From 818ddd5d31bd81507e274dd18022c1cdbd9be842 Mon Sep 17 00:00:00 2001 From: Ruben Fiszel Date: Wed, 7 Oct 2026 12:52:01 +0200 Subject: [PATCH 01/34] feat: default new raw apps to react 19 and ask for the data setup (#11586) * feat: default new raw apps to react 19 and ask for the data setup Co-Authored-By: Claude Opus 5.5 (1M context) * fix: say what app new --schema writes and soften the already-set-up wording Co-Authored-By: Claude Opus 5.5 (1M context) * fix: resolve bare init_app table names in the app schema, fix --schema help Co-Authored-By: Claude Opus 5.5 (1M context) --------- Co-authored-by: Claude Opus 5.5 (1M context) --- ai_evals/README.md | 6 + .../frontend/core/global/globalEvalRunner.ts | 2 + .../frontend/core/shared/baseEvalRunner.ts | 7 ++ .../adapters/frontend/core/shared/types.ts | 3 + ai_evals/cases/global.yaml | 107 +++++++++++++++++- ai_evals/core/types.ts | 4 + ai_evals/modes/global.ts | 1 + cli/src/commands/app/new.ts | 2 +- cli/src/guidance/core.ts | 2 +- cli/src/guidance/skills.gen.ts | 71 +++++++++--- .../copilot/chat/global/core.test.ts | 19 ++++ .../components/copilot/chat/global/core.ts | 56 +++++++-- .../auto-generated/cli/cli-commands.md | 2 +- system_prompts/auto-generated/prompts.ts | 37 +++++- .../skills/cli-commands/SKILL.md | 2 +- .../auto-generated/skills/raw-app/SKILL.md | 69 ++++++++--- system_prompts/base/raw-app-cli.md | 37 +++--- system_prompts/base/raw-app.md | 40 +++++++ 18 files changed, 407 insertions(+), 60 deletions(-) diff --git a/ai_evals/README.md b/ai_evals/README.md index bff4294e52..88623c7f33 100644 --- a/ai_evals/README.md +++ b/ai_evals/README.md @@ -164,6 +164,12 @@ the decrypted value, exactly as against a real backend. The chat's read path pas Seed a recognizable secret (the existing fixture uses `sk_live_do_not_leak_me`) and assert it via `valueExcludes` to catch a leak. +`runtime.userAnswers` scripts the user's side of `askUserQuestion` in a global case: one +answer per question, in the order they are asked, and a question past the last answer is +dismissed, so `userAnswers: []` dismisses every question. Without it the tool reports that +it cannot ask, and the model usually carries on with its own guess, which makes "asks +before creating anything" impossible to assert. + `toolExpect.toolCallArgs` entries support `sharedByAtLeast: `: at least `n` recorded calls to that tool must carry the same non-blank string in the field. Use it for calls that have to share an identifier, like two test runs of one chat conversation. diff --git a/ai_evals/adapters/frontend/core/global/globalEvalRunner.ts b/ai_evals/adapters/frontend/core/global/globalEvalRunner.ts index be8c1d74cc..fe20d77d05 100644 --- a/ai_evals/adapters/frontend/core/global/globalEvalRunner.ts +++ b/ai_evals/adapters/frontend/core/global/globalEvalRunner.ts @@ -123,6 +123,7 @@ export interface GlobalEvalOptions { planMode?: boolean; model?: string; maxIterations?: number; + userAnswers?: string[]; provider?: AIProvider; backend: WindmillBackendSettings; workspaceRoot?: string; @@ -220,6 +221,7 @@ export async function runGlobalEval( onToolCall: options.runContext?.onToolCall, options: { maxIterations: options.maxIterations, + userAnswers: options.userAnswers, model, workspace: workspaceRoot, provider: options.provider, diff --git a/ai_evals/adapters/frontend/core/shared/baseEvalRunner.ts b/ai_evals/adapters/frontend/core/shared/baseEvalRunner.ts index 3d0c6d6734..13aaa59806 100644 --- a/ai_evals/adapters/frontend/core/shared/baseEvalRunner.ts +++ b/ai_evals/adapters/frontend/core/shared/baseEvalRunner.ts @@ -85,6 +85,7 @@ export async function runEval( const model = options.model ?? "gpt-4o"; const maxIterations = options.maxIterations ?? 20; + const pendingAnswers = options.userAnswers && [...options.userAnswers]; const workspace = options.workspace ?? "test-workspace"; const provider = toFrontendEvalProvider(options.provider); @@ -138,6 +139,12 @@ export async function runEval( // edit the arguments, so a case can assert what the model proposed but never how // it reacts to the user changing something. requestRunArgs: async (_toolId, form) => form.args, + ...(pendingAnswers && { + requestUserQuestion: async () => { + const answer = pendingAnswers.shift(); + return answer === undefined ? undefined : [answer]; + }, + }), onNewToken: (token: string) => { if (shouldEmitMessageStart) { onAssistantMessageStart?.(); diff --git a/ai_evals/adapters/frontend/core/shared/types.ts b/ai_evals/adapters/frontend/core/shared/types.ts index c7af6c43e7..1ff783e258 100644 --- a/ai_evals/adapters/frontend/core/shared/types.ts +++ b/ai_evals/adapters/frontend/core/shared/types.ts @@ -16,6 +16,9 @@ export interface ToolCallDetail { export interface EvalRunnerOptions { backend: WindmillBackendSettings; maxIterations?: number; + // Scripted answers to the model's questions, one per question in order; a question past + // the last one is dismissed. Unset, the run cannot be asked anything. + userAnswers?: string[]; model?: string; workspace?: string; provider?: AIProvider; diff --git a/ai_evals/cases/global.yaml b/ai_evals/cases/global.yaml index 476218a066..b66af3e8dd 100644 --- a/ai_evals/cases/global.yaml +++ b/ai_evals/cases/global.yaml @@ -198,22 +198,127 @@ - uses the requested placeholder value and description - does not create a resource or deploy anything +# A new app that has to store data, with nothing said about where: the data setup is the +# user's call, so it is asked before anything is created. The question is dismissed here, +# which leaves nothing the model may build on. - id: global-test7-ambiguous-app-asks-question prompt: |- Create a new raw app for triaging support tickets. + initial: ai_evals/fixtures/frontend/global/initial/datatable_orders_seed.json runtime: - maxTurns: 4 + maxTurns: 6 + userAnswers: [] validate: draftCountExactly: 0 toolExpect: requiredToolsUsed: + - list_datatables - askUserQuestion forbiddenToolsUsed: - init_app + - exec_datatable_sql - write_app_file - write_app_runnable - deploy_workspace_item - delete_workspace_item + toolCallArgs: + - tool: askUserQuestion + field: question + stringIncludesAnyOf: + - data table + - datatable + - schema + - tables + - store + skipJudge: true + +# The same request with the question answered: the app is built on what the user chose. +- id: global-new-app-data-setup-answer-applied + prompt: |- + Create a new raw app for triaging support tickets. + initial: ai_evals/fixtures/frontend/global/initial/datatable_orders_seed.json + runtime: + maxTurns: 32 + userAnswers: + - A new schema named helpdesk + - Create new tables + validate: + draftCountExactly: 1 + requiredDrafts: + - type: app + valueIncludes: + - helpdesk + - react-dom/client + toolExpect: + requiredToolsUsed: + - askUserQuestion + - init_app + forbiddenToolsUsed: + - deploy_workspace_item + toolCallArgs: + - tool: init_app + field: framework + stringEqualsAnyOf: + - react19 + - tool: exec_datatable_sql + field: sql + stringIncludesAnyOf: + - helpdesk + skipJudge: true + +# No framework named, no app to follow, nothing to store: the modal's recommended +# framework is used without a question. +- id: global-new-app-defaults-to-react19 + prompt: |- + Build me a little app that converts temperatures between Celsius and Fahrenheit. + runtime: + maxTurns: 12 + validate: + draftCountExactly: 1 + requiredDrafts: + - type: app + valueIncludes: + - react-dom/client + toolExpect: + requiredToolsUsed: + - init_app + forbiddenToolsUsed: + - askUserQuestion + - exec_datatable_sql + - deploy_workspace_item + toolCallArgs: + - tool: init_app + field: framework + stringEqualsAnyOf: + - react19 + skipJudge: true + +# The user said where the data goes, so there is nothing left to ask. +- id: global-new-app-storage-specified-no-question + prompt: |- + Build a todo list app in React. Keep the todos in the main data table, in a new + schema called todo_app. + initial: ai_evals/fixtures/frontend/global/initial/datatable_orders_seed.json + runtime: + maxTurns: 20 + validate: + draftCountExactly: 1 + requiredDrafts: + - type: app + valueIncludes: + - todo_app + toolExpect: + requiredToolsUsed: + - init_app + - write_app_runnable + forbiddenToolsUsed: + - askUserQuestion + - deploy_workspace_item + toolCallArgs: + - tool: exec_datatable_sql + field: sql + stringIncludesAnyOf: + - todo_app skipJudge: true - id: global-test8-human-script-infer-path-language diff --git a/ai_evals/core/types.ts b/ai_evals/core/types.ts index 832a383a73..7e70191992 100644 --- a/ai_evals/core/types.ts +++ b/ai_evals/core/types.ts @@ -29,6 +29,10 @@ export interface EvalCaseRuntimeAppContextSpec { export interface EvalCaseRuntimeSpec { maxTurns?: number; + // Global mode: scripted answers to askUserQuestion, one per question in order; a question + // past the last one is dismissed, so `[]` dismisses them all. Unset, the question tool + // reports that it cannot ask. + userAnswers?: string[]; backendPreview?: EvalCaseRuntimeBackendPreview; appContext?: EvalCaseRuntimeAppContextSpec; // Global mode: run as a session chat (preview tools + session prompt) vs the standalone chat. diff --git a/ai_evals/modes/global.ts b/ai_evals/modes/global.ts index bf90988907..238a82a759 100644 --- a/ai_evals/modes/global.ts +++ b/ai_evals/modes/global.ts @@ -54,6 +54,7 @@ export function createGlobalModeRunner( sessionChat: context.evalCase?.runtime?.sessionChat, planMode: context.evalCase?.runtime?.planMode, maxIterations: context.evalCase?.runtime?.maxTurns, + userAnswers: context.evalCase?.runtime?.userAnswers, provider: modelConfig.provider, model: modelConfig.model, backend: backendSettings, diff --git a/cli/src/commands/app/new.ts b/cli/src/commands/app/new.ts index 87d40f161b..b011965ae8 100644 --- a/cli/src/commands/app/new.ts +++ b/cli/src/commands/app/new.ts @@ -908,7 +908,7 @@ const command = new Command() ) .option( "--schema ", - "Schema to use with --datatable. Created (CREATE SCHEMA IF NOT EXISTS) if it doesn't already exist." + "Schema to use with --datatable. If it doesn't exist yet, a sql_to_apply/ migration (CREATE SCHEMA IF NOT EXISTS) is written for it." ) .option( "--overwrite", diff --git a/cli/src/guidance/core.ts b/cli/src/guidance/core.ts index 6060f6b8a5..dc2a2f8d84 100644 --- a/cli/src/guidance/core.ts +++ b/cli/src/guidance/core.ts @@ -90,7 +90,7 @@ A data pipeline is NOT a flow: it is a set of independent scripts in one folder, ## Raw App Development You MUST use the \`raw-app\` skill to create or modify raw apps. -When a new app needs to be created, YOU run \`wmill app new\` yourself with \`--summary\`, \`--path\`, and \`--framework\` flags (and any other relevant flags). Do NOT ask the user to run it. If you don't have the values for those flags, ask the user via \`AskUserQuestion\` (one call, all missing fields) — never invent them. See the \`raw-app\` skill for the full procedure. +When a new app needs to be created, YOU run \`wmill app new\` yourself with \`--summary\`, \`--path\`, and \`--framework\` flags (and any other relevant flags). Do NOT ask the user to run it. If you don't have a summary or a path, ask the user via \`AskUserQuestion\` (one call, all missing fields) — never invent them. The framework is not asked: \`react19\` unless the user or the project's existing apps say otherwise. An app that stores data also needs its data table and schema settled with the user first. See the \`raw-app\` skill for the full procedure. ## Triggers diff --git a/cli/src/guidance/skills.gen.ts b/cli/src/guidance/skills.gen.ts index 86a1395861..3387f15b2d 100644 --- a/cli/src/guidance/skills.gen.ts +++ b/cli/src/guidance/skills.gen.ts @@ -6287,47 +6287,53 @@ This guide covers raw apps from the terminal: scaffolding via \`wmill app new\`, **You — the AI agent — create the app yourself by running \`wmill app new\` with the right flags. Do NOT tell the user to "run \`wmill app new\` and follow the prompts" or wait for them to do it.** The bare \`wmill app new\` is an interactive wizard that hangs waiting for stdin in any non-TTY context (which includes you). Always pass flags. -### Step 1 — Gather the three required values by asking the user +### Step 1 — Settle the setup -You need three things to run the command: +You need three values to run the command: 1. **summary** — a short description of the app 2. **path** — the windmill path, e.g. \`f/folder/my_app\` or \`u/username/my_app\` 3. **framework** — one of \`react19\` (recommended), \`react18\`, \`svelte5\`, \`vue\` -If the user's request did not supply *every* one of these explicitly, ask. Do not guess values, do not invent paths, do not pick a framework on the user's behalf, do not "just use react19 because it's the default". +**summary and path**: if the user's request did not supply them, ask. Do not guess values and do not invent paths. -Use whichever interactive question facility your runtime provides — a structured multi-choice tool if available, otherwise plain chat — and group all missing fields into a single round-trip so the user answers them at once: +**framework**: never ask. Use the one the user named, otherwise the one the project's existing apps use, otherwise \`react19\` (see "Starting a new app" in the authoring guide). + +**data setup**: when the app has to store data and the user did not say where, ask which data table, which schema and which tables, as "Data setup" in the authoring guide lays out. \`wmill datatable list\` gives the data tables to offer. + +Use whichever interactive question facility your runtime provides — a structured multi-choice tool if available, otherwise plain chat — and group everything missing into a single round-trip so the user answers at once: -- For \`framework\` — multiple-choice with the four allowed values; mark \`react19\` as \`(Recommended)\` and put it first. - For \`summary\` and \`path\` — provide one or two example values as multiple-choice options (the user can pick "Other" to type a free-form answer). +- For the data setup — the choices the authoring guide lists, the default first. -Only proceed once you have concrete values for all three. If the user replies with something ambiguous, ask again rather than guessing. +Only proceed once every value is concrete. If the user replies with something ambiguous, ask again rather than guessing. ### Step 2 — Run the command yourself -Once you have summary + path + framework, run it: +Once the setup is settled, run it: \`\`\`bash wmill app new \\ --summary "Customer dashboard" \\ --path f/sales/dashboard \\ - --framework react19 + --framework react19 \\ + --datatable main \\ + --schema app1 \`\`\` -That's the minimum. The datatable wizard and the "Open in Claude Desktop?" prompt are skipped silently because passing any of \`--summary\`/\`--path\`/\`--framework\` puts the command in non-interactive mode. +\`--summary\`, \`--path\` and \`--framework\` are the minimum. The datatable wizard and the "Open in Claude Desktop?" prompt are skipped silently because passing any of them puts the command in non-interactive mode, so the data setup only reaches the app through the flags below. ### Optional flags -Layer these in only when the user asked for them: - | Flag | When to add it | |---|---| -| \`--datatable \` | The user wants this app wired to a specific Windmill datatable. Without it, the app is created with no datatable. | -| \`--schema \` | Together with \`--datatable\`. Creates the schema with \`CREATE SCHEMA IF NOT EXISTS\` if it doesn't already exist. | +| \`--datatable \` | The app stores data: the data table settled in step 1. Without it, the app is created with no datatable. | +| \`--schema \` | Together with \`--datatable\`, when the app's tables go in a schema, new or existing. If the schema doesn't exist yet, writes a \`sql_to_apply/\` migration with \`CREATE SCHEMA IF NOT EXISTS\`, applied like any other migration (see "SQL Migrations" below). Leave it out for \`public\`. | | \`--overwrite\` | The target directory already exists and the user said it's OK to replace. Without it, non-interactive mode aborts with an error so you don't clobber existing work. | | \`--no-open-in-desktop\` | Already implied in non-interactive mode; only needed if you're somehow running interactively. | +Existing tables the app reuses have no flag: list them under \`data.tables\` in \`raw_app.yaml\` (see "Data tables" below). + ### Step 3 — Offer the visual preview After \`wmill app new\` and any initial edits to \`App.tsx\` / \`index.tsx\`, **offer** to open the visual preview as a one-sentence next step (e.g. "Want me to open the visual preview?"). Don't auto-open — opening the dev page has side effects (browser window, possibly a \`launch.json\` entry when an embedded preview tool is in play) the user should consent to. @@ -6338,8 +6344,9 @@ For apps the preview command runs from the app folder (\`cd __raw_app - ❌ Running \`wmill app new\` with no flags (the prompt will hang). - ❌ Telling the user to "run \`wmill app new\` and follow the prompts" — that's a step backwards from what you can do directly. -- ❌ Inventing a path/summary/framework instead of asking the user. -- ❌ Defaulting to \`react19\` because the user didn't say — even sensible defaults must be confirmed. +- ❌ Inventing a path or summary instead of asking the user. +- ❌ Asking which framework to use — \`react19\` is the default when nothing says otherwise. +- ❌ Creating a schema or tables for a new app before the user has said where its data goes. - ❌ Passing \`--overwrite\` automatically when the directory exists — confirm with the user first. ### Interactive (only when a human is at the terminal) @@ -6526,6 +6533,38 @@ A raw app has three logical parts: - **Backend runnables** — server-side scripts the frontend calls, each addressed by a unique key. - **Data** — optional whitelisted datatables (managed PostgreSQL) that the backend runnables can query. The frontend never queries the database directly; backend runnables are the only bridge. +## Starting a new app + +A new app gets the setup Windmill's own new-app dialog gives one: a framework, then where its data lives. + +### Framework + +Use the framework the user named. When they named none, follow what there is to