and compaction bounds the run's own loop.\n","properties":{"kind":{"type":"string","enum":["compaction"]},"context_window":{"type":"integer","description":"Overrides the context window looked up from the model, in tokens. Only a model\nWindmill does not know needs one; those fall back to 128000.\n"}},"required":["kind"]},"MemoryMessage":{"type":"object","description":"A single message in conversation history","properties":{"role":{"type":"string","enum":["user","assistant","system"]},"content":{"type":"string"}},"required":["role","content"]},"MemoryManual":{"type":"object","deprecated":true,"description":"Deprecated, still read as it was written. Move the step to `off` with `previous_messages` instead.","properties":{"kind":{"type":"string","enum":["manual"]},"messages":{"type":"array","items":{"$ref":"#/components/schemas/MemoryMessage"}}},"required":["kind","messages"]},"MemoryConfig":{"description":"Managed memory, stored by Windmill and replayed with each request. The memory is named by a memory id, see `memory_id`. While it is off, a step can supply its history in `previous_messages`.","oneOf":[{"$ref":"#/components/schemas/MemoryOff"},{"$ref":"#/components/schemas/MemoryWindow"},{"$ref":"#/components/schemas/MemoryCompaction"},{"$ref":"#/components/schemas/MemoryAuto"},{"$ref":"#/components/schemas/MemoryManual"}],"discriminator":{"propertyName":"kind","mapping":{"off":"#/components/schemas/MemoryOff","window":"#/components/schemas/MemoryWindow","compaction":"#/components/schemas/MemoryCompaction","auto":"#/components/schemas/MemoryAuto","manual":"#/components/schemas/MemoryManual"}}},"StaticMemoryTransform":{"type":"object","description":"Static memory configuration passed directly to the AI agent","properties":{"value":{"$ref":"#/components/schemas/MemoryConfig"},"type":{"type":"string","enum":["static"]}},"required":["type","value"]},"MemoryTransform":{"description":"Memory configuration - can be static (MemoryConfig), JavaScript expression, or AI-determined","oneOf":[{"$ref":"#/components/schemas/StaticMemoryTransform"},{"$ref":"#/components/schemas/JavascriptTransform"},{"$ref":"#/components/schemas/AiTransform"}],"discriminator":{"propertyName":"type","mapping":{"static":"#/components/schemas/StaticMemoryTransform","javascript":"#/components/schemas/JavascriptTransform","ai":"#/components/schemas/AiTransform"}}},"FlowModuleValue":{"description":"The actual implementation of a flow step. Can be a script (inline or referenced), subflow, loop, branch, or special module type","oneOf":[{"$ref":"#/components/schemas/RawScript"},{"$ref":"#/components/schemas/PathScript"},{"$ref":"#/components/schemas/PathFlow"},{"$ref":"#/components/schemas/ForloopFlow"},{"$ref":"#/components/schemas/WhileloopFlow"},{"$ref":"#/components/schemas/BranchOne"},{"$ref":"#/components/schemas/BranchAll"},{"$ref":"#/components/schemas/Identity"},{"$ref":"#/components/schemas/AiAgent"},{"$ref":"#/components/schemas/AiDecision"}],"discriminator":{"propertyName":"type","mapping":{"rawscript":"#/components/schemas/RawScript","script":"#/components/schemas/PathScript","flow":"#/components/schemas/PathFlow","forloopflow":"#/components/schemas/ForloopFlow","whileloopflow":"#/components/schemas/WhileloopFlow","branchone":"#/components/schemas/BranchOne","branchall":"#/components/schemas/BranchAll","identity":"#/components/schemas/Identity","aiagent":"#/components/schemas/AiAgent","aidecision":"#/components/schemas/AiDecision"}}},"RawScript":{"type":"object","description":"Inline script with code defined directly in the flow. Use 'bun' as default language if unspecified. The script receives arguments from input_transforms","properties":{"input_transforms":{"type":"object","description":"Map of parameter names to their values (static or JavaScript expressions). These become the script's input arguments","additionalProperties":{"$ref":"#/components/schemas/InputTransform"}},"content":{"type":"string","description":"The script source code. Should export a 'main' function"},"language":{"type":"string","description":"Programming language for this script","enum":["deno","bun","bunnative","python3","go","bash","powershell","postgresql","mysql","bigquery","snowflake","mssql","oracledb","graphql","nativets","php","rust","ansible","csharp","nu","java","ruby","rlang","duckdb"]},"path":{"type":"string","description":"Optional path for saving this script"},"lock":{"type":"string","description":"Lock file content for dependencies"},"type":{"type":"string","enum":["rawscript"]},"tag":{"type":"string","description":"Worker group tag for execution routing"},"concurrent_limit":{"type":"number","description":"Maximum concurrent executions of this script"},"concurrency_time_window_s":{"type":"number","description":"Time window for concurrent_limit"},"custom_concurrency_key":{"type":"string","description":"Custom key for grouping concurrent executions"},"is_trigger":{"type":"boolean","description":"If true, this script is a trigger that can start the flow"},"assets":{"type":"array","description":"External resources this script accesses (S3 objects, resources, etc.)","items":{"type":"object","required":["path","kind"],"properties":{"path":{"type":"string","description":"Path to the asset"},"kind":{"type":"string","description":"Type of asset","enum":["s3object","resource","ducklake","datatable","volume","dbt"]},"access_type":{"type":"string","nullable":true,"description":"Access level for this asset","enum":["r","w","rw"]},"alt_access_type":{"type":"string","nullable":true,"description":"Alternative access level","enum":["r","w","rw"]}}}}},"required":["type","content","language","input_transforms"]},"PathScript":{"type":"object","description":"Reference to an existing script by path. Use this when calling a previously saved script instead of writing inline code","properties":{"input_transforms":{"type":"object","description":"Map of parameter names to their values (static or JavaScript expressions). These become the script's input arguments","additionalProperties":{"$ref":"#/components/schemas/InputTransform"}},"path":{"type":"string","description":"Path to the script in the workspace (e.g., 'f/scripts/send_email')"},"hash":{"type":"string","description":"Optional specific version hash of the script to use"},"type":{"type":"string","enum":["script"]},"tag_override":{"type":"string","description":"Override the script's default worker group tag"},"is_trigger":{"type":"boolean","description":"If true, this script is a trigger that can start the flow"}},"required":["type","path","input_transforms"]},"PathFlow":{"type":"object","description":"Reference to an existing flow by path. Use this to call another flow as a subflow","properties":{"input_transforms":{"type":"object","description":"Map of parameter names to their values (static or JavaScript expressions). These become the subflow's input arguments","additionalProperties":{"$ref":"#/components/schemas/InputTransform"}},"path":{"type":"string","description":"Path to the flow in the workspace (e.g., 'f/flows/process_user')"},"type":{"type":"string","enum":["flow"]}},"required":["type","path","input_transforms"]},"ForloopFlow":{"type":"object","description":"Executes nested modules in a loop over an iterator. Inside the loop, use 'flow_input.iter.value' to access the current iteration value, and 'flow_input.iter.index' for the index. Supports parallel execution for better performance on I/O-bound operations","properties":{"modules":{"type":"array","description":"Steps to execute for each iteration. These can reference the iteration value via 'flow_input.iter.value'","items":{"$ref":"#/components/schemas/FlowModule"}},"iterator":{"description":"JavaScript expression that returns an array to iterate over. Can reference 'results.step_id' or 'flow_input'","$ref":"#/components/schemas/InputTransform"},"skip_failures":{"type":"boolean","description":"If true, iteration failures don't stop the loop. Failed iterations return null"},"type":{"type":"string","enum":["forloopflow"]},"parallel":{"type":"boolean","description":"If true, iterations run concurrently (faster for I/O-bound operations). Use with parallelism to control concurrency"},"parallelism":{"description":"Maximum number of concurrent iterations when parallel=true. Limits resource usage. Can be static number or expression","$ref":"#/components/schemas/InputTransform"},"squash":{"type":"boolean"}},"required":["modules","iterator","skip_failures","type"]},"WhileloopFlow":{"type":"object","description":"Executes nested modules repeatedly until stopped. The implicit iterator is the iteration counter, so 'flow_input.iter.value' equals 'flow_input.iter.index' (0, 1, 2, ...) and never carries state. To carry state across iterations, a step reads its own previous-iteration result via 'results.<its_own_id>' with a first-iteration fallback - the loop's stop_after_if must then be on that inner step (a plain single-step body with stop_after_if on the loop module does not resolve 'results' across iterations and never terminates); plain counters can instead be derived from 'flow_input.iter.index', which works in every configuration. stop_after_if is evaluated after each iteration - on the loop module 'result' is the last iteration's result","properties":{"modules":{"type":"array","description":"Steps to execute in each iteration","items":{"$ref":"#/components/schemas/FlowModule"}},"skip_failures":{"type":"boolean","description":"If true, iteration failures don't stop the loop. Failed iterations return null"},"type":{"type":"string","enum":["whileloopflow"]},"parallel":{"type":"boolean","description":"If true, iterations run concurrently (use with caution in while loops)"},"parallelism":{"description":"Maximum number of concurrent iterations when parallel=true","$ref":"#/components/schemas/InputTransform"},"squash":{"type":"boolean"}},"required":["modules","skip_failures","type"]},"BranchOne":{"type":"object","description":"Conditional branching where only the first matching branch executes. Branches are evaluated in order, and the first one with a true expression runs. If no branches match, the default branch executes","properties":{"branches":{"type":"array","description":"Array of branches to evaluate in order. The first branch with expr evaluating to true executes","items":{"type":"object","properties":{"summary":{"type":"string","description":"Short description of this branch condition"},"expr":{"type":"string","description":"JavaScript expression that returns boolean. Can use 'results.step_id' or 'flow_input'. First true expr wins"},"modules":{"type":"array","description":"Steps to execute if this branch's expr is true","items":{"$ref":"#/components/schemas/FlowModule"}}},"required":["modules","expr"]}},"default":{"type":"array","description":"Steps to execute if no branch expressions match","items":{"$ref":"#/components/schemas/FlowModule"}},"type":{"type":"string","enum":["branchone"]}},"required":["branches","default","type"]},"BranchAll":{"type":"object","description":"Parallel branching where all branches execute simultaneously. Unlike BranchOne, all branches run regardless of conditions. Useful for executing independent tasks concurrently","properties":{"branches":{"type":"array","description":"Array of branches that all execute (either in parallel or sequentially)","items":{"type":"object","properties":{"summary":{"type":"string","description":"Short description of this branch's purpose"},"skip_failure":{"type":"boolean","description":"If true, failure in this branch doesn't fail the entire flow"},"modules":{"type":"array","description":"Steps to execute in this branch","items":{"$ref":"#/components/schemas/FlowModule"}}},"required":["modules"]}},"type":{"type":"string","enum":["branchall"]},"parallel":{"type":"boolean","description":"If true, all branches execute concurrently. If false, they execute sequentially"}},"required":["branches","type"]},"AgentTool":{"type":"object","description":"A tool available to an AI agent. Can be a flow module or an external MCP (Model Context Protocol) tool","properties":{"id":{"type":"string","description":"Unique identifier for this tool. Cannot contain spaces - use underscores instead (e.g., 'get_user_data' not 'get user data')"},"summary":{"type":"string","description":"The name the AI agent calls this tool by, not a human label. On a flowmodule tool it must match ^[a-zA-Z0-9_]+$ - letters, numbers and underscores only (e.g. 'search_documentation', not 'Search documentation') - and always be set; on an mcp, websearch or question tool it is a plain label. Put the human-readable explanation in 'description'."},"description":{"type":"string","description":"Free-text description of the tool given to the AI to decide when and how to call it. Overrides the description auto-derived from the underlying script."},"job_token_scopes":{"type":"array","nullable":true,"items":{"type":"string"},"description":"Scopes the token of this tool's jobs is restricted to, on top of the agent step's own restriction: a tool can only narrow it."},"requires_approval":{"type":"boolean","description":"Flowmodule and mcp tools only. Each call waits for a person to approve or reject it from the flow's run page or chat, without the agent holding a worker. Calls in the same turn that do not require approval run right away. A rejected call, or one nobody answers within 30 minutes, is reported to the AI as not run."},"value":{"$ref":"#/components/schemas/ToolValue"}},"required":["id","value"]},"ToolValue":{"description":"The implementation of a tool. Can be a flow module (script/flow) or an MCP tool reference","oneOf":[{"$ref":"#/components/schemas/FlowModuleTool"},{"$ref":"#/components/schemas/McpToolValue"},{"$ref":"#/components/schemas/WebsearchToolValue"},{"$ref":"#/components/schemas/QuestionToolValue"}],"discriminator":{"propertyName":"tool_type","mapping":{"flowmodule":"#/components/schemas/FlowModuleTool","mcp":"#/components/schemas/McpToolValue","websearch":"#/components/schemas/WebsearchToolValue","question":"#/components/schemas/QuestionToolValue"}}},"FlowModuleTool":{"description":"A tool implemented as a flow module (script, flow, etc.). The AI can call this like any other flow module","allOf":[{"type":"object","properties":{"tool_type":{"type":"string","enum":["flowmodule"]}},"required":["tool_type"]},{"$ref":"#/components/schemas/FlowModuleValue"}]},"WebsearchToolValue":{"type":"object","description":"A tool implemented as a websearch tool. The AI can call this like any other websearch tool","properties":{"tool_type":{"type":"string","enum":["websearch"]}},"required":["tool_type"]},"QuestionToolValue":{"type":"object","description":"Built-in tool the AI calls as ask_question: the agent stops, releasing its worker, until someone answers from the flow's run page or chat or the question times out, then resumes with the answer as the tool result.","properties":{"tool_type":{"type":"string","enum":["question"]},"timeout":{"type":"integer","description":"Seconds to wait for an answer before the question is reported to the AI as timed out. Defaults to 1800."}},"required":["tool_type"]},"McpToolValue":{"type":"object","description":"Reference to an external MCP (Model Context Protocol) tool. The AI can call tools from MCP servers","properties":{"tool_type":{"type":"string","enum":["mcp"]},"resource_path":{"type":"string","description":"Path to the MCP resource/server configuration"},"include_tools":{"type":"array","description":"Whitelist of specific tools to include from this MCP server","items":{"type":"string"}},"exclude_tools":{"type":"array","description":"Blacklist of tools to exclude from this MCP server","items":{"type":"string"}}},"required":["tool_type","resource_path"]},"AiAgent":{"type":"object","description":"AI agent step that can use tools to accomplish tasks. The agent receives inputs and can call any of its configured tools to complete the task","properties":{"input_transforms":{"type":"object","description":"Input parameters for the AI agent mapped to their values","properties":{"provider":{"$ref":"#/components/schemas/ProviderTransform"},"output_type":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"Output format type.\nValid values: 'text' (default) - plain text response, 'image' - image generation\n"},"user_message":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"The user's prompt/message to the AI agent. Supports variable interpolation with\nflow.input syntax. Required unless memory is off and `previous_messages` supplies\nthe prompt; image output always needs it.\n"},"system_prompt":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"System instructions that guide the AI's behavior, persona, and response style. Optional."},"streaming":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"Boolean. If true, stream the AI response incrementally.\nStreaming events include: token_delta, reasoning_token_delta, tool_call, tool_call_arguments, tool_execution, tool_result\n"},"memory":{"$ref":"#/components/schemas/MemoryTransform"},"memory_id":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"String. Names the memory this step reads and writes, overriding the memory id the run\nwas started with (the chat conversation, an app chat session or the `memory_id` run\nparameter). Leave unset to use the run's memory id. A fixed value shares one memory\nacross every run; an expression such as `flow_input.customer_id` keeps one memory per\nkey. When it evaluates to an empty value the agent runs without memory. Read only\nwhile `memory` is `window` or `compaction`: it is ignored when memory is off, and an\nolder `auto` or `manual` memory reads neither history input.\n"},"previous_messages":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"Array of MemoryMessage. History supplied by the flow, sent between the system prompt\nand the user message. Read only while `memory` is off or absent: managed memory\nignores it, and an older `auto` or `manual` memory reads neither history input.\n"},"output_schema":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"JSON Schema object defining structured output format. Used when you need the AI to return data in a specific shape.\nSupports standard JSON Schema properties: type, properties, required, items, enum, pattern, minLength, maxLength, minimum, maximum, etc.\nExample: { type: 'object', properties: { name: { type: 'string' }, age: { type: 'integer' } }, required: ['name'] }\n"},"user_attachments":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"Array of file references (images or PDFs) for the AI agent.\nFormat: Array<{ bucket: string, key: string }> - S3 object references\nExample: [{ bucket: 'my-bucket', key: 'documents/report.pdf' }]\n"},"enabled_tools":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"Array of strings naming which of the tools configured in `tools` the agent may call\nthis run. Leaving it unset carries every one of them; an empty array carries none.\nA tool is named as the model is shown it. An entry the model is shown nothing of is\nnamed by what identifies it instead: an MCP server by its resource path, carrying\nevery tool it exposes (which of them stays that entry's include_tools/exclude_tools),\nand a websearch entry by the reserved name '__wm_web_search', whatever summary it carries\n(no tool may take that name).\nExample: ['get_user', 'u/admin/github_mcp', '__wm_web_search']\n"},"max_completion_tokens":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"Integer. Maximum number of tokens the AI will generate in its response.\nRange: 1 to 4,294,967,295. Typical values: 256-4096 for most use cases.\n"},"temperature":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"Float. Controls randomness/creativity of responses.\nRange: 0.0 to 2.0 (provider-dependent)\n- 0.0 = deterministic, focused responses\n- 0.7 = balanced (common default)\n- 1.0+ = more creative/random\n"},"max_iterations":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"Number. Limits how many times the agent can loop through reasoning and tool use.\nRange: 1-1000.\n"},"model":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"String. Only on a step linked to a saved agent (see `agent`): replaces the model\nsaved on the agent for this step's runs, on the agent's own provider resource. An\nempty value keeps the saved model. Set it to an expression such as\n`flow_input.model` to choose the model per run.\n"},"reasoning_effort":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"String. Only on a step linked to a saved agent (see `agent`): replaces the reasoning\neffort saved on the agent for this step's runs, as a provider-native token (e.g.\n'low', 'high', 'none'). An empty value sends no effort, so the model runs at its\ndefault. Leave the input out to keep the saved effort, which holds only while the\nstep runs the saved model. A step that is not linked sets both inside `provider`.\n"}}},"tools":{"type":"array","description":"Array of tools the agent can use. The agent decides which tools to call based on the task","items":{"$ref":"#/components/schemas/AgentTool"}},"type":{"type":"string","enum":["aiagent"]},"tag":{"type":"string","description":"Worker group tag for execution routing. If not set, the AI agent step runs on the flow's tag (default `flow`)"},"omit_output_from_conversation":{"type":"boolean","default":false,"description":"If true, this AI agent step does not persist its assistant or tool messages to the flow conversation when chat mode is enabled."},"agent":{"type":"string","description":"Path of a reusable `ai_agent` resource (hybrid linking). When set, the agent brain\nconfig (provider/model/system prompt/etc.) and tool set are resolved at runtime from\nthat resource; the module's input_transforms then only carry the flow-local inputs\n(user_message, user_attachments, enabled_tools and the history inputs memory_id and previous_messages)\nand, optionally, the `model` and `reasoning_effort` overrides of what the agent saved.\n"},"tool_inputs":{"type":"object","description":"Host-local wiring for an agent's tool inputs, keyed by tool id then input key. Binds the\nreferenced agent's tools to this flow's context (flow_input/results) without mutating the\nshared resource; overlaid onto the tools' input_transforms at runtime \u2014 including when\n`agent` is unset, since a step forked for editing keeps these overrides until it is saved\nback or unlinked.\n","additionalProperties":{"type":"object","additionalProperties":{"$ref":"#/components/schemas/InputTransform"}}},"parallel":{"type":"boolean","description":"If true, the agent can execute multiple tool calls in parallel"}},"required":["type","input_transforms"]},"AiDecision":{"type":"object","description":"AI decision step: one call to a decision model (TypeSafe's Jev, Cloudflare's\nJev-compatible Clef, or OpenAI's Decisions API) that answers typed questions about a\nstate with calibrated probabilities, instead of generating text.\nPrefer it over an AI agent to classify, route, score or check something: it is fast,\ncheap and its answers are structured. Its result is { output: { <question name>: answer },\nmodel, usage }, so a later step reads e.g. results.<id>.output.intent.choice. To route on\nthe answers, follow it with a branchone whose branch exprs read\nresults.<id>.output.<question>.choice. Usable as an AI agent tool, where the calling agent\nsupplies the state.\n","properties":{"input_transforms":{"type":"object","description":"Input parameters for the decision mapped to their values","properties":{"provider":{"$ref":"#/components/schemas/ProviderTransform"},"state":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"What the questions are asked about: a string, an object or an array of strings.\nAn object with descriptive keys holding only what the questions need works best.\nExample: { message: flow_input.message, plan: results.a.plan }\n"},"questions":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"Object mapping each question name to { type, instructions, criteria }, where type is:\n- 'choice': criteria maps each option to its description (up to 255); the answer\n has choice, probabilities and confidence\n- 'score': criteria is an ordered array of 2 to 10 level descriptions; the answer\n has score, legend, probabilities and confidence\n- 'noul': yes/no, criteria optionally { true, false } descriptions; the answer has\n noul, the probability of yes (0 to 1)\nExample: { intent: { type: 'choice', instructions: 'What does the customer want?',\ncriteria: { refund: 'Money back', bug: 'Something is broken' } } }\n"}},"required":["provider","state","questions"]},"type":{"type":"string","enum":["aidecision"]},"tag":{"type":"string","description":"Worker group tag for execution routing. If not set, the step runs on the flow's tag (default `flow`)"}},"required":["type","input_transforms"]},"Identity":{"type":"object","description":"Pass-through module that returns its input unchanged. Useful for flow structure or as a placeholder","properties":{"type":{"type":"string","enum":["identity"]},"flow":{"type":"boolean","description":"If true, marks this as a flow identity (special handling)"}},"required":["type"]},"FlowStatus":{"type":"object","properties":{"step":{"type":"integer"},"modules":{"type":"array","items":{"$ref":"#/components/schemas/FlowStatusModule"}},"user_states":{"additionalProperties":true},"preprocessor_module":{"allOf":[{"$ref":"#/components/schemas/FlowStatusModule"}]},"failure_module":{"allOf":[{"$ref":"#/components/schemas/FlowStatusModule"},{"type":"object","properties":{"parent_module":{"type":"string"}}}]},"retry":{"type":"object","properties":{"fail_count":{"type":"integer"},"failed_jobs":{"type":"array","items":{"type":"string","format":"uuid"}}}}},"required":["step","modules","failure_module"]},"FlowStatusModule":{"type":"object","properties":{"type":{"type":"string","enum":["WaitingForPriorSteps","WaitingForEvents","WaitingForExecutor","InProgress","Success","Failure"]},"id":{"type":"string"},"job":{"type":"string","format":"uuid"},"count":{"type":"integer"},"progress":{"type":"integer"},"iterator":{"type":"object","properties":{"index":{"type":"integer"},"itered":{"type":"array","items":{}},"itered_len":{"type":"integer"},"args":{}}},"flow_jobs":{"type":"array","items":{"type":"string"}},"flow_jobs_success":{"type":"array","items":{"type":"boolean"}},"flow_jobs_duration":{"type":"object","properties":{"started_at":{"type":"array","items":{"type":"string"}},"duration_ms":{"type":"array","items":{"type":"integer"}}}},"branch_chosen":{"type":"object","properties":{"type":{"type":"string","enum":["branch","default"]},"branch":{"type":"integer"}},"required":["type"]},"branchall":{"type":"object","properties":{"branch":{"type":"integer"},"len":{"type":"integer"}},"required":["branch","len"]},"approvers":{"type":"array","items":{"type":"object","properties":{"resume_id":{"type":"integer"},"approver":{"type":"string"}},"required":["resume_id","approver"]}},"failed_retries":{"type":"array","items":{"type":"string","format":"uuid"}},"skipped":{"type":"boolean"},"agent_actions":{"type":"array","items":{"type":"object","oneOf":[{"type":"object","properties":{"job_id":{"type":"string","format":"uuid"},"function_name":{"type":"string"},"type":{"type":"string","enum":["tool_call"]},"module_id":{"type":"string"}},"required":["job_id","function_name","type","module_id"]},{"type":"object","properties":{"call_id":{"type":"string","format":"uuid"},"function_name":{"type":"string"},"resource_path":{"type":"string"},"type":{"type":"string","enum":["mcp_tool_call"]},"arguments":{"type":"object"}},"required":["call_id","function_name","resource_path","type"]},{"type":"object","properties":{"type":{"type":"string","enum":["web_search"]}},"required":["type"]},{"type":"object","properties":{"type":{"type":"string","enum":["approval"]},"call_id":{"type":"string"},"calls":{"type":"array","items":{"type":"object","properties":{"function_name":{"type":"string"},"arguments":{}},"required":["function_name","arguments"]}},"expires_at":{"type":"string","format":"date-time"}},"required":["type","call_id","calls","expires_at"]},{"type":"object","properties":{"type":{"type":"string","enum":["question"]},"call_id":{"type":"string"},"question":{"type":"string"},"choices":{"type":"array","items":{"type":"string"},"description":"answers the model proposes; a free-text answer is always possible"},"multi_select":{"type":"boolean","description":"whether several choices can be picked together"},"expires_at":{"type":"string","format":"date-time"}},"required":["type","call_id","question","expires_at"]},{"type":"object","properties":{"type":{"type":"string","enum":["message"]}},"required":["content","type"]}]}},"agent_actions_success":{"type":"array","items":{"type":"boolean"}}},"required":["type"]}} \ No newline at end of file diff --git a/system_prompts/auto-generated/prompts.ts b/system_prompts/auto-generated/prompts.ts index e8ccf219d6..da2c4922c7 100644 --- a/system_prompts/auto-generated/prompts.ts +++ b/system_prompts/auto-generated/prompts.ts @@ -97,7 +97,10 @@ value: An \`aiagent\` module runs an LLM that can call tools. Each entry of \`value.tools\` is a module-shaped object with an extra \`value.tool_type\`: \`flowmodule\` for a script/flow tool, \`mcp\` for an MCP server -tool, \`websearch\` for web search. +tool, \`websearch\` for web search, \`question\` for a built-in \`ask_question\` tool (the agent stops, +without holding a worker, until someone answers from the run page or the chat; optional +\`value.timeout\` in seconds, default 1800). Set \`requires_approval: true\` on a \`flowmodule\` or \`mcp\` +tool to have a person approve or reject each of its calls before it runs. \`\`\`json { @@ -193,9 +196,9 @@ needs becomes unreachable. ### Tool Naming Rules -These rules cover \`flowmodule\` tools, the ones the agent calls by name. A \`websearch\` tool's -\`summary\` is a plain label (\`Web Search\`), and an \`mcp\` tool exposes the MCP server's own tool -names, so neither is name-checked at all — leave those summaries as they are. +These rules cover \`flowmodule\` tools, the ones the agent calls by name. A \`websearch\` or \`question\` +tool's \`summary\` is a plain label (\`Web Search\`), and an \`mcp\` tool exposes the MCP +server's own tool names, so none is name-checked at all — leave those summaries as they are. - A flowmodule tool's \`summary\` is the **name the agent calls it by**, not a human label. Put the human-readable explanation in \`description\` @@ -3747,7 +3750,7 @@ class SqlQuery: export const OPENFLOW_SCHEMA = `## OpenFlow Schema -{"OpenFlow":{"type":"object","description":"Top-level flow definition containing metadata, configuration, and the flow structure","properties":{"summary":{"type":"string","description":"Short description of what this flow does"},"description":{"type":"string","description":"Detailed documentation for this flow"},"value":{"$ref":"#/components/schemas/FlowValue"},"schema":{"type":"object","description":"JSON Schema for flow inputs. Use this to define input parameters, their types, defaults, and validation. For resource inputs, set type to 'object' and format to 'resource-<type>' (e.g., 'resource-stripe')"},"on_behalf_of_email":{"type":"string","description":"Address of the account the flow runs on behalf of. Derived from on_behalf_of on read; accepted on write, where it is resolved to the account it names."