From 2bdaea579085ef03112a1bd188c59da69499f681 Mon Sep 17 00:00:00 2001 From: hugocasa Date: Mon, 12 Oct 2026 10:45:08 +0200 Subject: [PATCH] feat: let a linked agent step override the model and reasoning effort --- backend/windmill-worker/src/ai_executor.rs | 61 ++++++++ cli/src/guidance/skills.gen.ts | 6 +- frontend/src/lib/components/ModuleTest.svelte | 4 +- .../copilot/chat/flow/openFlow.json | 2 +- .../copilot/chat/flow/openFlowZod.gen.ts | 4 +- .../components/copilot/chat/global/core.ts | 6 +- .../lib/components/flows/agentFormFields.ts | 43 ++++- .../flows/agentResourceUtils.test.ts | 37 +++++ .../components/flows/agentResourceUtils.ts | 90 ++++++++++- .../flows/content/AgentResourceBar.svelte | 20 ++- .../flows/content/AiAgentStepInputs.svelte | 135 +++++++++++++--- .../flows/content/FlowModuleComponent.svelte | 12 +- .../conversations/FlowChatInterface.svelte | 28 +++- .../FlowChatModelSettings.svelte | 5 +- .../conversations/agentChatInputs.test.ts | 48 ++++++ .../flows/conversations/agentChatInputs.ts | 147 ++++++++++++++---- .../src/lib/components/flows/flowInfers.ts | 21 ++- openflow.openapi.yaml | 17 ++ system_prompts/auto-generated/flow.md | 6 +- system_prompts/auto-generated/prompts.ts | 6 +- .../auto-generated/skills/write-flow/SKILL.md | 6 +- system_prompts/base/flow-base.md | 4 + 22 files changed, 615 insertions(+), 93 deletions(-) diff --git a/backend/windmill-worker/src/ai_executor.rs b/backend/windmill-worker/src/ai_executor.rs index 1b889aea34..2ccbdc42a9 100644 --- a/backend/windmill-worker/src/ai_executor.rs +++ b/backend/windmill-worker/src/ai_executor.rs @@ -260,6 +260,31 @@ fn keep_authored_memory_id( } } +/// A step's own `model` and `reasoning_effort` inputs replace the provider's, which is how a step +/// linked to a saved agent picks them per run. An empty value keeps the provider's. A reasoning +/// token is per model, so a different model without an effort of its own runs at its default. +fn override_provider_model( + provider: &mut ProviderWithResource, + local_args: &HashMap>, +) { + let given = |key: &str| { + local_args + .get(key) + .and_then(|v| serde_json::from_str::(v.get()).ok()) + .map(|s| s.trim().to_string()) + .filter(|s| !s.is_empty()) + }; + if let Some(model) = given("model") { + if model != provider.model { + provider.model = model; + provider.reasoning_effort = None; + } + } + if let Some(effort) = given("reasoning_effort") { + provider.reasoning_effort = Some(effort); + } +} + /// Reconciles the step's history inputs, the agent's memory policy and the run's memory id. A step /// holds one of two shapes: an older `auto` or `manual` memory, read as the editor that wrote it /// meant it, or the current setting plus the step's own history inputs. Also returns lines for the @@ -854,6 +879,7 @@ pub async fn handle_ai_agent_job( }; keep_authored_memory_id(&mut args, &step_input_transforms); + override_provider_model(&mut args.provider, &local_args); // Nesting is capped at flow → agent → nested agent. When this job is itself a nested tool, // a linked resource's tool set may still contain AIAgent or AIDecision tools (the editor can't @@ -2940,6 +2966,41 @@ mod tests { assert!(bounded_prompt_cache_key(&long).len() <= 64); } + #[test] + fn step_model_and_effort_replace_the_providers() { + use serde_json::json; + let run = |step: serde_json::Value| { + let mut provider: ProviderWithResource = serde_json::from_value(json!({ + "kind": "openai", + "resource": {}, + "model": "saved-model", + "reasoning_effort": "high" + })) + .unwrap(); + let local_args = serde_json::from_value(step).unwrap(); + override_provider_model(&mut provider, &local_args); + (provider.model, provider.reasoning_effort) + }; + let saved = ("saved-model".to_string(), Some("high".to_string())); + + assert_eq!(run(json!({})), saved); + assert_eq!(run(json!({ "model": "", "reasoning_effort": null })), saved); + assert_eq!(run(json!({ "model": "saved-model" })), saved); + assert_eq!( + run(json!({ "reasoning_effort": "low" })), + ("saved-model".to_string(), Some("low".to_string())) + ); + // The saved effort names a level of the saved model, so it does not follow to another one. + assert_eq!( + run(json!({ "model": "other" })), + ("other".to_string(), None) + ); + assert_eq!( + run(json!({ "model": "other", "reasoning_effort": "low" })), + ("other".to_string(), Some("low".to_string())) + ); + } + #[test] fn overlay_tool_inputs_binds_matching_flowmodule_tool_only() { fn js(expr: &str) -> InputTransform { diff --git a/cli/src/guidance/skills.gen.ts b/cli/src/guidance/skills.gen.ts index eb5d46ef57..f96226378b 100644 --- a/cli/src/guidance/skills.gen.ts +++ b/cli/src/guidance/skills.gen.ts @@ -5880,6 +5880,10 @@ needs becomes unreachable. references. A spread, a call or a computed key leaves the composer unable to tell which input feeds which field, so it offers no control at all — a bare \`flow_input.x\` for the whole object is read instead as that one input carrying every field +- A step linked to a saved agent (\`agent\` set) has no \`provider\` of its own. It exposes the same + two controls through its \`model\` and \`reasoning_effort\` inputs, which replace what the agent + saved: \`"model": { "type": "javascript", "expr": "flow_input.model" }\`. An empty value keeps the + saved one, and the provider resource always stays the agent's - \`memory\` is what lets the agent see earlier turns; without it every message starts from nothing - \`streaming\` on makes the answer and its thinking appear token by token instead of all at once - \`user_attachments\` points at a flow input typed as an array of s3 objects @@ -6330,7 +6334,7 @@ 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-' (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 '$res:path' (resource).","additionalProperties":{}},"priority":{"type":"number","description":"Execution priority (higher numbers run first)"},"early_return":{"type":"string","description":"JavaScript expression to return early from the flow"},"chat_input_enabled":{"type":"boolean","description":"Whether this flow accepts chat-style input"},"notes":{"type":"array","description":"Sticky notes attached to the flow","items":{"$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":[{"$ref":"#/components/schemas/InputTransform"}],"description":"Number. Limits how many times the agent can loop through reasoning and tool use.\\nRange: 1-1000.\\n"}}},"tools":{"type":"array","description":"Array of tools the agent can use. The agent decides which tools to call based on the task","items":{"$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 \\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"]}} +{"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 '$res:path' (resource).","additionalProperties":{}},"priority":{"type":"number","description":"Execution priority (higher numbers run first)"},"early_return":{"type":"string","description":"JavaScript expression to return early from the flow"},"chat_input_enabled":{"type":"boolean","description":"Whether this flow accepts chat-style input"},"notes":{"type":"array","description":"Sticky notes attached to the flow","items":{"$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":[{"$ref":"#/components/schemas/InputTransform"}],"description":"String. Only on a step linked to a saved agent (see \`agent\`): replaces the reasoning\\neffort saved on the agent for this step's runs, as a provider-native token (e.g.