follow: the app being edited, or the apps the request points at. With nothing to follow, use **React 19**, the recommended default, **without asking**. React 18, Svelte 5 and Vue are for when they are asked for. + +### Data setup + +When a new app has to store data and the user did not say where, **ask before creating anything**: no app, no schema, no table. Where the data lives is the user's decision, and tables created in the wrong place stay there. Look up the workspace's data tables first so every choice you offer exists, then ask, as proposed answers rather than open questions: + +1. **Data table**: which one to use, the default first (\`main\` when it exists, otherwise the first listed). Skip this one when the workspace has a single data table. +2. **Schema**: where the app's new tables go. + - A **new schema**, the usual choice, offered first. Suggest the first unused name among \`app1\`, \`app2\`, … + - An **existing schema** of that data table, by name. + - **None**: the tables go in \`public\`. +3. **Tables**: only when that data table already holds tables the app could use, whether to **reuse** them (name them) or **create new ones**. + +Do not ask when: + +- the user already said where the data goes. A part they left out takes its default above: the default data table, a new \`appN\` schema, new tables; +- the app, or its saved draft, already carries a data config (\`data.datatable\`, \`data.schema\` or \`data.tables\`). That config is the answer; +- the app stores nothing. + +With no data table in the workspace there is nothing to choose: say that one has to be configured in the workspace settings before the app can store data. + +A question left unanswered or dismissed is not a go-ahead for the defaults: stop there and say what is still needed. + +Then build what was chosen: the data table and schema become the app's \`data.datatable\` and \`data.schema\`, the tables it uses, reused or new, go in \`data.tables\`, and a new schema is created (\`CREATE SCHEMA IF NOT EXISTS\`) before the tables that go in it. +\`wmill app new --datatable --schema \` records both and, for a schema that does not exist yet, writes the migration in \`sql_to_apply/\` that creates it: nothing exists in the database until \`wmill app dev\` applies that migration, so the app's table migrations come after it. + ## Frontend ### Entrypoint @@ -7980,7 +8019,7 @@ app related commands - \`--path \` - App path (e.g., f/folder/my_app or u/username/my_app). Skips the prompt when provided. Triggers non-interactive mode. - \`--framework \` - Framework template: react19 | react18 | svelte5 | vue. Skips the prompt when provided. Triggers non-interactive mode. - \`--datatable \` - Datatable to wire up. Without this flag in non-interactive mode, no datatable is configured. - - \`--schema \` - Schema to use with --datatable. Created (CREATE SCHEMA IF NOT EXISTS) if it doesn't already exist. + - \`--schema \` - Schema to use with --datatable. If it doesn't exist yet, a sql_to_apply/ migration (CREATE SCHEMA IF NOT EXISTS) is written for it. - \`--overwrite\` - Overwrite the target directory if it already exists, without prompting. - \`--no-open-in-desktop\` - Do not prompt to open the new app in Claude Desktop. - \`app generate-agents [app_folder:string]\` - regenerate AGENTS.md and DATATABLES.md from remote workspace diff --git a/frontend/src/lib/components/copilot/chat/global/core.test.ts b/frontend/src/lib/components/copilot/chat/global/core.test.ts index 692c78bfb8..d510b21826 100644 --- a/frontend/src/lib/components/copilot/chat/global/core.test.ts +++ b/frontend/src/lib/components/copilot/chat/global/core.test.ts @@ -2607,6 +2607,25 @@ describe('global AI tools', () => { expect(raw).not.toContain('function New') }) + it('records the data setup a new app is initialized with', async () => { + await callGlobalTool('init_app', { + path: 'u/admin/tickets', + framework: 'react19', + data: { + datatable: 'main', + schema: 'helpdesk', + tables: ['helpdesk:tickets', 'notes', 'main/customers'] + } + }) + + const draft = getBackendDraft('raw_app', 'u/admin/tickets', { workspace: WORKSPACE }) + expect(draft?.data).toEqual({ + datatable: 'main', + schema: 'helpdesk', + tables: ['main/helpdesk:tickets', 'main/helpdesk:notes', 'main/customers'] + }) + }) + it('discards a draft without deleting the workspace item', async () => { await callGlobalTool('write_script', { path: 'f/scripts/discard-me', diff --git a/frontend/src/lib/components/copilot/chat/global/core.ts b/frontend/src/lib/components/copilot/chat/global/core.ts index 8f6dbd5128..23a80c4026 100644 --- a/frontend/src/lib/components/copilot/chat/global/core.ts +++ b/frontend/src/lib/components/copilot/chat/global/core.ts @@ -68,7 +68,10 @@ import { } from '$lib/components/job_args' import { processSecretArgs } from '$lib/components/secretArgUtils' import { PLAN_MODE_MESSAGES } from '../planModeMessages' -import { DEFAULT_DATA as DEFAULT_RAW_APP_DATA } from '$lib/components/raw_apps/dataTableRefUtils' +import { + DEFAULT_DATA as DEFAULT_RAW_APP_DATA, + formatDataTableRef +} from '$lib/components/raw_apps/dataTableRefUtils' import { appSourceToDraftValue } from '$lib/components/raw_apps/rawAppDraftValue' import type { RawAppDomQuery } from '$lib/components/raw_apps/rawAppDom' import { dataUrlToImagePart, normalizeImageDataUrl, type AttachedImage } from '../imageUtils' @@ -1294,7 +1297,22 @@ const initAppSchema = z.object({ framework: z .enum(FRAMEWORK_KEYS) .describe( - 'Frontend framework template. Confirm with the user before calling — never default silently. react19 is recommended for new apps.' + 'Frontend framework template: the one the user named or an app they point at uses, otherwise react19. Do not ask.' + ), + data: z + .object({ + datatable: z.string().describe('Data table the app stores its data in.'), + schema: z.string().optional().describe("Schema the app's new tables go in. Omit for public."), + tables: z + .array(z.string()) + .optional() + .describe( + 'Tables the app queries, reused or about to be created, each as `/` (public) or `/:
`.' + ) + }) + .optional() + .describe( + 'Data setup of an app that stores data, as the user gave or chose it. Omit for an app that stores nothing.' ) }) @@ -1546,7 +1564,7 @@ Raw apps: - A draft app is reachable by nobody; deploying is what exposes its backend runnables. deploy_workspace_item says so when the deploy widens who may open the app: anonymous means anyone with the URL, without logging in; guest means anyone the instance's identity provider authenticates, member of this workspace or not. Relay that in plain words and carry on. This is disclosure, not a gate: do not stop and ask for permission, and do not refuse the deploy. You cannot change who may open an app from chat; it is set on the app's deploy settings. - Use write_app_file, patch_app_file, and delete_app_file for frontend files. - Use write_app_runnable and delete_app_runnable for backend runnables. -- Use init_app only after confirming framework, path, and summary with the user. +- Use init_app for a new app, with framework react19 unless the user named one or points at an app to follow: do not ask about the framework, and write the summary and pick the path (path conventions above) yourself. When the app has to store data and the user did not say where, settle the data setup with askUserQuestion BEFORE init_app or any SQL (get_instructions subject "app" lists the questions, one askUserQuestion each), then pass the outcome as init_app's data. - Use deploy_workspace_item after explicit user deploy intent; raw app deploy bundles JS/CSS before saving.` )} @@ -2416,7 +2434,7 @@ function getAppInstructions(language?: ScriptLang): string { - Global mode edits raw app drafts only; it does not save or deploy unless the user explicitly asks to deploy. - App drafts are addressed by workspace path. Follow the path conventions in the system prompt: default to \`u//\` for bare names; only use \`f//\` when the folder is known to exist. The first write tool snapshots the workspace app onto the draft, and subsequent writes accumulate. -- To create a new app, use \`init_app\` with a path, optional summary, and a framework (\`react19\` / \`react18\` / \`svelte5\` / \`vue\`). Confirm framework + path + summary with the user before calling — do not silently default to \`react19\` even though it is the recommended choice. \`init_app\` errors if an app already exists at the path or a draft is already in flight; in that case, edit the existing one rather than re-initializing. +- To create a new app, use \`init_app\` with a path, optional summary, a framework (\`react19\` / \`react18\` / \`svelte5\` / \`vue\`) and, for an app that stores data, its \`data\` setup. "Starting a new app" below decides the framework and when the data setup is asked. Ask each of its questions with \`askUserQuestion\`, one question per call with the suggested answer first, before \`init_app\` and before any SQL. \`init_app\` only records \`data\`: a new schema is yours to create with the datatable SQL tool. \`init_app\` errors if an app already exists at the path or a draft is already in flight; in that case, edit the existing one rather than re-initializing. - \`init_app\` seeds a starter inline runnable named \`a\` (bun, \`main(x: string) => string\`) so the React/Svelte demo button works on first render. Replace or remove it once you start building real backend runnables. - Frontend file paths start with \`/\` (e.g. \`/index.tsx\`, \`/App.tsx\`, \`/styles.css\`). Use \`write_app_file\` / \`patch_app_file\` / \`delete_app_file\`. - Backend inline runnables are addressed as \`backend//main.{ts|py}\` from the file tools, but you create or update them via \`write_app_runnable\` / \`delete_app_runnable\` (which take the runnable shape directly: \`{ name, type, inlineScript?, path?, staticInputs? }\`). @@ -6511,16 +6529,31 @@ async function testRunFlowStepByPath( ) } +/** The `data.tables` entry for a table named without its data table (`schema:table`, + * `schema.table` or `table`), which models write for a table of the app's own data table. + * A bare name is a table of the app's own schema. */ +function appTableRef(datatable: string, schema: string | undefined, ref: string): string { + if (ref.includes('/')) return ref + const sep = ref.includes(':') ? ':' : '.' + const at = ref.indexOf(sep) + return formatDataTableRef( + at === -1 + ? { datatable, schema, table: ref } + : { datatable, schema: ref.slice(0, at), table: ref.slice(at + 1) } + ) +} + async function initApp( args: { path: string summary?: string framework: FrameworkKey + data?: { datatable: string; schema?: string; tables?: string[] } }, ctx: WriteDraftCtx ): Promise { const { workspace, toolId, toolCallbacks } = ctx - const { path, summary, framework } = args + const { path, summary, framework, data } = args if (await getGlobalDraft(workspace, 'app', path)) { throw new Error( @@ -6541,13 +6574,20 @@ async function initApp( const value: AppDraftValue = { summary, files: { ...template }, - runnables: structuredClone(STARTER_RUNNABLES) + runnables: structuredClone(STARTER_RUNNABLES), + ...(data && { + data: { + tables: (data.tables ?? []).map((ref) => appTableRef(data.datatable, data.schema, ref)), + datatable: data.datatable, + schema: data.schema + } + }) } await recomputeAppPolicy(value) const result = await saveAppDraft(workspace, path, value) return finishAppDraftWrite(result, ctx, () => ({ content: `Saved app "${path}" draft (${framework})`, - message: `Initialized a per-user draft app "${path}" from the ${framework} template (saved server-side, not a deployed workspace item). The template is a demo tour with starter runnables ${Object.keys(STARTER_RUNNABLES).join(', ')}: replace its UI and delete the runnables the app does not need (delete_app_runnable). Use write_app_file / write_app_runnable to evolve it.` + message: `Initialized a per-user draft app "${path}" from the ${framework} template (saved server-side, not a deployed workspace item). The template is a demo tour with starter runnables ${Object.keys(STARTER_RUNNABLES).join(', ')}: replace its UI and delete the runnables the app does not need (delete_app_runnable). Use write_app_file / write_app_runnable to evolve it.${data?.schema ? ` Its data config names schema "${data.schema}" of data table "${data.datatable}" without creating it: if it does not exist yet, create it before the tables that go in it.` : ''}` })) } @@ -8950,7 +8990,7 @@ export function prepareGlobalUserMessage( content += `isLiveDraft: true\n` if (activeEditor.isNew) { content += - 'isNew: true — the user just started this item from the new-item builder; it holds the starter template and is the item to build. Edit it in place; do not create another one.\n' + 'isNew: true — the user just started this item from the new-item builder; it holds the starter template and is the item to build. Edit it in place; do not create another one. For an app, its files are the framework it was started with and the `data` config read_workspace_item shows is the data setup it was started with: ask about neither.\n' } content += '\n' } diff --git a/system_prompts/auto-generated/cli/cli-commands.md b/system_prompts/auto-generated/cli/cli-commands.md index c8b829bf72..7b13702da6 100644 --- a/system_prompts/auto-generated/cli/cli-commands.md +++ b/system_prompts/auto-generated/cli/cli-commands.md @@ -43,7 +43,7 @@ app related commands - `--path ` - App path (e.g., f/folder/my_app or u/username/my_app). Skips the prompt when provided. Triggers non-interactive mode. - `--framework ` - Framework template: react19 | react18 | svelte5 | vue. Skips the prompt when provided. Triggers non-interactive mode. - `--datatable ` - Datatable to wire up. Without this flag in non-interactive mode, no datatable is configured. - - `--schema ` - Schema to use with --datatable. Created (CREATE SCHEMA IF NOT EXISTS) if it doesn't already exist. + - `--schema ` - Schema to use with --datatable. If it doesn't exist yet, a sql_to_apply/ migration (CREATE SCHEMA IF NOT EXISTS) is written for it. - `--overwrite` - Overwrite the target directory if it already exists, without prompting. - `--no-open-in-desktop` - Do not prompt to open the new app in Claude Desktop. - `app generate-agents [app_folder:string]` - regenerate AGENTS.md and DATATABLES.md from remote workspace diff --git a/system_prompts/auto-generated/prompts.ts b/system_prompts/auto-generated/prompts.ts index 211b73f786..e022709f59 100644 --- a/system_prompts/auto-generated/prompts.ts +++ b/system_prompts/auto-generated/prompts.ts @@ -888,6 +888,41 @@ A raw app has three logical parts: - **Backend runnables** — server-side scripts the frontend calls, each addressed by a unique key. - **Data** — optional whitelisted datatables (managed PostgreSQL) that the backend runnables can query. The frontend never queries the database directly; backend runnables are the only bridge. +## Starting a new app + +A new app gets the setup Windmill's own new-app dialog gives one: a framework, then where its data lives. + +### Framework + +Use the framework the user named. When they named none, follow what there is to follow: the app being edited, or the apps the request points at. With nothing to follow, use **React 19**, the recommended default, **without asking**. React 18, Svelte 5 and Vue are for when they are asked for. + +### Data setup + +When a new app has to store data and the user did not say where, **ask before creating anything**: no app, no schema, no table. Where the data lives is the user's decision, and tables created in the wrong place stay there. Look up the workspace's data tables first so every choice you offer exists, then ask, as proposed answers rather than open questions: + +1. **Data table**: which one to use, the default first (\`main\` when it exists, otherwise the first listed). Skip this one when the workspace has a single data table. +2. **Schema**: where the app's new tables go. + - A **new schema**, the usual choice, offered first. Suggest the first unused name among \`app1\`, \`app2\`, … + - An **existing schema** of that data table, by name. + - **None**: the tables go in \`public\`. +3. **Tables**: only when that data table already holds tables the app could use, whether to **reuse** them (name them) or **create new ones**. + +Do not ask when: + +- the user already said where the data goes. A part they left out takes its default above: the default data table, a new \`appN\` schema, new tables; +- the app, or its saved draft, already carries a data config (\`data.datatable\`, \`data.schema\` or \`data.tables\`). That config is the answer; +- the app stores nothing. + +With no data table in the workspace there is nothing to choose: say that one has to be configured in the workspace settings before the app can store data. + +A question left unanswered or dismissed is not a go-ahead for the defaults: stop there and say what is still needed. + +Then build what was chosen: the data table and schema become the app's \`data.datatable\` and \`data.schema\`, the tables it uses, reused or new, go in \`data.tables\`, and a new schema is created (\`CREATE SCHEMA IF NOT EXISTS\`) before the tables that go in it. + +### An app that arrives already set up + +An app the user just started from the new-app dialog is already set up: its files are the framework template it was started with, and a \`data\` config it carries (\`data.datatable\`, \`data.schema\` or \`data.tables\`) is the data setup it was started with. Build that app in place, with that data config, and in that framework unless the user now names another. Do not ask for either, and do not create a second app. Only when it carries no data config and has to store data is the data setup still to ask. + ## Frontend ### Entrypoint @@ -3479,7 +3514,7 @@ app related commands - \`--path \` - App path (e.g., f/folder/my_app or u/username/my_app). Skips the prompt when provided. Triggers non-interactive mode. - \`--framework \` - Framework template: react19 | react18 | svelte5 | vue. Skips the prompt when provided. Triggers non-interactive mode. - \`--datatable \` - Datatable to wire up. Without this flag in non-interactive mode, no datatable is configured. - - \`--schema \` - Schema to use with --datatable. Created (CREATE SCHEMA IF NOT EXISTS) if it doesn't already exist. + - \`--schema \` - Schema to use with --datatable. If it doesn't exist yet, a sql_to_apply/ migration (CREATE SCHEMA IF NOT EXISTS) is written for it. - \`--overwrite\` - Overwrite the target directory if it already exists, without prompting. - \`--no-open-in-desktop\` - Do not prompt to open the new app in Claude Desktop. - \`app generate-agents [app_folder:string]\` - regenerate AGENTS.md and DATATABLES.md from remote workspace diff --git a/system_prompts/auto-generated/skills/cli-commands/SKILL.md b/system_prompts/auto-generated/skills/cli-commands/SKILL.md index df19b6dac2..48ea832a31 100644 --- a/system_prompts/auto-generated/skills/cli-commands/SKILL.md +++ b/system_prompts/auto-generated/skills/cli-commands/SKILL.md @@ -48,7 +48,7 @@ app related commands - `--path ` - App path (e.g., f/folder/my_app or u/username/my_app). Skips the prompt when provided. Triggers non-interactive mode. - `--framework ` - Framework template: react19 | react18 | svelte5 | vue. Skips the prompt when provided. Triggers non-interactive mode. - `--datatable ` - Datatable to wire up. Without this flag in non-interactive mode, no datatable is configured. - - `--schema ` - Schema to use with --datatable. Created (CREATE SCHEMA IF NOT EXISTS) if it doesn't already exist. + - `--schema ` - Schema to use with --datatable. If it doesn't exist yet, a sql_to_apply/ migration (CREATE SCHEMA IF NOT EXISTS) is written for it. - `--overwrite` - Overwrite the target directory if it already exists, without prompting. - `--no-open-in-desktop` - Do not prompt to open the new app in Claude Desktop. - `app generate-agents [app_folder:string]` - regenerate AGENTS.md and DATATABLES.md from remote workspace diff --git a/system_prompts/auto-generated/skills/raw-app/SKILL.md b/system_prompts/auto-generated/skills/raw-app/SKILL.md index fe9f57c55d..2f7cd52d5f 100644 --- a/system_prompts/auto-generated/skills/raw-app/SKILL.md +++ b/system_prompts/auto-generated/skills/raw-app/SKILL.md @@ -11,47 +11,53 @@ This guide covers raw apps from the terminal: scaffolding via `wmill app new`, t **You — the AI agent — create the app yourself by running `wmill app new` with the right flags. Do NOT tell the user to "run `wmill app new` and follow the prompts" or wait for them to do it.