},"on_behalf_of":{"type":"string","description":"The flow runs with the permissions of this identity: u/{username}, g/{group}, or a bare email when the username is itself email-shaped. The only stored half of the identity; on_behalf_of_email is derived from it. Omit it when writing and it is resolved from that address instead."}},"required":["summary","value"]},"FlowValue":{"type":"object","description":"The flow structure containing modules and optional preprocessor/failure handlers","properties":{"modules":{"type":"array","description":"Array of steps that execute in sequence. Each step can be a script, subflow, loop, or branch","items":{"$ref":"#/components/schemas/FlowModule"}},"failure_module":{"description":"Special module that executes when the flow fails. Receives error object with message, name, stack, and step_id. Must have id 'failure'. Only supports script/rawscript types","$ref":"#/components/schemas/FlowModule"},"preprocessor_module":{"description":"Special module that runs before the first step on external triggers. Must have id 'preprocessor'. Only supports script/rawscript types. Cannot reference other step results","$ref":"#/components/schemas/FlowModule"},"same_worker":{"type":"boolean","description":"If true, all steps run on the same worker for better performance"},"preserve_step_tags":{"type":"boolean","description":"If true and the flow runs on a custom worker tag, steps that declare their own non-empty tag run on it instead of inheriting the flow tag. Steps without their own tag still inherit the flow tag."},"concurrent_limit":{"type":"number","description":"Maximum number of concurrent executions of this flow"},"concurrency_key":{"type":"string","description":"Expression to group concurrent executions (e.g., by user ID)"},"concurrency_time_window_s":{"type":"number","description":"Time window in seconds for concurrent_limit"},"debounce_delay_s":{"type":"integer","description":"Delay in seconds to debounce flow executions"},"debounce_key":{"type":"string","description":"Expression to group debounced executions"},"debounce_args_to_accumulate":{"type":"array","description":"Arguments to accumulate across debounced executions","items":{"type":"string"}},"max_total_debouncing_time":{"type":"integer","description":"Maximum total time in seconds that a job can be debounced"},"max_total_debounces_amount":{"type":"integer","description":"Maximum number of times a job can be debounced"},"skip_expr":{"type":"string","description":"JavaScript expression to conditionally skip the entire flow"},"cache_ttl":{"type":"number","description":"Cache duration in seconds for flow results"},"cache_ignore_s3_path":{"type":"boolean"},"delete_after_secs":{"type":"integer","description":"If set, delete the flow job's args, result and logs after this many seconds following job completion"},"flow_env":{"type":"object","description":"Environment variables available to all steps. Values can be strings, JSON values, or special references: '$var:path' (workspace variable) or '$res:path' (resource).","additionalProperties":{}},"priority":{"type":"number","description":"Execution priority (higher numbers run first)"},"early_return":{"type":"string","description":"Id of the step whose result a sync webhook returns as soon as that step completes, while the rest of the flow keeps running. When the step does not run, or fails while the flow has a failure module, the flow's final result is returned instead."},"chat_input_enabled":{"type":"boolean","description":"Whether this flow accepts chat-style input"},"notes":{"type":"array","description":"Sticky notes attached to the flow","items":{"$ref":"#/components/schemas/FlowNote"}},"groups":{"type":"array","description":"Semantic groups of modules for organizational purposes","items":{"$ref":"#/components/schemas/FlowGroup"}}},"required":["modules"]},"Retry":{"type":"object","description":"Retry configuration for failed module executions","properties":{"constant":{"type":"object","description":"Retry with constant delay between attempts","properties":{"attempts":{"type":"integer","description":"Number of retry attempts"},"seconds":{"type":"integer","description":"Seconds to wait between retries"}}},"exponential":{"type":"object","description":"Retry with exponential backoff: the n-th retry waits multiplier \\u00d7 seconds^n","properties":{"attempts":{"type":"integer","description":"Number of retry attempts"},"multiplier":{"type":"integer","description":"Multiplier for exponential backoff"},"seconds":{"type":"integer","minimum":1,"description":"Base of the exponential (seconds); the n-th retry waits multiplier \\u00d7 seconds^n, where n counts constant retries too"},"random_factor":{"type":"integer","minimum":0,"maximum":100,"description":"Random jitter percentage (0-100) to avoid thundering herd"}}},"retry_if":{"$ref":"#/components/schemas/RetryIf"}}},"FlowNote":{"type":"object","description":"A sticky note attached to a flow for documentation and annotation","properties":{"id":{"type":"string","description":"Unique identifier for the note"},"text":{"type":"string","description":"Content of the note"},"position":{"type":"object","description":"Position of the note in the flow editor","properties":{"x":{"type":"number","description":"X coordinate"},"y":{"type":"number","description":"Y coordinate"}},"required":["x","y"]},"size":{"type":"object","description":"Size of the note in the flow editor","properties":{"width":{"type":"number","description":"Width in pixels"},"height":{"type":"number","description":"Height in pixels"}},"required":["width","height"]},"color":{"type":"string","description":"Color of the note, one of: yellow, blue, green, purple, pink, orange, red, cyan, lime, gray. Any other value renders unstyled."},"type":{"type":"string","enum":["free","group"],"description":"Type of note - 'free' for standalone notes. 'group' notes are deprecated; segment a flow with FlowValue.groups instead."},"locked":{"type":"boolean","default":false,"description":"Whether the note is locked and cannot be edited or moved"},"contained_node_ids":{"type":"array","items":{"type":"string"},"description":"For group notes, the IDs of nodes contained within this group"}},"required":["id","text","color","type"]},"FlowGroup":{"type":"object","description":"A semantic group of flow modules for organizational purposes. Does not affect execution \\u2014 modules remain in their original position in the flow. Groups provide naming and collapsibility in the editor. Members are computed dynamically from all nodes on paths between start_id and end_id.","properties":{"summary":{"type":"string","description":"Display name for this group"},"note":{"type":"string","description":"Markdown note shown below the group header"},"autocollapse":{"type":"boolean","default":false,"description":"If true, this group is collapsed by default in the flow editor. UI hint only."},"start_id":{"type":"string","description":"ID of the first flow module in this group (topological entry point)"},"end_id":{"type":"string","description":"ID of the last flow module in this group (topological exit point)"},"color":{"type":"string","description":"Color for the group in the flow editor, one of: yellow, blue, green, purple, pink, orange, red, cyan, lime, gray. Omit it to let the editor pick one."}},"required":["start_id","end_id"]},"RetryIf":{"type":"object","description":"Conditional retry based on error or result","properties":{"expr":{"type":"string","description":"JavaScript expression that returns true to retry. Has access to 'result' and 'error' variables"}},"required":["expr"]},"StopAfterIf":{"type":"object","description":"Early termination condition for a module","properties":{"skip_if_stopped":{"type":"boolean","description":"If true, following steps are skipped when this condition triggers"},"expr":{"type":"string","description":"JavaScript expression evaluated after the module runs. Can use 'result' (step's result) or 'flow_input'. Return true to stop"},"error_message":{"type":"string","nullable":true,"description":"Custom error message when stopping with an error. Mutually exclusive with skip_if_stopped. If set to a non-empty string, the flow stops with this error. If empty string, a default error message is used. If null or omitted, no error is raised."},"error_include_result":{"type":"boolean","description":"When stopping with an error (error_message set), embed the stopping step's own result inside the raised error object (as error.result) instead of discarding it. The top-level result stays { error }. Defaults to false."}},"required":["expr"]},"FlowModule":{"type":"object","description":"A single step in a flow. Can be a script, subflow, loop, or branch","properties":{"id":{"type":"string","description":"Unique identifier for this step. Used to reference results via 'results.step_id'. Must be a valid identifier (alphanumeric, underscore, hyphen)"},"value":{"$ref":"#/components/schemas/FlowModuleValue"},"stop_after_if":{"description":"Early termination condition evaluated after this step completes","$ref":"#/components/schemas/StopAfterIf"},"stop_after_all_iters_if":{"description":"For loops only - early termination condition evaluated after all iterations complete","$ref":"#/components/schemas/StopAfterIf"},"skip_if":{"type":"object","description":"Conditionally skip this step based on previous results or flow inputs","properties":{"expr":{"type":"string","description":"JavaScript expression that returns true to skip. Can use 'flow_input' or 'results.<step_id>'"}},"required":["expr"]},"sleep":{"description":"Delay before executing this step (in seconds or as expression)","$ref":"#/components/schemas/InputTransform"},"cache_ttl":{"type":"number","description":"Cache duration in seconds for this step's results"},"cache_ignore_s3_path":{"type":"boolean"},"timeout":{"description":"Maximum execution time in seconds (static value or expression)","$ref":"#/components/schemas/InputTransform"},"delete_after_secs":{"type":"integer","description":"If set, delete the step's args, result and logs after this many seconds following job completion"},"summary":{"type":"string","description":"Short description of what this step does"},"mock":{"type":"object","description":"Mock configuration for testing without executing the actual step","properties":{"enabled":{"type":"boolean","description":"If true, return mock value instead of executing"},"return_value":{"description":"Value to return when mocked"}}},"suspend":{"type":"object","description":"Configuration for approval/resume steps that wait for user input","properties":{"required_events":{"type":"integer","description":"Number of approvals required before continuing"},"timeout":{"type":"integer","description":"Timeout in seconds before auto-continuing or canceling"},"resume_form":{"type":"object","description":"Form schema for collecting input when resuming","properties":{"schema":{"type":"object","description":"JSON Schema for the resume form"}}},"user_auth_required":{"type":"boolean","description":"If true, only authenticated users can approve"},"user_groups_required":{"description":"Expression or list of groups that can approve","$ref":"#/components/schemas/InputTransform"},"self_approval_disabled":{"type":"boolean","description":"If true, the user who started the flow cannot approve"},"hide_cancel":{"type":"boolean","description":"If true, hide the cancel button on the approval form"},"continue_on_disapprove_timeout":{"type":"boolean","description":"If true, continue flow on timeout instead of canceling"},"skin":{"type":"string","enum":["detailed","minimal"],"description":"How the approval request is presented, on the approval page and in Slack/Teams approval messages. 'detailed' (used when unset) shows the flow details (arguments, graph, approvers); 'minimal' shows only the request: the step description, form and approve/reject actions"}}},"priority":{"type":"number","description":"Execution priority for this step (higher numbers run first)"},"continue_on_error":{"type":"boolean","description":"If true, flow continues even if this step fails"},"job_token_scopes":{"type":"array","nullable":true,"items":{"type":"string"},"description":"Scopes the token of this step's jobs is restricted to (domain:action[:resource], e.g. oidc:write), on top of the flow's own restriction: a step can only narrow it. Applies to everything the step runs (loop and branch bodies, AI agent tools)."},"retry":{"description":"Retry configuration if this step fails","$ref":"#/components/schemas/Retry"},"debouncing":{"description":"Debounce configuration for this step (EE only)","type":"object","properties":{"debounce_delay_s":{"type":"integer","description":"Delay in seconds to debounce this step's executions across flow runs"},"debounce_key":{"type":"string","description":"Expression to group debounced executions. Supports $workspace and $args[name]. Default: $workspace/flow/<flow_path>-<step_id>"},"debounce_args_to_accumulate":{"type":"array","description":"Array-type arguments to accumulate across debounced executions","items":{"type":"string"}},"max_total_debouncing_time":{"type":"integer","description":"Maximum total time in seconds before forced execution"},"max_total_debounces_amount":{"type":"integer","description":"Maximum number of debounces before forced execution"}}}},"required":["value","id"]},"InputTransform":{"description":"Maps input parameters for a step. Can be a static value or a JavaScript expression that references previous results or flow inputs","oneOf":[{"$ref":"#/components/schemas/StaticTransform"},{"$ref":"#/components/schemas/JavascriptTransform"},{"$ref":"#/components/schemas/AiTransform"}],"discriminator":{"propertyName":"type","mapping":{"static":"#/components/schemas/StaticTransform","javascript":"#/components/schemas/JavascriptTransform","ai":"#/components/schemas/AiTransform"}}},"StaticTransform":{"type":"object","description":"Static value passed directly to the step. Use for hardcoded values or resource references like '$res:path/to/resource'","properties":{"value":{"description":"The static value. For resources, use format '$res:path/to/resource'"},"type":{"type":"string","enum":["static"]}},"required":["type"]},"JavascriptTransform":{"type":"object","description":"JavaScript expression evaluated at runtime. Can reference previous step results via 'results.step_id' or flow inputs via 'flow_input.property'. Inside for loops, use 'flow_input.iter.value' for the current iteration value (in while loops it equals 'flow_input.iter.index')","properties":{"expr":{"type":"string","description":"JavaScript expression returning the value. Available variables - results (object with all previous step results), flow_input (flow inputs), flow_input.iter (in loops)"},"type":{"type":"string","enum":["javascript"]}},"required":["expr","type"]},"AiTransform":{"type":"object","description":"Value resolved by the AI runtime for this input. The AI engine decides how to satisfy the parameter.","properties":{"type":{"type":"string","enum":["ai"]}},"required":["type"]},"AIProviderKind":{"type":"string","description":"Supported AI provider types","enum":["openai","azure_openai","azure_foundry","anthropic","mistral","deepseek","googleai","groq","openrouter","togetherai","customai","aws_bedrock","typesafe","cloudflare"]},"ProviderConfig":{"type":"object","description":"Complete AI provider configuration with resource reference and model selection","properties":{"kind":{"$ref":"#/components/schemas/AIProviderKind"},"resource":{"type":"string","description":"Resource reference in format '$res:{resource_path}' pointing to provider credentials"},"model":{"type":"string","description":"Model identifier (e.g., 'gpt-4', 'claude-3-opus-20240229', 'gemini-pro')"},"reasoning_effort":{"type":"string","description":"Provider-native reasoning effort token (e.g. 'low', 'high', 'none') for models that support extended thinking. Optional; unset leaves the provider default."}},"required":["kind","resource","model"]},"StaticProviderTransform":{"type":"object","description":"Static provider configuration passed directly to the AI agent","properties":{"value":{"$ref":"#/components/schemas/ProviderConfig"},"type":{"type":"string","enum":["static"]}},"required":["type","value"]},"ProviderTransform":{"description":"Provider configuration - can be static (ProviderConfig), JavaScript expression, or AI-determined","oneOf":[{"$ref":"#/components/schemas/StaticProviderTransform"},{"$ref":"#/components/schemas/JavascriptTransform"},{"$ref":"#/components/schemas/AiTransform"}],"discriminator":{"propertyName":"type","mapping":{"static":"#/components/schemas/StaticProviderTransform","javascript":"#/components/schemas/JavascriptTransform","ai":"#/components/schemas/AiTransform"}}},"MemoryOff":{"type":"object","description":"No conversation memory/context","properties":{"kind":{"type":"string","enum":["off"]}},"required":["kind"]},"MemoryWindow":{"type":"object","description":"Keeps the most recent messages of the memory named by the run's memory id (or the step's\\n\`memory_id\`). Without a memory id the agent runs without memory.\\n","properties":{"kind":{"type":"string","enum":["window"]},"context_length":{"type":"integer","description":"Number of most recent messages to load and store. 0 turns memory off."}},"required":["kind","context_length"]},"MemoryAuto":{"type":"object","deprecated":true,"description":"Deprecated, still read as it was written: the run's memory id, else the \`memory_id\` here.\\nThe step's own \`memory_id\` is not read while this kind is set; switch the kind to \`window\`\\nto use it. Without a \`context_length\`, or with 0, it is \`off\` and reads \`previous_messages\`.\\n","properties":{"kind":{"type":"string","enum":["auto"]},"context_length":{"type":"integer","description":"Maximum number of messages to retain in context"},"memory_id":{"type":"string","description":"Identifier for persistent memory across agent invocations"}},"required":["kind"]},"MemoryCompaction":{"type":"object","description":"Keeps the whole memory named by the run's memory id (or the step's \`memory_id\`), replacing\\nits older part with a summary as the conversation approaches the model's context window.\\nWithout a memory id the agent runs without memory, and compaction bounds the run's own loop.\\n","properties":{"kind":{"type":"string","enum":["compaction"]},"context_window":{"type":"integer","description":"Overrides the context window looked up from the model, in tokens. Only a model\\nWindmill does not know needs one; those fall back to 128000.\\n"}},"required":["kind"]},"MemoryMessage":{"type":"object","description":"A single message in conversation history","properties":{"role":{"type":"string","enum":["user","assistant","system"]},"content":{"type":"string"}},"required":["role","content"]},"MemoryManual":{"type":"object","deprecated":true,"description":"Deprecated, still read as it was written. Move the step to \`off\` with \`previous_messages\` instead.","properties":{"kind":{"type":"string","enum":["manual"]},"messages":{"type":"array","items":{"$ref":"#/components/schemas/MemoryMessage"}}},"required":["kind","messages"]},"MemoryConfig":{"description":"Managed memory, stored by Windmill and replayed with each request. The memory is named by a memory id, see \`memory_id\`. While it is off, a step can supply its history in \`previous_messages\`.","oneOf":[{"$ref":"#/components/schemas/MemoryOff"},{"$ref":"#/components/schemas/MemoryWindow"},{"$ref":"#/components/schemas/MemoryCompaction"},{"$ref":"#/components/schemas/MemoryAuto"},{"$ref":"#/components/schemas/MemoryManual"}],"discriminator":{"propertyName":"kind","mapping":{"off":"#/components/schemas/MemoryOff","window":"#/components/schemas/MemoryWindow","compaction":"#/components/schemas/MemoryCompaction","auto":"#/components/schemas/MemoryAuto","manual":"#/components/schemas/MemoryManual"}}},"StaticMemoryTransform":{"type":"object","description":"Static memory configuration passed directly to the AI agent","properties":{"value":{"$ref":"#/components/schemas/MemoryConfig"},"type":{"type":"string","enum":["static"]}},"required":["type","value"]},"MemoryTransform":{"description":"Memory configuration - can be static (MemoryConfig), JavaScript expression, or AI-determined","oneOf":[{"$ref":"#/components/schemas/StaticMemoryTransform"},{"$ref":"#/components/schemas/JavascriptTransform"},{"$ref":"#/components/schemas/AiTransform"}],"discriminator":{"propertyName":"type","mapping":{"static":"#/components/schemas/StaticMemoryTransform","javascript":"#/components/schemas/JavascriptTransform","ai":"#/components/schemas/AiTransform"}}},"FlowModuleValue":{"description":"The actual implementation of a flow step. Can be a script (inline or referenced), subflow, loop, branch, or special module type","oneOf":[{"$ref":"#/components/schemas/RawScript"},{"$ref":"#/components/schemas/PathScript"},{"$ref":"#/components/schemas/PathFlow"},{"$ref":"#/components/schemas/ForloopFlow"},{"$ref":"#/components/schemas/WhileloopFlow"},{"$ref":"#/components/schemas/BranchOne"},{"$ref":"#/components/schemas/BranchAll"},{"$ref":"#/components/schemas/Identity"},{"$ref":"#/components/schemas/AiAgent"},{"$ref":"#/components/schemas/AiDecision"}],"discriminator":{"propertyName":"type","mapping":{"rawscript":"#/components/schemas/RawScript","script":"#/components/schemas/PathScript","flow":"#/components/schemas/PathFlow","forloopflow":"#/components/schemas/ForloopFlow","whileloopflow":"#/components/schemas/WhileloopFlow","branchone":"#/components/schemas/BranchOne","branchall":"#/components/schemas/BranchAll","identity":"#/components/schemas/Identity","aiagent":"#/components/schemas/AiAgent","aidecision":"#/components/schemas/AiDecision"}}},"RawScript":{"type":"object","description":"Inline script with code defined directly in the flow. Use 'bun' as default language if unspecified. The script receives arguments from input_transforms","properties":{"input_transforms":{"type":"object","description":"Map of parameter names to their values (static or JavaScript expressions). These become the script's input arguments","additionalProperties":{"$ref":"#/components/schemas/InputTransform"}},"content":{"type":"string","description":"The script source code. Should export a 'main' function"},"language":{"type":"string","description":"Programming language for this script","enum":["deno","bun","bunnative","python3","go","bash","powershell","postgresql","mysql","bigquery","snowflake","mssql","oracledb","graphql","nativets","php","rust","ansible","csharp","nu","java","ruby","rlang","duckdb"]},"path":{"type":"string","description":"Optional path for saving this script"},"lock":{"type":"string","description":"Lock file content for dependencies"},"type":{"type":"string","enum":["rawscript"]},"tag":{"type":"string","description":"Worker group tag for execution routing"},"concurrent_limit":{"type":"number","description":"Maximum concurrent executions of this script"},"concurrency_time_window_s":{"type":"number","description":"Time window for concurrent_limit"},"custom_concurrency_key":{"type":"string","description":"Custom key for grouping concurrent executions"},"is_trigger":{"type":"boolean","description":"If true, this script is a trigger that can start the flow"},"assets":{"type":"array","description":"External resources this script accesses (S3 objects, resources, etc.)","items":{"type":"object","required":["path","kind"],"properties":{"path":{"type":"string","description":"Path to the asset"},"kind":{"type":"string","description":"Type of asset","enum":["s3object","resource","ducklake","datatable","volume","dbt"]},"access_type":{"type":"string","nullable":true,"description":"Access level for this asset","enum":["r","w","rw"]},"alt_access_type":{"type":"string","nullable":true,"description":"Alternative access level","enum":["r","w","rw"]}}}}},"required":["type","content","language","input_transforms"]},"PathScript":{"type":"object","description":"Reference to an existing script by path. Use this when calling a previously saved script instead of writing inline code","properties":{"input_transforms":{"type":"object","description":"Map of parameter names to their values (static or JavaScript expressions). These become the script's input arguments","additionalProperties":{"$ref":"#/components/schemas/InputTransform"}},"path":{"type":"string","description":"Path to the script in the workspace (e.g., 'f/scripts/send_email')"},"hash":{"type":"string","description":"Optional specific version hash of the script to use"},"type":{"type":"string","enum":["script"]},"tag_override":{"type":"string","description":"Override the script's default worker group tag"},"is_trigger":{"type":"boolean","description":"If true, this script is a trigger that can start the flow"}},"required":["type","path","input_transforms"]},"PathFlow":{"type":"object","description":"Reference to an existing flow by path. Use this to call another flow as a subflow","properties":{"input_transforms":{"type":"object","description":"Map of parameter names to their values (static or JavaScript expressions). These become the subflow's input arguments","additionalProperties":{"$ref":"#/components/schemas/InputTransform"}},"path":{"type":"string","description":"Path to the flow in the workspace (e.g., 'f/flows/process_user')"},"type":{"type":"string","enum":["flow"]}},"required":["type","path","input_transforms"]},"ForloopFlow":{"type":"object","description":"Executes nested modules in a loop over an iterator. Inside the loop, use 'flow_input.iter.value' to access the current iteration value, and 'flow_input.iter.index' for the index. Supports parallel execution for better performance on I/O-bound operations","properties":{"modules":{"type":"array","description":"Steps to execute for each iteration. These can reference the iteration value via 'flow_input.iter.value'","items":{"$ref":"#/components/schemas/FlowModule"}},"iterator":{"description":"JavaScript expression that returns an array to iterate over. Can reference 'results.step_id' or 'flow_input'","$ref":"#/components/schemas/InputTransform"},"skip_failures":{"type":"boolean","description":"If true, iteration failures don't stop the loop. Failed iterations return null"},"type":{"type":"string","enum":["forloopflow"]},"parallel":{"type":"boolean","description":"If true, iterations run concurrently (faster for I/O-bound operations). Use with parallelism to control concurrency"},"parallelism":{"description":"Maximum number of concurrent iterations when parallel=true. Limits resource usage. Can be static number or expression","$ref":"#/components/schemas/InputTransform"},"squash":{"type":"boolean"}},"required":["modules","iterator","skip_failures","type"]},"WhileloopFlow":{"type":"object","description":"Executes nested modules repeatedly until stopped. The implicit iterator is the iteration counter, so 'flow_input.iter.value' equals 'flow_input.iter.index' (0, 1, 2, ...) and never carries state. To carry state across iterations, a step reads its own previous-iteration result via 'results.