\\n'low', 'high', 'none'). An empty value keeps the saved effort, unless \`model\`\\nreplaces the saved model, which then runs at its default effort. A step that is\\nnot linked sets both inside \`provider\`.\\n"}}},"tools":{"type":"array","description":"Array of tools the agent can use. The agent decides which tools to call based on the task","items":{"$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).\\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"]}} `, "raw-app": `--- name: raw-app diff --git a/frontend/src/lib/components/ModuleTest.svelte b/frontend/src/lib/components/ModuleTest.svelte index 8d2b51e8d0..0842b49a32 100644 --- a/frontend/src/lib/components/ModuleTest.svelte +++ b/frontend/src/lib/components/ModuleTest.svelte @@ -19,7 +19,7 @@ normalizeAgentRef, type LinkedAgentDraft } from './flows/linkedAgentDrafts' - import { AGENT_FLOW_LOCAL_KEYS } from './flows/agentResourceUtils' + import { AGENT_LINKED_STEP_KEYS } from './flows/agentResourceUtils' import { agentTestInputTransforms } from './flows/agentFormFields' import { sendUserToast } from '$lib/toast' import { quickjsReady } from '$lib/utils/quickjsEval.svelte' @@ -186,7 +186,7 @@ const inputTransforms = agentTestInputTransforms( agentVal.agent ? {} : ((agentVal.input_transforms ?? {}) as Record), args, - draft ? AGENT_FLOW_LOCAL_KEYS : Object.keys(args) + draft ? AGENT_LINKED_STEP_KEYS : Object.keys(args) ) await jobLoader?.runFlowPreview( diff --git a/frontend/src/lib/components/copilot/chat/flow/openFlow.json b/frontend/src/lib/components/copilot/chat/flow/openFlow.json index 11cee5b724..8e2dddefe9 100644 --- a/frontend/src/lib/components/copilot/chat/flow/openFlow.json +++ b/frontend/src/lib/components/copilot/chat/flow/openFlow.json @@ -1 +1 @@ -{"openapi":"3.0.3","info":{"version":"1.825.0","title":"OpenFlow Spec","contact":{"name":"Ruben Fiszel","email":"ruben@windmill.dev","url":"https://windmill.dev"},"license":{"name":"Apache 2.0","url":"https://www.apache.org/licenses/LICENSE-2.0.html"}},"paths":{},"externalDocs":{"description":"documentation portal","url":"https://windmill.dev"},"components":{"schemas":{"OpenFlow":{"type":"object","description":"Top-level flow definition containing metadata, configuration, and the flow structure","properties":{"summary":{"type":"string","description":"Short description of what this flow does"},"description":{"type":"string","description":"Detailed documentation for this flow"},"value":{"$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-' (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 '$res:path' (resource).","additionalProperties":{}},"priority":{"type":"number","description":"Execution priority (higher numbers run first)"},"early_return":{"type":"string","description":"JavaScript expression to return early from the flow"},"chat_input_enabled":{"type":"boolean","description":"Whether this flow accepts chat-style input"},"notes":{"type":"array","description":"Sticky notes attached to the flow","items":{"$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","$ref":"#/components/schemas/StopAfterIf"},"skip_if":{"type":"object","description":"Conditionally skip this step based on previous results or flow inputs","properties":{"expr":{"type":"string","description":"JavaScript expression that returns true to skip. Can use 'flow_input' or 'results.'"}},"required":["expr"]},"sleep":{"description":"Delay before executing this step (in seconds or as expression)","$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"}},"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.' 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":{"$ref":"#/components/schemas/InputTransform"}}},"parallel":{"type":"boolean","description":"If true, the agent can execute multiple tool calls in parallel"}},"required":["type","input_transforms"]},"AiDecision":{"type":"object","description":"AI decision step: one call to a decision model (TypeSafe's Jev, Cloudflare's\nJev-compatible Clef, or OpenAI's Decisions API) that answers typed questions about a\nstate with calibrated probabilities, instead of generating text.\nPrefer it over an AI agent to classify, route, score or check something: it is fast,\ncheap and its answers are structured. Its result is { output: { : answer },\nmodel, usage }, so a later step reads e.g. results..output.intent.choice. To route on\nthe answers, follow it with a branchone whose branch exprs read\nresults..output..choice. Usable as an AI agent tool, where the calling agent\nsupplies the state.\n","properties":{"input_transforms":{"type":"object","description":"Input parameters for the decision mapped to their values","properties":{"provider":{"$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"]}}}} \ No newline at end of file +{"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-' (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 '$res:path' (resource).","additionalProperties":{}},"priority":{"type":"number","description":"Execution priority (higher numbers run first)"},"early_return":{"type":"string","description":"JavaScript expression to return early from the flow"},"chat_input_enabled":{"type":"boolean","description":"Whether this flow accepts chat-style input"},"notes":{"type":"array","description":"Sticky notes attached to the flow","items":{"$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","$ref":"#/components/schemas/StopAfterIf"},"skip_if":{"type":"object","description":"Conditionally skip this step based on previous results or flow inputs","properties":{"expr":{"type":"string","description":"JavaScript expression that returns true to skip. Can use 'flow_input' or 'results.'"}},"required":["expr"]},"sleep":{"description":"Delay before executing this step (in seconds or as expression)","$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"}},"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.' 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":[{"$ref":"#/components/schemas/InputTransform"}],"description":"Number. Limits how many times the agent can loop through reasoning and tool use.\nRange: 1-1000.\n"},"model":{"allOf":[{"$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":[{"$ref":"#/components/schemas/InputTransform"}],"description":"String. Only on a step linked to a saved agent (see `agent`): replaces the reasoning\neffort saved on the agent for this step's runs, as a provider-native token (e.g.\n'low', 'high', 'none'). An empty value keeps the saved effort, unless `model`\nreplaces the saved model, which then runs at its default effort. A step that is\nnot linked sets both inside `provider`.