** The bare `wmill app new` is an interactive wizard that hangs waiting for stdin in any non-TTY context (which includes you). Always pass flags. -### Step 1 — Gather the three required values by asking the user +### Step 1 — Settle the setup -You need three things to run the command: +You need three values to run the command: 1. **summary** — a short description of the app 2. **path** — the windmill path, e.g. `f/folder/my_app` or `u/username/my_app` 3. **framework** — one of `react19` (recommended), `react18`, `svelte5`, `vue` -If the user's request did not supply *every* one of these explicitly, ask. Do not guess values, do not invent paths, do not pick a framework on the user's behalf, do not "just use react19 because it's the default". +**summary and path**: if the user's request did not supply them, ask. Do not guess values and do not invent paths. -Use whichever interactive question facility your runtime provides — a structured multi-choice tool if available, otherwise plain chat — and group all missing fields into a single round-trip so the user answers them at once: +**framework**: never ask. Use the one the user named, otherwise the one the project's existing apps use, otherwise `react19` (see "Starting a new app" in the authoring guide). + +**data setup**: when the app has to store data and the user did not say where, ask which data table, which schema and which tables, as "Data setup" in the authoring guide lays out. `wmill datatable list` gives the data tables to offer. + +Use whichever interactive question facility your runtime provides — a structured multi-choice tool if available, otherwise plain chat — and group everything missing into a single round-trip so the user answers at once: -- For `framework` — multiple-choice with the four allowed values; mark `react19` as `(Recommended)` and put it first. - For `summary` and `path` — provide one or two example values as multiple-choice options (the user can pick "Other" to type a free-form answer). +- For the data setup — the choices the authoring guide lists, the default first. -Only proceed once you have concrete values for all three. If the user replies with something ambiguous, ask again rather than guessing. +Only proceed once every value is concrete. If the user replies with something ambiguous, ask again rather than guessing. ### Step 2 — Run the command yourself -Once you have summary + path + framework, run it: +Once the setup is settled, run it: ```bash wmill app new \ --summary "Customer dashboard" \ --path f/sales/dashboard \ - --framework react19 + --framework react19 \ + --datatable main \ + --schema app1 ``` -That's the minimum. The datatable wizard and the "Open in Claude Desktop?" prompt are skipped silently because passing any of `--summary`/`--path`/`--framework` puts the command in non-interactive mode. +`--summary`, `--path` and `--framework` are the minimum. The datatable wizard and the "Open in Claude Desktop?" prompt are skipped silently because passing any of them puts the command in non-interactive mode, so the data setup only reaches the app through the flags below. ### Optional flags -Layer these in only when the user asked for them: - | Flag | When to add it | |---|---| -| `--datatable ` | The user wants this app wired to a specific Windmill datatable. Without it, the app is created with no datatable. | -| `--schema ` | Together with `--datatable`. Creates the schema with `CREATE SCHEMA IF NOT EXISTS` if it doesn't already exist. | +| `--datatable ` | The app stores data: the data table settled in step 1. Without it, the app is created with no datatable. | +| `--schema ` | Together with `--datatable`, when the app's tables go in a schema, new or existing. If the schema doesn't exist yet, writes a `sql_to_apply/` migration with `CREATE SCHEMA IF NOT EXISTS`, applied like any other migration (see "SQL Migrations" below). Leave it out for `public`. | | `--overwrite` | The target directory already exists and the user said it's OK to replace. Without it, non-interactive mode aborts with an error so you don't clobber existing work. | | `--no-open-in-desktop` | Already implied in non-interactive mode; only needed if you're somehow running interactively. | +Existing tables the app reuses have no flag: list them under `data.tables` in `raw_app.yaml` (see "Data tables" below). + ### Step 3 — Offer the visual preview After `wmill app new` and any initial edits to `App.tsx` / `index.tsx`, **offer** to open the visual preview as a one-sentence next step (e.g. "Want me to open the visual preview?"). Don't auto-open — opening the dev page has side effects (browser window, possibly a `launch.json` entry when an embedded preview tool is in play) the user should consent to. @@ -62,8 +68,9 @@ For apps the preview command runs from the app folder (`cd __raw_app & - ❌ Running `wmill app new` with no flags (the prompt will hang). - ❌ Telling the user to "run `wmill app new` and follow the prompts" — that's a step backwards from what you can do directly. -- ❌ Inventing a path/summary/framework instead of asking the user. -- ❌ Defaulting to `react19` because the user didn't say — even sensible defaults must be confirmed. +- ❌ Inventing a path or summary instead of asking the user. +- ❌ Asking which framework to use — `react19` is the default when nothing says otherwise. +- ❌ Creating a schema or tables for a new app before the user has said where its data goes. - ❌ Passing `--overwrite` automatically when the directory exists — confirm with the user first. ### Interactive (only when a human is at the terminal) @@ -250,6 +257,38 @@ A raw app has three logical parts: - **Backend runnables** — server-side scripts the frontend calls, each addressed by a unique key. - **Data** — optional whitelisted datatables (managed PostgreSQL) that the backend runnables can query. The frontend never queries the database directly; backend runnables are the only bridge. +## Starting a new app + +A new app gets the setup Windmill's own new-app dialog gives one: a framework, then where its data lives. + +### Framework + +Use the framework the user named. When they named none, follow what there is to follow: the app being edited, or the apps the request points at. With nothing to follow, use **React 19**, the recommended default, **without asking**. React 18, Svelte 5 and Vue are for when they are asked for. + +### Data setup + +When a new app has to store data and the user did not say where, **ask before creating anything**: no app, no schema, no table. Where the data lives is the user's decision, and tables created in the wrong place stay there. Look up the workspace's data tables first so every choice you offer exists, then ask, as proposed answers rather than open questions: + +1. **Data table**: which one to use, the default first (`main` when it exists, otherwise the first listed). Skip this one when the workspace has a single data table. +2. **Schema**: where the app's new tables go. + - A **new schema**, the usual choice, offered first. Suggest the first unused name among `app1`, `app2`, … + - An **existing schema** of that data table, by name. + - **None**: the tables go in `public`. +3. **Tables**: only when that data table already holds tables the app could use, whether to **reuse** them (name them) or **create new ones**. + +Do not ask when: + +- the user already said where the data goes. A part they left out takes its default above: the default data table, a new `appN` schema, new tables; +- the app, or its saved draft, already carries a data config (`data.datatable`, `data.schema` or `data.tables`). That config is the answer; +- the app stores nothing. + +With no data table in the workspace there is nothing to choose: say that one has to be configured in the workspace settings before the app can store data. + +A question left unanswered or dismissed is not a go-ahead for the defaults: stop there and say what is still needed. + +Then build what was chosen: the data table and schema become the app's `data.datatable` and `data.schema`, the tables it uses, reused or new, go in `data.tables`, and a new schema is created (`CREATE SCHEMA IF NOT EXISTS`) before the tables that go in it. +`wmill app new --datatable --schema ` records both and, for a schema that does not exist yet, writes the migration in `sql_to_apply/` that creates it: nothing exists in the database until `wmill app dev` applies that migration, so the app's table migrations come after it. + ## Frontend ### Entrypoint diff --git a/system_prompts/base/raw-app-cli.md b/system_prompts/base/raw-app-cli.md index 0ff11a2b74..59ef0acb58 100644 --- a/system_prompts/base/raw-app-cli.md +++ b/system_prompts/base/raw-app-cli.md @@ -6,47 +6,53 @@ This guide covers raw apps from the terminal: scaffolding via `wmill app new`, t **You — the AI agent — create the app yourself by running `wmill app new` with the right flags. Do NOT tell the user to "run `wmill app new` and follow the prompts" or wait for them to do it.** The bare `wmill app new` is an interactive wizard that hangs waiting for stdin in any non-TTY context (which includes you). Always pass flags. -### Step 1 — Gather the three required values by asking the user +### Step 1 — Settle the setup -You need three things to run the command: +You need three values to run the command: 1. **summary** — a short description of the app 2. **path** — the windmill path, e.g. `f/folder/my_app` or `u/username/my_app` 3. **framework** — one of `react19` (recommended), `react18`, `svelte5`, `vue` -If the user's request did not supply *every* one of these explicitly, ask. Do not guess values, do not invent paths, do not pick a framework on the user's behalf, do not "just use react19 because it's the default". +**summary and path**: if the user's request did not supply them, ask. Do not guess values and do not invent paths. -Use whichever interactive question facility your runtime provides — a structured multi-choice tool if available, otherwise plain chat — and group all missing fields into a single round-trip so the user answers them at once: +**framework**: never ask. Use the one the user named, otherwise the one the project's existing apps use, otherwise `react19` (see "Starting a new app" in the authoring guide). + +**data setup**: when the app has to store data and the user did not say where, ask which data table, which schema and which tables, as "Data setup" in the authoring guide lays out. `wmill datatable list` gives the data tables to offer. + +Use whichever interactive question facility your runtime provides — a structured multi-choice tool if available, otherwise plain chat — and group everything missing into a single round-trip so the user answers at once: -- For `framework` — multiple-choice with the four allowed values; mark `react19` as `(Recommended)` and put it first. - For `summary` and `path` — provide one or two example values as multiple-choice options (the user can pick "Other" to type a free-form answer). +- For the data setup — the choices the authoring guide lists, the default first. -Only proceed once you have concrete values for all three. If the user replies with something ambiguous, ask again rather than guessing. +Only proceed once every value is concrete. If the user replies with something ambiguous, ask again rather than guessing. ### Step 2 — Run the command yourself -Once you have summary + path + framework, run it: +Once the setup is settled, run it: ```bash wmill app new \ --summary "Customer dashboard" \ --path f/sales/dashboard \ - --framework react19 + --framework react19 \ + --datatable main \ + --schema app1 ``` -That's the minimum. The datatable wizard and the "Open in Claude Desktop?" prompt are skipped silently because passing any of `--summary`/`--path`/`--framework` puts the command in non-interactive mode. +`--summary`, `--path` and `--framework` are the minimum. The datatable wizard and the "Open in Claude Desktop?" prompt are skipped silently because passing any of them puts the command in non-interactive mode, so the data setup only reaches the app through the flags below. ### Optional flags -Layer these in only when the user asked for them: - | Flag | When to add it | |---|---| -| `--datatable ` | The user wants this app wired to a specific Windmill datatable. Without it, the app is created with no datatable. | -| `--schema ` | Together with `--datatable`. Creates the schema with `CREATE SCHEMA IF NOT EXISTS` if it doesn't already exist. | +| `--datatable ` | The app stores data: the data table settled in step 1. Without it, the app is created with no datatable. | +| `--schema ` | Together with `--datatable`, when the app's tables go in a schema, new or existing. If the schema doesn't exist yet, writes a `sql_to_apply/` migration with `CREATE SCHEMA IF NOT EXISTS`, applied like any other migration (see "SQL Migrations" below). Leave it out for `public`. | | `--overwrite` | The target directory already exists and the user said it's OK to replace. Without it, non-interactive mode aborts with an error so you don't clobber existing work. | | `--no-open-in-desktop` | Already implied in non-interactive mode; only needed if you're somehow running interactively. | +Existing tables the app reuses have no flag: list them under `data.tables` in `raw_app.yaml` (see "Data tables" below). + ### Step 3 — Offer the visual preview After `wmill app new` and any initial edits to `App.tsx` / `index.tsx`, **offer** to open the visual preview as a one-sentence next step (e.g. "Want me to open the visual preview?"). Don't auto-open — opening the dev page has side effects (browser window, possibly a `launch.json` entry when an embedded preview tool is in play) the user should consent to. @@ -57,8 +63,9 @@ For apps the preview command runs from the app folder (`cd __raw_app & - ❌ Running `wmill app new` with no flags (the prompt will hang). - ❌ Telling the user to "run `wmill app new` and follow the prompts" — that's a step backwards from what you can do directly. -- ❌ Inventing a path/summary/framework instead of asking the user. -- ❌ Defaulting to `react19` because the user didn't say — even sensible defaults must be confirmed. +- ❌ Inventing a path or summary instead of asking the user. +- ❌ Asking which framework to use — `react19` is the default when nothing says otherwise. +- ❌ Creating a schema or tables for a new app before the user has said where its data goes. - ❌ Passing `--overwrite` automatically when the directory exists — confirm with the user first. ### Interactive (only when a human is at the terminal) diff --git a/system_prompts/base/raw-app.md b/system_prompts/base/raw-app.md index 56c6e900d4..03bde6ec71 100644 --- a/system_prompts/base/raw-app.md +++ b/system_prompts/base/raw-app.md @@ -10,6 +10,46 @@ A raw app has three logical parts: - **Backend runnables** — server-side scripts the frontend calls, each addressed by a unique key. - **Data** — optional whitelisted datatables (managed PostgreSQL) that the backend runnables can query. The frontend never queries the database directly; backend runnables are the only bridge. +## Starting a new app + +A new app gets the setup Windmill's own new-app dialog gives one: a framework, then where its data lives. + +### Framework + +Use the framework the user named. When they named none, follow what there is to follow: the app being edited, or the apps the request points at. With nothing to follow, use **React 19**, the recommended default, **without asking**. React 18, Svelte 5 and Vue are for when they are asked for. + +### Data setup + +When a new app has to store data and the user did not say where, **ask before creating anything**: no app, no schema, no table. Where the data lives is the user's decision, and tables created in the wrong place stay