<its_own_id>' with a first-iteration fallback - the loop's stop_after_if must then be on that inner step (a plain single-step body with stop_after_if on the loop module does not resolve 'results' across iterations and never terminates); plain counters can instead be derived from 'flow_input.iter.index', which works in every configuration. stop_after_if is evaluated after each iteration - on the loop module 'result' is the last iteration's result","properties":{"modules":{"type":"array","description":"Steps to execute in each iteration","items":{"$ref":"#/components/schemas/FlowModule"}},"skip_failures":{"type":"boolean","description":"If true, iteration failures don't stop the loop. Failed iterations return null"},"type":{"type":"string","enum":["whileloopflow"]},"parallel":{"type":"boolean","description":"If true, iterations run concurrently (use with caution in while loops)"},"parallelism":{"description":"Maximum number of concurrent iterations when parallel=true","$ref":"#/components/schemas/InputTransform"},"squash":{"type":"boolean"}},"required":["modules","skip_failures","type"]},"BranchOne":{"type":"object","description":"Conditional branching where only the first matching branch executes. Branches are evaluated in order, and the first one with a true expression runs. If no branches match, the default branch executes","properties":{"branches":{"type":"array","description":"Array of branches to evaluate in order. The first branch with expr evaluating to true executes","items":{"type":"object","properties":{"summary":{"type":"string","description":"Short description of this branch condition"},"expr":{"type":"string","description":"JavaScript expression that returns boolean. Can use 'results.step_id' or 'flow_input'. First true expr wins"},"modules":{"type":"array","description":"Steps to execute if this branch's expr is true","items":{"$ref":"#/components/schemas/FlowModule"}}},"required":["modules","expr"]}},"default":{"type":"array","description":"Steps to execute if no branch expressions match","items":{"$ref":"#/components/schemas/FlowModule"}},"type":{"type":"string","enum":["branchone"]}},"required":["branches","default","type"]},"BranchAll":{"type":"object","description":"Parallel branching where all branches execute simultaneously. Unlike BranchOne, all branches run regardless of conditions. Useful for executing independent tasks concurrently","properties":{"branches":{"type":"array","description":"Array of branches that all execute (either in parallel or sequentially)","items":{"type":"object","properties":{"summary":{"type":"string","description":"Short description of this branch's purpose"},"skip_failure":{"type":"boolean","description":"If true, failure in this branch doesn't fail the entire flow"},"modules":{"type":"array","description":"Steps to execute in this branch","items":{"$ref":"#/components/schemas/FlowModule"}}},"required":["modules"]}},"type":{"type":"string","enum":["branchall"]},"parallel":{"type":"boolean","description":"If true, all branches execute concurrently. If false, they execute sequentially"}},"required":["branches","type"]},"AgentTool":{"type":"object","description":"A tool available to an AI agent. Can be a flow module or an external MCP (Model Context Protocol) tool","properties":{"id":{"type":"string","description":"Unique identifier for this tool. Cannot contain spaces - use underscores instead (e.g., 'get_user_data' not 'get user data')"},"summary":{"type":"string","description":"The name the AI agent calls this tool by, not a human label. On a flowmodule tool it must match ^[a-zA-Z0-9_]+$ - letters, numbers and underscores only (e.g. 'search_documentation', not 'Search documentation') - and always be set; on an mcp or websearch tool it is a plain label. Put the human-readable explanation in 'description'."},"description":{"type":"string","description":"Free-text description of the tool given to the AI to decide when and how to call it. Overrides the description auto-derived from the underlying script."},"job_token_scopes":{"type":"array","nullable":true,"items":{"type":"string"},"description":"Scopes the token of this tool's jobs is restricted to, on top of the agent step's own restriction: a tool can only narrow it."},"value":{"$ref":"#/components/schemas/ToolValue"}},"required":["id","value"]},"ToolValue":{"description":"The implementation of a tool. Can be a flow module (script/flow) or an MCP tool reference","oneOf":[{"$ref":"#/components/schemas/FlowModuleTool"},{"$ref":"#/components/schemas/McpToolValue"},{"$ref":"#/components/schemas/WebsearchToolValue"}],"discriminator":{"propertyName":"tool_type","mapping":{"flowmodule":"#/components/schemas/FlowModuleTool","mcp":"#/components/schemas/McpToolValue","websearch":"#/components/schemas/WebsearchToolValue"}}},"FlowModuleTool":{"description":"A tool implemented as a flow module (script, flow, etc.). The AI can call this like any other flow module","allOf":[{"type":"object","properties":{"tool_type":{"type":"string","enum":["flowmodule"]}},"required":["tool_type"]},{"$ref":"#/components/schemas/FlowModuleValue"}]},"WebsearchToolValue":{"type":"object","description":"A tool implemented as a websearch tool. The AI can call this like any other websearch tool","properties":{"tool_type":{"type":"string","enum":["websearch"]}},"required":["tool_type"]},"McpToolValue":{"type":"object","description":"Reference to an external MCP (Model Context Protocol) tool. The AI can call tools from MCP servers","properties":{"tool_type":{"type":"string","enum":["mcp"]},"resource_path":{"type":"string","description":"Path to the MCP resource/server configuration"},"include_tools":{"type":"array","description":"Whitelist of specific tools to include from this MCP server","items":{"type":"string"}},"exclude_tools":{"type":"array","description":"Blacklist of tools to exclude from this MCP server","items":{"type":"string"}}},"required":["tool_type","resource_path"]},"AiAgent":{"type":"object","description":"AI agent step that can use tools to accomplish tasks. The agent receives inputs and can call any of its configured tools to complete the task","properties":{"input_transforms":{"type":"object","description":"Input parameters for the AI agent mapped to their values","properties":{"provider":{"$ref":"#/components/schemas/ProviderTransform"},"output_type":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"Output format type.\\nValid values: 'text' (default) - plain text response, 'image' - image generation\\n"},"user_message":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"The user's prompt/message to the AI agent. Supports variable interpolation with\\nflow.input syntax. Required unless memory is off and \`previous_messages\` supplies\\nthe prompt; image output always needs it.\\n"},"system_prompt":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"System instructions that guide the AI's behavior, persona, and response style. Optional."},"streaming":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"Boolean. If true, stream the AI response incrementally.\\nStreaming events include: token_delta, reasoning_token_delta, tool_call, tool_call_arguments, tool_execution, tool_result\\n"},"memory":{"$ref":"#/components/schemas/MemoryTransform"},"memory_id":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"String. Names the memory this step reads and writes, overriding the memory id the run\\nwas started with (the chat conversation, an app chat session or the \`memory_id\` run\\nparameter). Leave unset to use the run's memory id. A fixed value shares one memory\\nacross every run; an expression such as \`flow_input.customer_id\` keeps one memory per\\nkey. When it evaluates to an empty value the agent runs without memory. Read only\\nwhile \`memory\` is \`window\` or \`compaction\`: it is ignored when memory is off, and an\\nolder \`auto\` or \`manual\` memory reads neither history input.\\n"},"previous_messages":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"Array of MemoryMessage. History supplied by the flow, sent between the system prompt\\nand the user message. Read only while \`memory\` is off or absent: managed memory\\nignores it, and an older \`auto\` or \`manual\` memory reads neither history input.\\n"},"output_schema":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"JSON Schema object defining structured output format. Used when you need the AI to return data in a specific shape.\\nSupports standard JSON Schema properties: type, properties, required, items, enum, pattern, minLength, maxLength, minimum, maximum, etc.\\nExample: { type: 'object', properties: { name: { type: 'string' }, age: { type: 'integer' } }, required: ['name'] }\\n"},"user_attachments":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"Array of file references (images or PDFs) for the AI agent.\\nFormat: Array<{ bucket: string, key: string }> - S3 object references\\nExample: [{ bucket: 'my-bucket', key: 'documents/report.pdf' }]\\n"},"enabled_tools":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"Array of strings naming which of the tools configured in \`tools\` the agent may call\\nthis run. Leaving it unset carries every one of them; an empty array carries none.\\nA tool is named as the model is shown it. An entry the model is shown nothing of is\\nnamed by what identifies it instead: an MCP server by its resource path, carrying\\nevery tool it exposes (which of them stays that entry's include_tools/exclude_tools),\\nand a websearch entry by the reserved name '__wm_web_search', whatever summary it carries\\n(no tool may take that name).\\nExample: ['get_user', 'u/admin/github_mcp', '__wm_web_search']\\n"},"max_completion_tokens":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"Integer. Maximum number of tokens the AI will generate in its response.\\nRange: 1 to 4,294,967,295. Typical values: 256-4096 for most use cases.\\n"},"temperature":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"Float. Controls randomness/creativity of responses.\\nRange: 0.0 to 2.0 (provider-dependent)\\n- 0.0 = deterministic, focused responses\\n- 0.7 = balanced (common default)\\n- 1.0+ = more creative/random\\n"},"max_iterations":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"Number. Limits how many times the agent can loop through reasoning and tool use.\\nRange: 1-1000.\\n"},"model":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"String. Only on a step linked to a saved agent (see \`agent\`): replaces the model\\nsaved on the agent for this step's runs, on the agent's own provider resource. An\\nempty value keeps the saved model. Set it to an expression such as\\n\`flow_input.model\` to choose the model per run.\\n"},"reasoning_effort":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"String. Only on a step linked to a saved agent (see \`agent\`): replaces the reasoning\\neffort saved on the agent for this step's runs, as a provider-native token (e.g.\\n'low', 'high', 'none'). An empty value sends no effort, so the model runs at its\\ndefault. Leave the input out to keep the saved effort, which holds only while the\\nstep runs the saved model. A step that is not linked sets both inside \`provider\`.\\n"}}},"tools":{"type":"array","description":"Array of tools the agent can use. The agent decides which tools to call based on the task","items":{"$ref":"#/components/schemas/AgentTool"}},"type":{"type":"string","enum":["aiagent"]},"tag":{"type":"string","description":"Worker group tag for execution routing. If not set, the AI agent step runs on the flow's tag (default \`flow\`)"},"omit_output_from_conversation":{"type":"boolean","default":false,"description":"If true, this AI agent step does not persist its assistant or tool messages to the flow conversation when chat mode is enabled."},"agent":{"type":"string","description":"Path of a reusable \`ai_agent\` resource (hybrid linking). When set, the agent brain\\nconfig (provider/model/system prompt/etc.) and tool set are resolved at runtime from\\nthat resource; the module's input_transforms then only carry the flow-local inputs\\n(user_message, user_attachments, enabled_tools and the history inputs memory_id and previous_messages)\\nand, optionally, the \`model\` and \`reasoning_effort\` overrides of what the agent saved.\\n"},"tool_inputs":{"type":"object","description":"Host-local wiring for an agent's tool inputs, keyed by tool id then input key. Binds the\\nreferenced agent's tools to this flow's context (flow_input/results) without mutating the\\nshared resource; overlaid onto the tools' input_transforms at runtime \\u2014 including when\\n\`agent\` is unset, since a step forked for editing keeps these overrides until it is saved\\nback or unlinked.\\n","additionalProperties":{"type":"object","additionalProperties":{"$ref":"#/components/schemas/InputTransform"}}},"parallel":{"type":"boolean","description":"If true, the agent can execute multiple tool calls in parallel"}},"required":["type","input_transforms"]},"AiDecision":{"type":"object","description":"AI decision step: one call to a decision model (TypeSafe's Jev, Cloudflare's\\nJev-compatible Clef, or OpenAI's Decisions API) that answers typed questions about a\\nstate with calibrated probabilities, instead of generating text.\\nPrefer it over an AI agent to classify, route, score or check something: it is fast,\\ncheap and its answers are structured. Its result is { output: { <question name>: answer },\\nmodel, usage }, so a later step reads e.g. results.<id>.output.intent.choice. To route on\\nthe answers, follow it with a branchone whose branch exprs read\\nresults.<id>.output.<question>.choice. Usable as an AI agent tool, where the calling agent\\nsupplies the state.\\n","properties":{"input_transforms":{"type":"object","description":"Input parameters for the decision mapped to their values","properties":{"provider":{"$ref":"#/components/schemas/ProviderTransform"},"state":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"What the questions are asked about: a string, an object or an array of strings.\\nAn object with descriptive keys holding only what the questions need works best.\\nExample: { message: flow_input.message, plan: results.a.plan }\\n"},"questions":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"Object mapping each question name to { type, instructions, criteria }, where type is:\\n- 'choice': criteria maps each option to its description (up to 255); the answer\\n has choice, probabilities and confidence\\n- 'score': criteria is an ordered array of 2 to 10 level descriptions; the answer\\n has score, legend, probabilities and confidence\\n- 'noul': yes/no, criteria optionally { true, false } descriptions; the answer has\\n noul, the probability of yes (0 to 1)\\nExample: { intent: { type: 'choice', instructions: 'What does the customer want?',\\ncriteria: { refund: 'Money back', bug: 'Something is broken' } } }\\n"}},"required":["provider","state","questions"]},"type":{"type":"string","enum":["aidecision"]},"tag":{"type":"string","description":"Worker group tag for execution routing. If not set, the step runs on the flow's tag (default \`flow\`)"}},"required":["type","input_transforms"]},"Identity":{"type":"object","description":"Pass-through module that returns its input unchanged. Useful for flow structure or as a placeholder","properties":{"type":{"type":"string","enum":["identity"]},"flow":{"type":"boolean","description":"If true, marks this as a flow identity (special handling)"}},"required":["type"]},"FlowStatus":{"type":"object","properties":{"step":{"type":"integer"},"modules":{"type":"array","items":{"$ref":"#/components/schemas/FlowStatusModule"}},"user_states":{"additionalProperties":true},"preprocessor_module":{"allOf":[{"$ref":"#/components/schemas/FlowStatusModule"}]},"failure_module":{"allOf":[{"$ref":"#/components/schemas/FlowStatusModule"},{"type":"object","properties":{"parent_module":{"type":"string"}}}]},"retry":{"type":"object","properties":{"fail_count":{"type":"integer"},"failed_jobs":{"type":"array","items":{"type":"string","format":"uuid"}}}}},"required":["step","modules","failure_module"]},"FlowStatusModule":{"type":"object","properties":{"type":{"type":"string","enum":["WaitingForPriorSteps","WaitingForEvents","WaitingForExecutor","InProgress","Success","Failure"]},"id":{"type":"string"},"job":{"type":"string","format":"uuid"},"count":{"type":"integer"},"progress":{"type":"integer"},"iterator":{"type":"object","properties":{"index":{"type":"integer"},"itered":{"type":"array","items":{}},"itered_len":{"type":"integer"},"args":{}}},"flow_jobs":{"type":"array","items":{"type":"string"}},"flow_jobs_success":{"type":"array","items":{"type":"boolean"}},"flow_jobs_duration":{"type":"object","properties":{"started_at":{"type":"array","items":{"type":"string"}},"duration_ms":{"type":"array","items":{"type":"integer"}}}},"branch_chosen":{"type":"object","properties":{"type":{"type":"string","enum":["branch","default"]},"branch":{"type":"integer"}},"required":["type"]},"branchall":{"type":"object","properties":{"branch":{"type":"integer"},"len":{"type":"integer"}},"required":["branch","len"]},"approvers":{"type":"array","items":{"type":"object","properties":{"resume_id":{"type":"integer"},"approver":{"type":"string"}},"required":["resume_id","approver"]}},"failed_retries":{"type":"array","items":{"type":"string","format":"uuid"}},"skipped":{"type":"boolean"},"agent_actions":{"type":"array","items":{"type":"object","oneOf":[{"type":"object","properties":{"job_id":{"type":"string","format":"uuid"},"function_name":{"type":"string"},"type":{"type":"string","enum":["tool_call"]},"module_id":{"type":"string"}},"required":["job_id","function_name","type","module_id"]},{"type":"object","properties":{"call_id":{"type":"string","format":"uuid"},"function_name":{"type":"string"},"resource_path":{"type":"string"},"type":{"type":"string","enum":["mcp_tool_call"]},"arguments":{"type":"object"}},"required":["call_id","function_name","resource_path","type"]},{"type":"object","properties":{"type":{"type":"string","enum":["web_search"]}},"required":["type"]},{"type":"object","properties":{"type":{"type":"string","enum":["message"]}},"required":["content","type"]}]}},"agent_actions_success":{"type":"array","items":{"type":"boolean"}}},"required":["type"]}}`; +{"OpenFlow":{"type":"object","description":"Top-level flow definition containing metadata, configuration, and the flow structure","properties":{"summary":{"type":"string","description":"Short description of what this flow does"},"description":{"type":"string","description":"Detailed documentation for this flow"},"value":{"$ref":"#/components/schemas/FlowValue"},"schema":{"type":"object","description":"JSON Schema for flow inputs. Use this to define input parameters, their types, defaults, and validation. For resource inputs, set type to 'object' and format to 'resource-<type>' (e.g., 'resource-stripe')"},"on_behalf_of_email":{"type":"string","description":"Address of the account the flow runs on behalf of. Derived from on_behalf_of on read; accepted on write, where it is resolved to the account it names."},"on_behalf_of":{"type":"string","description":"The flow runs with the permissions of this identity: u/{username}, g/{group}, or a bare email when the username is itself email-shaped. The only stored half of the identity; on_behalf_of_email is derived from it. Omit it when writing and it is resolved from that address instead."}},"required":["summary","value"]},"FlowValue":{"type":"object","description":"The flow structure containing modules and optional preprocessor/failure handlers","properties":{"modules":{"type":"array","description":"Array of steps that execute in sequence. Each step can be a script, subflow, loop, or branch","items":{"$ref":"#/components/schemas/FlowModule"}},"failure_module":{"description":"Special module that executes when the flow fails. Receives error object with message, name, stack, and step_id. Must have id 'failure'. Only supports script/rawscript types","$ref":"#/components/schemas/FlowModule"},"preprocessor_module":{"description":"Special module that runs before the first step on external triggers. Must have id 'preprocessor'. Only supports script/rawscript types. Cannot reference other step results","$ref":"#/components/schemas/FlowModule"},"same_worker":{"type":"boolean","description":"If true, all steps run on the same worker for better performance"},"preserve_step_tags":{"type":"boolean","description":"If true and the flow runs on a custom worker tag, steps that declare their own non-empty tag run on it instead of inheriting the flow tag. Steps without their own tag still inherit the flow tag."},"concurrent_limit":{"type":"number","description":"Maximum number of concurrent executions of this flow"},"concurrency_key":{"type":"string","description":"Expression to group concurrent executions (e.g., by user ID)"},"concurrency_time_window_s":{"type":"number","description":"Time window in seconds for concurrent_limit"},"debounce_delay_s":{"type":"integer","description":"Delay in seconds to debounce flow executions"},"debounce_key":{"type":"string","description":"Expression to group debounced executions"},"debounce_args_to_accumulate":{"type":"array","description":"Arguments to accumulate across debounced executions","items":{"type":"string"}},"max_total_debouncing_time":{"type":"integer","description":"Maximum total time in seconds that a job can be debounced"},"max_total_debounces_amount":{"type":"integer","description":"Maximum number of times a job can be debounced"},"skip_expr":{"type":"string","description":"JavaScript expression to conditionally skip the entire flow"},"cache_ttl":{"type":"number","description":"Cache duration in seconds for flow results"},"cache_ignore_s3_path":{"type":"boolean"},"delete_after_secs":{"type":"integer","description":"If set, delete the flow job's args, result and logs after this many seconds following job completion"},"flow_env":{"type":"object","description":"Environment variables available to all steps. Values can be strings, JSON values, or special references: '$var:path' (workspace variable) or '$res:path' (resource).","additionalProperties":{}},"priority":{"type":"number","description":"Execution priority (higher numbers run first)"},"early_return":{"type":"string","description":"Id of the step whose result a sync webhook returns as soon as that step completes, while the rest of the flow keeps running. When the step does not run, or fails while the flow has a failure module, the flow's final result is returned instead."},"chat_input_enabled":{"type":"boolean","description":"Whether this flow accepts chat-style input"},"notes":{"type":"array","description":"Sticky notes attached to the flow","items":{"$ref":"#/components/schemas/FlowNote"}},"groups":{"type":"array","description":"Semantic groups of modules for organizational purposes","items":{"$ref":"#/components/schemas/FlowGroup"}}},"required":["modules"]},"Retry":{"type":"object","description":"Retry configuration for failed module executions","properties":{"constant":{"type":"object","description":"Retry with constant delay between attempts","properties":{"attempts":{"type":"integer","description":"Number of retry attempts"},"seconds":{"type":"integer","description":"Seconds to wait between retries"}}},"exponential":{"type":"object","description":"Retry with exponential backoff: the n-th retry waits multiplier \\u00d7 seconds^n","properties":{"attempts":{"type":"integer","description":"Number of retry attempts"},"multiplier":{"type":"integer","description":"Multiplier for exponential backoff"},"seconds":{"type":"integer","minimum":1,"description":"Base of the exponential (seconds); the n-th retry waits multiplier \\u00d7 seconds^n, where n counts constant retries too"},"random_factor":{"type":"integer","minimum":0,"maximum":100,"description":"Random jitter percentage (0-100) to avoid thundering herd"}}},"retry_if":{"$ref":"#/components/schemas/RetryIf"}}},"FlowNote":{"type":"object","description":"A sticky note attached to a flow for documentation and annotation","properties":{"id":{"type":"string","description":"Unique identifier for the note"},"text":{"type":"string","description":"Content of the note"},"position":{"type":"object","description":"Position of the note in the flow editor","properties":{"x":{"type":"number","description":"X coordinate"},"y":{"type":"number","description":"Y coordinate"}},"required":["x","y"]},"size":{"type":"object","description":"Size of the note in the flow editor","properties":{"width":{"type":"number","description":"Width in pixels"},"height":{"type":"number","description":"Height in pixels"}},"required":["width","height"]},"color":{"type":"string","description":"Color of the note, one of: yellow, blue, green, purple, pink, orange, red, cyan, lime, gray. Any other value renders unstyled."