\n"}}},"tools":{"type":"array","description":"Array of tools the agent can use. The agent decides which tools to call based on the task","items":{"$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).\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":{"$ref":"#/components/schemas/InputTransform"}}},"parallel":{"type":"boolean","description":"If true, the agent can execute multiple tool calls in parallel"}},"required":["type","input_transforms"]},"AiDecision":{"type":"object","description":"AI decision step: one call to a decision model (TypeSafe's Jev, Cloudflare's\nJev-compatible Clef, or OpenAI's Decisions API) that answers typed questions about a\nstate with calibrated probabilities, instead of generating text.\nPrefer it over an AI agent to classify, route, score or check something: it is fast,\ncheap and its answers are structured. Its result is { output: { : answer },\nmodel, usage }, so a later step reads e.g. results..output.intent.choice. To route on\nthe answers, follow it with a branchone whose branch exprs read\nresults..output..choice. Usable as an AI agent tool, where the calling agent\nsupplies the state.\n","properties":{"input_transforms":{"type":"object","description":"Input parameters for the decision mapped to their values","properties":{"provider":{"$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"]}}}} \ 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 88cb8fe875..b327b27de3 100644 --- a/frontend/src/lib/components/copilot/chat/flow/openFlowZod.gen.ts +++ b/frontend/src/lib/components/copilot/chat/flow/openFlowZod.gen.ts @@ -1,6 +1,6 @@ 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. 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.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.lazy(() => flowModuleValueSchema), "stop_after_if": z.object({ "skip_if_stopped": z.boolean().describe("If true, following steps are skipped when this condition triggers").optional(), "expr": z.string().describe("JavaScript expression evaluated after the module runs. Can use 'result' (step's result) or 'flow_input'. Return true to stop"), "error_message": z.string().nullable().describe("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.").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(), "stop_after_all_iters_if": z.object({ "skip_if_stopped": z.boolean().describe("If true, following steps are skipped when this condition triggers").optional(), "expr": z.string().describe("JavaScript expression evaluated after the module runs. Can use 'result' (step's result) or 'flow_input'. Return true to stop"), "error_message": z.string().nullable().describe("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.").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.'") }).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. Use for hardcoded values or resource references like '$res:path/to/resource'"), z.object({ "expr": z.string().describe("JavaScript expression returning the value. Available variables - results (object with all previous step results), flow_input (flow inputs), flow_input.iter (in loops)"), "type": z.literal("javascript") }).describe("JavaScript expression evaluated at runtime. Can reference previous step results via 'results.step_id' or flow inputs via 'flow_input.property'. Inside for loops, use 'flow_input.iter.value' for the current iteration value (in while loops it equals 'flow_input.iter.index')"), z.object({ "type": z.literal("ai") }).describe("Value resolved by the AI runtime for this input. The AI engine decides how to satisfy the parameter.")]).describe("Maps input parameters for a step. Can be a static value or a JavaScript expression that references previous results or flow inputs").optional(), "cache_ttl": z.number().describe("Cache duration in seconds for this step's results").optional(), "cache_ignore_s3_path": z.boolean().optional(), "timeout": z.discriminatedUnion("type", [z.object({ "value": z.any().describe("The static value. For resources, use format '$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. 'detailed' (used when unset) shows the flow details (arguments, graph, approvers); 'minimal' shows only the request: the step description, form and approve/reject actions").optional() }).describe("Configuration for approval/resume steps that wait for user input").optional(), "priority": z.number().describe("Execution priority for this step (higher numbers run first)").optional(), "continue_on_error": z.boolean().describe("If true, flow continues even if this step fails").optional(), "job_token_scopes": z.array(z.string()).nullable().describe("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).").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. Has access to 'result' and 'error' variables") }).describe("Conditional retry based on error or result").optional() }).describe("Retry configuration for failed module executions").optional(), "debouncing": z.object({ "debounce_delay_s": z.number().int().describe("Delay in seconds to debounce this step's executions across flow runs").optional(), "debounce_key": z.string().describe("Expression to group debounced executions. Supports $workspace and $args[name]. Default: $workspace/flow/-").optional(), "debounce_args_to_accumulate": z.array(z.string()).describe("Array-type arguments to accumulate across debounced executions").optional(), "max_total_debouncing_time": z.number().int().describe("Maximum total time in seconds before forced execution").optional(), "max_total_debounces_amount": z.number().int().describe("Maximum number of debounces before forced execution").optional() }).describe("Debounce configuration for this step (EE only)").optional() }).describe("A single step in a flow. Can be a script, subflow, loop, or branch")).describe("Steps to execute for each iteration. These can reference the iteration value via 'flow_input.iter.value'"), "iterator": z.discriminatedUnion("type", [z.object({ "value": z.any().describe("The static value. For resources, use format '$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.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.lazy(() => flowModuleValueSchema), "stop_after_if": z.object({ "skip_if_stopped": z.boolean().describe("If true, following steps are skipped when this condition triggers").optional(), "expr": z.string().describe("JavaScript expression evaluated after the module runs. Can use 'result' (step's result) or 'flow_input'. Return true to stop"), "error_message": z.string().nullable().describe("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.").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(), "stop_after_all_iters_if": z.object({ "skip_if_stopped": z.boolean().describe("If true, following steps are skipped when this condition triggers").optional(), "expr": z.string().describe("JavaScript expression evaluated after the module runs. Can use 'result' (step's result) or 'flow_input'. Return true to stop"), "error_message": z.string().nullable().describe("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.").