there. Look up the workspace's data tables first so every choice you offer exists, then ask, as proposed answers rather than open questions: + +1. **Data table**: which one to use, the default first (`main` when it exists, otherwise the first listed). Skip this one when the workspace has a single data table. +2. **Schema**: where the app's new tables go. + - A **new schema**, the usual choice, offered first. Suggest the first unused name among `app1`, `app2`, … + - An **existing schema** of that data table, by name. + - **None**: the tables go in `public`. +3. **Tables**: only when that data table already holds tables the app could use, whether to **reuse** them (name them) or **create new ones**. + +Do not ask when: + +- the user already said where the data goes. A part they left out takes its default above: the default data table, a new `appN` schema, new tables; +- the app, or its saved draft, already carries a data config (`data.datatable`, `data.schema` or `data.tables`). That config is the answer; +- the app stores nothing. + +With no data table in the workspace there is nothing to choose: say that one has to be configured in the workspace settings before the app can store data. + +A question left unanswered or dismissed is not a go-ahead for the defaults: stop there and say what is still needed. + +Then build what was chosen: the data table and schema become the app's `data.datatable` and `data.schema`, the tables it uses, reused or new, go in `data.tables`, and a new schema is created (`CREATE SCHEMA IF NOT EXISTS`) before the tables that go in it. + +`wmill app new --datatable --schema ` records both and, for a schema that does not exist yet, writes the migration in `sql_to_apply/` that creates it: nothing exists in the database until `wmill app dev` applies that migration, so the app's table migrations come after it. + + + +### An app that arrives already set up + +An app the user just started from the new-app dialog is already set up: its files are the framework template it was started with, and a `data` config it carries (`data.datatable`, `data.schema` or `data.tables`) is the data setup it was started with. Build that app in place, with that data config, and in that framework unless the user now names another. Do not ask for either, and do not create a second app. Only when it carries no data config and has to store data is the data setup still to ask. + + ## Frontend ### Entrypoint From b1af8b0e03315aa7f51e69c822188d2792d78057 Mon Sep 17 00:00:00 2001 From: Ruben Fiszel Date: Wed, 7 Oct 2026 13:21:46 +0200 Subject: [PATCH 02/34] [ee] fix: concurrency limit over-admits when counter row is missing (#11587) * fix: concurrency limit over-admits when the counter row is missing * chore: bump ee ref * fix: restore sqlx entry for the locked counter read and bump ee ref --- ...3062a8f706e70bc9c4b3764cd1d6f99b9440a.json | 23 +++++++++++++++++ backend/ee-repo-ref.txt | 2 +- .../tests/concurrency_counter_test.rs | 25 +++++-------------- 3 files changed, 30 insertions(+), 20 deletions(-) create mode 100644 backend/.sqlx/query-03cc00b0b5b8b1ffcc14ac5f6cb3062a8f706e70bc9c4b3764cd1d6f99b9440a.json diff --git a/backend/.sqlx/query-03cc00b0b5b8b1ffcc14ac5f6cb3062a8f706e70bc9c4b3764cd1d6f99b9440a.json b/backend/.sqlx/query-03cc00b0b5b8b1ffcc14ac5f6cb3062a8f706e70bc9c4b3764cd1d6f99b9440a.json new file mode 100644 index 0000000000..ccd8b05822 --- /dev/null +++ b/backend/.sqlx/query-03cc00b0b5b8b1ffcc14ac5f6cb3062a8f706e70bc9c4b3764cd1d6f99b9440a.json @@ -0,0 +1,23 @@ +{ + "db_name": "PostgreSQL", + "query": "\nINSERT INTO concurrency_counter(concurrency_id, job_uuids)\nVALUES ($1, '{}'::jsonb)\nON CONFLICT (concurrency_id)\nDO UPDATE SET job_uuids = concurrency_counter.job_uuids\nRETURNING (SELECT COUNT(*)\n FROM jsonb_object_keys(job_uuids) AS keys(key)\n WHERE key <> $2)", + "describe": { + "columns": [ + { + "ordinal": 0, + "name": "count", + "type_info": "Int8" + } + ], + "parameters": { + "Left": [ + "Varchar", + "Text" + ] + }, + "nullable": [ + null + ] + }, + "hash": "03cc00b0b5b8b1ffcc14ac5f6cb3062a8f706e70bc9c4b3764cd1d6f99b9440a" +} diff --git a/backend/ee-repo-ref.txt b/backend/ee-repo-ref.txt index 7f8d64aa9d..b18c7bc91f 100644 --- a/backend/ee-repo-ref.txt +++ b/backend/ee-repo-ref.txt @@ -1 +1 @@ -065c2c64c3904d5c0b2766b424210d34f9e54d2d \ No newline at end of file +9cc330f1a8e80bc075a6ad9839966d3b344f8ddd \ No newline at end of file diff --git a/backend/windmill-queue/tests/concurrency_counter_test.rs b/backend/windmill-queue/tests/concurrency_counter_test.rs index 3edb0d3b72..b341c317bb 100644 --- a/backend/windmill-queue/tests/concurrency_counter_test.rs +++ b/backend/windmill-queue/tests/concurrency_counter_test.rs @@ -33,32 +33,19 @@ mod concurrency { .unwrap_or(0) } - /// Stress: N concurrent admit-attempts on a pre-existing key with limit - /// L < N. Asserts admitted count is exactly L (never over-admits) AND - /// that the row's job_uuids reflects exactly L entries. + /// Stress: N concurrent admit-attempts on a key with limit L < N. Asserts + /// admitted count is exactly L (never over-admits) AND that the row's + /// job_uuids reflects exactly L entries. /// - /// The row is pre-seeded with an empty `job_uuids` because there is a - /// known preexisting race when the `concurrency_counter` row does not - /// exist yet: `SELECT ... FOR UPDATE` on a missing row locks nothing, - /// so all concurrent transactions see `running=0` and all admit via - /// `INSERT ... ON CONFLICT DO UPDATE`. That race is inherited from - /// the legacy code path and is out of scope for this PR. This test - /// validates the property we *do* preserve: no over-admit once the - /// row exists. + /// The `concurrency_counter` row is deliberately absent at the start: the + /// monitor deletes empty rows while jobs for the key are still queued, so + /// the admit path has to serialize without a pre-existing row to lock. #[sqlx::test(migrations = "../migrations")] async fn stress_never_over_admits(db: Pool) { let key = "stress-never-over-admits".to_string(); let limit: i32 = 5; let workers: usize = 50; - sqlx::query!( - "INSERT INTO concurrency_counter(concurrency_id, job_uuids) VALUES ($1, '{}'::jsonb)", - key, - ) - .execute(&db) - .await - .expect("seed empty counter row"); - let mut tasks = Vec::with_capacity(workers); for _ in 0..workers { let db = db.clone(); From 046df9e44db2f2fae3059ccd7a3d6c6955ee8971 Mon Sep 17 00:00:00 2001 From: Ruben Fiszel Date: Wed, 7 Oct 2026 14:05:04 +0200 Subject: [PATCH 03/34] feat: run AI decision steps on OpenAI's Decisions API (#11590) * feat: run AI decision steps on OpenAI's Decisions API Co-Authored-By: Claude Opus 5.5 (1M context) * fix: fail refused openai decisions and keep structured criteria Co-Authored-By: Claude Opus 5.5 (1M context) * fix: send only user message lists as openai decision messages Co-Authored-By: Claude Opus 5.5 (1M context) * fix: omit descriptions the openai decision step does not have Co-Authored-By: Claude Opus 5.5 (1M context) * fix: pass only exact openai user messages through as decision input Co-Authored-By: Claude Opus 5.5 (1M context) * fix: check the payload of openai decision message parts Co-Authored-By: Claude Opus 5.5 (1M context) --------- Co-authored-by: Claude Opus 5.5 (1M context) --- backend/tests/ai_decision.rs | 23 +- backend/windmill-ai/src/ai_providers.rs | 8 +- backend/windmill-ai/src/decision.rs | 390 +++++++++++++++--- backend/windmill-types/src/flows.rs | 2 +- backend/windmill-worker/src/ai_executor.rs | 8 +- cli/src/guidance/skills.gen.ts | 15 +- .../lib/components/AIProviderPicker.svelte | 24 +- .../chat/flow/aiAgentProviderCatalog.ts | 4 +- .../chat/flow/aiAgentProviders.test.ts | 9 +- .../copilot/chat/flow/aiAgentProviders.ts | 26 +- .../copilot/chat/flow/openFlow.json | 2 +- .../copilot/chat/flow/openFlowZod.gen.ts | 8 +- frontend/src/lib/components/copilot/lib.ts | 9 +- .../src/lib/components/flows/flowInfers.ts | 7 +- openflow.openapi.yaml | 10 +- system_prompts/auto-generated/flow.md | 15 +- system_prompts/auto-generated/prompts.ts | 15 +- .../auto-generated/skills/write-flow/SKILL.md | 15 +- system_prompts/base/flow-base.md | 13 +- 19 files changed, 502 insertions(+), 101 deletions(-) diff --git a/backend/tests/ai_decision.rs b/backend/tests/ai_decision.rs index 98c219dfb2..04b310f2c1 100644 --- a/backend/tests/ai_decision.rs +++ b/backend/tests/ai_decision.rs @@ -1,5 +1,6 @@ -//! AI decision steps run end to end against a stand-in for System One endpoints: TypeSafe's, and -//! Cloudflare Workers AI's, which serves each model at its own URL inside an API envelope. +//! AI decision steps run end to end against a stand-in for the decision endpoints: TypeSafe's +//! System One, Cloudflare Workers AI's, which serves each model at its own URL inside an API +//! envelope, and OpenAI's Decisions API. use axum::{routing::post, Json, Router}; use serde_json::{json, Value}; @@ -37,6 +38,19 @@ async fn start_decision_stub() -> anyhow::Result { post(|Json(body): Json| async move { Json(json!({"result": refund_answers(&body), "success": true, "errors": []})) }), + ) + // OpenAI's Decisions API takes the questions as a list and answers with one. + .route( + "/openai/v1/decisions", + post(|Json(body): Json| async move { + let answers = body["questions"] + .as_array() + .into_iter() + .flatten() + .map(|q| json!({"type": "choice", "name": q["name"], "choice": "refund"})) + .collect::>(); + Json(json!({"answers": answers})) + }), ); let listener = tokio::net::TcpListener::bind("127.0.0.1:0").await?; let port = listener.local_addr()?.port(); @@ -72,6 +86,11 @@ async fn test_ai_decision_answers_route_a_following_branch( }, "model": "clef-flash" }), + json!({ + "kind": "openai", + "resource": {"api_key": "key", "base_url": format!("http://127.0.0.1:{stub_port}/openai/v1")}, + "model": "gpt-6-luna" + }), ] { let flow: FlowValue = serde_json::from_value(json!({ "modules": [ diff --git a/backend/windmill-ai/src/ai_providers.rs b/backend/windmill-ai/src/ai_providers.rs index 4cd41f34a8..3b3af833d6 100644 --- a/backend/windmill-ai/src/ai_providers.rs +++ b/backend/windmill-ai/src/ai_providers.rs @@ -124,7 +124,7 @@ pub enum AIProvider { #[serde(rename = "aws_bedrock")] AWSBedrock, /// TypeSafe's Jev decision model. It answers typed questions rather than chatting, so only - /// an AI decision runs it (`run_systemone`), never the agent loop. + /// an AI decision runs it (`run_decision`), never the agent loop. TypeSafe, /// Cloudflare Workers AI, for its Jev-compatible decision models (Clef). Decisions only, as /// for TypeSafe; its base URL comes from the resource's account id. @@ -152,6 +152,12 @@ impl AIProvider { matches!(self, AIProvider::TypeSafe | AIProvider::Cloudflare) } + /// A provider an AI decision runs on: the decision providers, and OpenAI, whose Decisions + /// API sits next to its chat routes on the same resource. + pub fn runs_decisions(&self) -> bool { + self.is_decision_provider() || matches!(self, AIProvider::OpenAI) + } + /// Get the base URL for the AI provider pub async fn get_base_url(&self, resource_base_url: Option, db: &DB) -> Result { if let Some(base_url) = resource_base_url { diff --git a/backend/windmill-ai/src/decision.rs b/backend/windmill-ai/src/decision.rs index 31b525cf2d..b3a35dab2a 100644 --- a/backend/windmill-ai/src/decision.rs +++ b/backend/windmill-ai/src/decision.rs @@ -1,6 +1,7 @@ -//! AI decision steps: one call to a System One endpoint (TypeSafe's Jev, or Cloudflare's -//! Jev-compatible Clef on Workers AI), which answers typed questions (`choice`, `score`, `noul`) -//! about a state with calibrated probabilities instead of text. +//! AI decision steps: one call to a decision endpoint, which answers typed questions (`choice`, +//! `score`, `noul`) about a state with calibrated probabilities instead of text. The questions and +//! answers are System One's (TypeSafe's Jev, Cloudflare's Jev-compatible Clef on Workers AI); +//! OpenAI's Decisions API is asked and read through a translation to that shape. use std::time::Duration; @@ -30,6 +31,8 @@ pub struct AIDecisionArgs { pub const TYPESAFE_DEFAULT_MODEL: &str = "jev-latest"; /// Cloudflare's larger decision model, run when the step names none. pub const CLOUDFLARE_DEFAULT_MODEL: &str = "clef"; +/// The model OpenAI's Decisions API serves, run when the step names none. +pub const OPENAI_DEFAULT_MODEL: &str = "gpt-6-luna"; #[derive(Serialize)] struct SystemOneRequest<'a> { @@ -108,7 +111,263 @@ pub fn decision_inputs<'a>( Ok((state, questions)) } -pub async fn run_systemone( +/// Posts a decision request with the resource's bearer key and returns the response body. +async fn post_decision( + credentials: &ProviderCredentials, + endpoint: &str, + vendor: &str, + payload: &T, + timeout: Duration, +) -> Result { + let auth_headers = retain_effective_credentials( + credentials, + vec![( + "Authorization", + format!( + "Bearer {}", + credentials.api_key.as_deref().unwrap_or_default() + ), + )], + ); + + // The endpoint derives from the resource's base URL, so the connect is pinned to the + // address the SSRF check validated. + let client = pinned_ai_client_for(&credentials.base_url).await?; + let mut request = client.post(endpoint).timeout(timeout); + for (name, value) in auth_headers { + request = request.header(name, value); + } + for (name, value) in common_outbound_headers(credentials) { + request = request.header(name, value); + } + + let response = request + .json(payload) + .send() + .await + .map_err(|e| Error::ExecutionErr(format!("Failed to call {vendor}: {e}")))?; + + let status = response.status(); + if !status.is_success() { + let body = response + .text() + .await + .unwrap_or_else(|_| "".to_string()); + return Err(Error::ExecutionErr(format!( + "{vendor} error calling {endpoint}: {status} - {body}" + ))); + } + + response + .text() + .await + .map_err(|e| Error::ExecutionErr(format!("Failed to read the {vendor} response: {e}"))) +} + +/// Answers a decision on the endpoint its provider serves. +pub async fn run_decision( + credentials: &ProviderCredentials, + model: &str, + state: &Value, + questions: &Map, + timeout: Duration, +) -> Result { + if credentials.provider == AIProvider::OpenAI { + run_openai_decisions(credentials, model, state, questions, timeout).await + } else { + run_systemone(credentials, model, state, questions, timeout).await + } +} + +#[derive(Serialize)] +struct OpenAIDecisionsRequest<'a> { + model: &'a str, + input: Value, + questions: Vec, +} + +#[derive(Deserialize)] +struct OpenAIDecisionsResponse { + #[serde(default)] + model: Option, + answers: Vec>, + #[serde(default)] + usage: Option, +} + +/// The state as a Decisions `input`. OpenAI reads a text or a list of user messages, so a list of +/// user messages (the only way to pass an image) goes as it is and any other object or array, +/// a chat history included, as its JSON text. +fn openai_input(state: &Value) -> Value { + match state { + Value::String(_) => state.clone(), + Value::Array(items) if !items.is_empty() && items.iter().all(is_openai_user_message) => { + state.clone() + } + _ => Value::String(state.to_string()), + } +} + +/// Exactly a message the Decisions API reads: `role: "user"` with a text, or with parts that are +/// each an `input_text` or an `input_image`. +fn is_openai_user_message(message: &Value) -> bool { + let is_part = |part: &Value| match part.get("type").and_then(Value::as_str) { + Some("input_text") => part.get("text").is_some_and(Value::is_string), + Some("input_image") => part.get("image_url").is_some_and(Value::is_string), + _ => false, + }; + message.get("role").and_then(Value::as_str) == Some("user") + && match message.get("content") { + Some(Value::String(_)) => true, + Some(Value::Array(parts)) => !parts.is_empty() && parts.iter().all(is_part), + _ => false, + } +} + +/// The questions as OpenAI's Decisions API takes them: a list naming each question, with a +/// `noul` asked as its `predicate` and each score level as a label. +fn openai_questions(questions: &Map) -> Result> { + let text = |v: &Value| match v { + Value::String(s) => s.clone(), + v => v.to_string(), + }; + // A structured description goes as its JSON text, as structured instructions do. + let stated = |description: Option<&Value>| match description { + None | Some(Value::Null) => None, + Some(Value::String(d)) if d.trim().is_empty() => None, + Some(d) => Some(text(d)), + }; + questions + .iter() + .map(|(name, question)| { + let criteria = question.get("criteria"); + let mut instructions = question.get("instructions").map(text).unwrap_or_default(); + let mut asked = Map::new(); + let kind = match question.get("type").and_then(Value::as_str) { + Some("choice") => { + let choices = criteria + .and_then(Value::as_object) + .filter(|c| !c.is_empty()) + .ok_or_else(|| { + Error::BadRequest(format!( + "The choice question '{name}' needs its options as 'criteria'" + )) + })? + .iter() + .map(|(value, d)| match stated(Some(d)) { + Some(d) => serde_json::json!({"value": value, "description": d}), + None => serde_json::json!({"value": value}), + }) + .collect(); + asked.insert("choices".to_string(), Value::Array(choices)); + "choice" + } + Some("score") => { + let levels = criteria + .and_then(Value::as_array) + .filter(|c| !c.is_empty()) + .ok_or_else(|| { + Error::BadRequest(format!( + "The score question '{name}' needs its levels as 'criteria'" + )) + })? + .iter() + .map(|level| serde_json::json!({"label": text(level)})) + .collect(); + asked.insert("levels".to_string(), Value::Array(levels)); + "score" + } + Some("noul") => { + for (key, meaning) in [("true", "Yes"), ("false", "No")] { + if let Some(d) = stated(criteria.and_then(|c| c.get(key))) { + instructions.push_str(&format!("\n{meaning}: {d}")); + } + } + "predicate" + } + other => { + return Err(Error::BadRequest(format!( + "The question '{name}' has type {}, which is not 'choice', 'score' or 'noul'", + other.map_or("none".to_string(), |t| format!