},"type":{"type":"string","enum":["free","group"],"description":"Type of note - 'free' for standalone notes. 'group' notes are deprecated; segment a flow with FlowValue.groups instead."},"locked":{"type":"boolean","default":false,"description":"Whether the note is locked and cannot be edited or moved"},"contained_node_ids":{"type":"array","items":{"type":"string"},"description":"For group notes, the IDs of nodes contained within this group"}},"required":["id","text","color","type"]},"FlowGroup":{"type":"object","description":"A semantic group of flow modules for organizational purposes. Does not affect execution \\u2014 modules remain in their original position in the flow. Groups provide naming and collapsibility in the editor. Members are computed dynamically from all nodes on paths between start_id and end_id.","properties":{"summary":{"type":"string","description":"Display name for this group"},"note":{"type":"string","description":"Markdown note shown below the group header"},"autocollapse":{"type":"boolean","default":false,"description":"If true, this group is collapsed by default in the flow editor. UI hint only."},"start_id":{"type":"string","description":"ID of the first flow module in this group (topological entry point)"},"end_id":{"type":"string","description":"ID of the last flow module in this group (topological exit point)"},"color":{"type":"string","description":"Color for the group in the flow editor, one of: yellow, blue, green, purple, pink, orange, red, cyan, lime, gray. Omit it to let the editor pick one."}},"required":["start_id","end_id"]},"RetryIf":{"type":"object","description":"Conditional retry based on error or result","properties":{"expr":{"type":"string","description":"JavaScript expression that returns true to retry. Has access to 'result' and 'error' variables"}},"required":["expr"]},"StopAfterIf":{"type":"object","description":"Early termination condition for a module","properties":{"skip_if_stopped":{"type":"boolean","description":"If true, following steps are skipped when this condition triggers"},"expr":{"type":"string","description":"JavaScript expression evaluated after the module runs. Can use 'result' (step's result) or 'flow_input'. Return true to stop"},"error_message":{"type":"string","nullable":true,"description":"Custom error message when stopping with an error. Mutually exclusive with skip_if_stopped. If set to a non-empty string, the flow stops with this error. If empty string, a default error message is used. If null or omitted, no error is raised."},"error_include_result":{"type":"boolean","description":"When stopping with an error (error_message set), embed the stopping step's own result inside the raised error object (as error.result) instead of discarding it. The top-level result stays { error }. Defaults to false."}},"required":["expr"]},"FlowModule":{"type":"object","description":"A single step in a flow. Can be a script, subflow, loop, or branch","properties":{"id":{"type":"string","description":"Unique identifier for this step. Used to reference results via 'results.step_id'. Must be a valid identifier (alphanumeric, underscore, hyphen)"},"value":{"$ref":"#/components/schemas/FlowModuleValue"},"stop_after_if":{"description":"Early termination condition evaluated after this step completes","$ref":"#/components/schemas/StopAfterIf"},"stop_after_all_iters_if":{"description":"For loops only - early termination condition evaluated after all iterations complete","$ref":"#/components/schemas/StopAfterIf"},"skip_if":{"type":"object","description":"Conditionally skip this step based on previous results or flow inputs","properties":{"expr":{"type":"string","description":"JavaScript expression that returns true to skip. Can use 'flow_input' or 'results.<step_id>'"}},"required":["expr"]},"sleep":{"description":"Delay before executing this step (in seconds or as expression)","$ref":"#/components/schemas/InputTransform"},"cache_ttl":{"type":"number","description":"Cache duration in seconds for this step's results"},"cache_ignore_s3_path":{"type":"boolean"},"timeout":{"description":"Maximum execution time in seconds (static value or expression)","$ref":"#/components/schemas/InputTransform"},"delete_after_secs":{"type":"integer","description":"If set, delete the step's args, result and logs after this many seconds following job completion"},"summary":{"type":"string","description":"Short description of what this step does"},"mock":{"type":"object","description":"Mock configuration for testing without executing the actual step","properties":{"enabled":{"type":"boolean","description":"If true, return mock value instead of executing"},"return_value":{"description":"Value to return when mocked"}}},"suspend":{"type":"object","description":"Configuration for approval/resume steps that wait for user input","properties":{"required_events":{"type":"integer","description":"Number of approvals required before continuing"},"timeout":{"type":"integer","description":"Timeout in seconds before auto-continuing or canceling"},"resume_form":{"type":"object","description":"Form schema for collecting input when resuming","properties":{"schema":{"type":"object","description":"JSON Schema for the resume form"}}},"user_auth_required":{"type":"boolean","description":"If true, only authenticated users can approve"},"user_groups_required":{"description":"Expression or list of groups that can approve","$ref":"#/components/schemas/InputTransform"},"self_approval_disabled":{"type":"boolean","description":"If true, the user who started the flow cannot approve"},"hide_cancel":{"type":"boolean","description":"If true, hide the cancel button on the approval form"},"continue_on_disapprove_timeout":{"type":"boolean","description":"If true, continue flow on timeout instead of canceling"},"skin":{"type":"string","enum":["detailed","minimal"],"description":"How the approval request is presented, on the approval page and in Slack/Teams approval messages. 'detailed' (used when unset) shows the flow details (arguments, graph, approvers); 'minimal' shows only the request: the step description, form and approve/reject actions"}}},"priority":{"type":"number","description":"Execution priority for this step (higher numbers run first)"},"continue_on_error":{"type":"boolean","description":"If true, flow continues even if this step fails"},"job_token_scopes":{"type":"array","nullable":true,"items":{"type":"string"},"description":"Scopes the token of this step's jobs is restricted to (domain:action[:resource], e.g. oidc:write), on top of the flow's own restriction: a step can only narrow it. Applies to everything the step runs (loop and branch bodies, AI agent tools)."},"retry":{"description":"Retry configuration if this step fails","$ref":"#/components/schemas/Retry"},"debouncing":{"description":"Debounce configuration for this step (EE only)","type":"object","properties":{"debounce_delay_s":{"type":"integer","description":"Delay in seconds to debounce this step's executions across flow runs"},"debounce_key":{"type":"string","description":"Expression to group debounced executions. Supports $workspace and $args[name]. Default: $workspace/flow/<flow_path>-<step_id>"},"debounce_args_to_accumulate":{"type":"array","description":"Array-type arguments to accumulate across debounced executions","items":{"type":"string"}},"max_total_debouncing_time":{"type":"integer","description":"Maximum total time in seconds before forced execution"},"max_total_debounces_amount":{"type":"integer","description":"Maximum number of debounces before forced execution"}}}},"required":["value","id"]},"InputTransform":{"description":"Maps input parameters for a step. Can be a static value or a JavaScript expression that references previous results or flow inputs","oneOf":[{"$ref":"#/components/schemas/StaticTransform"},{"$ref":"#/components/schemas/JavascriptTransform"},{"$ref":"#/components/schemas/AiTransform"}],"discriminator":{"propertyName":"type","mapping":{"static":"#/components/schemas/StaticTransform","javascript":"#/components/schemas/JavascriptTransform","ai":"#/components/schemas/AiTransform"}}},"StaticTransform":{"type":"object","description":"Static value passed directly to the step. Use for hardcoded values or resource references like '$res:path/to/resource'","properties":{"value":{"description":"The static value. For resources, use format '$res:path/to/resource'"},"type":{"type":"string","enum":["static"]}},"required":["type"]},"JavascriptTransform":{"type":"object","description":"JavaScript expression evaluated at runtime. Can reference previous step results via 'results.step_id' or flow inputs via 'flow_input.property'. Inside for loops, use 'flow_input.iter.value' for the current iteration value (in while loops it equals 'flow_input.iter.index')","properties":{"expr":{"type":"string","description":"JavaScript expression returning the value. Available variables - results (object with all previous step results), flow_input (flow inputs), flow_input.iter (in loops)"},"type":{"type":"string","enum":["javascript"]}},"required":["expr","type"]},"AiTransform":{"type":"object","description":"Value resolved by the AI runtime for this input. The AI engine decides how to satisfy the parameter.","properties":{"type":{"type":"string","enum":["ai"]}},"required":["type"]},"AIProviderKind":{"type":"string","description":"Supported AI provider types","enum":["openai","azure_openai","azure_foundry","anthropic","mistral","deepseek","googleai","groq","openrouter","togetherai","customai","aws_bedrock","typesafe","cloudflare"]},"ProviderConfig":{"type":"object","description":"Complete AI provider configuration with resource reference and model selection","properties":{"kind":{"$ref":"#/components/schemas/AIProviderKind"},"resource":{"type":"string","description":"Resource reference in format '$res:{resource_path}' pointing to provider credentials"},"model":{"type":"string","description":"Model identifier (e.g., 'gpt-4', 'claude-3-opus-20240229', 'gemini-pro')"},"reasoning_effort":{"type":"string","description":"Provider-native reasoning effort token (e.g. 'low', 'high', 'none') for models that support extended thinking. Optional; unset leaves the provider default."}},"required":["kind","resource","model"]},"StaticProviderTransform":{"type":"object","description":"Static provider configuration passed directly to the AI agent","properties":{"value":{"$ref":"#/components/schemas/ProviderConfig"},"type":{"type":"string","enum":["static"]}},"required":["type","value"]},"ProviderTransform":{"description":"Provider configuration - can be static (ProviderConfig), JavaScript expression, or AI-determined","oneOf":[{"$ref":"#/components/schemas/StaticProviderTransform"},{"$ref":"#/components/schemas/JavascriptTransform"},{"$ref":"#/components/schemas/AiTransform"}],"discriminator":{"propertyName":"type","mapping":{"static":"#/components/schemas/StaticProviderTransform","javascript":"#/components/schemas/JavascriptTransform","ai":"#/components/schemas/AiTransform"}}},"MemoryOff":{"type":"object","description":"No conversation memory/context","properties":{"kind":{"type":"string","enum":["off"]}},"required":["kind"]},"MemoryWindow":{"type":"object","description":"Keeps the most recent messages of the memory named by the run's memory id (or the step's\\n\`memory_id\`). Without a memory id the agent runs without memory.\\n","properties":{"kind":{"type":"string","enum":["window"]},"context_length":{"type":"integer","description":"Number of most recent messages to load and store. 0 turns memory off."}},"required":["kind","context_length"]},"MemoryAuto":{"type":"object","deprecated":true,"description":"Deprecated, still read as it was written: the run's memory id, else the \`memory_id\` here.\\nThe step's own \`memory_id\` is not read while this kind is set; switch the kind to \`window\`\\nto use it. Without a \`context_length\`, or with 0, it is \`off\` and reads \`previous_messages\`.\\n","properties":{"kind":{"type":"string","enum":["auto"]},"context_length":{"type":"integer","description":"Maximum number of messages to retain in context"},"memory_id":{"type":"string","description":"Identifier for persistent memory across agent invocations"}},"required":["kind"]},"MemoryCompaction":{"type":"object","description":"Keeps the whole memory named by the run's memory id (or the step's \`memory_id\`), replacing\\nits older part with a summary as the conversation approaches the model's context window.\\nWithout a memory id the agent runs without memory, and compaction bounds the run's own loop.\\n","properties":{"kind":{"type":"string","enum":["compaction"]},"context_window":{"type":"integer","description":"Overrides the context window looked up from the model, in tokens. Only a model\\nWindmill does not know needs one; those fall back to 128000.\\n"}},"required":["kind"]},"MemoryMessage":{"type":"object","description":"A single message in conversation history","properties":{"role":{"type":"string","enum":["user","assistant","system"]},"content":{"type":"string"}},"required":["role","content"]},"MemoryManual":{"type":"object","deprecated":true,"description":"Deprecated, still read as it was written. Move the step to \`off\` with \`previous_messages\` instead.","properties":{"kind":{"type":"string","enum":["manual"]},"messages":{"type":"array","items":{"$ref":"#/components/schemas/MemoryMessage"}}},"required":["kind","messages"]},"MemoryConfig":{"description":"Managed memory, stored by Windmill and replayed with each request. The memory is named by a memory id, see \`memory_id\`. While it is off, a step can supply its history in \`previous_messages\`.","oneOf":[{"$ref":"#/components/schemas/MemoryOff"},{"$ref":"#/components/schemas/MemoryWindow"},{"$ref":"#/components/schemas/MemoryCompaction"},{"$ref":"#/components/schemas/MemoryAuto"},{"$ref":"#/components/schemas/MemoryManual"}],"discriminator":{"propertyName":"kind","mapping":{"off":"#/components/schemas/MemoryOff","window":"#/components/schemas/MemoryWindow","compaction":"#/components/schemas/MemoryCompaction","auto":"#/components/schemas/MemoryAuto","manual":"#/components/schemas/MemoryManual"}}},"StaticMemoryTransform":{"type":"object","description":"Static memory configuration passed directly to the AI agent","properties":{"value":{"$ref":"#/components/schemas/MemoryConfig"},"type":{"type":"string","enum":["static"]}},"required":["type","value"]},"MemoryTransform":{"description":"Memory configuration - can be static (MemoryConfig), JavaScript expression, or AI-determined","oneOf":[{"$ref":"#/components/schemas/StaticMemoryTransform"},{"$ref":"#/components/schemas/JavascriptTransform"},{"$ref":"#/components/schemas/AiTransform"}],"discriminator":{"propertyName":"type","mapping":{"static":"#/components/schemas/StaticMemoryTransform","javascript":"#/components/schemas/JavascriptTransform","ai":"#/components/schemas/AiTransform"}}},"FlowModuleValue":{"description":"The actual implementation of a flow step. Can be a script (inline or referenced), subflow, loop, branch, or special module type","oneOf":[{"$ref":"#/components/schemas/RawScript"},{"$ref":"#/components/schemas/PathScript"},{"$ref":"#/components/schemas/PathFlow"},{"$ref":"#/components/schemas/ForloopFlow"},{"$ref":"#/components/schemas/WhileloopFlow"},{"$ref":"#/components/schemas/BranchOne"},{"$ref":"#/components/schemas/BranchAll"},{"$ref":"#/components/schemas/Identity"},{"$ref":"#/components/schemas/AiAgent"},{"$ref":"#/components/schemas/AiDecision"}],"discriminator":{"propertyName":"type","mapping":{"rawscript":"#/components/schemas/RawScript","script":"#/components/schemas/PathScript","flow":"#/components/schemas/PathFlow","forloopflow":"#/components/schemas/ForloopFlow","whileloopflow":"#/components/schemas/WhileloopFlow","branchone":"#/components/schemas/BranchOne","branchall":"#/components/schemas/BranchAll","identity":"#/components/schemas/Identity","aiagent":"#/components/schemas/AiAgent","aidecision":"#/components/schemas/AiDecision"}}},"RawScript":{"type":"object","description":"Inline script with code defined directly in the flow. Use 'bun' as default language if unspecified. The script receives arguments from input_transforms","properties":{"input_transforms":{"type":"object","description":"Map of parameter names to their values (static or JavaScript expressions). These become the script's input arguments","additionalProperties":{"$ref":"#/components/schemas/InputTransform"}},"content":{"type":"string","description":"The script source code. Should export a 'main' function"},"language":{"type":"string","description":"Programming language for this script","enum":["deno","bun","bunnative","python3","go","bash","powershell","postgresql","mysql","bigquery","snowflake","mssql","oracledb","graphql","nativets","php","rust","ansible","csharp","nu","java","ruby","rlang","duckdb"]},"path":{"type":"string","description":"Optional path for saving this script"},"lock":{"type":"string","description":"Lock file content for dependencies"},"type":{"type":"string","enum":["rawscript"]},"tag":{"type":"string","description":"Worker group tag for execution routing"},"concurrent_limit":{"type":"number","description":"Maximum concurrent executions of this script"},"concurrency_time_window_s":{"type":"number","description":"Time window for concurrent_limit"},"custom_concurrency_key":{"type":"string","description":"Custom key for grouping concurrent executions"},"is_trigger":{"type":"boolean","description":"If true, this script is a trigger that can start the flow"},"assets":{"type":"array","description":"External resources this script accesses (S3 objects, resources, etc.)","items":{"type":"object","required":["path","kind"],"properties":{"path":{"type":"string","description":"Path to the asset"},"kind":{"type":"string","description":"Type of asset","enum":["s3object","resource","ducklake","datatable","volume","dbt"]},"access_type":{"type":"string","nullable":true,"description":"Access level for this asset","enum":["r","w","rw"]},"alt_access_type":{"type":"string","nullable":true,"description":"Alternative access level","enum":["r","w","rw"]}}}}},"required":["type","content","language","input_transforms"]},"PathScript":{"type":"object","description":"Reference to an existing script by path. Use this when calling a previously saved script instead of writing inline code","properties":{"input_transforms":{"type":"object","description":"Map of parameter names to their values (static or JavaScript expressions). These become the script's input arguments","additionalProperties":{"$ref":"#/components/schemas/InputTransform"}},"path":{"type":"string","description":"Path to the script in the workspace (e.g., 'f/scripts/send_email')"},"hash":{"type":"string","description":"Optional specific version hash of the script to use"},"type":{"type":"string","enum":["script"]},"tag_override":{"type":"string","description":"Override the script's default worker group tag"},"is_trigger":{"type":"boolean","description":"If true, this script is a trigger that can start the flow"}},"required":["type","path","input_transforms"]},"PathFlow":{"type":"object","description":"Reference to an existing flow by path. Use this to call another flow as a subflow","properties":{"input_transforms":{"type":"object","description":"Map of parameter names to their values (static or JavaScript expressions). These become the subflow's input arguments","additionalProperties":{"$ref":"#/components/schemas/InputTransform"}},"path":{"type":"string","description":"Path to the flow in the workspace (e.g., 'f/flows/process_user')"},"type":{"type":"string","enum":["flow"]}},"required":["type","path","input_transforms"]},"ForloopFlow":{"type":"object","description":"Executes nested modules in a loop over an iterator. Inside the loop, use 'flow_input.iter.value' to access the current iteration value, and 'flow_input.iter.index' for the index. Supports parallel execution for better performance on I/O-bound operations","properties":{"modules":{"type":"array","description":"Steps to execute for each iteration. These can reference the iteration value via 'flow_input.iter.value'","items":{"$ref":"#/components/schemas/FlowModule"}},"iterator":{"description":"JavaScript expression that returns an array to iterate over. Can reference 'results.step_id' or 'flow_input'","$ref":"#/components/schemas/InputTransform"},"skip_failures":{"type":"boolean","description":"If true, iteration failures don't stop the loop. Failed iterations return null"},"type":{"type":"string","enum":["forloopflow"]},"parallel":{"type":"boolean","description":"If true, iterations run concurrently (faster for I/O-bound operations). Use with parallelism to control concurrency"},"parallelism":{"description":"Maximum number of concurrent iterations when parallel=true. Limits resource usage. Can be static number or expression","$ref":"#/components/schemas/InputTransform"},"squash":{"type":"boolean"}},"required":["modules","iterator","skip_failures","type"]},"WhileloopFlow":{"type":"object","description":"Executes nested modules repeatedly until stopped. The implicit iterator is the iteration counter, so 'flow_input.iter.value' equals 'flow_input.iter.index' (0, 1, 2, ...) and never carries state. To carry state across iterations, a step reads its own previous-iteration result via 'results.<its_own_id>' with a first-iteration fallback - the loop's stop_after_if must then be on that inner step (a plain single-step body with stop_after_if on the loop module does not resolve 'results' across iterations and never terminates); plain counters can instead be derived from 'flow_input.iter.index', which works in every configuration. stop_after_if is evaluated after each iteration - on the loop module 'result' is the last iteration's result","properties":{"modules":{"type":"array","description":"Steps to execute in each iteration","items":{"$ref":"#/components/schemas/FlowModule"}},"skip_failures":{"type":"boolean","description":"If true, iteration failures don't stop the loop. Failed iterations return null"},"type":{"type":"string","enum":["whileloopflow"]},"parallel":{"type":"boolean","description":"If true, iterations run concurrently (use with caution in while loops)"},"parallelism":{"description":"Maximum number of concurrent iterations when parallel=true","$ref":"#/components/schemas/InputTransform"},"squash":{"type":"boolean"}},"required":["modules","skip_failures","type"]},"BranchOne":{"type":"object","description":"Conditional branching where only the first matching branch executes. Branches are evaluated in order, and the first one with a true expression runs. If no branches match, the default branch executes","properties":{"branches":{"type":"array","description":"Array of branches to evaluate in order. The first branch with expr evaluating to true executes","items":{"type":"object","properties":{"summary":{"type":"string","description":"Short description of this branch condition"},"expr":{"type":"string","description":"JavaScript expression that returns boolean. Can use 'results.step_id' or 'flow_input'. First true expr wins"},"modules":{"type":"array","description":"Steps to execute if this branch's expr is true","items":{"$ref":"#/components/schemas/FlowModule"}}},"required":["modules","expr"]}},"default":{"type":"array","description":"Steps to execute if no branch expressions match","items":{"$ref":"#/components/schemas/FlowModule"}},"type":{"type":"string","enum":["branchone"]}},"required":["branches","default","type"]},"BranchAll":{"type":"object","description":"Parallel branching where all branches execute simultaneously. Unlike BranchOne, all branches run regardless of conditions. Useful for executing independent tasks concurrently","properties":{"branches":{"type":"array","description":"Array of branches that all execute (either in parallel or sequentially)","items":{"type":"object","properties":{"summary":{"type":"string","description":"Short description of this branch's purpose"},"skip_failure":{"type":"boolean","description":"If true, failure in this branch doesn't fail the entire flow"},"modules":{"type":"array","description":"Steps to execute in this branch","items":{"$ref":"#/components/schemas/FlowModule"}}},"required":["modules"]}},"type":{"type":"string","enum":["branchall"]},"parallel":{"type":"boolean","description":"If true, all branches execute concurrently. If false, they execute sequentially"}},"required":["branches","type"]},"AgentTool":{"type":"object","description":"A tool available to an AI agent. Can be a flow module or an external MCP (Model Context Protocol) tool","properties":{"id":{"type":"string","description":"Unique identifier for this tool. Cannot contain spaces - use underscores instead (e.g., 'get_user_data' not 'get user data')"},"summary":{"type":"string","description":"The name the AI agent calls this tool by, not a human label. On a flowmodule tool it must match ^[a-zA-Z0-9_]+$ - letters, numbers and underscores only (e.g. 'search_documentation', not 'Search documentation') - and always be set; on an mcp, websearch or question tool it is a plain label. Put the human-readable explanation in 'description'."},"description":{"type":"string","description":"Free-text description of the tool given to the AI to decide when and how to call it. Overrides the description auto-derived from the underlying script."},"job_token_scopes":{"type":"array","nullable":true,"items":{"type":"string"},"description":"Scopes the token of this tool's jobs is restricted to, on top of the agent step's own restriction: a tool can only narrow it."},"requires_approval":{"type":"boolean","description":"Flowmodule and mcp tools only. Each call waits for a person to approve or reject it from the flow's run page or chat, without the agent holding a worker. Calls in the same turn that do not require approval run right away. A rejected call, or one nobody answers within 30 minutes, is reported to the AI as not run."},"value":{"$ref":"#/components/schemas/ToolValue"}},"required":["id","value"]},"ToolValue":{"description":"The implementation of a tool. Can be a flow module (script/flow) or an MCP tool reference","oneOf":[{"$ref":"#/components/schemas/FlowModuleTool"},{"$ref":"#/components/schemas/McpToolValue"},{"$ref":"#/components/schemas/WebsearchToolValue"},{"$ref":"#/components/schemas/QuestionToolValue"}],"discriminator":{"propertyName":"tool_type","mapping":{"flowmodule":"#/components/schemas/FlowModuleTool","mcp":"#/components/schemas/McpToolValue","websearch":"#/components/schemas/WebsearchToolValue","question":"#/components/schemas/QuestionToolValue"}}},"FlowModuleTool":{"description":"A tool implemented as a flow module (script, flow, etc.). The AI can call this like any other flow module","allOf":[{"type":"object","properties":{"tool_type":{"type":"string","enum":["flowmodule"]}},"required":["tool_type"]},{"$ref":"#/components/schemas/FlowModuleValue"}]},"WebsearchToolValue":{"type":"object","description":"A tool implemented as a websearch tool. The AI can call this like any other websearch tool","properties":{"tool_type":{"type":"string","enum":["websearch"]}},"required":["tool_type"]},"QuestionToolValue":{"type":"object","description":"Built-in tool the AI calls as ask_question: the agent stops, releasing its worker, until someone answers from the flow's run page or chat or the question times out, then resumes with the answer as the tool result.","properties":{"tool_type":{"type":"string","enum":["question"]},"timeout":{"type":"integer","description":"Seconds to wait for an answer before the question is reported to the AI as timed out. Defaults to 1800."