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.'") }).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. Use for hardcoded values or resource references like '$res:path/to/resource'"), z.object({ "expr": z.string().describe("JavaScript expression returning the value. Available variables - results (object with all previous step results), flow_input (flow inputs), flow_input.iter (in loops)"), "type": z.literal("javascript") }).describe("JavaScript expression evaluated at runtime. Can reference previous step results via 'results.step_id' or flow inputs via 'flow_input.property'. Inside for loops, use 'flow_input.iter.value' for the current iteration value (in while loops it equals 'flow_input.iter.index')"), z.object({ "type": z.literal("ai") }).describe("Value resolved by the AI runtime for this input. The AI engine decides how to satisfy the parameter.")]).describe("Maps input parameters for a step. Can be a static value or a JavaScript expression that references previous results or flow inputs").optional(), "cache_ttl": z.number().describe("Cache duration in seconds for this step's results").optional(), "cache_ignore_s3_path": z.boolean().optional(), "timeout": z.discriminatedUnion("type", [z.object({ "value": z.any().describe("The static value. For resources, use format '$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. 'detailed' (used when unset) shows the flow details (arguments, graph, approvers); 'minimal' shows only the request: the step description, form and approve/reject actions").optional() }).describe("Configuration for approval/resume steps that wait for user input").optional(), "priority": z.number().describe("Execution priority for this step (higher numbers run first)").optional(), "continue_on_error": z.boolean().describe("If true, flow continues even if this step fails").optional(), "job_token_scopes": z.array(z.string()).nullable().describe("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).").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. Has access to 'result' and 'error' variables") }).describe("Conditional retry based on error or result").optional() }).describe("Retry configuration for failed module executions").optional(), "debouncing": z.object({ "debounce_delay_s": z.number().int().describe("Delay in seconds to debounce this step's executions across flow runs").optional(), "debounce_key": z.string().describe("Expression to group debounced executions. Supports $workspace and $args[name]. Default: $workspace/flow/-").optional(), "debounce_args_to_accumulate": z.array(z.string()).describe("Array-type arguments to accumulate across debounced executions").optional(), "max_total_debouncing_time": z.number().int().describe("Maximum total time in seconds before forced execution").optional(), "max_total_debounces_amount": z.number().int().describe("Maximum number of debounces before forced execution").optional() }).describe("Debounce configuration for this step (EE only)").optional() }).describe("A single step in a flow. 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Can reference previous step results via 'results.step_id' or flow inputs via 'flow_input.property'. Inside for loops, use 'flow_input.iter.value' for the current iteration value (in while loops it equals 'flow_input.iter.index')"), z.object({ "type": z.literal("ai") }).describe("Value resolved by the AI runtime for this input. The AI engine decides how to satisfy the parameter.")]).describe("Maps input parameters for a step. Can be a static value or a JavaScript expression that references previous results or flow inputs").optional(), "cache_ttl": z.number().describe("Cache duration in seconds for this step's results").optional(), "cache_ignore_s3_path": z.boolean().optional(), "timeout": z.discriminatedUnion("type", [z.object({ "value": z.any().describe("The static value. For resources, use format '$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. 'detailed' (used when unset) shows the flow details (arguments, graph, approvers); 'minimal' shows only the request: the step description, form and approve/reject actions").optional() }).describe("Configuration for approval/resume steps that wait for user input").optional(), "priority": z.number().describe("Execution priority for this step (higher numbers run first)").optional(), "continue_on_error": z.boolean().describe("If true, flow continues even if this step fails").optional(), "job_token_scopes": z.array(z.string()).nullable().describe("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).").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. Has access to 'result' and 'error' variables") }).describe("Conditional retry based on error or result").optional() }).describe("Retry configuration for failed module executions").optional(), "debouncing": z.object({ "debounce_delay_s": z.number().int().describe("Delay in seconds to debounce this step's executions across flow runs").optional(), "debounce_key": z.string().describe("Expression to group debounced executions. Supports $workspace and $args[name]. Default: $workspace/flow/-").optional(), "debounce_args_to_accumulate": z.array(z.string()).describe("Array-type arguments to accumulate across debounced executions").optional(), "max_total_debouncing_time": z.number().int().describe("Maximum total time in seconds before forced execution").optional(), "max_total_debounces_amount": z.number().int().describe("Maximum number of debounces before forced execution").optional() }).describe("Debounce configuration for this step (EE only)").optional() }).describe("A single step in a flow. Can be a script, subflow, loop, or branch")).describe("Steps to execute in this branch") })).describe("Array of branches that all execute (either in parallel or sequentially)"), "type": z.literal("branchall"), "parallel": z.boolean().describe("If true, all branches execute concurrently. If false, they execute sequentially").optional() }).describe("Parallel branching where all branches execute simultaneously. Unlike BranchOne, all branches run regardless of conditions. Useful for executing independent tasks concurrently"), z.object({ "type": z.literal("identity"), "flow": z.boolean().describe("If true, marks this as a flow identity (special handling)").optional() }).describe("Pass-through module that returns its input unchanged. Useful for flow structure or as a placeholder"), z.object({ "input_transforms": z.object({ "provider": z.discriminatedUnion("type", [z.object({ "value": z.object({ "kind": z.enum(["openai","azure_openai","azure_foundry","anthropic","mistral","deepseek","googleai","groq","openrouter","togetherai","customai","aws_bedrock","typesafe","cloudflare"]).describe("Supported AI provider types"), "resource": z.string().describe("Resource reference in format '$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() }).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) => { +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). 