("'{t}'")) + ))) + } + }; + asked.insert("type".to_string(), kind.into()); + asked.insert("name".to_string(), name.as_str().into()); + asked.insert("instructions".to_string(), instructions.into()); + Ok(Value::Object(asked)) + }) + .collect() +} + +/// OpenAI's answers keyed by question name, as every decision's are. A predicate's probability is +/// also given as `noul`, so a flow reads a yes/no answer the same way whichever provider gave it. +/// A refused question fails the decision: left in the output it has no `choice` or `noul`, so a +/// branch on it would quietly take its "no" or default arm. +fn openai_answers(answers: Vec>) -> Result> { + let mut by_name = Map::new(); + for mut answer in answers { + let Some(Value::String(name)) = answer.remove("name") else { + continue; + }; + match answer.get("type").and_then(Value::as_str) { + Some("refusal") => { + return Err(Error::ExecutionErr(format!( + "OpenAI refused to answer the question '{name}': {}", + Value::Object(answer) + ))) + } + Some("predicate") => { + if let Some(probability) = answer.get("probability").cloned() { + answer.insert("noul".to_string(), probability); + } + } + _ => {} + } + by_name.insert(name, Value::Object(answer)); + } + Ok(by_name) +} + +async fn run_openai_decisions( + credentials: &ProviderCredentials, + model: &str, + state: &Value, + questions: &Map, + timeout: Duration, +) -> Result { + let model = match model.trim() { + "" => OPENAI_DEFAULT_MODEL, + model => model, + }; + let endpoint = format!("{}/decisions", credentials.base_url.trim_end_matches('/')); + let body = post_decision( + credentials, + &endpoint, + "OpenAI", + &OpenAIDecisionsRequest { + model, + input: openai_input(state), + questions: openai_questions(questions)?, + }, + timeout, + ) + .await?; + let parsed = serde_json::from_str::(&body) + .map_err(|e| Error::ExecutionErr(format!("Unexpected OpenAI response ({e}): {body}")))?; + + Ok(DecisionResult { + output: serde_json::value::to_raw_value(&openai_answers(parsed.answers)?) + .map_err(|e| Error::internal_err(format!("serializing decision answers: {e}")))?, + model: parsed.model, + usage: parsed + .usage + .map(|u| TokenUsage::from_input_output(u.input_tokens, u.output_tokens)) + .filter(|u| !u.is_empty()), + }) +} + +async fn run_systemone( credentials: &ProviderCredentials, model: &str, state: &Value, @@ -138,49 +397,14 @@ pub async fn run_systemone( format!("{base}/systemone") }; let vendor = if cloudflare { "Cloudflare" } else { "TypeSafe" }; - let auth_headers = retain_effective_credentials( + let body = post_decision( credentials, - vec![( - "Authorization", - format!( - "Bearer {}", - credentials.api_key.as_deref().unwrap_or_default() - ), - )], - ); - - // The endpoint derives from the resource's base URL, so the connect is pinned to the - // address the SSRF check validated. - let client = pinned_ai_client_for(&credentials.base_url).await?; - let mut request = client.post(&endpoint).timeout(timeout); - for (name, value) in auth_headers { - request = request.header(name, value); - } - for (name, value) in common_outbound_headers(credentials) { - request = request.header(name, value); - } - - let response = request - .json(&SystemOneRequest { model, state, questions }) - .send() - .await - .map_err(|e| Error::ExecutionErr(format!("Failed to call {vendor}: {e}")))?; - - let status = response.status(); - if !status.is_success() { - let body = response - .text() - .await - .unwrap_or_else(|_| "".to_string()); - return Err(Error::ExecutionErr(format!( - "{vendor} error calling {endpoint}: {status} - {body}" - ))); - } - - let body = response - .text() - .await - .map_err(|e| Error::ExecutionErr(format!("Failed to read the {vendor} response: {e}")))?; + &endpoint, + vendor, + &SystemOneRequest { model, state, questions }, + timeout, + ) + .await?; // Tried in turn rather than as an untagged enum, which cannot hold the raw `answers`. let parsed = match serde_json::from_str::(&body) { Ok(parsed) => parsed, @@ -223,6 +447,80 @@ mod tests { } } + /// A `noul` goes out as a predicate with its yes/no meanings in the instructions, and comes + /// back readable as `noul`; choices and levels go out as lists, answers come back by name. + #[test] + fn openai_questions_and_answers_translate() { + let questions = json!({ + "intent": {"type": "choice", "instructions": "Why?", "criteria": {"refund": {"when": "paid"}, "bug": ""}}, + "urgency": {"type": "score", "instructions": "How urgent?", "criteria": ["Can wait", "Now"]}, + "angry": {"type": "noul", "instructions": "Angry?", "criteria": {"true": "Insults"}} + }); + let asked = Value::Array(openai_questions(questions.as_object().unwrap()).unwrap()); + assert_eq!( + asked, + json!([ + {"choices": [ + {"value": "refund", "description": "{\"when\":\"paid\"}"}, + {"value": "bug"} + ], "type": "choice", "name": "intent", "instructions": "Why?"}, + {"levels": [ + {"label": "Can wait"}, + {"label": "Now"} + ], "type": "score", "name": "urgency", "instructions": "How urgent?"}, + {"type": "predicate", "name": "angry", "instructions": "Angry?\nYes: Insults"} + ]) + ); + for bad in [ + json!({"q": {"type": "choice", "instructions": "?"}}), + json!({"q": {"type": "score", "instructions": "?", "criteria": []}}), + json!({"q": {"type": "predicate", "instructions": "?"}}), + ] { + assert!(openai_questions(bad.as_object().unwrap()).is_err(), "{bad}"); + } + + let answers = serde_json::from_value(json!([ + {"type": "predicate", "name": "angry", "probability": 0.92}, + {"type": "choice", "name": "intent", "choice": "refund", "confidence": 0.9} + ])) + .unwrap(); + assert_eq!( + Value::Object(openai_answers(answers).unwrap()), + json!({ + "angry": {"type": "predicate", "probability": 0.92, "noul": 0.92}, + "intent": {"type": "choice", "choice": "refund", "confidence": 0.9} + }) + ); + + let messages = json!([{"role": "user", "content": [{"type": "input_text", "text": "hi"}]}]); + assert_eq!(openai_input(&messages), messages); + assert_eq!(openai_input(&json!({"m": "hi"})), json!("{\"m\":\"hi\"}")); + assert_eq!( + openai_input(&json!([{"role": "admin"}])), + json!("[{\"role\":\"admin\"}]") + ); + for records in [ + json!([{"role": "user", "content": {"ticket": "charged twice"}}]), + json!([{"role": "user", "content": null}]), + json!([{"role": "user", "content": ["a"]}]), + json!([{"role": "user", "content": [{"type": "input_text", "text": {"t": 1}}]}]), + json!([{"role": "user", "content": [{"type": "input_image"}]}]), + ] { + assert_eq!(openai_input(&records), json!(records.to_string())); + } + assert_eq!( + openai_input(&json!([{"role": "user", "content": "Hi"}])), + json!([{"role": "user", "content": "Hi"}]) + ); + // A chat history is evaluated as text: OpenAI takes user messages only. + let history = + json!([{"role": "user", "content": "Hi"}, {"role": "assistant", "content": "Yo"}]); + assert_eq!(openai_input(&history), json!(history.to_string())); + let refused = + serde_json::from_value(json!([{"type": "refusal", "name": "angry"}])).unwrap(); + assert!(openai_answers(refused).is_err()); + } + /// Refused are the values a flow produces when it forgot the input (no key, `null`, a blank /// string from an empty expression) and the scalars TypeSafe rejects. A text, an object or an /// array is a state, whatever it holds. diff --git a/backend/windmill-types/src/flows.rs b/backend/windmill-types/src/flows.rs index 3f71191415..890318b8aa 100644 --- a/backend/windmill-types/src/flows.rs +++ b/backend/windmill-types/src/flows.rs @@ -1140,7 +1140,7 @@ pub enum FlowModuleValue { #[serde(default, skip_serializing_if = "HashMap::is_empty")] tool_inputs: HashMap>, }, - /// One call to a decision model (TypeSafe's Jev) answering the typed `questions` of its + /// One call to a decision model (such as TypeSafe's Jev) answering the typed `questions` of its /// `input_transforms` about a `state`. A flow branches on the answers with a `BranchOne`. AIDecision { input_transforms: HashMap, diff --git a/backend/windmill-worker/src/ai_executor.rs b/backend/windmill-worker/src/ai_executor.rs index 133a0a0b0d..7dd2382731 100644 --- a/backend/windmill-worker/src/ai_executor.rs +++ b/backend/windmill-worker/src/ai_executor.rs @@ -28,7 +28,7 @@ use windmill_mcp::McpClient; use crate::ai::tools::McpClientStub as McpClient; use windmill_ai::{ ai_providers::AIProvider, - decision::{decision_inputs, run_systemone, AIDecisionArgs}, + decision::{decision_inputs, run_decision, AIDecisionArgs}, image_handler::upload_image_to_s3, model_context::model_context_window, providers::{ @@ -2449,9 +2449,9 @@ async fn handle_ai_decision( worker_name: &str, ) -> error::Result> { let args = serde_json::from_str::(&serde_json::to_string(local_args)?)?; - if !args.provider.kind.is_decision_provider() { + if !args.provider.kind.runs_decisions() { return Err(Error::BadRequest(format!( - "An AI decision runs on a TypeSafe or Cloudflare resource, not {:?}", + "An AI decision runs on a TypeSafe, Cloudflare or OpenAI resource, not {:?}", args.provider.kind ))); } @@ -2467,7 +2467,7 @@ async fn handle_ai_decision( conn, mem_peak, canceled_by, - run_systemone( + run_decision( &credentials, args.provider.get_model(), state, diff --git a/cli/src/guidance/skills.gen.ts b/cli/src/guidance/skills.gen.ts index 3387f15b2d..8dd9a8a329 100644 --- a/cli/src/guidance/skills.gen.ts +++ b/cli/src/guidance/skills.gen.ts @@ -5864,7 +5864,7 @@ names, so neither is name-checked at all — leave those summaries as they are. ## AI Decision Modules -An \`aidecision\` module asks a decision model (TypeSafe's Jev or Cloudflare's Clef) typed questions about a \`state\` and +An \`aidecision\` module asks a decision model (TypeSafe's Jev, Cloudflare's Clef or OpenAI's Decisions API) typed questions about a \`state\` and answers each with calibrated probabilities instead of text. Prefer it over an \`aiagent\` when the step is a judgment (classify, route, score or a yes/no check) that needs no tools and no free text: it is faster, cheaper, and its answers have a fixed shape. @@ -5902,8 +5902,9 @@ is faster, cheaper, and its answers have a fixed shape. } \`\`\` -- \`provider.kind\` is \`typesafe\` (\`model\` \`jev-latest\` unless a version is pinned) or \`cloudflare\` - (\`model\` \`clef\`, or \`clef-flash\` for faster answers); the resource is of that same type +- \`provider.kind\` is \`typesafe\` (\`model\` \`jev-latest\` unless a version is pinned), \`cloudflare\` + (\`model\` \`clef\`, or \`clef-flash\` for faster answers) or \`openai\` (\`model\` \`gpt-6-luna\`, never a + chat model); the resource is of that same type - \`state\` is the content to evaluate: usually a text, such as the message to classify. To combine several values, pass an object with descriptive keys holding only what the questions need (\`({ message: flow_input.message, plan: results.get_account.plan })\`); an array of strings also works @@ -5917,6 +5918,12 @@ is faster, cheaper, and its answers have a fixed shape. - The result is \`{ output, model, usage }\` with \`output\` keyed by question name, so a later step reads \`results.triage.output.intent.choice\`, \`results.triage.output.urgency.score\` or \`results.triage.output.angry.noul > 0.7\` +- On \`openai\` the same \`questions\` are translated for its Decisions API and the answers read the + same way (\`choice\`, \`score\`, \`noul\`), except that \`probabilities\` is a list of + \`{ value, probability }\` (plus \`label\` on a score) and a score has no \`legend\`. A question OpenAI + refuses to answer fails the step. A \`state\` that is + an array of user messages (\`[{ role: "user", content: [{ type: "input_text", text }, { type: "input_image", image_url: "data:image/png;base64,..." }] }]\`) + is sent as is, which is how an image is evaluated; any other object or array is sent as JSON text ### Branching on the Answers @@ -6272,7 +6279,7 @@ 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 (delay doubles each time)","properties":{"attempts":{"type":"integer","description":"Number of retry attempts"},"multiplier":{"type":"integer","description":"Multiplier for exponential backoff"},"seconds":{"type":"integer","minimum":1,"description":"Initial delay in seconds"},"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":{"$ref":"#/components/schemas/InputTransform"}}},"parallel":{"type":"boolean","description":"If true, the agent can execute multiple tool calls in parallel"}},"required":["type","input_transforms"]},"AiDecision":{"type":"object","description":"AI decision step: one call to a decision model (TypeSafe's Jev, or Cloudflare's\\nJev-compatible Clef) that answers typed questions about a state with calibrated\\nprobabilities, instead of generating text.\\nPrefer it over an AI agent to classify, route, score or check something: it is fast,\\ncheap and its answers are structured. Its result is { output: { : answer },\\nmodel, usage }, so a later step reads e.g. results..output.intent.choice. To route on\\nthe answers, follow it with a branchone whose branch exprs read\\nresults..output..choice. Usable as an AI agent tool, where the calling agent\\nsupplies the state.\\n","properties":{"input_transforms":{"type":"object","description":"Input parameters for the decision mapped to their values","properties":{"provider":{"$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":{"$ref":"#/components/schemas/FlowGroup"}}},"required":["modules"]},"Retry":{"type":"object","description":"Retry configuration for failed module executions","properties":{"constant":{"type":"object","description":"Retry with constant delay between attempts","properties":{"attempts":{"type":"integer","description":"Number of retry attempts"},"seconds":{"type":"integer","description":"Seconds to wait between retries"}}},"exponential":{"type":"object","description":"Retry with exponential backoff (delay doubles each time)","properties":{"attempts":{"type":"integer","description":"Number of retry attempts"},"multiplier":{"type":"integer","description":"Multiplier for exponential backoff"},"seconds":{"type":"integer","minimum":1,"description":"Initial delay in seconds"},"random_factor":{"type":"integer","minimum":0,"maximum":100,"description":"Random jitter percentage (0-100) to avoid thundering herd"}}},"retry_if":{"$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"]}} `, "raw-app": `--- name: raw-app diff --git a/frontend/src/lib/components/AIProviderPicker.svelte b/frontend/src/lib/components/AIProviderPicker.svelte index 6369d0abb1..67afad9be6 100644 --- a/frontend/src/lib/components/AIProviderPicker.svelte +++ b/frontend/src/lib/components/AIProviderPicker.svelte @@ -24,8 +24,8 @@ * other than the one being navigated. Resources and the models read off them are per * workspace, so without it this offers what the wrong one holds. */ workspace?: string | undefined - /** Offer the decision providers (TypeSafe, Cloudflare) in place of the chat ones, for an AI - * decision. */ + /** Offer the decision providers (TypeSafe, Cloudflare, OpenAI) and their decision models in + * place of the chat ones, for an AI decision. */ decision?: boolean } @@ -84,6 +84,15 @@ return r }) + // A decision provider's models are the ones Windmill knows: none has a listing of its decision + // models, and an OpenAI resource's lists its chat models. + function defaultModels(provider: AIProvider): string[] { + return decision + ? ((DECISION_AI_PROVIDERS as Record)[provider] + ?.defaultModels ?? []) + : aiProviderDetails(provider).defaultModels + } + async function loadModels(signal?: AbortSignal) { const provider = value?.kind const resourceValue = value?.resource @@ -92,6 +101,11 @@ if (!provider || !resourcePath) { return } + if (decision) { + availableModels = defaultModels(provider) + loading = false + return + } loading = true const cacheKey = `${effectiveWorkspace}:${provider}:${resourcePath}` @@ -113,8 +127,7 @@ return } // Fall back to default models for this provider - const defaultModels = aiProviderDetails(provider).defaultModels - availableModels = defaultModels + availableModels = defaultModels(provider) } finally { if (!signal?.aborted) { loading = false @@ -178,8 +191,7 @@ if (provider && resourcePath) { loadModels(abortController.signal) } else { - const defaultModels = provider ? aiProviderDetails(provider).defaultModels : [] - availableModels = defaultModels + availableModels = provider ? defaultModels(provider) : [] loading = false } diff --git a/frontend/src/lib/components/copilot/chat/flow/aiAgentProviderCatalog.ts b/frontend/src/lib/components/copilot/chat/flow/aiAgentProviderCatalog.ts index b3c1e456e1..37bdec30ce 100644 --- a/frontend/src/lib/components/copilot/chat/flow/aiAgentProviderCatalog.ts +++ b/frontend/src/lib/components/copilot/chat/flow/aiAgentProviderCatalog.ts @@ -19,7 +19,9 @@ import { // included so an AI decision step's resource validates; `validateAiAgentProviders` keeps each kind // to its step type. const aiResourceTypes = () => - [...Object.keys(AI_PROVIDERS), ...Object.keys(DECISION_AI_PROVIDERS)] as AIProvider[] + [ + ...new Set([...Object.keys(AI_PROVIDERS), ...Object.keys(DECISION_AI_PROVIDERS)]) + ] as AIProvider[] /** Kinds whose model listing `fetchAvailableModels` narrows before returning it: OpenAI and Azure * OpenAI keep only `gpt-`/`o`/`codex` ids (so a fine-tune never appears), Bedrock keeps text diff --git a/frontend/src/lib/components/copilot/chat/flow/aiAgentProviders.test.ts b/frontend/src/lib/components/copilot/chat/flow/aiAgentProviders.test.ts index 318efd9731..14720bb001 100644 --- a/frontend/src/lib/components/copilot/chat/flow/aiAgentProviders.test.ts +++ b/frontend/src/lib/components/copilot/chat/flow/aiAgentProviders.test.ts @@ -128,8 +128,15 @@ describe('validateAiAgentProviders', () => { ] expect(() => validateAiAgentProviders(decision(anthropic), undefined)).toThrow( - /Step "d".*must be "typesafe" or "cloudflare"/ + /Step "d".*must be "typesafe", "cloudflare" or "openai"/ ) + // OpenAI runs both: its resource serves the decision model next to the chat ones. + const openai = (model: string) => ({ + type: 'static', + value: { kind: 'openai', resource: '$res:u/admin/openai', model } + }) + expect(() => validateAiAgentProviders(decision(openai('gpt-6-luna')), undefined)).not.toThrow() + expect(() => validateAiAgentProviders(agentStep(openai('gpt-5')), undefined)).not.toThrow() expect(() => validateAiAgentProviders(agentStep(typesafe), undefined)).toThrow( /Step "agent".