}},"required":["tool_type"]},"McpToolValue":{"type":"object","description":"Reference to an external MCP (Model Context Protocol) tool. The AI can call tools from MCP servers","properties":{"tool_type":{"type":"string","enum":["mcp"]},"resource_path":{"type":"string","description":"Path to the MCP resource/server configuration"},"include_tools":{"type":"array","description":"Whitelist of specific tools to include from this MCP server","items":{"type":"string"}},"exclude_tools":{"type":"array","description":"Blacklist of tools to exclude from this MCP server","items":{"type":"string"}}},"required":["tool_type","resource_path"]},"AiAgent":{"type":"object","description":"AI agent step that can use tools to accomplish tasks. The agent receives inputs and can call any of its configured tools to complete the task","properties":{"input_transforms":{"type":"object","description":"Input parameters for the AI agent mapped to their values","properties":{"provider":{"$ref":"#/components/schemas/ProviderTransform"},"output_type":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"Output format type.\\nValid values: 'text' (default) - plain text response, 'image' - image generation\\n"},"user_message":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"The user's prompt/message to the AI agent. Supports variable interpolation with\\nflow.input syntax. Required unless memory is off and \`previous_messages\` supplies\\nthe prompt; image output always needs it.\\n"},"system_prompt":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"System instructions that guide the AI's behavior, persona, and response style. Optional."},"streaming":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"Boolean. If true, stream the AI response incrementally.\\nStreaming events include: token_delta, reasoning_token_delta, tool_call, tool_call_arguments, tool_execution, tool_result\\n"},"memory":{"$ref":"#/components/schemas/MemoryTransform"},"memory_id":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"String. Names the memory this step reads and writes, overriding the memory id the run\\nwas started with (the chat conversation, an app chat session or the \`memory_id\` run\\nparameter). Leave unset to use the run's memory id. A fixed value shares one memory\\nacross every run; an expression such as \`flow_input.customer_id\` keeps one memory per\\nkey. When it evaluates to an empty value the agent runs without memory. Read only\\nwhile \`memory\` is \`window\` or \`compaction\`: it is ignored when memory is off, and an\\nolder \`auto\` or \`manual\` memory reads neither history input.\\n"},"previous_messages":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"Array of MemoryMessage. History supplied by the flow, sent between the system prompt\\nand the user message. Read only while \`memory\` is off or absent: managed memory\\nignores it, and an older \`auto\` or \`manual\` memory reads neither history input.\\n"},"output_schema":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"JSON Schema object defining structured output format. Used when you need the AI to return data in a specific shape.\\nSupports standard JSON Schema properties: type, properties, required, items, enum, pattern, minLength, maxLength, minimum, maximum, etc.\\nExample: { type: 'object', properties: { name: { type: 'string' }, age: { type: 'integer' } }, required: ['name'] }\\n"},"user_attachments":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"Array of file references (images or PDFs) for the AI agent.\\nFormat: Array<{ bucket: string, key: string }> - S3 object references\\nExample: [{ bucket: 'my-bucket', key: 'documents/report.pdf' }]\\n"},"enabled_tools":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"Array of strings naming which of the tools configured in \`tools\` the agent may call\\nthis run. Leaving it unset carries every one of them; an empty array carries none.\\nA tool is named as the model is shown it. An entry the model is shown nothing of is\\nnamed by what identifies it instead: an MCP server by its resource path, carrying\\nevery tool it exposes (which of them stays that entry's include_tools/exclude_tools),\\nand a websearch entry by the reserved name '__wm_web_search', whatever summary it carries\\n(no tool may take that name).\\nExample: ['get_user', 'u/admin/github_mcp', '__wm_web_search']\\n"},"max_completion_tokens":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"Integer. Maximum number of tokens the AI will generate in its response.\\nRange: 1 to 4,294,967,295. Typical values: 256-4096 for most use cases.\\n"},"temperature":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"Float. Controls randomness/creativity of responses.\\nRange: 0.0 to 2.0 (provider-dependent)\\n- 0.0 = deterministic, focused responses\\n- 0.7 = balanced (common default)\\n- 1.0+ = more creative/random\\n"},"max_iterations":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"Number. Limits how many times the agent can loop through reasoning and tool use.\\nRange: 1-1000.\\n"},"model":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"String. Only on a step linked to a saved agent (see \`agent\`): replaces the model\\nsaved on the agent for this step's runs, on the agent's own provider resource. An\\nempty value keeps the saved model. Set it to an expression such as\\n\`flow_input.model\` to choose the model per run.\\n"},"reasoning_effort":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"String. Only on a step linked to a saved agent (see \`agent\`): replaces the reasoning\\neffort saved on the agent for this step's runs, as a provider-native token (e.g.\\n'low', 'high', 'none'). An empty value sends no effort, so the model runs at its\\ndefault. Leave the input out to keep the saved effort, which holds only while the\\nstep runs the saved model. A step that is not linked sets both inside \`provider\`.\\n"}}},"tools":{"type":"array","description":"Array of tools the agent can use. The agent decides which tools to call based on the task","items":{"$ref":"#/components/schemas/AgentTool"}},"type":{"type":"string","enum":["aiagent"]},"tag":{"type":"string","description":"Worker group tag for execution routing. If not set, the AI agent step runs on the flow's tag (default \`flow\`)"},"omit_output_from_conversation":{"type":"boolean","default":false,"description":"If true, this AI agent step does not persist its assistant or tool messages to the flow conversation when chat mode is enabled."},"agent":{"type":"string","description":"Path of a reusable \`ai_agent\` resource (hybrid linking). When set, the agent brain\\nconfig (provider/model/system prompt/etc.) and tool set are resolved at runtime from\\nthat resource; the module's input_transforms then only carry the flow-local inputs\\n(user_message, user_attachments, enabled_tools and the history inputs memory_id and previous_messages)\\nand, optionally, the \`model\` and \`reasoning_effort\` overrides of what the agent saved.\\n"},"tool_inputs":{"type":"object","description":"Host-local wiring for an agent's tool inputs, keyed by tool id then input key. Binds the\\nreferenced agent's tools to this flow's context (flow_input/results) without mutating the\\nshared resource; overlaid onto the tools' input_transforms at runtime \\u2014 including when\\n\`agent\` is unset, since a step forked for editing keeps these overrides until it is saved\\nback or unlinked.\\n","additionalProperties":{"type":"object","additionalProperties":{"$ref":"#/components/schemas/InputTransform"}}},"parallel":{"type":"boolean","description":"If true, the agent can execute multiple tool calls in parallel"}},"required":["type","input_transforms"]},"AiDecision":{"type":"object","description":"AI decision step: one call to a decision model (TypeSafe's Jev, Cloudflare's\\nJev-compatible Clef, or OpenAI's Decisions API) that answers typed questions about a\\nstate with calibrated probabilities, instead of generating text.\\nPrefer it over an AI agent to classify, route, score or check something: it is fast,\\ncheap and its answers are structured. Its result is { output: { <question name>: answer },\\nmodel, usage }, so a later step reads e.g. results.<id>.output.intent.choice. To route on\\nthe answers, follow it with a branchone whose branch exprs read\\nresults.<id>.output.<question>.choice. Usable as an AI agent tool, where the calling agent\\nsupplies the state.\\n","properties":{"input_transforms":{"type":"object","description":"Input parameters for the decision mapped to their values","properties":{"provider":{"$ref":"#/components/schemas/ProviderTransform"},"state":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"What the questions are asked about: a string, an object or an array of strings.\\nAn object with descriptive keys holding only what the questions need works best.\\nExample: { message: flow_input.message, plan: results.a.plan }\\n"},"questions":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"Object mapping each question name to { type, instructions, criteria }, where type is:\\n- 'choice': criteria maps each option to its description (up to 255); the answer\\n has choice, probabilities and confidence\\n- 'score': criteria is an ordered array of 2 to 10 level descriptions; the answer\\n has score, legend, probabilities and confidence\\n- 'noul': yes/no, criteria optionally { true, false } descriptions; the answer has\\n noul, the probability of yes (0 to 1)\\nExample: { intent: { type: 'choice', instructions: 'What does the customer want?',\\ncriteria: { refund: 'Money back', bug: 'Something is broken' } } }\\n"}},"required":["provider","state","questions"]},"type":{"type":"string","enum":["aidecision"]},"tag":{"type":"string","description":"Worker group tag for execution routing. If not set, the step runs on the flow's tag (default \`flow\`)"}},"required":["type","input_transforms"]},"Identity":{"type":"object","description":"Pass-through module that returns its input unchanged. Useful for flow structure or as a placeholder","properties":{"type":{"type":"string","enum":["identity"]},"flow":{"type":"boolean","description":"If true, marks this as a flow identity (special handling)"}},"required":["type"]},"FlowStatus":{"type":"object","properties":{"step":{"type":"integer"},"modules":{"type":"array","items":{"$ref":"#/components/schemas/FlowStatusModule"}},"user_states":{"additionalProperties":true},"preprocessor_module":{"allOf":[{"$ref":"#/components/schemas/FlowStatusModule"}]},"failure_module":{"allOf":[{"$ref":"#/components/schemas/FlowStatusModule"},{"type":"object","properties":{"parent_module":{"type":"string"}}}]},"retry":{"type":"object","properties":{"fail_count":{"type":"integer"},"failed_jobs":{"type":"array","items":{"type":"string","format":"uuid"}}}}},"required":["step","modules","failure_module"]},"FlowStatusModule":{"type":"object","properties":{"type":{"type":"string","enum":["WaitingForPriorSteps","WaitingForEvents","WaitingForExecutor","InProgress","Success","Failure"]},"id":{"type":"string"},"job":{"type":"string","format":"uuid"},"count":{"type":"integer"},"progress":{"type":"integer"},"iterator":{"type":"object","properties":{"index":{"type":"integer"},"itered":{"type":"array","items":{}},"itered_len":{"type":"integer"},"args":{}}},"flow_jobs":{"type":"array","items":{"type":"string"}},"flow_jobs_success":{"type":"array","items":{"type":"boolean"}},"flow_jobs_duration":{"type":"object","properties":{"started_at":{"type":"array","items":{"type":"string"}},"duration_ms":{"type":"array","items":{"type":"integer"}}}},"branch_chosen":{"type":"object","properties":{"type":{"type":"string","enum":["branch","default"]},"branch":{"type":"integer"}},"required":["type"]},"branchall":{"type":"object","properties":{"branch":{"type":"integer"},"len":{"type":"integer"}},"required":["branch","len"]},"approvers":{"type":"array","items":{"type":"object","properties":{"resume_id":{"type":"integer"},"approver":{"type":"string"}},"required":["resume_id","approver"]}},"failed_retries":{"type":"array","items":{"type":"string","format":"uuid"}},"skipped":{"type":"boolean"},"agent_actions":{"type":"array","items":{"type":"object","oneOf":[{"type":"object","properties":{"job_id":{"type":"string","format":"uuid"},"function_name":{"type":"string"},"type":{"type":"string","enum":["tool_call"]},"module_id":{"type":"string"}},"required":["job_id","function_name","type","module_id"]},{"type":"object","properties":{"call_id":{"type":"string","format":"uuid"},"function_name":{"type":"string"},"resource_path":{"type":"string"},"type":{"type":"string","enum":["mcp_tool_call"]},"arguments":{"type":"object"}},"required":["call_id","function_name","resource_path","type"]},{"type":"object","properties":{"type":{"type":"string","enum":["web_search"]}},"required":["type"]},{"type":"object","properties":{"type":{"type":"string","enum":["approval"]},"call_id":{"type":"string"},"calls":{"type":"array","items":{"type":"object","properties":{"function_name":{"type":"string"},"arguments":{}},"required":["function_name","arguments"]}},"expires_at":{"type":"string","format":"date-time"}},"required":["type","call_id","calls","expires_at"]},{"type":"object","properties":{"type":{"type":"string","enum":["question"]},"call_id":{"type":"string"},"question":{"type":"string"},"choices":{"type":"array","items":{"type":"string"},"description":"answers the model proposes; a free-text answer is always possible"},"multi_select":{"type":"boolean","description":"whether several choices can be picked together"},"expires_at":{"type":"string","format":"date-time"}},"required":["type","call_id","question","expires_at"]},{"type":"object","properties":{"type":{"type":"string","enum":["message"]}},"required":["content","type"]}]}},"agent_actions_success":{"type":"array","items":{"type":"boolean"}}},"required":["type"]}}`; export const CLI_COMMANDS = `# Windmill CLI Commands diff --git a/system_prompts/auto-generated/skills/write-flow/SKILL.md b/system_prompts/auto-generated/skills/write-flow/SKILL.md index 906f416184..8308f33c6b 100644 --- a/system_prompts/auto-generated/skills/write-flow/SKILL.md +++ b/system_prompts/auto-generated/skills/write-flow/SKILL.md @@ -155,7 +155,10 @@ value: An `aiagent` module runs an LLM that can call tools. Each entry of `value.tools` is a module-shaped object with an extra `value.tool_type`: `flowmodule` for a script/flow tool, `mcp` for an MCP server -tool, `websearch` for web search. +tool, `websearch` for web search, `question` for a built-in `ask_question` tool (the agent stops, +without holding a worker, until someone answers from the run page or the chat; optional +`value.timeout` in seconds, default 1800). Set `requires_approval: true` on a `flowmodule` or `mcp` +tool to have a person approve or reject each of its calls before it runs. ```json { @@ -251,9 +254,9 @@ needs becomes unreachable. ### Tool Naming Rules -These rules cover `flowmodule` tools, the ones the agent calls by name. A `websearch` tool's -`summary` is a plain label (`Web Search`), and an `mcp` tool exposes the MCP server's own tool -names, so neither is name-checked at all — leave those summaries as they are. +These rules cover `flowmodule` tools, the ones the agent calls by name. A `websearch` or `question` +tool's `summary` is a plain label (`Web Search`), and an `mcp` tool exposes the MCP +server's own tool names, so none is name-checked at all — leave those summaries as they are. - A flowmodule tool's `summary` is the **name the agent calls it by**, not a human label. Put the human-readable explanation in `description` @@ -698,4 +701,4 @@ Reference a specific resource using `$res:` prefix: ## OpenFlow Schema -{"OpenFlow":{"type":"object","description":"Top-level flow definition containing metadata, configuration, and the flow structure","properties":{"summary":{"type":"string","description":"Short description of what this flow does"},"description":{"type":"string","description":"Detailed documentation for this flow"},"value":{"$ref":"#/components/schemas/FlowValue"},"schema":{"type":"object","description":"JSON Schema for flow inputs. Use this to define input parameters, their types, defaults, and validation. For resource inputs, set type to 'object' and format to 'resource-<type>' (e.g., 'resource-stripe')"},"on_behalf_of_email":{"type":"string","description":"Address of the account the flow runs on behalf of. Derived from on_behalf_of on read; accepted on write, where it is resolved to the account it names."},"on_behalf_of":{"type":"string","description":"The flow runs with the permissions of this identity: u/{username}, g/{group}, or a bare email when the username is itself email-shaped. The only stored half of the identity; on_behalf_of_email is derived from it. Omit it when writing and it is resolved from that address instead."}},"required":["summary","value"]},"FlowValue":{"type":"object","description":"The flow structure containing modules and optional preprocessor/failure handlers","properties":{"modules":{"type":"array","description":"Array of steps that execute in sequence. Each step can be a script, subflow, loop, or branch","items":{"$ref":"#/components/schemas/FlowModule"}},"failure_module":{"description":"Special module that executes when the flow fails. Receives error object with message, name, stack, and step_id. Must have id 'failure'. Only supports script/rawscript types","$ref":"#/components/schemas/FlowModule"},"preprocessor_module":{"description":"Special module that runs before the first step on external triggers. Must have id 'preprocessor'. Only supports script/rawscript types. Cannot reference other step results","$ref":"#/components/schemas/FlowModule"},"same_worker":{"type":"boolean","description":"If true, all steps run on the same worker for better performance"},"preserve_step_tags":{"type":"boolean","description":"If true and the flow runs on a custom worker tag, steps that declare their own non-empty tag run on it instead of inheriting the flow tag. Steps without their own tag still inherit the flow tag."},"concurrent_limit":{"type":"number","description":"Maximum number of concurrent executions of this flow"},"concurrency_key":{"type":"string","description":"Expression to group concurrent executions (e.g., by user ID)"},"concurrency_time_window_s":{"type":"number","description":"Time window in seconds for concurrent_limit"},"debounce_delay_s":{"type":"integer","description":"Delay in seconds to debounce flow executions"},"debounce_key":{"type":"string","description":"Expression to group debounced executions"},"debounce_args_to_accumulate":{"type":"array","description":"Arguments to accumulate across debounced executions","items":{"type":"string"}},"max_total_debouncing_time":{"type":"integer","description":"Maximum total time in seconds that a job can be debounced"},"max_total_debounces_amount":{"type":"integer","description":"Maximum number of times a job can be debounced"},"skip_expr":{"type":"string","description":"JavaScript expression to conditionally skip the entire flow"},"cache_ttl":{"type":"number","description":"Cache duration in seconds for flow results"},"cache_ignore_s3_path":{"type":"boolean"},"delete_after_secs":{"type":"integer","description":"If set, delete the flow job's args, result and logs after this many seconds following job completion"},"flow_env":{"type":"object","description":"Environment variables available to all steps. Values can be strings, JSON values, or special references: '$var:path' (workspace variable) or '$res:path' (resource).","additionalProperties":{}},"priority":{"type":"number","description":"Execution priority (higher numbers run first)"},"early_return":{"type":"string","description":"Id of the step whose result a sync webhook returns as soon as that step completes, while the rest of the flow keeps running. When the step does not run, or fails while the flow has a failure module, the flow's final result is returned instead."},"chat_input_enabled":{"type":"boolean","description":"Whether this flow accepts chat-style input"},"notes":{"type":"array","description":"Sticky notes attached to the flow","items":{"$ref":"#/components/schemas/FlowNote"}},"groups":{"type":"array","description":"Semantic groups of modules for organizational purposes","items":{"$ref":"#/components/schemas/FlowGroup"}}},"required":["modules"]},"Retry":{"type":"object","description":"Retry configuration for failed module executions","properties":{"constant":{"type":"object","description":"Retry with constant delay between attempts","properties":{"attempts":{"type":"integer","description":"Number of retry attempts"},"seconds":{"type":"integer","description":"Seconds to wait between retries"}}},"exponential":{"type":"object","description":"Retry with exponential backoff: the n-th retry waits multiplier \u00d7 seconds^n","properties":{"attempts":{"type":"integer","description":"Number of retry attempts"},"multiplier":{"type":"integer","description":"Multiplier for exponential backoff"},"seconds":{"type":"integer","minimum":1,"description":"Base of the exponential (seconds); the n-th retry waits multiplier \u00d7 seconds^n, where n counts constant retries too"},"random_factor":{"type":"integer","minimum":0,"maximum":100,"description":"Random jitter percentage (0-100) to avoid thundering herd"}}},"retry_if":{"$ref":"#/components/schemas/RetryIf"}}},"FlowNote":{"type":"object","description":"A sticky note attached to a flow for documentation and annotation","properties":{"id":{"type":"string","description":"Unique identifier for the note"},"text":{"type":"string","description":"Content of the note"},"position":{"type":"object","description":"Position of the note in the flow editor","properties":{"x":{"type":"number","description":"X coordinate"},"y":{"type":"number","description":"Y coordinate"}},"required":["x","y"]},"size":{"type":"object","description":"Size of the note in the flow editor","properties":{"width":{"type":"number","description":"Width in pixels"},"height":{"type":"number","description":"Height in pixels"}},"required":["width","height"]},"color":{"type":"string","description":"Color of the note, one of: yellow, blue, green, purple, pink, orange, red, cyan, lime, gray. Any other value renders unstyled."},"type":{"type":"string","enum":["free","group"],"description":"Type of note - 'free' for standalone notes. 'group' notes are deprecated; segment a flow with FlowValue.groups instead."},"locked":{"type":"boolean","default":false,"description":"Whether the note is locked and cannot be edited or moved"},"contained_node_ids":{"type":"array","items":{"type":"string"},"description":"For group notes, the IDs of nodes contained within this group"}},"required":["id","text","color","type"]},"FlowGroup":{"type":"object","description":"A semantic group of flow modules for organizational purposes. Does not affect execution \u2014 modules remain in their original position in the flow. Groups provide naming and collapsibility in the editor. Members are computed dynamically from all nodes on paths between start_id and end_id.","properties":{"summary":{"type":"string","description":"Display name for this group"},"note":{"type":"string","description":"Markdown note shown below the group header"},"autocollapse":{"type":"boolean","default":false,"description":"If true, this group is collapsed by default in the flow editor. UI hint only."},"start_id":{"type":"string","description":"ID of the first flow module in this group (topological entry point)"},"end_id":{"type":"string","description":"ID of the last flow module in this group (topological exit point)"},"color":{"type":"string","description":"Color for the group in the flow editor, one of: yellow, blue, green, purple, pink, orange, red, cyan, lime, gray. Omit it to let the editor pick one."}},"required":["start_id","end_id"]},"RetryIf":{"type":"object","description":"Conditional retry based on error or result","properties":{"expr":{"type":"string","description":"JavaScript expression that returns true to retry. Has access to 'result' and 'error' variables"}},"required":["expr"]},"StopAfterIf":{"type":"object","description":"Early termination condition for a module","properties":{"skip_if_stopped":{"type":"boolean","description":"If true, following steps are skipped when this condition triggers"},"expr":{"type":"string","description":"JavaScript expression evaluated after the module runs. Can use 'result' (step's result) or 'flow_input'. Return true to stop"},"error_message":{"type":"string","nullable":true,"description":"Custom error message when stopping with an error. Mutually exclusive with skip_if_stopped. If set to a non-empty string, the flow stops with this error. If empty string, a default error message is used. If null or omitted, no error is raised."},"error_include_result":{"type":"boolean","description":"When stopping with an error (error_message set), embed the stopping step's own result inside the raised error object (as error.result) instead of discarding it. The top-level result stays { error }. Defaults to false."}},"required":["expr"]},"FlowModule":{"type":"object","description":"A single step in a flow. Can be a script, subflow, loop, or branch","properties":{"id":{"type":"string","description":"Unique identifier for this step. Used to reference results via 'results.step_id'. Must be a valid identifier (alphanumeric, underscore, hyphen)"},"value":{"$ref":"#/components/schemas/FlowModuleValue"},"stop_after_if":{"description":"Early termination condition evaluated after this step completes","$ref":"#/components/schemas/StopAfterIf"},"stop_after_all_iters_if":{"description":"For loops only - early termination condition evaluated after all iterations complete","$ref":"#/components/schemas/StopAfterIf"},"skip_if":{"type":"object","description":"Conditionally skip this step based on previous results or flow inputs","properties":{"expr":{"type":"string","description":"JavaScript expression that returns true to skip. Can use 'flow_input' or 'results.<step_id>'"}},"required":["expr"]},"sleep":{"description":"Delay before executing this step (in seconds or as expression)","$ref":"#/components/schemas/InputTransform"},"cache_ttl":{"type":"number","description":"Cache duration in seconds for this step's results"},"cache_ignore_s3_path":{"type":"boolean"},"timeout":{"description":"Maximum execution time in seconds (static value or expression)","$ref":"#/components/schemas/InputTransform"},"delete_after_secs":{"type":"integer","description":"If set, delete the step's args, result and logs after this many seconds following job completion"},"summary":{"type":"string","description":"Short description of what this step does"},"mock":{"type":"object","description":"Mock configuration for testing without executing the actual step","properties":{"enabled":{"type":"boolean","description":"If true, return mock value instead of executing"},"return_value":{"description":"Value to return when mocked"}}},"suspend":{"type":"object","description":"Configuration for approval/resume steps that wait for user input","properties":{"required_events":{"type":"integer","description":"Number of approvals required before continuing"},"timeout":{"type":"integer","description":"Timeout in seconds before auto-continuing or canceling"},"resume_form":{"type":"object","description":"Form schema for collecting input when resuming","properties":{"schema":{"type":"object","description":"JSON Schema for the resume form"}}},"user_auth_required":{"type":"boolean","description":"If true, only authenticated users can approve"},"user_groups_required":{"description":"Expression or list of groups that can approve","$ref":"#/components/schemas/InputTransform"},"self_approval_disabled":{"type":"boolean","description":"If true, the user who started the flow cannot approve"},"hide_cancel":{"type":"boolean","description":"If true, hide the cancel button on the approval form"},"continue_on_disapprove_timeout":{"type":"boolean","description":"If true, continue flow on timeout instead of canceling"},"skin":{"type":"string","enum":["detailed","minimal"],"description":"How the approval request is presented, on the approval page and in Slack/Teams approval messages. 