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.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.lazy(() => flowModuleValueSchema), "stop_after_if": z.object({ "skip_if_stopped": z.boolean().describe("If true, following steps are skipped when this condition triggers").optional(), "expr": z.string().describe("JavaScript expression evaluated after the module runs. Can use 'result' (step's result) or 'flow_input'. Return true to stop"), "error_message": z.string().nullable().describe("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.").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(), "stop_after_all_iters_if": z.object({ "skip_if_stopped": z.boolean().describe("If true, following steps are skipped when this condition triggers").optional(), "expr": z.string().describe("JavaScript expression evaluated after the module runs. Can use 'result' (step's result) or 'flow_input'. Return true to stop"), "error_message": z.string().nullable().describe("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.").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.'") }).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 '$res:path/to/resource'").optional(), "type": z.literal("static") }).describe("Static value passed directly to the step. Use for hardcoded values or resource references like '$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(), "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. 'detailed' (used when unset) shows the flow details (arguments, graph, approvers); 'minimal' shows only the request: the step description, form and approve/reject actions").optional() }).describe("Configuration for approval/resume steps that wait for user input").optional(), "priority": z.number().describe("Execution priority for this step (higher numbers run first)").optional(), "continue_on_error": z.boolean().describe("If true, flow continues even if this step fails").optional(), "job_token_scopes": z.array(z.string()).nullable().describe("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).").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. Has access to 'result' and 'error' variables") }).describe("Conditional retry based on error or result").optional() }).describe("Retry configuration for failed module executions").optional(), "debouncing": z.object({ "debounce_delay_s": z.number().int().describe("Delay in seconds to debounce this step's executions across flow runs").optional(), "debounce_key": z.string().describe("Expression to group debounced executions. Supports $workspace and $args[name]. Default: $workspace/flow/-").optional(), "debounce_args_to_accumulate": z.array(z.string()).describe("Array-type arguments to accumulate across debounced executions").optional(), "max_total_debouncing_time": z.number().int().describe("Maximum total time in seconds before forced execution").optional(), "max_total_debounces_amount": z.number().int().describe("Maximum number of debounces before forced execution").optional() }).describe("Debounce configuration for this step (EE only)").optional() }).describe("A single step in a flow. Can be a script, subflow, loop, or branch")).describe("Steps to execute for each iteration. These can reference the iteration value via 'flow_input.iter.value'"), "iterator": z.discriminatedUnion("type", [z.object({ "value": z.any().describe("The static value. For resources, use format '$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.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.lazy(() => flowModuleValueSchema), "stop_after_if": z.object({ "skip_if_stopped": z.boolean().describe("If true, following steps are skipped when this condition triggers").optional(), "expr": z.string().describe("JavaScript expression evaluated after the module runs. Can use 'result' (step's result) or 'flow_input'. Return true to stop"), "error_message": z.string().nullable().describe("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.").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(), "stop_after_all_iters_if": z.object({ "skip_if_stopped": z.boolean().describe("If true, following steps are skipped when this condition triggers").optional(), "expr": z.string().describe("JavaScript expression evaluated after the module runs. Can use 'result' (step's result) or 'flow_input'. Return true to stop"), "error_message": z.string().nullable().describe("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.").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.'") }).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. Use for hardcoded values or resource references like '$res:path/to/resource'"), z.object({ "expr": z.string().describe("JavaScript expression returning the value. Available variables - results (object with all previous step results), flow_input (flow inputs), flow_input.iter (in loops)"), "type": z.literal("javascript") }).describe("JavaScript expression evaluated at runtime. Can reference previous step results via 'results.step_id' or flow inputs via 'flow_input.property'. Inside for loops, use 'flow_input.iter.value' for the current iteration value (in while loops it equals 'flow_input.iter.index')"), z.object({ "type": z.literal("ai") }).describe("Value resolved by the AI runtime for this input. The AI engine decides how to satisfy the parameter.")]).describe("Maps input parameters for a step. Can be a static value or a JavaScript expression that references previous results or flow inputs").optional(), "cache_ttl": z.number().describe("Cache duration in seconds for this step's results").optional(), "cache_ignore_s3_path": z.boolean().optional(), "timeout": z.discriminatedUnion("type", [z.object({ "value": z.any().describe("The static value. For resources, use format '$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. 'detailed' (used when unset) shows the flow details (arguments, graph, approvers); 'minimal' shows only the request: the step description, form and approve/reject actions").optional() }).describe("Configuration for approval/resume steps that wait for user input").optional(), "priority": z.number().describe("Execution priority for this step (higher numbers run first)").optional(), "continue_on_error": z.boolean().describe("If true, flow continues even if this step fails").optional(), "job_token_scopes": z.array(z.string()).nullable().describe("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).").