*use an "aidecision" step/ ) diff --git a/frontend/src/lib/components/copilot/chat/flow/aiAgentProviders.ts b/frontend/src/lib/components/copilot/chat/flow/aiAgentProviders.ts index 69b5c71624..799c1f0cef 100644 --- a/frontend/src/lib/components/copilot/chat/flow/aiAgentProviders.ts +++ b/frontend/src/lib/components/copilot/chat/flow/aiAgentProviders.ts @@ -29,8 +29,15 @@ export type AiAgentProviderCatalog = { defaultModel?: { kind: AIProvider; model: string } } -/** The providers an AI decision step runs on, and the kinds an AI agent step cannot. */ -const DECISION_PROVIDER_KINDS: readonly string[] = ['typesafe', 'cloudflare'] +/** The kinds that serve decision models only, which an AI agent step cannot run on. */ +const DECISION_ONLY_KINDS: readonly string[] = ['typesafe', 'cloudflare'] + +/** The model of OpenAI's Decisions API, which an `openai` resource serves next to its chat + * models: the one kind both step types run on. */ +const OPENAI_DECISION_MODEL = 'gpt-6-luna' + +/** The providers an AI decision step runs on. */ +const DECISION_PROVIDER_KINDS: readonly string[] = [...DECISION_ONLY_KINDS, 'openai'] /** A model id as every provider writes one: `claude-sonnet-5`, `meta-llama/Llama-3.3-70B`, * `anthropic.claude-haiku-4-5-20251001-v1:0`, `ft:gpt-4o:acme::abc`. Anything else is not @@ -150,7 +157,7 @@ This workspace has none, so an AI agent step has no model to run on. ${ ? '' : '\nThis list is incomplete: the workspace has AI provider resources that are not shown.' const decisionLine = catalog.options.some((o) => DECISION_PROVIDER_KINDS.includes(o.kind)) - ? `\nA \`typesafe\` or \`cloudflare\` resource serves AI decision steps only, and AI decision steps run on nothing else.` + ? `\nA \`typesafe\` or \`cloudflare\` resource serves AI decision steps only. AI decision steps run on those or on an \`openai\` resource with model \`${OPENAI_DECISION_MODEL}\`, and on nothing else.` : '' return `## AI provider resources in this workspace @@ -249,10 +256,10 @@ function checkProviderValue( } if (stepType === 'aidecision' && !DECISION_PROVIDER_KINDS.includes(kind)) { return blocking( - `an AI decision step runs on a decision model: provider.kind must be "typesafe" or "cloudflare", not "${kind}"` + `an AI decision step runs on a decision model: provider.kind must be "typesafe", "cloudflare" or "openai", not "${kind}"` ) } - if (stepType !== 'aidecision' && DECISION_PROVIDER_KINDS.includes(kind)) { + if (stepType !== 'aidecision' && DECISION_ONLY_KINDS.includes(kind)) { return blocking( `"${kind}" serves decision models, which answer typed questions rather than messages: use an "aidecision" step rather than an AI agent` ) @@ -286,6 +293,15 @@ function checkProviderValue( `provider.kind "${kind}" does not match "${resource}", which is a \`${match.kind}\` resource` ) } + // An OpenAI resource lists its chat models, which says nothing about its decision model. + if (stepType === 'aidecision' && kind === 'openai') { + return model === OPENAI_DECISION_MODEL + ? undefined + : { + message: `model "${model}" is not the model OpenAI's Decisions API is known to serve, "${OPENAI_DECISION_MODEL}"`, + blocking: false + } + } if (match.modelsAreLive && !match.models.ids.includes(model)) { return { message: `model "${model}" is not in the model listing of "${resource}"`, diff --git a/frontend/src/lib/components/copilot/chat/flow/openFlow.json b/frontend/src/lib/components/copilot/chat/flow/openFlow.json index da28803f7c..2224d89b78 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":"1.820.0","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 (delay doubles each time)","properties":{"attempts":{"type":"integer","description":"Number of retry attempts"},"multiplier":{"type":"integer","description":"Multiplier for exponential backoff"},"seconds":{"type":"integer","minimum":1,"description":"Initial delay in seconds"},"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","$ref":"#/components/schemas/InputTransform"},"self_approval_disabled":{"type":"boolean","description":"If true, the user who started the flow cannot approve"},"hide_cancel":{"type":"boolean","description":"If true, hide the cancel button on the approval form"},"continue_on_disapprove_timeout":{"type":"boolean","description":"If true, continue flow on timeout instead of canceling"},"skin":{"type":"string","enum":["detailed","minimal"],"description":"How the approval request is presented, on the approval page and in Slack/Teams approval messages. 'detailed' (used when unset) shows the flow details (arguments, graph, approvers); 'minimal' shows only the request: the step description, form and approve/reject actions"}}},"priority":{"type":"number","description":"Execution priority for this step (higher numbers run first)"},"continue_on_error":{"type":"boolean","description":"If true, flow continues even if this step fails"},"retry":{"description":"Retry configuration if this step fails","$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."},"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":{"$ref":"#/components/schemas/InputTransform"}}},"parallel":{"type":"boolean","description":"If true, the agent can execute multiple tool calls in parallel"}},"required":["type","input_transforms"]},"AiDecision":{"type":"object","description":"AI decision step: one call to a decision model (TypeSafe's Jev, or Cloudflare's\nJev-compatible Clef) that answers typed questions about a state with calibrated\nprobabilities, instead of generating text.\nPrefer it over an AI agent to classify, route, score or check something: it is fast,\ncheap and its answers are structured. Its result is { output: { : answer },\nmodel, usage }, so a later step reads e.g. results..output.intent.choice. To route on\nthe answers, follow it with a branchone whose branch exprs read\nresults..output..choice. Usable as an AI agent tool, where the calling agent\nsupplies the state.\n","properties":{"input_transforms":{"type":"object","description":"Input parameters for the decision mapped to their values","properties":{"provider":{"$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":"1.825.0","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":{"$ref":"#/components/schemas/FlowGroup"}}},"required":["modules"]},"Retry":{"type":"object","description":"Retry configuration for failed module executions","properties":{"constant":{"type":"object","description":"Retry with constant delay between attempts","properties":{"attempts":{"type":"integer","description":"Number of retry attempts"},"seconds":{"type":"integer","description":"Seconds to wait between retries"}}},"exponential":{"type":"object","description":"Retry with exponential backoff (delay doubles each time)","properties":{"attempts":{"type":"integer","description":"Number of retry attempts"},"multiplier":{"type":"integer","description":"Multiplier for exponential backoff"},"seconds":{"type":"integer","minimum":1,"description":"Initial delay in seconds"},"random_factor":{"type":"integer","minimum":0,"maximum":100,"description":"Random jitter percentage (0-100) to avoid thundering herd"}}},"retry_if":{"$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 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 128dd03f3f..570c83f52d 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(), "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("Initial delay in seconds").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 (delay doubles each time)").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. 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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(), "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("Initial delay in seconds").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 (delay doubles each time)").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. 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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. 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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'. 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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. 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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").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(), "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("Initial delay in seconds").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 (delay doubles each time)").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("Initial delay in seconds").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 (delay doubles each time)").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: $workspace/flow/-").optional(), "debounce_args_to_accumulate": z.array(z.string()).describe("Array-type arguments to accumulate across debounced executions").optional(), "max_total_debouncing_time": z.number().int().describe("Maximum total time in seconds before forced execution").optional(), "max_total_debounces_amount": z.number().int().describe("Maximum number of debounces before forced execution").optional() }).describe("Debounce configuration for this step (EE only)").optional() }).describe("A single step in a flow. 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Use for hardcoded values or resource references like '$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("Initial delay in seconds").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 (delay doubles each time)").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) => { 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) => @@ -17,10 +17,10 @@ export const flowModuleValueSchema = z.discriminatedUnion("type", [z.object({ "i message: "Invalid input: Should pass single schema", }); } - }).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, or Cloudflare's\nJev-compatible Clef) that answers typed questions about a state with calibrated\nprobabilities, 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") + }).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(), "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 '$res:path/to/resource'"), z.object({ "expr": z.string().describe("JavaScript expression returning the value. Available variables - results (object with all previous step results), flow_input (flow inputs), flow_input.iter (in loops)"), "type": z.literal("javascript") }).describe("JavaScript expression evaluated at runtime. Can reference previous step results via 'results.step_id' or flow inputs via 'flow_input.property'. Inside for loops, use 'flow_input.iter.value' for the current iteration value (in while loops it equals 'flow_input.iter.index')"), z.object({ "type": z.literal("ai") }).describe("Value resolved by the AI runtime for this input. The AI engine decides how to satisfy the parameter.")]).describe("Maps input parameters for a step. Can be a static value or a JavaScript expression that references previous results or flow inputs").describe("Number. Limits how many times the agent can loop through reasoning and tool use.\nRange: 1-1000.\n").optional() }).describe("Input parameters for the AI agent mapped to their values"), "tools": z.array(z.object({ "id": z.string().describe("Unique identifier for this tool. Cannot contain spaces - use underscores instead (e.g., 'get_user_data' not 'get user data')"), "summary": z.string().describe("The name the AI agent calls this tool by, not a human label. On a flowmodule tool it must match ^[a-zA-Z0-9_]+$ - 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) => @@ -37,7 +37,7 @@ export const flowModuleSchema = z.object({ "id": z.string().describe("Unique ide message: "Invalid input: Should pass single schema", }); } - }).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, or Cloudflare's\nJev-compatible Clef) that answers typed questions about a state with calibrated\nprobabilities, 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"), "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(), "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("Initial delay in seconds").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 (delay doubles each time)").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: $workspace/flow/-").optional(), "debounce_args_to_accumulate": z.array(z.string()).describe("Array-type arguments to accumulate across debounced executions").optional(), "max_total_debouncing_time": z.number().int().describe("Maximum total time in seconds before forced execution").optional(), "max_total_debounces_amount": z.number().int().describe("Maximum number of debounces before forced execution").optional() }).describe("Debounce configuration for this step (EE only)").optional() }).describe("A single step in a flow. Can be a script, subflow, loop, or branch") + }).describe("The implementation of a tool. Can be a flow module (script/flow) or an MCP tool reference") }).describe("A tool available to an AI agent. Can be a flow module or an external MCP (Model Context Protocol) tool")).describe("Array of tools the agent can use. The agent decides which tools to call based on the task").optional(), "type": z.literal("aiagent"), "tag": z.string().describe("Worker group tag for execution routing. If not set, the AI agent step runs on the flow's tag (default `flow`)").optional(), "omit_output_from_conversation": z.boolean().describe("If true, this AI agent step does not persist its assistant or tool messages to the flow conversation when chat mode is enabled.").default(false), "agent": z.string().describe("Path of a reusable `ai_agent` resource (hybrid linking). When set, the agent brain\nconfig (provider/model/system prompt/etc.) and tool set are resolved at runtime from\nthat resource; the module's input_transforms then only carry the flow-local inputs\n(user_message, user_attachments, enabled_tools and the history inputs memory_id and previous_messages).\n").optional(), "tool_inputs": z.record(z.string(), z.record(z.string(), z.discriminatedUnion("type", [z.object({ "value": z.any().describe("The static value. For resources, use format '$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"), "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("Initial delay in seconds").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 (delay doubles each time)").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") export const flowModulesSchema = z.array(flowModuleSchema) diff --git a/frontend/src/lib/components/copilot/lib.ts b/frontend/src/lib/components/copilot/lib.ts index 08d407a329..c53028031d 100644 --- a/frontend/src/lib/components/copilot/lib.ts +++ b/frontend/src/lib/components/copilot/lib.ts @@ -168,12 +168,17 @@ export const AI_PROVIDERS: Record = { } /** Decision models answer typed questions instead of messages, so only an AI decision offers - * them: TypeSafe's Jev, and Cloudflare's Jev-compatible Clef. The pinned Jev version is there + * them: TypeSafe's Jev, Cloudflare's Jev-compatible Clef, and the model of OpenAI's Decisions + * API, which an OpenAI resource serves next to its chat models. The pinned Jev version is there * for flows tuned against its probabilities. */ export const DECISION_AI_PROVIDERS: Record< - Exclude, + Exclude | 'openai', AIProviderDetails > = { + openai: { + label: 'OpenAI', + defaultModels: ['gpt-6-luna'] + }, typesafe: { label: 'TypeSafe', defaultModels: ['jev-latest', 'jev-1.13.0'] diff --git a/frontend/src/lib/components/flows/flowInfers.ts b/frontend/src/lib/components/flows/flowInfers.ts index d38f5c1945..f2beefa0de 100644 --- a/frontend/src/lib/components/flows/flowInfers.ts +++ b/frontend/src/lib/components/flows/flowInfers.ts @@ -212,15 +212,16 @@ export const AI_AGENT_SCHEMA: Schema = { ] } -/** The inputs of an AI decision step: one call to a decision model (TypeSafe's Jev, or - * Cloudflare's Clef). */ +/** The inputs of an AI decision step: one call to a decision model (TypeSafe's Jev, Cloudflare's + * Clef, or OpenAI's Decisions API). */ export const AI_DECISION_SCHEMA: Schema = { $schema: 'https://json-schema.org/draft/2020-12/schema', properties: { provider: { type: 'object', format: 'ai-decision-provider', - description: 'The decision model to ask: TypeSafe (Jev) or Cloudflare (Clef).' + description: + 'The decision model to ask: TypeSafe (Jev), Cloudflare (Clef) or OpenAI (Decisions API).' }, // Untyped, so the static editor takes any JSON: TypeSafe reads a string, an object or an // array of strings. diff --git a/openflow.openapi.yaml b/openflow.openapi.yaml index fc6309609f..b3c6faacf4 100644 --- a/openflow.openapi.yaml +++ b/openflow.openapi.yaml @@ -1231,9 +1231,9 @@ components: AiDecision: type: object description: | - AI decision step: one call to a decision model (TypeSafe's Jev, or Cloudflare's - Jev-compatible Clef) that answers typed questions about a state with calibrated - probabilities, instead of generating text. + AI decision step: one call to a decision model (TypeSafe's Jev, Cloudflare's + Jev-compatible Clef, or OpenAI's Decisions API) that answers typed questions about a + state with calibrated probabilities, instead of generating text. Prefer it over an AI agent to classify, route, score or check something: it is fast, cheap and its answers are structured. Its result is { output: { : answer }, model, usage }, so a later step reads e.g. results..output.intent.choice. To route on @@ -1245,8 +1245,8 @@ components: type: object description: Input parameters for the decision mapped to their values properties: - # A provider config whose kind is 'typesafe' (model 'jev-latest' unless pinned) or - # 'cloudflare' (model 'clef' or 'clef-flash'). + # A provider config whose kind is 'typesafe' (model 'jev-latest' unless pinned), + # 'cloudflare' (model 'clef' or 'clef-flash') or 'openai' (model 'gpt-6-luna'). provider: $ref: '#/components/schemas/ProviderTransform' state: diff --git a/system_prompts/auto-generated/flow.md b/system_prompts/auto-generated/flow.md index 6ecb856a4c..4ffe39cfde 100644 --- a/system_prompts/auto-generated/flow.md +++ b/system_prompts/auto-generated/flow.md @@ -179,7 +179,7 @@ names, so neither is name-checked at all — leave those summaries as they are. ## AI Decision Modules -An `aidecision` module asks a decision model (TypeSafe's Jev or Cloudflare's Clef) typed questions about a `state` and +An `aidecision` module asks a decision model (TypeSafe's Jev, Cloudflare's Clef or OpenAI's Decisions API) typed questions about a `state` and answers each with calibrated probabilities instead of text. Prefer it over an `aiagent` when the step is a judgment (classify, route, score or a yes/no check) that needs no tools and no free text: it is faster, cheaper, and its answers have a fixed shape. @@ -217,8 +217,9 @@ is faster, cheaper, and its answers have a fixed shape. } ``` -- `provider.kind` is `typesafe` (`model` `jev-latest` unless a version is pinned) or `cloudflare` - (`model` `clef`, or `clef-flash` for faster answers); the resource is of that same type +- `provider.kind` is `typesafe` (`model` `jev-latest` unless a version is pinned), `cloudflare` + (`model` `clef`, or `clef-flash` for faster answers) or `openai` (`model` `gpt-6-luna`, never a + chat model); the resource is of that same type - `state` is the content to evaluate: usually a text, such as the message to classify. To combine several values, pass an object with descriptive keys holding only what the questions need (`({ message: flow_input.message, plan: results.get_account.plan })`); an array of strings also works @@ -232,6 +233,12 @@ is faster, cheaper, and its answers have a fixed shape. - The result is `{ output, model, usage }` with `output` keyed by question name, so a later step reads `results.triage.output.intent.choice`, `results.triage.output.urgency.score` or `results.triage.output.angry.noul > 0.7` +- On `openai` the same `questions` are translated for its Decisions API and the answers read the + same way (`choice`, `score`, `noul`), except that `probabilities` is a list of + `{ value, probability }` (plus `label` on a score) and a score has no `legend`. A question OpenAI + refuses to answer fails the step. A `state` that is + an array of user messages (`[{ role: "user", content: [{ type: "input_text", text }, { type: "input_image", image_url: "data:image/png;base64,..." }] }]`) + is sent as is, which is how an image is evaluated; any other object or array is sent as JSON text ### Branching on the Answers @@ -586,4 +593,4 @@ Reference a specific resource using `$res:` prefix: ## OpenFlow Schema -{"OpenFlow":{"type":"object","description":"Top-level flow definition containing metadata, configuration, and the flow structure","properties":{"summary":{"type":"string","description":"Short description of what this flow does"},"description":{"type":"string","description":"Detailed documentation for this flow"},"value":{"$ref":"#/components/schemas/FlowValue"},"schema":{"type":"object","description":"JSON Schema for flow inputs. Use this to define input parameters, their types, defaults, and validation. For resource inputs, set type to 'object' and format to 'resource-' (e.g., 'resource-stripe')"},"on_behalf_of_email":{"type":"string","description":"Address of the account the flow runs on behalf of. Derived from on_behalf_of on read; accepted on write, where it is resolved to the account it names."},"on_behalf_of":{"type":"string","description":"The flow runs with the permissions of this identity: u/{username}, g/{group}, or a bare email when the username is itself email-shaped. The only stored half of the identity; on_behalf_of_email is derived from it. Omit it when writing and it is resolved from that address instead."}},"required":["summary","value"]},"FlowValue":{"type":"object","description":"The flow structure containing modules and optional preprocessor/failure handlers","properties":{"modules":{"type":"array","description":"Array of steps that execute in sequence. Each step can be a script, subflow, loop, or branch","items":{"$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 (delay doubles each time)","properties":{"attempts":{"type":"integer","description":"Number of retry attempts"},"multiplier":{"type":"integer","description":"Multiplier for exponential backoff"},"seconds":{"type":"integer","minimum":1,"description":"Initial delay in seconds"},"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":{"$ref":"#/components/schemas/InputTransform"}}},"parallel":{"type":"boolean","description":"If true, the agent can execute multiple tool calls in parallel"}},"required":["type","input_transforms"]},"AiDecision":{"type":"object","description":"AI decision step: one call to a decision model (TypeSafe's Jev, or Cloudflare's\nJev-compatible Clef) that answers typed questions about a state with calibrated\nprobabilities, instead of generating text.\nPrefer it over an AI agent to classify, route, score or check something: it is fast,\ncheap and its answers are structured. Its result is { output: { : answer },\nmodel, usage }, so a later step reads e.g. results..output.intent.choice. To route on\nthe answers, follow it with a branchone whose branch exprs read\nresults..output..choice. Usable as an AI agent tool, where the calling agent\nsupplies the state.\n","properties":{"input_transforms":{"type":"object","description":"Input parameters for the decision mapped to their values","properties":{"provider":{"$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 +{"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":{"$ref":"#/components/schemas/FlowGroup"}}},"required":["modules"]},"Retry":{"type":"object","description":"Retry configuration for failed module executions","properties":{"constant":{"type":"object","description":"Retry with constant delay between attempts","properties":{"attempts":{"type":"integer","description":"Number of retry attempts"},"seconds":{"type":"integer","description":"Seconds to wait between retries"}}},"exponential":{"type":"object","description":"Retry with exponential backoff (delay doubles each time)","properties":{"attempts":{"type":"integer","description":"Number of retry attempts"},"multiplier":{"type":"integer","description":"Multiplier for exponential backoff"},"seconds":{"type":"integer","minimum":1,"description":"Initial delay in seconds"},"random_factor":{"type":"integer","minimum":0,"maximum":100,"description":"Random jitter percentage (0-100) to avoid thundering herd"}}},"retry_if":{"$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"]}} \ No newline at end of file diff --git a/system_prompts/auto-generated/prompts.ts b/system_prompts/auto-generated/prompts.ts index e022709f59..562c817af7 100644 --- a/system_prompts/auto-generated/prompts.ts +++ b/system_prompts/auto-generated/prompts.ts @@ -206,7 +206,7 @@ names, so neither is name-checked at all — leave those summaries as they are. ## AI Decision Modules -An \`aidecision\` module asks a decision model (TypeSafe's Jev or Cloudflare's Clef) typed questions about a \`state\` and +An \`aidecision\` module asks a decision model (TypeSafe's Jev, Cloudflare's Clef or OpenAI's Decisions API) typed questions about a \`state\` and answers each with calibrated probabilities instead of text. Prefer it over an \`aiagent\` when the step is a judgment (classify, route, score or a yes/no check) that needs no tools and no free text: it is faster, cheaper, and its answers have a fixed shape. @@ -244,8 +244,9 @@ is faster, cheaper, and its answers have a fixed shape. } \`\`\` -- \`provider.kind\` is \`typesafe\` (\`model\` \`jev-latest\` unless a version is pinned) or \`cloudflare\` - (\`model\` \`clef\`, or \`clef-flash\` for faster answers); the resource is of that same type +- \`provider.kind\` is \`typesafe\` (\`model\` \`jev-latest\` unless a version is pinned), \`cloudflare\` + (\`model\` \`clef\`, or \`clef-flash\` for faster answers) or \`openai\` (\`model\` \`gpt-6-luna\`, never a + chat model); the resource is of that same type - \`state\` is the content to evaluate: usually a text, such as the message to classify. To combine several values, pass an object with descriptive keys holding only what the questions need (\`({ message: flow_input.message, plan: results.get_account.plan })\`); an array of strings also works @@ -259,6 +260,12 @@ is faster, cheaper, and its answers have a fixed shape. - The result is \`{ output, model, usage }\` with \`output\` keyed by question name, so a later step reads \`results.triage.output.intent.choice\`, \`results.triage.output.urgency.score\` or \`results.triage.output.angry.noul > 0.7\` +- On \`openai\` the same \`questions\` are translated for its Decisions API and the answers read the + same way (\`choice\`, \`score\`, \`noul\`), except that \`probabilities\` is a list of + \`{ value, probability }\` (plus \`label\` on a score) and a score has no \`legend\`. A question OpenAI + refuses to answer fails the step. A \`state\` that is + an array of user messages (\`[{ role: "user", content: [{ type: "input_text", text }, { type: "input_image", image_url: "data:image/png;base64,..." }] }]\`) + is sent as is, which is how an image is evaluated; any other object or array is sent as JSON text ### Branching on the Answers @@ -3467,7 +3474,7 @@ class SqlQuery: export const OPENFLOW_SCHEMA = `## OpenFlow Schema -{"OpenFlow":{"type":"object","description":"Top-level flow definition containing metadata, configuration, and the flow structure","properties":{"summary":{"type":"string","description":"Short description of what this flow does"},"description":{"type":"string","description":"Detailed documentation for this flow"},"value":{"$ref":"#/components/schemas/FlowValue"},"schema":{"type":"object","description":"JSON Schema for flow inputs. Use this to define input parameters, their types, defaults, and validation. For resource inputs, set type to 'object' and format to 'resource-' (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":{"$ref":"#/components/schemas/FlowGroup"}}},"required":["modules"]},"Retry":{"type":"object","description":"Retry configuration for failed module executions","properties":{"constant":{"type":"object","description":"Retry with constant delay between attempts","properties":{"attempts":{"type":"integer","description":"Number of retry attempts"},"seconds":{"type":"integer","description":"Seconds to wait between retries"}}},"exponential":{"type":"object","description":"Retry with exponential backoff (delay doubles each time)","properties":{"attempts":{"type":"integer","description":"Number of retry attempts"},"multiplier":{"type":"integer","description":"Multiplier for exponential backoff"},"seconds":{"type":"integer","minimum":1,"description":"Initial delay in seconds"},"random_factor":{"type":"integer","minimum":0,"maximum":100,"description":"Random jitter percentage (0-100) to avoid thundering herd"}}},"retry_if":{"$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":{"$ref":"#/components/schemas/InputTransform"}}},"parallel":{"type":"boolean","description":"If true, the agent can execute multiple tool calls in parallel"}},"required":["type","input_transforms"]},"AiDecision":{"type":"object","description":"AI decision step: one call to a decision model (TypeSafe's Jev, or Cloudflare's\\nJev-compatible Clef) that answers typed questions about a state with calibrated\\nprobabilities, instead of generating text.\\nPrefer it over an AI agent to classify, route, score or check something: it is fast,\\ncheap and its answers are structured. Its result is { output: { : answer },\\nmodel, usage }, so a later step reads e.g. results..output.intent.choice. To route on\\nthe answers, follow it with a branchone whose branch exprs read\\nresults..output..choice. Usable as an AI agent tool, where the calling agent\\nsupplies the state.\\n","properties":{"input_transforms":{"type":"object","description":"Input parameters for the decision mapped to their values","properties":{"provider":{"$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":{"$ref":"#/components/schemas/FlowGroup"}}},"required":["modules"]},"Retry":{"type":"object","description":"Retry configuration for failed module executions","properties":{"constant":{"type":"object","description":"Retry with constant delay between attempts","properties":{"attempts":{"type":"integer","description":"Number of retry attempts"},"seconds":{"type":"integer","description":"Seconds to wait between retries"}}},"exponential":{"type":"object","description":"Retry with exponential backoff (delay doubles each time)","properties":{"attempts":{"type":"integer","description":"Number of retry attempts"},"multiplier":{"type":"integer","description":"Multiplier for exponential backoff"},"seconds":{"type":"integer","minimum":1,"description":"Initial delay in seconds"},"random_factor":{"type":"integer","minimum":0,"maximum":100,"description":"Random jitter percentage (0-100) to avoid thundering herd"}}},"retry_if":{"$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"]}}`; export const CLI_COMMANDS = `# Windmill CLI Commands diff --git a/system_prompts/auto-generated/skills/write-flow/SKILL.md b/system_prompts/auto-generated/skills/write-flow/SKILL.md index 66bf3d0fa4..3a5fd09bae 100644 --- a/system_prompts/auto-generated/skills/write-flow/SKILL.md +++ b/system_prompts/auto-generated/skills/write-flow/SKILL.md @@ -266,7 +266,7 @@ names, so neither is name-checked at all — leave those summaries as they are. ## AI Decision Modules -An `aidecision` module asks a decision model (TypeSafe's Jev or Cloudflare's Clef) typed questions about a `state` and +An `aidecision` module asks a decision model (TypeSafe's Jev, Cloudflare's Clef or OpenAI's Decisions API) typed questions about a `state` and answers each with calibrated probabilities instead of text. Prefer it over an `aiagent` when the step is a judgment (classify, route, score or a yes/no check) that needs no tools and no free text: it is faster, cheaper, and its answers have a fixed shape. @@ -304,8 +304,9 @@ is faster, cheaper, and its answers have a fixed shape. } ``` -- `provider.kind` is `typesafe` (`model` `jev-latest` unless a version is pinned) or `cloudflare` - (`model` `clef`, or `clef-flash` for faster answers); the resource is of that same type +- `provider.kind` is `typesafe` (`model` `jev-latest` unless a version is pinned), `cloudflare` + (`model` `clef`, or `clef-flash` for faster answers) or `openai` (`model` `gpt-6-luna`, never a + chat model); the resource is of that same type - `state` is the content to evaluate: usually a text, such as the message to classify. To combine several values, pass an object with descriptive keys holding only what the questions need (`({ message: flow_input.message, plan: results.get_account.plan })`); an array of strings also works @@ -319,6 +320,12 @@ is faster, cheaper, and its answers have a fixed shape. - The result is `{ output, model, usage }` with `output` keyed by question name, so a later step reads `results.triage.output.intent.choice`, `results.triage.output.urgency.score` or `results.triage.output.angry.noul > 0.7` +- On `openai` the same `questions` are translated for its Decisions API and the answers read the + same way (`choice`, `score`, `noul`), except that `probabilities` is a list of + `{ value, probability }` (plus `label` on a score) and a score has no `legend`. A question OpenAI + refuses to answer fails the step. A `state` that is + an array of user messages (`[{ role: "user", content: [{ type: "input_text", text }, { type: "input_image", image_url: "data:image/png;base64,..." }] }]`) + is sent as is, which is how an image is evaluated; any other object or array is sent as JSON text ### Branching on the Answers @@ -674,4 +681,4 @@ Reference a specific resource using `$res:` prefix: ## OpenFlow Schema -{"OpenFlow":{"type":"object","description":"Top-level flow definition containing metadata, configuration, and the flow structure","properties":{"summary":{"type":"string","description":"Short description of what this flow does"},"description":{"type":"string","description":"Detailed documentation for this flow"},"value":{"$ref":"#/components/schemas/FlowValue"},"schema":{"type":"object","description":"JSON Schema for flow inputs. Use this to define input parameters, their types, defaults, and validation. For resource inputs, set type to 'object' and format to 'resource-' (e.g., 'resource-stripe')"},"on_behalf_of_email":{"type":"string","description":"Address of the account the flow runs on behalf of. Derived from on_behalf_of on read; accepted on write, where it is resolved to the account it names."},"on_behalf_of":{"type":"string","description":"The flow runs with the permissions of this identity: u/{username}, g/{group}, or a bare email when the username is itself email-shaped. The only stored half of the identity; on_behalf_of_email is derived from it. Omit it when writing and it is resolved from that address instead."}},"required":["summary","value"]},"FlowValue":{"type":"object","description":"The flow structure containing modules and optional preprocessor/failure handlers","properties":{"modules":{"type":"array","description":"Array of steps that execute in sequence. Each step can be a script, subflow, loop, or branch","items":{"$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 (delay doubles each time)","properties":{"attempts":{"type":"integer","description":"Number of retry attempts"},"multiplier":{"type":"integer","description":"Multiplier for exponential backoff"},"seconds":{"type":"integer","minimum":1,"description":"Initial delay in seconds"},"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":{"$ref":"#/components/schemas/InputTransform"}}},"parallel":{"type":"boolean","description":"If true, the agent can execute multiple tool calls in parallel"}},"required":["type","input_transforms"]},"AiDecision":{"type":"object","description":"AI decision step: one call to a decision model (TypeSafe's Jev, or Cloudflare's\nJev-compatible Clef) that answers typed questions about a state with calibrated\nprobabilities, instead of generating text.\nPrefer it over an AI agent to classify, route, score or check something: it is fast,\ncheap and its answers are structured. Its result is { output: { : answer },\nmodel, usage }, so a later step reads e.g. results..output.intent.choice. To route on\nthe answers, follow it with a branchone whose branch exprs read\nresults..output..choice. Usable as an AI agent tool, where the calling agent\nsupplies the state.