'detailed' (used when unset) shows the flow details (arguments, graph, approvers); 'minimal' shows only the request: the step description, form and approve/reject actions"}}},"priority":{"type":"number","description":"Execution priority for this step (higher numbers run first)"},"continue_on_error":{"type":"boolean","description":"If true, flow continues even if this step fails"},"job_token_scopes":{"type":"array","nullable":true,"items":{"type":"string"},"description":"Scopes the token of this step's jobs is restricted to (domain:action[:resource], e.g. oidc:write), on top of the flow's own restriction: a step can only narrow it. Applies to everything the step runs (loop and branch bodies, AI agent tools)."},"retry":{"description":"Retry configuration if this step fails","$ref":"#/components/schemas/Retry"},"debouncing":{"description":"Debounce configuration for this step (EE only)","type":"object","properties":{"debounce_delay_s":{"type":"integer","description":"Delay in seconds to debounce this step's executions across flow runs"},"debounce_key":{"type":"string","description":"Expression to group debounced executions. Supports $workspace and $args[name]. Default: $workspace/flow/<flow_path>-<step_id>"},"debounce_args_to_accumulate":{"type":"array","description":"Array-type arguments to accumulate across debounced executions","items":{"type":"string"}},"max_total_debouncing_time":{"type":"integer","description":"Maximum total time in seconds before forced execution"},"max_total_debounces_amount":{"type":"integer","description":"Maximum number of debounces before forced execution"}}}},"required":["value","id"]},"InputTransform":{"description":"Maps input parameters for a step. Can be a static value or a JavaScript expression that references previous results or flow inputs","oneOf":[{"$ref":"#/components/schemas/StaticTransform"},{"$ref":"#/components/schemas/JavascriptTransform"},{"$ref":"#/components/schemas/AiTransform"}],"discriminator":{"propertyName":"type","mapping":{"static":"#/components/schemas/StaticTransform","javascript":"#/components/schemas/JavascriptTransform","ai":"#/components/schemas/AiTransform"}}},"StaticTransform":{"type":"object","description":"Static value passed directly to the step. Use for hardcoded values or resource references like '$res:path/to/resource'","properties":{"value":{"description":"The static value. For resources, use format '$res:path/to/resource'"},"type":{"type":"string","enum":["static"]}},"required":["type"]},"JavascriptTransform":{"type":"object","description":"JavaScript expression evaluated at runtime. Can reference previous step results via 'results.step_id' or flow inputs via 'flow_input.property'. Inside for loops, use 'flow_input.iter.value' for the current iteration value (in while loops it equals 'flow_input.iter.index')","properties":{"expr":{"type":"string","description":"JavaScript expression returning the value. Available variables - results (object with all previous step results), flow_input (flow inputs), flow_input.iter (in loops)"},"type":{"type":"string","enum":["javascript"]}},"required":["expr","type"]},"AiTransform":{"type":"object","description":"Value resolved by the AI runtime for this input. The AI engine decides how to satisfy the parameter.","properties":{"type":{"type":"string","enum":["ai"]}},"required":["type"]},"AIProviderKind":{"type":"string","description":"Supported AI provider types","enum":["openai","azure_openai","azure_foundry","anthropic","mistral","deepseek","googleai","groq","openrouter","togetherai","customai","aws_bedrock","typesafe","cloudflare"]},"ProviderConfig":{"type":"object","description":"Complete AI provider configuration with resource reference and model selection","properties":{"kind":{"$ref":"#/components/schemas/AIProviderKind"},"resource":{"type":"string","description":"Resource reference in format '$res:{resource_path}' pointing to provider credentials"},"model":{"type":"string","description":"Model identifier (e.g., 'gpt-4', 'claude-3-opus-20240229', 'gemini-pro')"},"reasoning_effort":{"type":"string","description":"Provider-native reasoning effort token (e.g. 'low', 'high', 'none') for models that support extended thinking. Optional; unset leaves the provider default."}},"required":["kind","resource","model"]},"StaticProviderTransform":{"type":"object","description":"Static provider configuration passed directly to the AI agent","properties":{"value":{"$ref":"#/components/schemas/ProviderConfig"},"type":{"type":"string","enum":["static"]}},"required":["type","value"]},"ProviderTransform":{"description":"Provider configuration - can be static (ProviderConfig), JavaScript expression, or AI-determined","oneOf":[{"$ref":"#/components/schemas/StaticProviderTransform"},{"$ref":"#/components/schemas/JavascriptTransform"},{"$ref":"#/components/schemas/AiTransform"}],"discriminator":{"propertyName":"type","mapping":{"static":"#/components/schemas/StaticProviderTransform","javascript":"#/components/schemas/JavascriptTransform","ai":"#/components/schemas/AiTransform"}}},"MemoryOff":{"type":"object","description":"No conversation memory/context","properties":{"kind":{"type":"string","enum":["off"]}},"required":["kind"]},"MemoryWindow":{"type":"object","description":"Keeps the most recent messages of the memory named by the run's memory id (or the step's\n`memory_id`). Without a memory id the agent runs without memory.\n","properties":{"kind":{"type":"string","enum":["window"]},"context_length":{"type":"integer","description":"Number of most recent messages to load and store. 0 turns memory off."}},"required":["kind","context_length"]},"MemoryAuto":{"type":"object","deprecated":true,"description":"Deprecated, still read as it was written: the run's memory id, else the `memory_id` here.\nThe step's own `memory_id` is not read while this kind is set; switch the kind to `window`\nto use it. Without a `context_length`, or with 0, it is `off` and reads `previous_messages`.\n","properties":{"kind":{"type":"string","enum":["auto"]},"context_length":{"type":"integer","description":"Maximum number of messages to retain in context"},"memory_id":{"type":"string","description":"Identifier for persistent memory across agent invocations"}},"required":["kind"]},"MemoryCompaction":{"type":"object","description":"Keeps the whole memory named by the run's memory id (or the step's `memory_id`), replacing\nits older part with a summary as the conversation approaches the model's context window.\nWithout a memory id the agent runs without memory, and compaction bounds the run's own loop.\n","properties":{"kind":{"type":"string","enum":["compaction"]},"context_window":{"type":"integer","description":"Overrides the context window looked up from the model, in tokens. Only a model\nWindmill does not know needs one; those fall back to 128000.\n"}},"required":["kind"]},"MemoryMessage":{"type":"object","description":"A single message in conversation history","properties":{"role":{"type":"string","enum":["user","assistant","system"]},"content":{"type":"string"}},"required":["role","content"]},"MemoryManual":{"type":"object","deprecated":true,"description":"Deprecated, still read as it was written. Move the step to `off` with `previous_messages` instead.","properties":{"kind":{"type":"string","enum":["manual"]},"messages":{"type":"array","items":{"$ref":"#/components/schemas/MemoryMessage"}}},"required":["kind","messages"]},"MemoryConfig":{"description":"Managed memory, stored by Windmill and replayed with each request. The memory is named by a memory id, see `memory_id`. While it is off, a step can supply its history in `previous_messages`.","oneOf":[{"$ref":"#/components/schemas/MemoryOff"},{"$ref":"#/components/schemas/MemoryWindow"},{"$ref":"#/components/schemas/MemoryCompaction"},{"$ref":"#/components/schemas/MemoryAuto"},{"$ref":"#/components/schemas/MemoryManual"}],"discriminator":{"propertyName":"kind","mapping":{"off":"#/components/schemas/MemoryOff","window":"#/components/schemas/MemoryWindow","compaction":"#/components/schemas/MemoryCompaction","auto":"#/components/schemas/MemoryAuto","manual":"#/components/schemas/MemoryManual"}}},"StaticMemoryTransform":{"type":"object","description":"Static memory configuration passed directly to the AI agent","properties":{"value":{"$ref":"#/components/schemas/MemoryConfig"},"type":{"type":"string","enum":["static"]}},"required":["type","value"]},"MemoryTransform":{"description":"Memory configuration - can be static (MemoryConfig), JavaScript expression, or AI-determined","oneOf":[{"$ref":"#/components/schemas/StaticMemoryTransform"},{"$ref":"#/components/schemas/JavascriptTransform"},{"$ref":"#/components/schemas/AiTransform"}],"discriminator":{"propertyName":"type","mapping":{"static":"#/components/schemas/StaticMemoryTransform","javascript":"#/components/schemas/JavascriptTransform","ai":"#/components/schemas/AiTransform"}}},"FlowModuleValue":{"description":"The actual implementation of a flow step. Can be a script (inline or referenced), subflow, loop, branch, or special module type","oneOf":[{"$ref":"#/components/schemas/RawScript"},{"$ref":"#/components/schemas/PathScript"},{"$ref":"#/components/schemas/PathFlow"},{"$ref":"#/components/schemas/ForloopFlow"},{"$ref":"#/components/schemas/WhileloopFlow"},{"$ref":"#/components/schemas/BranchOne"},{"$ref":"#/components/schemas/BranchAll"},{"$ref":"#/components/schemas/Identity"},{"$ref":"#/components/schemas/AiAgent"},{"$ref":"#/components/schemas/AiDecision"}],"discriminator":{"propertyName":"type","mapping":{"rawscript":"#/components/schemas/RawScript","script":"#/components/schemas/PathScript","flow":"#/components/schemas/PathFlow","forloopflow":"#/components/schemas/ForloopFlow","whileloopflow":"#/components/schemas/WhileloopFlow","branchone":"#/components/schemas/BranchOne","branchall":"#/components/schemas/BranchAll","identity":"#/components/schemas/Identity","aiagent":"#/components/schemas/AiAgent","aidecision":"#/components/schemas/AiDecision"}}},"RawScript":{"type":"object","description":"Inline script with code defined directly in the flow. Use 'bun' as default language if unspecified. The script receives arguments from input_transforms","properties":{"input_transforms":{"type":"object","description":"Map of parameter names to their values (static or JavaScript expressions). These become the script's input arguments","additionalProperties":{"$ref":"#/components/schemas/InputTransform"}},"content":{"type":"string","description":"The script source code. Should export a 'main' function"},"language":{"type":"string","description":"Programming language for this script","enum":["deno","bun","bunnative","python3","go","bash","powershell","postgresql","mysql","bigquery","snowflake","mssql","oracledb","graphql","nativets","php","rust","ansible","csharp","nu","java","ruby","rlang","duckdb"]},"path":{"type":"string","description":"Optional path for saving this script"},"lock":{"type":"string","description":"Lock file content for dependencies"},"type":{"type":"string","enum":["rawscript"]},"tag":{"type":"string","description":"Worker group tag for execution routing"},"concurrent_limit":{"type":"number","description":"Maximum concurrent executions of this script"},"concurrency_time_window_s":{"type":"number","description":"Time window for concurrent_limit"},"custom_concurrency_key":{"type":"string","description":"Custom key for grouping concurrent executions"},"is_trigger":{"type":"boolean","description":"If true, this script is a trigger that can start the flow"},"assets":{"type":"array","description":"External resources this script accesses (S3 objects, resources, etc.)","items":{"type":"object","required":["path","kind"],"properties":{"path":{"type":"string","description":"Path to the asset"},"kind":{"type":"string","description":"Type of asset","enum":["s3object","resource","ducklake","datatable","volume","dbt"]},"access_type":{"type":"string","nullable":true,"description":"Access level for this asset","enum":["r","w","rw"]},"alt_access_type":{"type":"string","nullable":true,"description":"Alternative access level","enum":["r","w","rw"]}}}}},"required":["type","content","language","input_transforms"]},"PathScript":{"type":"object","description":"Reference to an existing script by path. Use this when calling a previously saved script instead of writing inline code","properties":{"input_transforms":{"type":"object","description":"Map of parameter names to their values (static or JavaScript expressions). These become the script's input arguments","additionalProperties":{"$ref":"#/components/schemas/InputTransform"}},"path":{"type":"string","description":"Path to the script in the workspace (e.g., 'f/scripts/send_email')"},"hash":{"type":"string","description":"Optional specific version hash of the script to use"},"type":{"type":"string","enum":["script"]},"tag_override":{"type":"string","description":"Override the script's default worker group tag"},"is_trigger":{"type":"boolean","description":"If true, this script is a trigger that can start the flow"}},"required":["type","path","input_transforms"]},"PathFlow":{"type":"object","description":"Reference to an existing flow by path. Use this to call another flow as a subflow","properties":{"input_transforms":{"type":"object","description":"Map of parameter names to their values (static or JavaScript expressions). These become the subflow's input arguments","additionalProperties":{"$ref":"#/components/schemas/InputTransform"}},"path":{"type":"string","description":"Path to the flow in the workspace (e.g., 'f/flows/process_user')"},"type":{"type":"string","enum":["flow"]}},"required":["type","path","input_transforms"]},"ForloopFlow":{"type":"object","description":"Executes nested modules in a loop over an iterator. Inside the loop, use 'flow_input.iter.value' to access the current iteration value, and 'flow_input.iter.index' for the index. Supports parallel execution for better performance on I/O-bound operations","properties":{"modules":{"type":"array","description":"Steps to execute for each iteration. These can reference the iteration value via 'flow_input.iter.value'","items":{"$ref":"#/components/schemas/FlowModule"}},"iterator":{"description":"JavaScript expression that returns an array to iterate over. Can reference 'results.step_id' or 'flow_input'","$ref":"#/components/schemas/InputTransform"},"skip_failures":{"type":"boolean","description":"If true, iteration failures don't stop the loop. Failed iterations return null"},"type":{"type":"string","enum":["forloopflow"]},"parallel":{"type":"boolean","description":"If true, iterations run concurrently (faster for I/O-bound operations). Use with parallelism to control concurrency"},"parallelism":{"description":"Maximum number of concurrent iterations when parallel=true. Limits resource usage. Can be static number or expression","$ref":"#/components/schemas/InputTransform"},"squash":{"type":"boolean"}},"required":["modules","iterator","skip_failures","type"]},"WhileloopFlow":{"type":"object","description":"Executes nested modules repeatedly until stopped. The implicit iterator is the iteration counter, so 'flow_input.iter.value' equals 'flow_input.iter.index' (0, 1, 2, ...) and never carries state. To carry state across iterations, a step reads its own previous-iteration result via 'results.<its_own_id>' with a first-iteration fallback - the loop's stop_after_if must then be on that inner step (a plain single-step body with stop_after_if on the loop module does not resolve 'results' across iterations and never terminates); plain counters can instead be derived from 'flow_input.iter.index', which works in every configuration. stop_after_if is evaluated after each iteration - on the loop module 'result' is the last iteration's result","properties":{"modules":{"type":"array","description":"Steps to execute in each iteration","items":{"$ref":"#/components/schemas/FlowModule"}},"skip_failures":{"type":"boolean","description":"If true, iteration failures don't stop the loop. Failed iterations return null"},"type":{"type":"string","enum":["whileloopflow"]},"parallel":{"type":"boolean","description":"If true, iterations run concurrently (use with caution in while loops)"},"parallelism":{"description":"Maximum number of concurrent iterations when parallel=true","$ref":"#/components/schemas/InputTransform"},"squash":{"type":"boolean"}},"required":["modules","skip_failures","type"]},"BranchOne":{"type":"object","description":"Conditional branching where only the first matching branch executes. Branches are evaluated in order, and the first one with a true expression runs. If no branches match, the default branch executes","properties":{"branches":{"type":"array","description":"Array of branches to evaluate in order. The first branch with expr evaluating to true executes","items":{"type":"object","properties":{"summary":{"type":"string","description":"Short description of this branch condition"},"expr":{"type":"string","description":"JavaScript expression that returns boolean. Can use 'results.step_id' or 'flow_input'. First true expr wins"},"modules":{"type":"array","description":"Steps to execute if this branch's expr is true","items":{"$ref":"#/components/schemas/FlowModule"}}},"required":["modules","expr"]}},"default":{"type":"array","description":"Steps to execute if no branch expressions match","items":{"$ref":"#/components/schemas/FlowModule"}},"type":{"type":"string","enum":["branchone"]}},"required":["branches","default","type"]},"BranchAll":{"type":"object","description":"Parallel branching where all branches execute simultaneously. Unlike BranchOne, all branches run regardless of conditions. Useful for executing independent tasks concurrently","properties":{"branches":{"type":"array","description":"Array of branches that all execute (either in parallel or sequentially)","items":{"type":"object","properties":{"summary":{"type":"string","description":"Short description of this branch's purpose"},"skip_failure":{"type":"boolean","description":"If true, failure in this branch doesn't fail the entire flow"},"modules":{"type":"array","description":"Steps to execute in this branch","items":{"$ref":"#/components/schemas/FlowModule"}}},"required":["modules"]}},"type":{"type":"string","enum":["branchall"]},"parallel":{"type":"boolean","description":"If true, all branches execute concurrently. If false, they execute sequentially"}},"required":["branches","type"]},"AgentTool":{"type":"object","description":"A tool available to an AI agent. Can be a flow module or an external MCP (Model Context Protocol) tool","properties":{"id":{"type":"string","description":"Unique identifier for this tool. Cannot contain spaces - use underscores instead (e.g., 'get_user_data' not 'get user data')"},"summary":{"type":"string","description":"The name the AI agent calls this tool by, not a human label. On a flowmodule tool it must match ^[a-zA-Z0-9_]+$ - letters, numbers and underscores only (e.g. 'search_documentation', not 'Search documentation') - and always be set; on an mcp or websearch tool it is a plain label. Put the human-readable explanation in 'description'."},"description":{"type":"string","description":"Free-text description of the tool given to the AI to decide when and how to call it. Overrides the description auto-derived from the underlying script."},"job_token_scopes":{"type":"array","nullable":true,"items":{"type":"string"},"description":"Scopes the token of this tool's jobs is restricted to, on top of the agent step's own restriction: a tool can only narrow it."},"value":{"$ref":"#/components/schemas/ToolValue"}},"required":["id","value"]},"ToolValue":{"description":"The implementation of a tool. Can be a flow module (script/flow) or an MCP tool reference","oneOf":[{"$ref":"#/components/schemas/FlowModuleTool"},{"$ref":"#/components/schemas/McpToolValue"},{"$ref":"#/components/schemas/WebsearchToolValue"}],"discriminator":{"propertyName":"tool_type","mapping":{"flowmodule":"#/components/schemas/FlowModuleTool","mcp":"#/components/schemas/McpToolValue","websearch":"#/components/schemas/WebsearchToolValue"}}},"FlowModuleTool":{"description":"A tool implemented as a flow module (script, flow, etc.). The AI can call this like any other flow module","allOf":[{"type":"object","properties":{"tool_type":{"type":"string","enum":["flowmodule"]}},"required":["tool_type"]},{"$ref":"#/components/schemas/FlowModuleValue"}]},"WebsearchToolValue":{"type":"object","description":"A tool implemented as a websearch tool. The AI can call this like any other websearch tool","properties":{"tool_type":{"type":"string","enum":["websearch"]}},"required":["tool_type"]},"McpToolValue":{"type":"object","description":"Reference to an external MCP (Model Context Protocol) tool. The AI can call tools from MCP servers","properties":{"tool_type":{"type":"string","enum":["mcp"]},"resource_path":{"type":"string","description":"Path to the MCP resource/server configuration"},"include_tools":{"type":"array","description":"Whitelist of specific tools to include from this MCP server","items":{"type":"string"}},"exclude_tools":{"type":"array","description":"Blacklist of tools to exclude from this MCP server","items":{"type":"string"}}},"required":["tool_type","resource_path"]},"AiAgent":{"type":"object","description":"AI agent step that can use tools to accomplish tasks. The agent receives inputs and can call any of its configured tools to complete the task","properties":{"input_transforms":{"type":"object","description":"Input parameters for the AI agent mapped to their values","properties":{"provider":{"$ref":"#/components/schemas/ProviderTransform"},"output_type":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"Output format type.\nValid values: 'text' (default) - plain text response, 'image' - image generation\n"},"user_message":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"The user's prompt/message to the AI agent. Supports variable interpolation with\nflow.input syntax. Required unless memory is off and `previous_messages` supplies\nthe prompt; image output always needs it.\n"},"system_prompt":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"System instructions that guide the AI's behavior, persona, and response style. Optional."},"streaming":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"Boolean. If true, stream the AI response incrementally.\nStreaming events include: token_delta, reasoning_token_delta, tool_call, tool_call_arguments, tool_execution, tool_result\n"},"memory":{"$ref":"#/components/schemas/MemoryTransform"},"memory_id":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"String. Names the memory this step reads and writes, overriding the memory id the run\nwas started with (the chat conversation, an app chat session or the `memory_id` run\nparameter). Leave unset to use the run's memory id. A fixed value shares one memory\nacross every run; an expression such as `flow_input.customer_id` keeps one memory per\nkey. When it evaluates to an empty value the agent runs without memory. Read only\nwhile `memory` is `window` or `compaction`: it is ignored when memory is off, and an\nolder `auto` or `manual` memory reads neither history input.\n"},"previous_messages":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"Array of MemoryMessage. History supplied by the flow, sent between the system prompt\nand the user message. Read only while `memory` is off or absent: managed memory\nignores it, and an older `auto` or `manual` memory reads neither history input.\n"},"output_schema":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"JSON Schema object defining structured output format. Used when you need the AI to return data in a specific shape.\nSupports standard JSON Schema properties: type, properties, required, items, enum, pattern, minLength, maxLength, minimum, maximum, etc.\nExample: { type: 'object', properties: { name: { type: 'string' }, age: { type: 'integer' } }, required: ['name'] }\n"},"user_attachments":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"Array of file references (images or PDFs) for the AI agent.\nFormat: Array<{ bucket: string, key: string }> - S3 object references\nExample: [{ bucket: 'my-bucket', key: 'documents/report.pdf' }]\n"},"enabled_tools":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"Array of strings naming which of the tools configured in `tools` the agent may call\nthis run. Leaving it unset carries every one of them; an empty array carries none.\nA tool is named as the model is shown it. An entry the model is shown nothing of is\nnamed by what identifies it instead: an MCP server by its resource path, carrying\nevery tool it exposes (which of them stays that entry's include_tools/exclude_tools),\nand a websearch entry by the reserved name '__wm_web_search', whatever summary it carries\n(no tool may take that name).\nExample: ['get_user', 'u/admin/github_mcp', '__wm_web_search']\n"},"max_completion_tokens":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"Integer. Maximum number of tokens the AI will generate in its response.\nRange: 1 to 4,294,967,295. Typical values: 256-4096 for most use cases.\n"},"temperature":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"Float. Controls randomness/creativity of responses.\nRange: 0.0 to 2.0 (provider-dependent)\n- 0.0 = deterministic, focused responses\n- 0.7 = balanced (common default)\n- 1.0+ = more creative/random\n"},"max_iterations":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"Number. Limits how many times the agent can loop through reasoning and tool use.\nRange: 1-1000.\n"},"model":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"String. Only on a step linked to a saved agent (see `agent`): replaces the model\nsaved on the agent for this step's runs, on the agent's own provider resource. An\nempty value keeps the saved model. Set it to an expression such as\n`flow_input.model` to choose the model per run.\n"},"reasoning_effort":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"String. Only on a step linked to a saved agent (see `agent`): replaces the reasoning\neffort saved on the agent for this step's runs, as a provider-native token (e.g.\n'low', 'high', 'none'). An empty value sends no effort, so the model runs at its\ndefault. Leave the input out to keep the saved effort, which holds only while the\nstep runs the saved model. A step that is not linked sets both inside `provider`.\n"}}},"tools":{"type":"array","description":"Array of tools the agent can use. The agent decides which tools to call based on the task","items":{"$ref":"#/components/schemas/AgentTool"}},"type":{"type":"string","enum":["aiagent"]},"tag":{"type":"string","description":"Worker group tag for execution routing. If not set, the AI agent step runs on the flow's tag (default `flow`)"},"omit_output_from_conversation":{"type":"boolean","default":false,"description":"If true, this AI agent step does not persist its assistant or tool messages to the flow conversation when chat mode is enabled."},"agent":{"type":"string","description":"Path of a reusable `ai_agent` resource (hybrid linking). When set, the agent brain\nconfig (provider/model/system prompt/etc.) and tool set are resolved at runtime from\nthat resource; the module's input_transforms then only carry the flow-local inputs\n(user_message, user_attachments, enabled_tools and the history inputs memory_id and previous_messages)\nand, optionally, the `model` and `reasoning_effort` overrides of what the agent saved.