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. Has access to 'result' and 'error' variables") }).describe("Conditional retry based on error or result").optional() }).describe("Retry configuration for failed module executions").optional(), "debouncing": z.object({ "debounce_delay_s": z.number().int().describe("Delay in seconds to debounce this step's executions across flow runs").optional(), "debounce_key": z.string().describe("Expression to group debounced executions. Supports $workspace and $args[name]. Default: $workspace/flow/-").optional(), "debounce_args_to_accumulate": z.array(z.string()).describe("Array-type arguments to accumulate across debounced executions").optional(), "max_total_debouncing_time": z.number().int().describe("Maximum total time in seconds before forced execution").optional(), "max_total_debounces_amount": z.number().int().describe("Maximum number of debounces before forced execution").optional() }).describe("Debounce configuration for this step (EE only)").optional() }).describe("A single step in a flow. Can be a script, subflow, loop, or branch")).describe("Steps to execute in each iteration"), "skip_failures": z.boolean().describe("If true, iteration failures don't stop the loop. Failed iterations return null"), "type": z.literal("whileloopflow"), "parallel": z.boolean().describe("If true, iterations run concurrently (use with caution in while loops)").optional(), "parallelism": z.discriminatedUnion("type", [z.object({ "value": z.any().describe("The static value. For resources, use format '$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. 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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. 'detailed' (used when unset) shows the flow details (arguments, graph, approvers); 'minimal' shows only the request: the step description, form and approve/reject actions").optional() }).describe("Configuration for approval/resume steps that wait for user input").optional(), "priority": z.number().describe("Execution priority for this step (higher numbers run first)").optional(), "continue_on_error": z.boolean().describe("If true, flow continues even if this step fails").optional(), "job_token_scopes": z.array(z.string()).nullable().describe("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).").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. Has access to 'result' and 'error' variables") }).describe("Conditional retry based on error or result").optional() }).describe("Retry configuration for failed module executions").optional(), "debouncing": z.object({ "debounce_delay_s": z.number().int().describe("Delay in seconds to debounce this step's executions across flow runs").optional(), "debounce_key": z.string().describe("Expression to group debounced executions. Supports $workspace and $args[name]. Default: $workspace/flow/-").optional(), "debounce_args_to_accumulate": z.array(z.string()).describe("Array-type arguments to accumulate across debounced executions").optional(), "max_total_debouncing_time": z.number().int().describe("Maximum total time in seconds before forced execution").optional(), "max_total_debounces_amount": z.number().int().describe("Maximum number of debounces before forced execution").optional() }).describe("Debounce configuration for this step (EE only)").optional() }).describe("A single step in a flow. Can be a script, subflow, loop, or branch")).describe("Steps to execute in this branch") })).describe("Array of branches that all execute (either in parallel or sequentially)"), "type": z.literal("branchall"), "parallel": z.boolean().describe("If true, all branches execute concurrently. If false, they execute sequentially").optional() }).describe("Parallel branching where all branches execute simultaneously. Unlike BranchOne, all branches run regardless of conditions. Useful for executing independent tasks concurrently"), z.object({ "type": z.literal("identity"), "flow": z.boolean().describe("If true, marks this as a flow identity (special handling)").optional() }).describe("Pass-through module that returns its input unchanged. Useful for flow structure or as a placeholder"), z.object({ "input_transforms": z.object({ "provider": z.discriminatedUnion("type", [z.object({ "value": z.object({ "kind": z.enum(["openai","azure_openai","azure_foundry","anthropic","mistral","deepseek","googleai","groq","openrouter","togetherai","customai","aws_bedrock","typesafe","cloudflare"]).describe("Supported AI provider types"), "resource": z.string().describe("Resource reference in format '$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 keeps the saved effort, unless `model`\nreplaces the saved model, which then runs at its default effort. A step that is\nnot 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")]; const errors = schemas.reduce( (errors, schema) => @@ -20,7 +20,7 @@ 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).\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: { : 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")]).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.' 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() }).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) => { +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.' 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 '$res:path/to/resource'"), z.object({ "expr": z.string().describe("JavaScript expression returning the value. Available variables - results (object with all previous step results), flow_input (flow inputs), flow_input.iter (in loops)"), "type": z.literal("javascript") }).describe("JavaScript expression evaluated at runtime. Can reference previous step results via 'results.step_id' or flow inputs via 'flow_input.property'. Inside for loops, use 'flow_input.iter.value' for the current iteration value (in while loops it equals 'flow_input.iter.index')"), z.object({ "type": z.literal("ai") }).describe("Value resolved by the AI runtime for this input. The AI engine decides how to satisfy the parameter.")]).describe("Maps input parameters for a step. Can be a static value or a JavaScript expression that references previous results or flow inputs").describe("String. Only on a step linked to a saved agent (see `agent`): replaces the reasoning\neffort saved on the agent for this step's runs, as a provider-native token (e.g.\n'low', 'high', 'none'). An empty value keeps the saved effort, unless `model`\nreplaces the saved model, which then runs at its default effort. A step that is\nnot linked sets both inside `provider`.\n").optional() }).describe("Input parameters for the AI agent mapped to their values"), "tools": z.array(z.object({ "id": z.string().describe("Unique identifier for this tool. Cannot contain spaces - use underscores instead (e.g., 'get_user_data' not 'get user data')"), "summary": z.string().describe("The name the AI agent calls this tool by, not a human label. On a flowmodule tool it must match ^[a-zA-Z0-9_]+$ - 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")]; const errors = schemas.reduce( (errors, schema) => diff --git a/frontend/src/lib/components/copilot/chat/global/core.ts b/frontend/src/lib/components/copilot/chat/global/core.ts index 2a795f1f81..ce804b77ec 100644 --- a/frontend/src/lib/components/copilot/chat/global/core.ts +++ b/frontend/src/lib/components/copilot/chat/global/core.ts @@ -46,7 +46,7 @@ import type { ScriptLang } from '$lib/gen/types.gen' import { loadSchemaFromModule, memoryPropertyFor } from '$lib/components/flows/flowInfers' -import { flowLocalAgentSchema } from '$lib/components/flows/agentResourceUtils' +import { linkedAgentStepSchema } from '$lib/components/flows/agentResourceUtils' import { AGENT_FIELDS, initialVisibleAgentFields } from '$lib/components/flows/agentFormFields' import { withAgentDrafts } from '$lib/components/flows/linkedAgentDrafts' import { resolveLinkedAgentTools } from '$lib/components/flows/flowState' @@ -6092,9 +6092,9 @@ async function agentStepRunForm( ): Promise<{ schema: Record; args: Record }> { const transforms = (module.value as { input_transforms?: Record }).input_transforms // A linked step's brain belongs to the resource rather than to this flow, so only the inputs - // this flow supplies are its to edit. + // this flow supplies, and its overrides, are its to edit. const full = (await loadSchemaFromModule(module, workspace)).schema - const schema = (module.value as { agent?: string }).agent ? flowLocalAgentSchema(full) : full + const schema = (module.value as { agent?: string }).agent ? linkedAgentStepSchema(full) : full const visible = initialVisibleAgentFields(transforms, schema.properties) // What the model asked to set, shown even where the step configures nothing: this form has no diff --git a/frontend/src/lib/components/flows/agentFormFields.ts b/frontend/src/lib/components/flows/agentFormFields.ts index e8c5584407..5a5736edf3 100644 --- a/frontend/src/lib/components/flows/agentFormFields.ts +++ b/frontend/src/lib/components/flows/agentFormFields.ts @@ -10,15 +10,21 @@ import type { InputTransform, MemoryConfig } from '$lib/gen' * the two cannot cycle. */ -export type AgentFieldGroup = 'model' | 'messages' | 'tools' | 'output' +export type AgentFieldGroup = 'model' | 'messages' | 'tools' | 'output' | 'overrides' /** Groups in the order a run assembles the request: pick a model, build the messages, let it call - * tools, shape what comes back. */ -export const AGENT_FIELD_GROUPS: { id: AgentFieldGroup; label: string }[] = [ + * tools, shape what comes back. Overrides come last: only a step linked to a saved agent has + * them, and they replace what the agent saved rather than add to the request. */ +export const AGENT_FIELD_GROUPS: { id: AgentFieldGroup; label: string; caption?: string }[] = [ { id: 'model', label: 'Model' }, { id: 'messages', label: 'Messages' }, { id: 'tools', label: 'Tools' }, - { id: 'output', label: 'Output' } + { id: 'output', label: 'Output' }, + { + id: 'overrides', + label: 'Agent overrides', + caption: "Replace what is saved on the agent, for this step's runs only." + } ] /** The tool roster, which reads `flowModule.value.tools` rather than an `input_transforms` key. @@ -30,6 +36,17 @@ export const AGENT_TOOLS_ROW = 'tools' export const AGENT_HISTORY_KEYS = ['memory_id', 'previous_messages'] as const export type AgentHistoryKey = (typeof AGENT_HISTORY_KEYS)[number] +/** A linked step's overrides of its saved agent. Never seeded either: a step with no override + * holds no key for one. */ +export const AGENT_OVERRIDE_KEYS = ['model', 'reasoning_effort'] as const +export type AgentOverrideKey = (typeof AGENT_OVERRIDE_KEYS)[number] + +/** The inputs whose row exists exactly while the step holds the key. */ +export const AGENT_UNSEEDED_KEYS: readonly string[] = [ + ...AGENT_HISTORY_KEYS, + ...AGENT_OVERRIDE_KEYS +] + /** The input transforms a one-off test of an agent step runs with: each form key is fed from * `flow_input`, over the step's own transforms. A blank history input is unset, as on the step: * an expression evaluating to nothing reads as an empty memory id, and the step's transform is @@ -256,6 +273,24 @@ export const AGENT_FIELDS: AgentFieldSpec[] = [ implicit: true, defaultHint: 'Default: on', textOnly: true + }, + { + key: 'model', + group: 'overrides', + label: 'Model', + tooltip: + "Runs this step on another model than the one saved on the agent, through the agent's own provider resource. Set it to an expression to choose the model per run: an empty value keeps the saved model.", + implicit: '', + defaultHint: 'Default: the model saved on the agent' + }, + { + key: 'reasoning_effort', + group: 'overrides', + label: 'Reasoning effort', + tooltip: + 'Runs this step at another reasoning effort than the one saved on the agent. Set it to an expression to choose the effort per run: an empty value keeps the saved effort. Overriding the model without it runs that model at its default effort.', + implicit: '', + defaultHint: 'Default: the effort saved on the agent' } ] diff --git a/frontend/src/lib/components/flows/agentResourceUtils.test.ts b/frontend/src/lib/components/flows/agentResourceUtils.test.ts index 96b9cf83ff..24546be928 100644 --- a/frontend/src/lib/components/flows/agentResourceUtils.test.ts +++ b/frontend/src/lib/components/flows/agentResourceUtils.test.ts @@ -6,6 +6,7 @@ import { flowLocalInputs, inputTransformsToAgentConfig, nonStaticBrainKeys, + providerWithOverrides, summarizeAgentBrain, toolInputOverrides, transformValuedBrainKeys @@ -193,3 +194,39 @@ describe('toolInputOverrides', () => { }) }) }) + +describe('providerWithOverrides', () => { + const saved = { + kind: 'openai', + resource: '$res:u/a/openai', + model: 'gpt-5', + reasoning_effort: 'high' + } + + it('folds static overrides into a static provider, as the worker reads them', () => { + expect( + providerWithOverrides(saved, { reasoning_effort: { type: 'static', value: 'low' } }) + ).toEqual({ type: 'static', value: { ...saved, reasoning_effort: 'low' } }) + // The saved effort names a level of the saved model, so it does not follow to another one. + expect( + providerWithOverrides(saved, { model: { type: 'static', value: 'gpt-5-mini' } }) + ).toEqual({ + type: 'static', + value: { kind: 'openai', resource: '$res:u/a/openai', model: 'gpt-5-mini' } + }) + expect(providerWithOverrides(saved, { model: { type: 'static', value: '' } })).toEqual({ + type: 'static', + value: saved + }) + }) + + it('keeps an expression, falling back to the saved value when it is empty', () => { + const folded = providerWithOverrides(saved, { + reasoning_effort: { type: 'javascript', expr: 'flow_input.effort' } + }) as { type: 'javascript'; expr: string } + expect(folded.type).toBe('javascript') + const run = (effort: unknown) => new Function('flow_input', `return ${folded.expr}`)({ effort }) + expect(run('low')).toEqual({ ...saved, reasoning_effort: 'low' }) + expect(run('')).toEqual(saved) + }) +}) diff --git a/frontend/src/lib/components/flows/agentResourceUtils.ts b/frontend/src/lib/components/flows/agentResourceUtils.ts index 3ee0eaa77e..290c303d3a 100644 --- a/frontend/src/lib/components/flows/agentResourceUtils.ts +++ b/frontend/src/lib/components/flows/agentResourceUtils.ts @@ -1,6 +1,11 @@ import { deepEqual } from 'fast-equals' import type { InputTransform } from '$lib/gen' -import { AGENT_FIELDS, describeMemoryPolicy } from './agentFormFields' +import { + AGENT_FIELDS, + AGENT_OVERRIDE_KEYS, + describeMemoryPolicy, + type AgentOverrideKey +} from './agentFormFields' // The brain fields stored flat in an `ai_agent` resource value. The flow-local inputs below are // intentionally excluded — they are supplied per-flow. @@ -31,6 +36,13 @@ export const AGENT_FLOW_LOCAL_KEYS = [ 'previous_messages' ] as const +/** Every input a linked step holds itself: the flow-local ones, and its overrides of what the + * agent saved inside `provider`. */ +export const AGENT_LINKED_STEP_KEYS: readonly string[] = [ + ...AGENT_FLOW_LOCAL_KEYS, + ...AGENT_OVERRIDE_KEYS +] + export type AgentTool = Record /** @@ -59,7 +71,7 @@ export function nonStaticBrainKeys( } /** - * Keep only the flow-local inputs on a step's input_transforms. Used when linking: the brain comes + * Keep only the inputs a linked step holds on a step's input_transforms. Used when linking: the brain comes * from the resource, so the step must not carry stale `provider`/`system_prompt`/… transforms — at * runtime they'd still be resolved (an unnecessary, possibly failing provider `$res:` fetch) yet * never used, since the linked branch takes the brain from the resource. @@ -68,7 +80,7 @@ export function flowLocalInputs( inputTransforms: Record | undefined ): Record { const out: Record = {} - for (const key of AGENT_FLOW_LOCAL_KEYS) { + for (const key of AGENT_LINKED_STEP_KEYS) { if (inputTransforms?.[key]) { out[key] = inputTransforms[key] } @@ -149,6 +161,76 @@ export function flowLocalAgentSchema(schema: any): any { } } +/** + * The schema of a step linked to a saved agent, in a flow: its flow-local inputs, plus the saved + * settings it may override. + */ +export function linkedAgentStepSchema(schema: any): any { + const local = flowLocalAgentSchema(schema) + if (!local?.properties) { + return local + } + return { + ...local, + properties: { + ...local.properties, + model: { + type: 'string', + description: "Replaces the model saved on the agent for this step's runs." + }, + reasoning_effort: { + type: 'string', + description: "Replaces the reasoning effort saved on the agent for this step's runs." + } + }, + order: [...local.order, ...AGENT_OVERRIDE_KEYS] + } +} + +/** + * The `provider` of a step unlinked from its agent: the saved one with the step's overrides folded + * in, since an unlinked step sets model and effort nowhere else. Mirrors the worker: an empty + * override keeps the saved value, and another model drops the saved effort. + */ +export function providerWithOverrides( + provider: any, + overrides: Partial> | undefined +): InputTransform | undefined { + if (!provider || typeof provider !== 'object') return undefined + const set = (key: AgentOverrideKey): any => { + const t = overrides?.[key] as any + if (t?.type === 'javascript' && t.expr) return t + if (t?.type === 'static' && typeof t.value === 'string' && t.value.trim()) return t + return undefined + } + const model = set('model') + const effort = set('reasoning_effort') + const folded = { ...provider } + if (model && !(model.type === 'static' && model.value.trim() === provider.model) && !effort) { + delete folded.reasoning_effort + } + if (model?.type !== 'javascript' && effort?.type !== 'javascript') { + if (model) folded.model = model.value.trim() + if (effort) folded.reasoning_effort = effort.value.trim() + return { type: 'static', value: folded } + } + const field = (key: AgentOverrideKey, t: any) => { + if (!t) return folded[key] === undefined ? [] : [`${key}: ${JSON.stringify(folded[key])}`] + if (t.type === 'static') return [`${key}: ${JSON.stringify(t.value.trim())}`] + const saved = folded[key] === undefined ? 'undefined' : JSON.stringify(folded[key]) + return [`${key}: (${t.expr}) || ${saved}`] + } + const { model: _m, reasoning_effort: _e, ...rest } = folded + const fields = [ + ...Object.entries(rest).map( + ([key, value]) => `${JSON.stringify(key)}: ${JSON.stringify(value)}` + ), + ...field('model', model), + ...field('reasoning_effort', effort) + ] + return { type: 'javascript', expr: `({ ${fields.join(', ')} })` } +} + /** Read off the form's own registry, so a linked agent's summary cannot name a field differently * from the form that edits it. */ export const AGENT_BRAIN_LABELS: Record = Object.fromEntries( @@ -182,7 +264,7 @@ export function summarizeAgentBrain( if (v === undefined || v === null || v === '') continue let value: string if (key === 'provider') { - value = [v.kind, v.model].filter(Boolean).join(' · ') || 'configured' + value = [v.kind, v.model, v.reasoning_effort].filter(Boolean).join(' · ') || 'configured' } else if (key === 'memory') { value = typeof v === 'object' ? describeMemoryPolicy(v) : String(v) } else if (key === 'output_schema') { diff --git a/frontend/src/lib/components/flows/content/AgentResourceBar.svelte b/frontend/src/lib/components/flows/content/AgentResourceBar.svelte index 3359f20080..6aa5a902e8 100644 --- a/frontend/src/lib/components/flows/content/AgentResourceBar.svelte +++ b/frontend/src/lib/components/flows/content/AgentResourceBar.svelte @@ -18,6 +18,7 @@ flowLocalInputs, inputTransformsToAgentConfig, nonStaticBrainKeys, + providerWithOverrides, summarizeAgentBrain, type AIAgentConfig, type AgentTool @@ -61,7 +62,7 @@ flowPath = '', fromAgentEditor = false, chatInputEnabled = false, - linkedMemory = $bindable() + linkedAgent = $bindable() }: { agent: string | undefined inputTransforms: Record @@ -80,8 +81,9 @@ // is the wrong way in. fromAgentEditor?: boolean chatInputEnabled?: boolean - // The linked agent's memory once its config has loaded, for the step's history inputs. - linkedMemory?: { memory: unknown } | undefined + // The linked agent's memory and provider once its config has loaded, for the step's history + // inputs and its overrides. + linkedAgent?: { memory: unknown; provider?: unknown } | undefined } = $props() let ws = $derived(opWorkspace ?? $operatingWorkspace) @@ -226,7 +228,9 @@ loadedInfo?.ws === ws && loadedInfo?.path === agent ? loadedInfo : undefined ) $effect(() => { - linkedMemory = linkedInfo ? { memory: linkedInfo.config?.memory } : undefined + linkedAgent = linkedInfo + ? { memory: linkedInfo.config?.memory, provider: linkedInfo.config?.provider } + : undefined }) let inheritedTools = $derived(linkedInfo?.tools ?? []) let brainParams = $derived(summarizeAgentBrain(linkedInfo?.config)) @@ -512,7 +516,13 @@ local[key] = inputTransforms[key] } } - const forkedInputs = { ...agentConfigToInputTransforms(cfg), ...local } + // An unlinked step sets model and effort inside `provider`, so its overrides move there. + const provider = providerWithOverrides(cfg.provider, inputTransforms) + const forkedInputs = { + ...agentConfigToInputTransforms(cfg), + ...(provider ? { provider } : {}), + ...local + } const forkedTools = cfg.tools ?? [] inputTransforms = forkedInputs for (const tool of forkedTools) { diff --git a/frontend/src/lib/components/flows/content/AiAgentStepInputs.svelte b/frontend/src/lib/components/flows/content/AiAgentStepInputs.svelte index 4e7c7692a5..dcb1b795cf 100644 --- a/frontend/src/lib/components/flows/content/AiAgentStepInputs.svelte +++ b/frontend/src/lib/components/flows/content/AiAgentStepInputs.svelte @@ -29,7 +29,7 @@