\n"},"tool_inputs":{"type":"object","description":"Host-local wiring for an agent's tool inputs, keyed by tool id then input key. Binds the\nreferenced agent's tools to this flow's context (flow_input/results) without mutating the\nshared resource; overlaid onto the tools' input_transforms at runtime \u2014 including when\n`agent` is unset, since a step forked for editing keeps these overrides until it is saved\nback or unlinked.\n","additionalProperties":{"type":"object","additionalProperties":{"$ref":"#/components/schemas/InputTransform"}}},"parallel":{"type":"boolean","description":"If true, the agent can execute multiple tool calls in parallel"}},"required":["type","input_transforms"]},"AiDecision":{"type":"object","description":"AI decision step: one call to a decision model (TypeSafe's Jev, Cloudflare's\nJev-compatible Clef, or OpenAI's Decisions API) that answers typed questions about a\nstate with calibrated probabilities, instead of generating text.\nPrefer it over an AI agent to classify, route, score or check something: it is fast,\ncheap and its answers are structured. Its result is { output: { <question name>: answer },\nmodel, usage }, so a later step reads e.g. results.<id>.output.intent.choice. To route on\nthe answers, follow it with a branchone whose branch exprs read\nresults.<id>.output.<question>.choice. Usable as an AI agent tool, where the calling agent\nsupplies the state.\n","properties":{"input_transforms":{"type":"object","description":"Input parameters for the decision mapped to their values","properties":{"provider":{"$ref":"#/components/schemas/ProviderTransform"},"state":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"What the questions are asked about: a string, an object or an array of strings.\nAn object with descriptive keys holding only what the questions need works best.\nExample: { message: flow_input.message, plan: results.a.plan }\n"},"questions":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"Object mapping each question name to { type, instructions, criteria }, where type is:\n- 'choice': criteria maps each option to its description (up to 255); the answer\n has choice, probabilities and confidence\n- 'score': criteria is an ordered array of 2 to 10 level descriptions; the answer\n has score, legend, probabilities and confidence\n- 'noul': yes/no, criteria optionally { true, false } descriptions; the answer has\n noul, the probability of yes (0 to 1)\nExample: { intent: { type: 'choice', instructions: 'What does the customer want?',\ncriteria: { refund: 'Money back', bug: 'Something is broken' } } }\n"}},"required":["provider","state","questions"]},"type":{"type":"string","enum":["aidecision"]},"tag":{"type":"string","description":"Worker group tag for execution routing. If not set, the step runs on the flow's tag (default `flow`)"}},"required":["type","input_transforms"]},"Identity":{"type":"object","description":"Pass-through module that returns its input unchanged. Useful for flow structure or as a placeholder","properties":{"type":{"type":"string","enum":["identity"]},"flow":{"type":"boolean","description":"If true, marks this as a flow identity (special handling)"}},"required":["type"]},"FlowStatus":{"type":"object","properties":{"step":{"type":"integer"},"modules":{"type":"array","items":{"$ref":"#/components/schemas/FlowStatusModule"}},"user_states":{"additionalProperties":true},"preprocessor_module":{"allOf":[{"$ref":"#/components/schemas/FlowStatusModule"}]},"failure_module":{"allOf":[{"$ref":"#/components/schemas/FlowStatusModule"},{"type":"object","properties":{"parent_module":{"type":"string"}}}]},"retry":{"type":"object","properties":{"fail_count":{"type":"integer"},"failed_jobs":{"type":"array","items":{"type":"string","format":"uuid"}}}}},"required":["step","modules","failure_module"]},"FlowStatusModule":{"type":"object","properties":{"type":{"type":"string","enum":["WaitingForPriorSteps","WaitingForEvents","WaitingForExecutor","InProgress","Success","Failure"]},"id":{"type":"string"},"job":{"type":"string","format":"uuid"},"count":{"type":"integer"},"progress":{"type":"integer"},"iterator":{"type":"object","properties":{"index":{"type":"integer"},"itered":{"type":"array","items":{}},"itered_len":{"type":"integer"},"args":{}}},"flow_jobs":{"type":"array","items":{"type":"string"}},"flow_jobs_success":{"type":"array","items":{"type":"boolean"}},"flow_jobs_duration":{"type":"object","properties":{"started_at":{"type":"array","items":{"type":"string"}},"duration_ms":{"type":"array","items":{"type":"integer"}}}},"branch_chosen":{"type":"object","properties":{"type":{"type":"string","enum":["branch","default"]},"branch":{"type":"integer"}},"required":["type"]},"branchall":{"type":"object","properties":{"branch":{"type":"integer"},"len":{"type":"integer"}},"required":["branch","len"]},"approvers":{"type":"array","items":{"type":"object","properties":{"resume_id":{"type":"integer"},"approver":{"type":"string"}},"required":["resume_id","approver"]}},"failed_retries":{"type":"array","items":{"type":"string","format":"uuid"}},"skipped":{"type":"boolean"},"agent_actions":{"type":"array","items":{"type":"object","oneOf":[{"type":"object","properties":{"job_id":{"type":"string","format":"uuid"},"function_name":{"type":"string"},"type":{"type":"string","enum":["tool_call"]},"module_id":{"type":"string"}},"required":["job_id","function_name","type","module_id"]},{"type":"object","properties":{"call_id":{"type":"string","format":"uuid"},"function_name":{"type":"string"},"resource_path":{"type":"string"},"type":{"type":"string","enum":["mcp_tool_call"]},"arguments":{"type":"object"}},"required":["call_id","function_name","resource_path","type"]},{"type":"object","properties":{"type":{"type":"string","enum":["web_search"]}},"required":["type"]},{"type":"object","properties":{"type":{"type":"string","enum":["message"]}},"required":["content","type"]}]}},"agent_actions_success":{"type":"array","items":{"type":"boolean"}}},"required":["type"]}} +{"OpenFlow":{"type":"object","description":"Top-level flow definition containing metadata, configuration, and the flow structure","properties":{"summary":{"type":"string","description":"Short description of what this flow does"},"description":{"type":"string","description":"Detailed documentation for this flow"},"value":{"$ref":"#/components/schemas/FlowValue"},"schema":{"type":"object","description":"JSON Schema for flow inputs. Use this to define input parameters, their types, defaults, and validation. For resource inputs, set type to 'object' and format to 'resource-<type>' (e.g., 'resource-stripe')"},"on_behalf_of_email":{"type":"string","description":"Address of the account the flow runs on behalf of. Derived from on_behalf_of on read; accepted on write, where it is resolved to the account it names."},"on_behalf_of":{"type":"string","description":"The flow runs with the permissions of this identity: u/{username}, g/{group}, or a bare email when the username is itself email-shaped. The only stored half of the identity; on_behalf_of_email is derived from it. Omit it when writing and it is resolved from that address instead."}},"required":["summary","value"]},"FlowValue":{"type":"object","description":"The flow structure containing modules and optional preprocessor/failure handlers","properties":{"modules":{"type":"array","description":"Array of steps that execute in sequence. Each step can be a script, subflow, loop, or branch","items":{"$ref":"#/components/schemas/FlowModule"}},"failure_module":{"description":"Special module that executes when the flow fails. Receives error object with message, name, stack, and step_id. Must have id 'failure'. Only supports script/rawscript types","$ref":"#/components/schemas/FlowModule"},"preprocessor_module":{"description":"Special module that runs before the first step on external triggers. Must have id 'preprocessor'. Only supports script/rawscript types. Cannot reference other step results","$ref":"#/components/schemas/FlowModule"},"same_worker":{"type":"boolean","description":"If true, all steps run on the same worker for better performance"},"preserve_step_tags":{"type":"boolean","description":"If true and the flow runs on a custom worker tag, steps that declare their own non-empty tag run on it instead of inheriting the flow tag. Steps without their own tag still inherit the flow tag."},"concurrent_limit":{"type":"number","description":"Maximum number of concurrent executions of this flow"},"concurrency_key":{"type":"string","description":"Expression to group concurrent executions (e.g., by user ID)"},"concurrency_time_window_s":{"type":"number","description":"Time window in seconds for concurrent_limit"},"debounce_delay_s":{"type":"integer","description":"Delay in seconds to debounce flow executions"},"debounce_key":{"type":"string","description":"Expression to group debounced executions"},"debounce_args_to_accumulate":{"type":"array","description":"Arguments to accumulate across debounced executions","items":{"type":"string"}},"max_total_debouncing_time":{"type":"integer","description":"Maximum total time in seconds that a job can be debounced"},"max_total_debounces_amount":{"type":"integer","description":"Maximum number of times a job can be debounced"},"skip_expr":{"type":"string","description":"JavaScript expression to conditionally skip the entire flow"},"cache_ttl":{"type":"number","description":"Cache duration in seconds for flow results"},"cache_ignore_s3_path":{"type":"boolean"},"delete_after_secs":{"type":"integer","description":"If set, delete the flow job's args, result and logs after this many seconds following job completion"},"flow_env":{"type":"object","description":"Environment variables available to all steps. Values can be strings, JSON values, or special references: '$var:path' (workspace variable) or '$res:path' (resource).","additionalProperties":{}},"priority":{"type":"number","description":"Execution priority (higher numbers run first)"},"early_return":{"type":"string","description":"Id of the step whose result a sync webhook returns as soon as that step completes, while the rest of the flow keeps running. When the step does not run, or fails while the flow has a failure module, the flow's final result is returned instead."},"chat_input_enabled":{"type":"boolean","description":"Whether this flow accepts chat-style input"},"notes":{"type":"array","description":"Sticky notes attached to the flow","items":{"$ref":"#/components/schemas/FlowNote"}},"groups":{"type":"array","description":"Semantic groups of modules for organizational purposes","items":{"$ref":"#/components/schemas/FlowGroup"}}},"required":["modules"]},"Retry":{"type":"object","description":"Retry configuration for failed module executions","properties":{"constant":{"type":"object","description":"Retry with constant delay between attempts","properties":{"attempts":{"type":"integer","description":"Number of retry attempts"},"seconds":{"type":"integer","description":"Seconds to wait between retries"}}},"exponential":{"type":"object","description":"Retry with exponential backoff: the n-th retry waits multiplier \u00d7 seconds^n","properties":{"attempts":{"type":"integer","description":"Number of retry attempts"},"multiplier":{"type":"integer","description":"Multiplier for exponential backoff"},"seconds":{"type":"integer","minimum":1,"description":"Base of the exponential (seconds); the n-th retry waits multiplier \u00d7 seconds^n, where n counts constant retries too"},"random_factor":{"type":"integer","minimum":0,"maximum":100,"description":"Random jitter percentage (0-100) to avoid thundering herd"}}},"retry_if":{"$ref":"#/components/schemas/RetryIf"}}},"FlowNote":{"type":"object","description":"A sticky note attached to a flow for documentation and annotation","properties":{"id":{"type":"string","description":"Unique identifier for the note"},"text":{"type":"string","description":"Content of the note"},"position":{"type":"object","description":"Position of the note in the flow editor","properties":{"x":{"type":"number","description":"X coordinate"},"y":{"type":"number","description":"Y coordinate"}},"required":["x","y"]},"size":{"type":"object","description":"Size of the note in the flow editor","properties":{"width":{"type":"number","description":"Width in pixels"},"height":{"type":"number","description":"Height in pixels"}},"required":["width","height"]},"color":{"type":"string","description":"Color of the note, one of: yellow, blue, green, purple, pink, orange, red, cyan, lime, gray. Any other value renders unstyled."},"type":{"type":"string","enum":["free","group"],"description":"Type of note - 'free' for standalone notes. 'group' notes are deprecated; segment a flow with FlowValue.groups instead."},"locked":{"type":"boolean","default":false,"description":"Whether the note is locked and cannot be edited or moved"},"contained_node_ids":{"type":"array","items":{"type":"string"},"description":"For group notes, the IDs of nodes contained within this group"}},"required":["id","text","color","type"]},"FlowGroup":{"type":"object","description":"A semantic group of flow modules for organizational purposes. Does not affect execution \u2014 modules remain in their original position in the flow. Groups provide naming and collapsibility in the editor. Members are computed dynamically from all nodes on paths between start_id and end_id.","properties":{"summary":{"type":"string","description":"Display name for this group"},"note":{"type":"string","description":"Markdown note shown below the group header"},"autocollapse":{"type":"boolean","default":false,"description":"If true, this group is collapsed by default in the flow editor. UI hint only."},"start_id":{"type":"string","description":"ID of the first flow module in this group (topological entry point)"},"end_id":{"type":"string","description":"ID of the last flow module in this group (topological exit point)"},"color":{"type":"string","description":"Color for the group in the flow editor, one of: yellow, blue, green, purple, pink, orange, red, cyan, lime, gray. Omit it to let the editor pick one."}},"required":["start_id","end_id"]},"RetryIf":{"type":"object","description":"Conditional retry based on error or result","properties":{"expr":{"type":"string","description":"JavaScript expression that returns true to retry. Has access to 'result' and 'error' variables"}},"required":["expr"]},"StopAfterIf":{"type":"object","description":"Early termination condition for a module","properties":{"skip_if_stopped":{"type":"boolean","description":"If true, following steps are skipped when this condition triggers"},"expr":{"type":"string","description":"JavaScript expression evaluated after the module runs. Can use 'result' (step's result) or 'flow_input'. Return true to stop"},"error_message":{"type":"string","nullable":true,"description":"Custom error message when stopping with an error. Mutually exclusive with skip_if_stopped. If set to a non-empty string, the flow stops with this error. If empty string, a default error message is used. If null or omitted, no error is raised."},"error_include_result":{"type":"boolean","description":"When stopping with an error (error_message set), embed the stopping step's own result inside the raised error object (as error.result) instead of discarding it. The top-level result stays { error }. Defaults to false."}},"required":["expr"]},"FlowModule":{"type":"object","description":"A single step in a flow. Can be a script, subflow, loop, or branch","properties":{"id":{"type":"string","description":"Unique identifier for this step. Used to reference results via 'results.step_id'. Must be a valid identifier (alphanumeric, underscore, hyphen)"},"value":{"$ref":"#/components/schemas/FlowModuleValue"},"stop_after_if":{"description":"Early termination condition evaluated after this step completes","$ref":"#/components/schemas/StopAfterIf"},"stop_after_all_iters_if":{"description":"For loops only - early termination condition evaluated after all iterations complete","$ref":"#/components/schemas/StopAfterIf"},"skip_if":{"type":"object","description":"Conditionally skip this step based on previous results or flow inputs","properties":{"expr":{"type":"string","description":"JavaScript expression that returns true to skip. Can use 'flow_input' or 'results.<step_id>'"}},"required":["expr"]},"sleep":{"description":"Delay before executing this step (in seconds or as expression)","$ref":"#/components/schemas/InputTransform"},"cache_ttl":{"type":"number","description":"Cache duration in seconds for this step's results"},"cache_ignore_s3_path":{"type":"boolean"},"timeout":{"description":"Maximum execution time in seconds (static value or expression)","$ref":"#/components/schemas/InputTransform"},"delete_after_secs":{"type":"integer","description":"If set, delete the step's args, result and logs after this many seconds following job completion"},"summary":{"type":"string","description":"Short description of what this step does"},"mock":{"type":"object","description":"Mock configuration for testing without executing the actual step","properties":{"enabled":{"type":"boolean","description":"If true, return mock value instead of executing"},"return_value":{"description":"Value to return when mocked"}}},"suspend":{"type":"object","description":"Configuration for approval/resume steps that wait for user input","properties":{"required_events":{"type":"integer","description":"Number of approvals required before continuing"},"timeout":{"type":"integer","description":"Timeout in seconds before auto-continuing or canceling"},"resume_form":{"type":"object","description":"Form schema for collecting input when resuming","properties":{"schema":{"type":"object","description":"JSON Schema for the resume form"}}},"user_auth_required":{"type":"boolean","description":"If true, only authenticated users can approve"},"user_groups_required":{"description":"Expression or list of groups that can approve","$ref":"#/components/schemas/InputTransform"},"self_approval_disabled":{"type":"boolean","description":"If true, the user who started the flow cannot approve"},"hide_cancel":{"type":"boolean","description":"If true, hide the cancel button on the approval form"},"continue_on_disapprove_timeout":{"type":"boolean","description":"If true, continue flow on timeout instead of canceling"},"skin":{"type":"string","enum":["detailed","minimal"],"description":"How the approval request is presented, on the approval page and in Slack/Teams approval messages. 'detailed' (used when unset) shows the flow details (arguments, graph, approvers); 'minimal' shows only the request: the step description, form and approve/reject actions"}}},"priority":{"type":"number","description":"Execution priority for this step (higher numbers run first)"},"continue_on_error":{"type":"boolean","description":"If true, flow continues even if this step fails"},"job_token_scopes":{"type":"array","nullable":true,"items":{"type":"string"},"description":"Scopes the token of this step's jobs is restricted to (domain:action[:resource], e.g. oidc:write), on top of the flow's own restriction: a step can only narrow it. Applies to everything the step runs (loop and branch bodies, AI agent tools)."},"retry":{"description":"Retry configuration if this step fails","$ref":"#/components/schemas/Retry"},"debouncing":{"description":"Debounce configuration for this step (EE only)","type":"object","properties":{"debounce_delay_s":{"type":"integer","description":"Delay in seconds to debounce this step's executions across flow runs"},"debounce_key":{"type":"string","description":"Expression to group debounced executions. Supports $workspace and $args[name]. Default: $workspace/flow/<flow_path>-<step_id>"},"debounce_args_to_accumulate":{"type":"array","description":"Array-type arguments to accumulate across debounced executions","items":{"type":"string"}},"max_total_debouncing_time":{"type":"integer","description":"Maximum total time in seconds before forced execution"},"max_total_debounces_amount":{"type":"integer","description":"Maximum number of debounces before forced execution"}}}},"required":["value","id"]},"InputTransform":{"description":"Maps input parameters for a step. Can be a static value or a JavaScript expression that references previous results or flow inputs","oneOf":[{"$ref":"#/components/schemas/StaticTransform"},{"$ref":"#/components/schemas/JavascriptTransform"},{"$ref":"#/components/schemas/AiTransform"}],"discriminator":{"propertyName":"type","mapping":{"static":"#/components/schemas/StaticTransform","javascript":"#/components/schemas/JavascriptTransform","ai":"#/components/schemas/AiTransform"}}},"StaticTransform":{"type":"object","description":"Static value passed directly to the step. Use for hardcoded values or resource references like '$res:path/to/resource'","properties":{"value":{"description":"The static value. For resources, use format '$res:path/to/resource'"},"type":{"type":"string","enum":["static"]}},"required":["type"]},"JavascriptTransform":{"type":"object","description":"JavaScript expression evaluated at runtime. Can reference previous step results via 'results.step_id' or flow inputs via 'flow_input.property'. Inside for loops, use 'flow_input.iter.value' for the current iteration value (in while loops it equals 'flow_input.iter.index')","properties":{"expr":{"type":"string","description":"JavaScript expression returning the value. Available variables - results (object with all previous step results), flow_input (flow inputs), flow_input.iter (in loops)"},"type":{"type":"string","enum":["javascript"]}},"required":["expr","type"]},"AiTransform":{"type":"object","description":"Value resolved by the AI runtime for this input. The AI engine decides how to satisfy the parameter.","properties":{"type":{"type":"string","enum":["ai"]}},"required":["type"]},"AIProviderKind":{"type":"string","description":"Supported AI provider types","enum":["openai","azure_openai","azure_foundry","anthropic","mistral","deepseek","googleai","groq","openrouter","togetherai","customai","aws_bedrock","typesafe","cloudflare"]},"ProviderConfig":{"type":"object","description":"Complete AI provider configuration with resource reference and model selection","properties":{"kind":{"$ref":"#/components/schemas/AIProviderKind"},"resource":{"type":"string","description":"Resource reference in format '$res:{resource_path}' pointing to provider credentials"},"model":{"type":"string","description":"Model identifier (e.g., 'gpt-4', 'claude-3-opus-20240229', 'gemini-pro')"},"reasoning_effort":{"type":"string","description":"Provider-native reasoning effort token (e.g. 'low', 'high', 'none') for models that support extended thinking. Optional; unset leaves the provider default."}},"required":["kind","resource","model"]},"StaticProviderTransform":{"type":"object","description":"Static provider configuration passed directly to the AI agent","properties":{"value":{"$ref":"#/components/schemas/ProviderConfig"},"type":{"type":"string","enum":["static"]}},"required":["type","value"]},"ProviderTransform":{"description":"Provider configuration - can be static (ProviderConfig), JavaScript expression, or AI-determined","oneOf":[{"$ref":"#/components/schemas/StaticProviderTransform"},{"$ref":"#/components/schemas/JavascriptTransform"},{"$ref":"#/components/schemas/AiTransform"}],"discriminator":{"propertyName":"type","mapping":{"static":"#/components/schemas/StaticProviderTransform","javascript":"#/components/schemas/JavascriptTransform","ai":"#/components/schemas/AiTransform"}}},"MemoryOff":{"type":"object","description":"No conversation memory/context","properties":{"kind":{"type":"string","enum":["off"]}},"required":["kind"]},"MemoryWindow":{"type":"object","description":"Keeps the most recent messages of the memory named by the run's memory id (or the step's\n`memory_id`). Without a memory id the agent runs without memory.\n","properties":{"kind":{"type":"string","enum":["window"]},"context_length":{"type":"integer","description":"Number of most recent messages to load and store. 0 turns memory off."}},"required":["kind","context_length"]},"MemoryAuto":{"type":"object","deprecated":true,"description":"Deprecated, still read as it was written: the run's memory id, else the `memory_id` here.\nThe step's own `memory_id` is not read while this kind is set; switch the kind to `window`\nto use it. Without a `context_length`, or with 0, it is `off` and reads `previous_messages`.\n","properties":{"kind":{"type":"string","enum":["auto"]},"context_length":{"type":"integer","description":"Maximum number of messages to retain in context"},"memory_id":{"type":"string","description":"Identifier for persistent memory across agent invocations"}},"required":["kind"]},"MemoryCompaction":{"type":"object","description":"Keeps the whole memory named by the run's memory id (or the step's `memory_id`), replacing\nits older part with a summary as the conversation approaches the model's context window.\nWithout a memory id the agent runs without memory, and compaction bounds the run's own loop.\n","properties":{"kind":{"type":"string","enum":["compaction"]},"context_window":{"type":"integer","description":"Overrides the context window looked up from the model, in tokens. Only a model\nWindmill does not know needs one; those fall back to 128000.\n"}},"required":["kind"]},"MemoryMessage":{"type":"object","description":"A single message in conversation history","properties":{"role":{"type":"string","enum":["user","assistant","system"]},"content":{"type":"string"}},"required":["role","content"]},"MemoryManual":{"type":"object","deprecated":true,"description":"Deprecated, still read as it was written. Move the step to `off` with `previous_messages` instead.","properties":{"kind":{"type":"string","enum":["manual"]},"messages":{"type":"array","items":{"$ref":"#/components/schemas/MemoryMessage"}}},"required":["kind","messages"]},"MemoryConfig":{"description":"Managed memory, stored by Windmill and replayed with each request. The memory is named by a memory id, see `memory_id`. While it is off, a step can supply its history in `previous_messages`.","oneOf":[{"$ref":"#/components/schemas/MemoryOff"},{"$ref":"#/components/schemas/MemoryWindow"},{"$ref":"#/components/schemas/MemoryCompaction"},{"$ref":"#/components/schemas/MemoryAuto"},{"$ref":"#/components/schemas/MemoryManual"}],"discriminator":{"propertyName":"kind","mapping":{"off":"#/components/schemas/MemoryOff","window":"#/components/schemas/MemoryWindow","compaction":"#/components/schemas/MemoryCompaction","auto":"#/components/schemas/MemoryAuto","manual":"#/components/schemas/MemoryManual"}}},"StaticMemoryTransform":{"type":"object","description":"Static memory configuration passed directly to the AI agent","properties":{"value":{"$ref":"#/components/schemas/MemoryConfig"},"type":{"type":"string","enum":["static"]}},"required":["type","value"]},"MemoryTransform":{"description":"Memory configuration - can be static (MemoryConfig), JavaScript expression, or AI-determined","oneOf":[{"$ref":"#/components/schemas/StaticMemoryTransform"},{"$ref":"#/components/schemas/JavascriptTransform"},{"$ref":"#/components/schemas/AiTransform"}],"discriminator":{"propertyName":"type","mapping":{"static":"#/components/schemas/StaticMemoryTransform","javascript":"#/components/schemas/JavascriptTransform","ai":"#/components/schemas/AiTransform"}}},"FlowModuleValue":{"description":"The actual implementation of a flow step. Can be a script (inline or referenced), subflow, loop, branch, or special module type","oneOf":[{"$ref":"#/components/schemas/RawScript"},{"$ref":"#/components/schemas/PathScript"},{"$ref":"#/components/schemas/PathFlow"},{"$ref":"#/components/schemas/ForloopFlow"},{"$ref":"#/components/schemas/WhileloopFlow"},{"$ref":"#/components/schemas/BranchOne"},{"$ref":"#/components/schemas/BranchAll"},{"$ref":"#/components/schemas/Identity"},{"$ref":"#/components/schemas/AiAgent"},{"$ref":"#/components/schemas/AiDecision"}],"discriminator":{"propertyName":"type","mapping":{"rawscript":"#/components/schemas/RawScript","script":"#/components/schemas/PathScript","flow":"#/components/schemas/PathFlow","forloopflow":"#/components/schemas/ForloopFlow","whileloopflow":"#/components/schemas/WhileloopFlow","branchone":"#/components/schemas/BranchOne","branchall":"#/components/schemas/BranchAll","identity":"#/components/schemas/Identity","aiagent":"#/components/schemas/AiAgent","aidecision":"#/components/schemas/AiDecision"}}},"RawScript":{"type":"object","description":"Inline script with code defined directly in the flow. Use 'bun' as default language if unspecified. The script receives arguments from input_transforms","properties":{"input_transforms":{"type":"object","description":"Map of parameter names to their values (static or JavaScript expressions). These become the script's input arguments","additionalProperties":{"$ref":"#/components/schemas/InputTransform"}},"content":{"type":"string","description":"The script source code. Should export a 'main' function"},"language":{"type":"string","description":"Programming language for this script","enum":["deno","bun","bunnative","python3","go","bash","powershell","postgresql","mysql","bigquery","snowflake","mssql","oracledb","graphql","nativets","php","rust","ansible","csharp","nu","java","ruby","rlang","duckdb"]},"path":{"type":"string","description":"Optional path for saving this script"},"lock":{"type":"string","description":"Lock file content for dependencies"},"type":{"type":"string","enum":["rawscript"]},"tag":{"type":"string","description":"Worker group tag for execution routing"},"concurrent_limit":{"type":"number","description":"Maximum concurrent executions of this script"},"concurrency_time_window_s":{"type":"number","description":"Time window for concurrent_limit"},"custom_concurrency_key":{"type":"string","description":"Custom key for grouping concurrent executions"},"is_trigger":{"type":"boolean","description":"If true, this script is a trigger that can start the flow"},"assets":{"type":"array","description":"External resources this script accesses (S3 objects, resources, etc.)","items":{"type":"object","required":["path","kind"],"properties":{"path":{"type":"string","description":"Path to the asset"},"kind":{"type":"string","description":"Type of asset","enum":["s3object","resource","ducklake","datatable","volume","dbt"]},"access_type":{"type":"string","nullable":true,"description":"Access level for this asset","enum":["r","w","rw"]},"alt_access_type":{"type":"string","nullable":true,"description":"Alternative access level","enum":["r","w","rw"]}}}}},"required":["type","content","language","input_transforms"]},"PathScript":{"type":"object","description":"Reference to an existing script by path. Use this when calling a previously saved script instead of writing inline code","properties":{"input_transforms":{"type":"object","description":"Map of parameter names to their values (static or JavaScript expressions). These become the script's input arguments","additionalProperties":{"$ref":"#/components/schemas/InputTransform"}},"path":{"type":"string","description":"Path to the script in the workspace (e.g., 'f/scripts/send_email')"},"hash":{"type":"string","description":"Optional specific version hash of the script to use"},"type":{"type":"string","enum":["script"]},"tag_override":{"type":"string","description":"Override the script's default worker group tag"},"is_trigger":{"type":"boolean","description":"If true, this script is a trigger that can start the flow"}},"required":["type","path","input_transforms"]},"PathFlow":{"type":"object","description":"Reference to an existing flow by path. Use this to call another flow as a subflow","properties":{"input_transforms":{"type":"object","description":"Map of parameter names to their values (static or JavaScript expressions). These become the subflow's input arguments","additionalProperties":{"$ref":"#/components/schemas/InputTransform"}},"path":{"type":"string","description":"Path to the flow in the workspace (e.g., 'f/flows/process_user')"},"type":{"type":"string","enum":["flow"]}},"required":["type","path","input_transforms"]},"ForloopFlow":{"type":"object","description":"Executes nested modules in a loop over an iterator. Inside the loop, use 'flow_input.iter.value' to access the current iteration value, and 'flow_input.iter.index' for the index. Supports parallel execution for better performance on I/O-bound operations","properties":{"modules":{"type":"array","description":"Steps to execute for each iteration. These can reference the iteration value via 'flow_input.iter.value'","items":{"$ref":"#/components/schemas/FlowModule"}},"iterator":{"description":"JavaScript expression that returns an array to iterate over. Can reference 'results.step_id' or 'flow_input'","$ref":"#/components/schemas/InputTransform"},"skip_failures":{"type":"boolean","description":"If true, iteration failures don't stop the loop. Failed iterations return null"},"type":{"type":"string","enum":["forloopflow"]},"parallel":{"type":"boolean","description":"If true, iterations run concurrently (faster for I/O-bound operations). Use with parallelism to control concurrency"},"parallelism":{"description":"Maximum number of concurrent iterations when parallel=true. Limits resource usage. Can be static number or expression","$ref":"#/components/schemas/InputTransform"},"squash":{"type":"boolean"}},"required":["modules","iterator","skip_failures","type"]},"WhileloopFlow":{"type":"object","description":"Executes nested modules repeatedly until stopped. The implicit iterator is the iteration counter, so 'flow_input.iter.value' equals 'flow_input.iter.index' (0, 1, 2, ...) and never carries state. To carry state across iterations, a step reads its own previous-iteration result via 'results.<its_own_id>' with a first-iteration fallback - the loop's stop_after_if must then be on that inner step (a plain single-step body with stop_after_if on the loop module does not resolve 'results' across iterations and never terminates); plain counters can instead be derived from 'flow_input.iter.index', which works in every configuration. stop_after_if is evaluated after each iteration - on the loop module 'result' is the last iteration's result","properties":{"modules":{"type":"array","description":"Steps to execute in each iteration","items":{"$ref":"#/components/schemas/FlowModule"}},"skip_failures":{"type":"boolean","description":"If true, iteration failures don't stop the loop. Failed iterations return null"},"type":{"type":"string","enum":["whileloopflow"]},"parallel":{"type":"boolean","description":"If true, iterations run concurrently (use with caution in while loops)"},"parallelism":{"description":"Maximum number of concurrent iterations when parallel=true","$ref":"#/components/schemas/InputTransform"},"squash":{"type":"boolean"}},"required":["modules","skip_failures","type"]},"BranchOne":{"type":"object","description":"Conditional branching where only the first matching branch executes. Branches are evaluated in order, and the first one with a true expression runs. If no branches match, the default branch executes","properties":{"branches":{"type":"array","description":"Array of branches to evaluate in order. The first branch with expr evaluating to true executes","items":{"type":"object","properties":{"summary":{"type":"string","description":"Short description of this branch condition"},"expr":{"type":"string","description":"JavaScript expression that returns boolean. Can use 'results.step_id' or 'flow_input'. First true expr wins"},"modules":{"type":"array","description":"Steps to execute if this branch's expr is true","items":{"$ref":"#/components/schemas/FlowModule"}}},"required":["modules","expr"]}},"default":{"type":"array","description":"Steps to execute if no branch expressions match","items":{"$ref":"#/components/schemas/FlowModule"}},"type":{"type":"string","enum":["branchone"]}},"required":["branches","default","type"]},"BranchAll":{"type":"object","description":"Parallel branching where all branches execute simultaneously. Unlike BranchOne, all branches run regardless of conditions. Useful for executing independent tasks concurrently","properties":{"branches":{"type":"array","description":"Array of branches that all execute (either in parallel or sequentially)","items":{"type":"object","properties":{"summary":{"type":"string","description":"Short description of this branch's purpose"},"skip_failure":{"type":"boolean","description":"If true, failure in this branch doesn't fail the entire flow"},"modules":{"type":"array","description":"Steps to execute in this branch","items":{"$ref":"#/components/schemas/FlowModule"}}},"required":["modules"]}},"type":{"type":"string","enum":["branchall"]},"parallel":{"type":"boolean","description":"If true, all branches execute concurrently. If false, they execute sequentially"}},"required":["branches","type"]},"AgentTool":{"type":"object","description":"A tool available to an AI agent. Can be a flow module or an external MCP (Model Context Protocol) tool","properties":{"id":{"type":"string","description":"Unique identifier for this tool. Cannot contain spaces - use underscores instead (e.g., 'get_user_data' not 'get user data')"},"summary":{"type":"string","description":"The name the AI agent calls this tool by, not a human label. On a flowmodule tool it must match ^[a-zA-Z0-9_]+$ - letters, numbers and underscores only (e.g. 'search_documentation', not 'Search documentation') - and always be set; on an mcp, websearch or question tool it is a plain label. Put the human-readable explanation in 'description'."},"description":{"type":"string","description":"Free-text description of the tool given to the AI to decide when and how to call it. Overrides the description auto-derived from the underlying script."},"job_token_scopes":{"type":"array","nullable":true,"items":{"type":"string"},"description":"Scopes the token of this tool's jobs is restricted to, on top of the agent step's own restriction: a tool can only narrow it."},"requires_approval":{"type":"boolean","description":"Flowmodule and mcp tools only. Each call waits for a person to approve or reject it from the flow's run page or chat, without the agent holding a worker. Calls in the same turn that do not require approval run right away. A rejected call, or one nobody answers within 30 minutes, is reported to the AI as not run."},"value":{"$ref":"#/components/schemas/ToolValue"}},"required":["id","value"]},"ToolValue":{"description":"The implementation of a tool. Can be a flow module (script/flow) or an MCP tool reference","oneOf":[{"$ref":"#/components/schemas/FlowModuleTool"},{"$ref":"#/components/schemas/McpToolValue"},{"$ref":"#/components/schemas/WebsearchToolValue"},{"$ref":"#/components/schemas/QuestionToolValue"}],"discriminator":{"propertyName":"tool_type","mapping":{"flowmodule":"#/components/schemas/FlowModuleTool","mcp":"#/components/schemas/McpToolValue","websearch":"#/components/schemas/WebsearchToolValue","question":"#/components/schemas/QuestionToolValue"}}},"FlowModuleTool":{"description":"A tool implemented as a flow module (script, flow, etc.). The AI can call this like any other flow module","allOf":[{"type":"object","properties":{"tool_type":{"type":"string","enum":["flowmodule"]}},"required":["tool_type"]},{"$ref":"#/components/schemas/FlowModuleValue"}]},"WebsearchToolValue":{"type":"object","description":"A tool implemented as a websearch tool. The AI can call this like any other websearch tool","properties":{"tool_type":{"type":"string","enum":["websearch"]}},"required":["tool_type"]},"QuestionToolValue":{"type":"object","description":"Built-in tool the AI calls as ask_question: the agent stops, releasing its worker, until someone answers from the flow's run page or chat or the question times out, then resumes with the answer as the tool result.","properties":{"tool_type":{"type":"string","enum":["question"]},"timeout":{"type":"integer","description":"Seconds to wait for an answer before the question is reported to the AI as timed out. Defaults to 1800."}},"required":["tool_type"]},"McpToolValue":{"type":"object","description":"Reference to an external MCP (Model Context Protocol) tool. The AI can call tools from MCP servers","properties":{"tool_type":{"type":"string","enum":["mcp"]},"resource_path":{"type":"string","description":"Path to the MCP resource/server configuration"},"include_tools":{"type":"array","description":"Whitelist of specific tools to include from this MCP server","items":{"type":"string"}},"exclude_tools":{"type":"array","description":"Blacklist of tools to exclude from this MCP server","items":{"type":"string"}}},"required":["tool_type","resource_path"]},"AiAgent":{"type":"object","description":"AI agent step that can use tools to accomplish tasks. The agent receives inputs and can call any of its configured tools to complete the task","properties":{"input_transforms":{"type":"object","description":"Input parameters for the AI agent mapped to their values","properties":{"provider":{"$ref":"#/components/schemas/ProviderTransform"},"output_type":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"Output format type.\nValid values: 'text' (default) - plain text response, 'image' - image generation\n"},"user_message":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"The user's prompt/message to the AI agent. Supports variable interpolation with\nflow.input syntax. Required unless memory is off and `previous_messages` supplies\nthe prompt; image output always needs it.\n"},"system_prompt":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"System instructions that guide the AI's behavior, persona, and response style. Optional."},"streaming":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"Boolean. If true, stream the AI response incrementally.\nStreaming events include: token_delta, reasoning_token_delta, tool_call, tool_call_arguments, tool_execution, tool_result\n"},"memory":{"$ref":"#/components/schemas/MemoryTransform"},"memory_id":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"String. Names the memory this step reads and writes, overriding the memory id the run\nwas started with (the chat conversation, an app chat session or the `memory_id` run\nparameter). Leave unset to use the run's memory id. A fixed value shares one memory\nacross every run; an expression such as `flow_input.customer_id` keeps one memory per\nkey. When it evaluates to an empty value the agent runs without memory. Read only\nwhile `memory` is `window` or `compaction`: it is ignored when memory is off, and an\nolder `auto` or `manual` memory reads neither history input.\n"},"previous_messages":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"Array of MemoryMessage. History supplied by the flow, sent between the system prompt\nand the user message. Read only while `memory` is off or absent: managed memory\nignores it, and an older `auto` or `manual` memory reads neither history input.\n"},"output_schema":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"JSON Schema object defining structured output format. Used when you need the AI to return data in a specific shape.\nSupports standard JSON Schema properties: type, properties, required, items, enum, pattern, minLength, maxLength, minimum, maximum, etc.\nExample: { type: 'object', properties: { name: { type: 'string' }, age: { type: 'integer' } }, required: ['name'] }\n"},"user_attachments":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"Array of file references (images or PDFs) for the AI agent.\nFormat: Array<{ bucket: string, key: string }> - S3 object references\nExample: [{ bucket: 'my-bucket', key: 'documents/report.pdf' }]\n"},"enabled_tools":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"Array of strings naming which of the tools configured in `tools` the agent may call\nthis run. Leaving it unset carries every one of them; an empty array carries none.\nA tool is named as the model is shown it. An entry the model is shown nothing of is\nnamed by what identifies it instead: an MCP server by its resource path, carrying\nevery tool it exposes (which of them stays that entry's include_tools/exclude_tools),\nand a websearch entry by the reserved name '__wm_web_search', whatever summary it carries\n(no tool may take that name).\nExample: ['get_user', 'u/admin/github_mcp', '__wm_web_search']\n"},"max_completion_tokens":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"Integer. Maximum number of tokens the AI will generate in its response.\nRange: 1 to 4,294,967,295. Typical values: 256-4096 for most use cases.\n"},"temperature":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"Float. Controls randomness/creativity of responses.\nRange: 0.0 to 2.0 (provider-dependent)\n- 0.0 = deterministic, focused responses\n- 0.7 = balanced (common default)\n- 1.0+ = more creative/random\n"},"max_iterations":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"Number. Limits how many times the agent can loop through reasoning and tool use.\nRange: 1-1000.\n"},"model":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"String. Only on a step linked to a saved agent (see `agent`): replaces the model\nsaved on the agent for this step's runs, on the agent's own provider resource. An\nempty value keeps the saved model. Set it to an expression such as\n`flow_input.model` to choose the model per run.\n"},"reasoning_effort":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"String. Only on a step linked to a saved agent (see `agent`): replaces the reasoning\neffort saved on the agent for this step's runs, as a provider-native token (e.g.\n'low', 'high', 'none'). An empty value sends no effort, so the model runs at its\ndefault. Leave the input out to keep the saved effort, which holds only while the\nstep runs the saved model. A step that is not linked sets both inside `provider`.\n"}}},"tools":{"type":"array","description":"Array of tools the agent can use. The agent decides which tools to call based on the task","items":{"$ref":"#/components/schemas/AgentTool"}},"type":{"type":"string","enum":["aiagent"]},"tag":{"type":"string","description":"Worker group tag for execution routing. If not set, the AI agent step runs on the flow's tag (default `flow`)"},"omit_output_from_conversation":{"type":"boolean","default":false,"description":"If true, this AI agent step does not persist its assistant or tool messages to the flow conversation when chat mode is enabled."},"agent":{"type":"string","description":"Path of a reusable `ai_agent` resource (hybrid linking). When set, the agent brain\nconfig (provider/model/system prompt/etc.) and tool set are resolved at runtime from\nthat resource; the module's input_transforms then only carry the flow-local inputs\n(user_message, user_attachments, enabled_tools and the history inputs memory_id and previous_messages)\nand, optionally, the `model` and `reasoning_effort` overrides of what the agent saved.\n"},"tool_inputs":{"type":"object","description":"Host-local wiring for an agent's tool inputs, keyed by tool id then input key. Binds the\nreferenced agent's tools to this flow's context (flow_input/results) without mutating the\nshared resource; overlaid onto the tools' input_transforms at runtime \u2014 including when\n`agent` is unset, since a step forked for editing keeps these overrides until it is saved\nback or unlinked.\n","additionalProperties":{"type":"object","additionalProperties":{"$ref":"#/components/schemas/InputTransform"}}},"parallel":{"type":"boolean","description":"If true, the agent can execute multiple tool calls in parallel"}},"required":["type","input_transforms"]},"AiDecision":{"type":"object","description":"AI decision step: one call to a decision model (TypeSafe's Jev, Cloudflare's\nJev-compatible Clef, or OpenAI's Decisions API) that answers typed questions about a\nstate with calibrated probabilities, instead of generating text.\nPrefer it over an AI agent to classify, route, score or check something: it is fast,\ncheap and its answers are structured. Its result is { output: { <question name>: answer },\nmodel, usage }, so a later step reads e.g. results.<id>.output.intent.choice. To route on\nthe answers, follow it with a branchone whose branch exprs read\nresults.<id>.output.<question>.choice. Usable as an AI agent tool, where the calling agent\nsupplies the state.\n","properties":{"input_transforms":{"type":"object","description":"Input parameters for the decision mapped to their values","properties":{"provider":{"$ref":"#/components/schemas/ProviderTransform"},"state":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"What the questions are asked about: a string, an object or an array of strings.\nAn object with descriptive keys holding only what the questions need works best.\nExample: { message: flow_input.message, plan: results.a.plan }\n"},"questions":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"Object mapping each question name to { type, instructions, criteria }, where type is:\n- 'choice': criteria maps each option to its description (up to 255); the answer\n has choice, probabilities and confidence\n- 'score': criteria is an ordered array of 2 to 10 level descriptions; the answer\n has score, legend, probabilities and confidence\n- 'noul': yes/no, criteria optionally { true, false } descriptions; the answer has\n noul, the probability of yes (0 to 1)\nExample: { intent: { type: 'choice', instructions: 'What does the customer want?',\ncriteria: { refund: 'Money back', bug: 'Something is broken' } } }\n"}},"required":["provider","state","questions"]},"type":{"type":"string","enum":["aidecision"]},"tag":{"type":"string","description":"Worker group tag for execution routing. If not set, the step runs on the flow's tag (default `flow`)"}},"required":["type","input_transforms"]},"Identity":{"type":"object","description":"Pass-through module that returns its input unchanged. Useful for flow structure or as a placeholder","properties":{"type":{"type":"string","enum":["identity"]},"flow":{"type":"boolean","description":"If true, marks this as a flow identity (special handling)"}},"required":["type"]},"FlowStatus":{"type":"object","properties":{"step":{"type":"integer"},"modules":{"type":"array","items":{"$ref":"#/components/schemas/FlowStatusModule"}},"user_states":{"additionalProperties":true},"preprocessor_module":{"allOf":[{"$ref":"#/components/schemas/FlowStatusModule"}]},"failure_module":{"allOf":[{"$ref":"#/components/schemas/FlowStatusModule"},{"type":"object","properties":{"parent_module":{"type":"string"}}}]},"retry":{"type":"object","properties":{"fail_count":{"type":"integer"},"failed_jobs":{"type":"array","items":{"type":"string","format":"uuid"}}}}},"required":["step","modules","failure_module"]},"FlowStatusModule":{"type":"object","properties":{"type":{"type":"string","enum":["WaitingForPriorSteps","WaitingForEvents","WaitingForExecutor","InProgress","Success","Failure"]},"id":{"type":"string"},"job":{"type":"string","format":"uuid"},"count":{"type":"integer"},"progress":{"type":"integer"},"iterator":{"type":"object","properties":{"index":{"type":"integer"},"itered":{"type":"array","items":{}},"itered_len":{"type":"integer"},"args":{}}},"flow_jobs":{"type":"array","items":{"type":"string"}},"flow_jobs_success":{"type":"array","items":{"type":"boolean"}},"flow_jobs_duration":{"type":"object","properties":{"started_at":{"type":"array","items":{"type":"string"}},"duration_ms":{"type":"array","items":{"type":"integer"}}}},"branch_chosen":{"type":"object","properties":{"type":{"type":"string","enum":["branch","default"]},"branch":{"type":"integer"}},"required":["type"]},"branchall":{"type":"object","properties":{"branch":{"type":"integer"},"len":{"type":"integer"}},"required":["branch","len"]},"approvers":{"type":"array","items":{"type":"object","properties":{"resume_id":{"type":"integer"},"approver":{"type":"string"}},"required":["resume_id","approver"]}},"failed_retries":{"type":"array","items":{"type":"string","format":"uuid"}},"skipped":{"type":"boolean"},"agent_actions":{"type":"array","items":{"type":"object","oneOf":[{"type":"object","properties":{"job_id":{"type":"string","format":"uuid"},"function_name":{"type":"string"},"type":{"type":"string","enum":["tool_call"]},"module_id":{"type":"string"}},"required":["job_id","function_name","type","module_id"]},{"type":"object","properties":{"call_id":{"type":"string","format":"uuid"},"function_name":{"type":"string"},"resource_path":{"type":"string"},"type":{"type":"string","enum":["mcp_tool_call"]},"arguments":{"type":"object"}},"required":["call_id","function_name","resource_path","type"]},{"type":"object","properties":{"type":{"type":"string","enum":["web_search"]}},"required":["type"]},{"type":"object","properties":{"type":{"type":"string","enum":["approval"]},"call_id":{"type":"string"},"calls":{"type":"array","items":{"type":"object","properties":{"function_name":{"type":"string"},"arguments":{}},"required":["function_name","arguments"]}},"expires_at":{"type":"string","format":"date-time"}},"required":["type","call_id","calls","expires_at"]},{"type":"object","properties":{"type":{"type":"string","enum":["question"]},"call_id":{"type":"string"},"question":{"type":"string"},"choices":{"type":"array","items":{"type":"string"},"description":"answers the model proposes; a free-text answer is always possible"},"multi_select":{"type":"boolean","description":"whether several choices can be picked together"},"expires_at":{"type":"string","format":"date-time"}},"required":["type","call_id","question","expires_at"]},{"type":"object","properties":{"type":{"type":"string","enum":["message"]}},"required":["content","type"]}]}},"agent_actions_success":{"type":"array","items":{"type":"boolean"}}},"required":["type"]}} diff --git a/system_prompts/base/flow-base.md b/system_prompts/base/flow-base.md index 80a83e948a..bc5542145e 100644 --- a/system_prompts/base/flow-base.md +++ b/system_prompts/base/flow-base.md @@ -68,7 +68,10 @@ value: An `aiagent` module runs an LLM that can call tools. Each entry of `value.tools` is a module-shaped object with an extra `value.tool_type`: `flowmodule` for a script/flow tool, `mcp` for an MCP server -tool, `websearch` for web search. +tool, `websearch` for web search, `question` for a built-in `ask_question` tool (the agent stops, +without holding a worker, until someone answers from the run page or the chat; optional +`value.timeout` in seconds, default 1800). Set `requires_approval: true` on a `flowmodule` or `mcp` +tool to have a person approve or reject each of its calls before it runs. ```json { @@ -164,9 +167,9 @@ needs becomes unreachable. ### Tool Naming Rules -These rules cover `flowmodule` tools, the ones the agent calls by name. A `websearch` tool's -`summary` is a plain label (`Web Search`), and an `mcp` tool exposes the MCP server's own tool -names, so neither is name-checked at all — leave those summaries as they are. +These rules cover `flowmodule` tools, the ones the agent calls by name. A `websearch` or `question` +tool's `summary` is a plain label (`Web Search`), and an `mcp` tool exposes the MCP +server's own tool names, so none is name-checked at all — leave those summaries as they are. - A flowmodule tool's `summary` is the **name the agent calls it by**, not a human label. Put the human-readable explanation in `description`