\n","properties":{"input_transforms":{"type":"object","description":"Input parameters for the decision mapped to their values","properties":{"provider":{"$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":{"$ref":"#/components/schemas/FlowGroup"}}},"required":["modules"]},"Retry":{"type":"object","description":"Retry configuration for failed module executions","properties":{"constant":{"type":"object","description":"Retry with constant delay between attempts","properties":{"attempts":{"type":"integer","description":"Number of retry attempts"},"seconds":{"type":"integer","description":"Seconds to wait between retries"}}},"exponential":{"type":"object","description":"Retry with exponential backoff (delay doubles each time)","properties":{"attempts":{"type":"integer","description":"Number of retry attempts"},"multiplier":{"type":"integer","description":"Multiplier for exponential backoff"},"seconds":{"type":"integer","minimum":1,"description":"Initial delay in seconds"},"random_factor":{"type":"integer","minimum":0,"maximum":100,"description":"Random jitter percentage (0-100) to avoid thundering herd"}}},"retry_if":{"$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"]}} diff --git a/system_prompts/base/flow-base.md b/system_prompts/base/flow-base.md index c615a628f3..83d96b9291 100644 --- a/system_prompts/base/flow-base.md +++ b/system_prompts/base/flow-base.md @@ -184,7 +184,7 @@ names, so neither is name-checked at all — leave those summaries as they are. ## AI Decision Modules -An `aidecision` module asks a decision model (TypeSafe's Jev or Cloudflare's Clef) typed questions about a `state` and +An `aidecision` module asks a decision model (TypeSafe's Jev, Cloudflare's Clef or OpenAI's Decisions API) typed questions about a `state` and answers each with calibrated probabilities instead of text. Prefer it over an `aiagent` when the step is a judgment (classify, route, score or a yes/no check) that needs no tools and no free text: it is faster, cheaper, and its answers have a fixed shape. @@ -222,8 +222,9 @@ is faster, cheaper, and its answers have a fixed shape. } ``` -- `provider.kind` is `typesafe` (`model` `jev-latest` unless a version is pinned) or `cloudflare` - (`model` `clef`, or `clef-flash` for faster answers); the resource is of that same type +- `provider.kind` is `typesafe` (`model` `jev-latest` unless a version is pinned), `cloudflare` + (`model` `clef`, or `clef-flash` for faster answers) or `openai` (`model` `gpt-6-luna`, never a + chat model); the resource is of that same type - `state` is the content to evaluate: usually a text, such as the message to classify. To combine several values, pass an object with descriptive keys holding only what the questions need (`({ message: flow_input.message, plan: results.get_account.plan })`); an array of strings also works @@ -237,6 +238,12 @@ is faster, cheaper, and its answers have a fixed shape. - The result is `{ output, model, usage }` with `output` keyed by question name, so a later step reads `results.triage.output.intent.choice`, `results.triage.output.urgency.score` or `results.triage.output.angry.noul > 0.7` +- On `openai` the same `questions` are translated for its Decisions API and the answers read the + same way (`choice`, `score`, `noul`), except that `probabilities` is a list of + `{ value, probability }` (plus `label` on a score) and a score has no `legend`. A question OpenAI + refuses to answer fails the step. A `state` that is + an array of user messages (`[{ role: "user", content: [{ type: "input_text", text }, { type: "input_image", image_url: "data:image/png;base64,..." }] }]`) + is sent as is, which is how an image is evaluated; any other object or array is sent as JSON text ### Branching on the Answers From fc6c84c6974bba1850e90a088fad5460c8c93ba3 Mon Sep 17 00:00:00 2001 From: hugocasa Date: Wed, 7 Oct 2026 15:52:32 +0200 Subject: [PATCH 04/34] fix: avoid URLSearchParams.keys() so the frontend check passes (#11599) Co-authored-by: Claude Opus 5.5 --- frontend/src/routes/(root)/(logged)/apps_raw/add/+page.ts | 5 +++-- 1 file changed, 3 insertions(+), 2 deletions(-) diff --git a/frontend/src/routes/(root)/(logged)/apps_raw/add/+page.ts b/frontend/src/routes/(root)/(logged)/apps_raw/add/+page.ts index 4ebbb6a846..8bd1ba1ba3 100644 --- a/frontend/src/routes/(root)/(logged)/apps_raw/add/+page.ts +++ b/frontend/src/routes/(root)/(logged)/apps_raw/add/+page.ts @@ -18,8 +18,9 @@ const openInEditor = makeDraftAddLoad('apps_raw/edit') * the user has sessions and AI to build with. Anything that arrives with content of its * own (an import, a seeded path) is an editor hand-off and stays one. */ async function newAppSessionHref(url: URL): Promise { - const params = [...url.searchParams.keys()].filter((k) => k !== 'workspace') - if (params.length > 0 || get(importStore) || sessionStorage.getItem('rawAppImport')) { + let hasOwnParams = false + url.searchParams.forEach((_, k) => (hasOwnParams ||= k !== 'workspace')) + if (hasOwnParams || get(importStore) || sessionStorage.getItem('rawAppImport')) { return undefined } const user = get(userStore) From 0792332859a88b1359ea1be64250d38dd071a0a9 Mon Sep 17 00:00:00 2001 From: Ruben Fiszel Date: Wed, 7 Oct 2026 16:27:20 +0200 Subject: [PATCH 05/34] feat: audit instance settings writes, stable audit OTel target (#11593) * feat: audit instance settings writes and bulk job cancels Co-Authored-By: Claude Opus 5.5 (1M context) * fix: audit each setting of a bulk save as it is written Co-Authored-By: Claude Opus 5.5 (1M context) * chore: update ee-repo-ref to acb254ac509aff244849c09e50a8d39aae185138 This commit updates the EE repository reference after PR #852 was merged in windmill-ee-private. Previous ee-repo-ref: 3dfc563bc95881183fb6c49d39984023b9b83075 New ee-repo-ref: acb254ac509aff244849c09e50a8d39aae185138 Automated by sync-ee-ref workflow. --------- Co-authored-by: Claude Opus 5.5 (1M context) Co-authored-by: windmill-internal-app[bot] --- backend/Cargo.lock | 2 + backend/ee-repo-ref.txt | 2 +- backend/windmill-api-jobs/Cargo.toml | 1 + backend/windmill-api-jobs/src/execution.rs | 36 ++- backend/windmill-api-schedule/src/lib.rs | 5 +- backend/windmill-api-settings/src/lib.rs | 242 +++++++++++++++++- .../windmill-api-workspaces/src/workspaces.rs | 6 +- .../src/workspaces_extra.rs | 2 +- backend/windmill-api/src/jobs.rs | 2 +- backend/windmill-audit/Cargo.toml | 5 +- backend/windmill-audit/src/audit_oss.rs | 15 ++ backend/windmill-common/src/tracing_init.rs | 5 + .../windmill-trigger/src/global_handler.rs | 2 +- 13 files changed, 303 insertions(+), 22 deletions(-) diff --git a/backend/Cargo.lock b/backend/Cargo.lock index 5e0f480e08..61e705a11c 100644 --- a/backend/Cargo.lock +++ b/backend/Cargo.lock @@ -15372,6 +15372,7 @@ dependencies = [ "uuid", "windmill-api-auth", "windmill-api-sse", + "windmill-audit", "windmill-common", "windmill-queue", ] @@ -15617,6 +15618,7 @@ dependencies = [ "sql-builder", "sqlx", "tracing", + "tracing-subscriber", "windmill-common", ] diff --git a/backend/ee-repo-ref.txt b/backend/ee-repo-ref.txt index b18c7bc91f..5f22bddd84 100644 --- a/backend/ee-repo-ref.txt +++ b/backend/ee-repo-ref.txt @@ -1 +1 @@ -9cc330f1a8e80bc075a6ad9839966d3b344f8ddd \ No newline at end of file +acb254ac509aff244849c09e50a8d39aae185138 diff --git a/backend/windmill-api-jobs/Cargo.toml b/backend/windmill-api-jobs/Cargo.toml index d3e10205ac..dad6469947 100644 --- a/backend/windmill-api-jobs/Cargo.toml +++ b/backend/windmill-api-jobs/Cargo.toml @@ -15,6 +15,7 @@ enterprise = ["windmill-common/enterprise"] [dependencies] windmill-api-auth.workspace = true windmill-api-sse.workspace = true +windmill-audit.workspace = true windmill-common = { workspace = true, default-features = false } windmill-queue.workspace = true axum.workspace = true diff --git a/backend/windmill-api-jobs/src/execution.rs b/backend/windmill-api-jobs/src/execution.rs index c35b9e41b0..5e08949138 100644 --- a/backend/windmill-api-jobs/src/execution.rs +++ b/backend/windmill-api-jobs/src/execution.rs @@ -23,6 +23,10 @@ use std::sync::Arc; use tokio::sync::RwLock; use uuid::Uuid; use windmill_api_auth::{check_scopes, get_scope_tags, ApiAuthed}; +use windmill_audit::{ + audit_oss::{audit_log_many, AuditAuthorable}, + ActionKind, +}; use windmill_common::{ db::{UserDB, UserDbWithAuthed}, error::{self, Error}, @@ -196,11 +200,15 @@ pub async fn check_license_key_valid() -> error::Result<()> { pub async fn cancel_jobs( jobs: Vec, db: &DB, - username: &str, + author: &(impl AuditAuthorable + Sync), w_id: &str, force_cancel: bool, ) -> error::JsonResult> { + let username = author.username(); let mut uuids = vec![]; + // A job that completed before its turn is reported back like the others but was not + // cancelled, so it gets no audit entry. + let mut audited = vec![]; tracing::info!("Cancelling jobs: {:?}", jobs); let mut tx = db.begin().await?; let trivial_jobs = sqlx::query!("INSERT INTO v2_job_completed AS cj @@ -246,7 +254,7 @@ pub async fn cancel_jobs( } match tokio::time::timeout(tokio::time::Duration::from_secs(5), async move { let tx = db.begin().await?; - let (tx, _) = cancel_job( + let (tx, cancelled) = cancel_job( username, None, job_id.clone(), @@ -258,13 +266,14 @@ pub async fn cancel_jobs( ) .await?; tx.commit().await?; - Ok::<_, anyhow::Error>(()) + Ok::<_, anyhow::Error>(cancelled) }) .await { Ok(result) => match result { - Ok(_) => { + Ok(cancelled) => { uuids.push(job_id); + audited.extend(cancelled); } Err(e) => { tracing::error!("Failed to cancel job {:?}: {:?}", job_id, e); @@ -279,8 +288,27 @@ pub async fn cancel_jobs( } } + audited.extend(trivial_jobs.iter().copied()); uuids.extend(trivial_jobs); + // The cancels are committed by now: failing here would report them as not done. + if let Err(e) = audit_log_many( + db, + author, + if force_cancel { + "jobs.force_cancel" + } else { + "jobs.cancel" + }, + ActionKind::Delete, + w_id, + &audited.iter().map(|id| id.to_string()).collect::>(), + ) + .await + { + tracing::error!("Failed to write audit entries for cancelled jobs in {w_id}: {e:#}"); + } + Ok(Json(uuids)) } diff --git a/backend/windmill-api-schedule/src/lib.rs b/backend/windmill-api-schedule/src/lib.rs index 7a523c89fa..855f687431 100644 --- a/backend/windmill-api-schedule/src/lib.rs +++ b/backend/windmill-api-schedule/src/lib.rs @@ -1487,11 +1487,12 @@ async fn set_default_error_handler( } }; - if let Some(value_content) = value { - windmill_api_settings::set_global_setting_internal(&db, key, value_content).await?; + if let Some(value_content) = value.clone() { + windmill_api_settings::set_global_setting_internal(&db, key.clone(), value_content).await?; } else { windmill_api_settings::delete_global_setting(&db, key.as_str()).await?; } + windmill_api_settings::audit_setting_write(&db, &authed, &key, value.as_ref()).await?; if payload.override_existing { // The rewrite and its history rows go in one transaction: on separate diff --git a/backend/windmill-api-settings/src/lib.rs b/backend/windmill-api-settings/src/lib.rs index 7e2ec536c0..c79b596617 100644 --- a/backend/windmill-api-settings/src/lib.rs +++ b/backend/windmill-api-settings/src/lib.rs @@ -29,6 +29,7 @@ mod log_cleanup; mod storage_usage; use windmill_api_auth::{require_devops_role, require_super_admin, ApiAuthed}; +use windmill_audit::{audit_oss::audit_log, ActionKind}; use windmill_common::utils::HTTP_CLIENT_PERMISSIVE as HTTP_CLIENT; use windmill_common::DB; @@ -829,7 +830,71 @@ pub async fn set_global_setting( Json(value): Json, ) -> error::Result<()> { require_super_admin(&db, &authed).await?; - set_global_setting_internal(&db, key, value.value.unwrap_or(serde_json::Value::Null)).await + let value = value.value.unwrap_or(serde_json::Value::Null); + set_global_setting_internal(&db, key.clone(), value.clone()).await?; + audit_setting_write(&db, &authed, &key, Some(&value)).await +} + +/// A setting is recorded by name, with its value only when that is a boolean or a number. +/// Any other shape can carry a credential (a registry URL, a webhook, a header map), and no +/// list of secret-bearing settings stays complete as settings are added. +/// +/// AUTHORIZATION: records a write, checks nothing. The caller must have established that +/// `authed` may change instance settings before performing the write this records. +pub async fn audit_setting_write( + db: &DB, + authed: &ApiAuthed, + key: &str, + value: Option<&serde_json::Value>, +) -> error::Result<()> { + let deleted = match value { + None | Some(serde_json::Value::Null) => true, + Some(serde_json::Value::String(s)) => s.trim().is_empty(), + Some(_) => false, + }; + let recorded = match value { + Some(v @ (serde_json::Value::Bool(_) | serde_json::Value::Number(_))) => { + Some(v.to_string()) + } + _ => None, + }; + audit_log( + db, + authed, + if deleted { + "global_settings.delete" + } else { + "global_settings.update" + }, + if deleted { + ActionKind::Delete + } else { + ActionKind::Update + }, + "global", + Some(key), + recorded.as_deref().map(|v| [("value", v)].into()), + ) + .await +} + +async fn audit_instance_action( + db: &DB, + authed: &ApiAuthed, + operation: &str, + action_kind: ActionKind, + parameters: Option>, +) -> error::Result<()> { + audit_log( + db, + authed, + operation, + action_kind, + "global", + Some(&authed.email), + parameters, + ) + .await } pub async fn set_global_setting_internal( @@ -1305,15 +1370,61 @@ async fn set_instance_config( run_setting_pre_write_hook(&db, key, value).await?; } } + // The external-instance write removes its own key from the diff. + let external = settings_diff + .upserts + .get(EXTERNAL_INSTANCE_PG_SETTING) + .cloned() + .map(Some) + .or_else(|| { + settings_diff + .deletes + .iter() + .any(|k| k == EXTERNAL_INSTANCE_PG_SETTING) + .then_some(None) + }); windmill_common::external_instance_pg::write_external_instance_pg_from_diff( &db, &mut settings_diff, ) .await?; + if let Some(value) = external { + audit_setting_write(&db, &authed, EXTERNAL_INSTANCE_PG_SETTING, value.as_ref()).await?; + } - instance_config::apply_settings_diff(&db, &settings_diff) - .await - .map_err(|e| error::Error::internal_err(e.to_string()))?; + // Applied and audited one setting at a time: the writes are not transactional, so a + // batch that fails midway must not leave the settings it did write unrecorded. + let instance_config::SettingsDiff { upserts, deletes, mut previous_values, unchanged_count } = + settings_diff; + let steps = upserts + .into_iter() + .map(|(k, v)| (k, Some(v))) + .chain(deletes.into_iter().map(|k| (k, None))) + .map(Some) + .chain(std::iter::once(None)); + for step in steps { + let mut diff = instance_config::SettingsDiff::default(); + match &step { + Some((key, value)) => { + if let Some(previous) = previous_values.remove(key) { + diff.previous_values.insert(key.clone(), previous); + } + match value { + Some(value) => { + diff.upserts.insert(key.clone(), value.clone()); + } + None => diff.deletes.push(key.clone()), + } + } + None => diff.unchanged_count = unchanged_count, + } + instance_config::apply_settings_diff(&db, &diff) + .await + .map_err(|e| error::Error::internal_err(e.to_string()))?; + if let Some((key, value)) = &step { + audit_setting_write(&db, &authed, key, value.as_ref()).await?; + } + } if ai_config_changed { bump_instance_ai_config_revision(); @@ -1343,9 +1454,37 @@ async fn set_instance_config( .collect(); let configs_diff = instance_config::diff_worker_configs(¤t_wc, &desired_wc, ApplyMode::Merge); - instance_config::apply_configs_diff(&db, &configs_diff) - .await - .map_err(|e| error::Error::internal_err(e.to_string()))?; + let steps = configs_diff + .upserts + .into_iter() + .map(|(g, c)| (g, Some(c))) + .chain(configs_diff.deletes.into_iter().map(|g| (g, None))); + for (group, config) in steps { + let mut diff = instance_config::ConfigsDiff::default(); + let (operation, action_kind) = match config { + Some(config) => { + diff.upserts.insert(group.clone(), config); + ("worker_config.update", ActionKind::Update) + } + None => { + diff.deletes.push(group.clone()); + ("worker_config.delete", ActionKind::Delete) + } + }; + instance_config::apply_configs_diff(&db, &diff) + .await + .map_err(|e| error::Error::internal_err(e.to_string()))?; + audit_log( + &db, + &authed, + operation, + action_kind, + "global", + Some(&format!("worker__{group}")), + None, + ) + .await?; + } } Ok(()) @@ -1583,6 +1722,14 @@ pub async fn renew_license_key( } ))); } else { + audit_instance_action( + &db, + &authed, + "settings.renew_license_key", + ActionKind::Update, + None, + ) + .await?; return Ok("Renewed license key".to_string()); } } @@ -1812,6 +1959,14 @@ async fn refresh_custom_instance_user_pwd( require_super_admin(&db, &authed).await?; windmill_common::utils::refresh_custom_instance_user_pwd(&db).await?; windmill_common::utils::refresh_custom_instance_replication_user_pwd(&db).await?; + audit_instance_action( + &db, + &authed, + "settings.refresh_custom_instance_user_pwd", + ActionKind::Update, + None, + ) + .await?; Ok(Json(())) } @@ -1970,7 +2125,8 @@ async fn setup_custom_instance_pg_database( windmill_common::datatable_roles::lock_instance_databases_governance(&mut tx, [dbname.trim()]) .await?; let mut logs = CustomInstanceDbLogs::default(); - let result = setup_custom_instance_pg_database_inner(authed, &db, &dbname, &mut logs).await; + let result = + setup_custom_instance_pg_database_inner(authed.clone(), &db, &dbname, &mut logs).await; let success = result.is_ok(); let error = result.err().map(|e| e.to_string()); let status = CustomInstanceDb { @@ -1998,6 +2154,20 @@ async fn setup_custom_instance_pg_database( .fetch_one(&mut *tx) .await?; tx.commit().await?; + audit_instance_action( + &db, + &authed, + "settings.setup_custom_instance_pg_database", + ActionKind::Create, + Some( + [ + ("dbname", dbname.as_str()), + ("success", if success { "true" } else { "false" }), + ] + .into(), + ), + ) + .await?; let status: CustomInstanceDb = serde_json::from_value(saved).map_err(to_anyhow)?; Ok(Json(status)) @@ -2176,6 +2346,14 @@ async fn drop_custom_instance_pg_database( require_super_admin(&db, &authed).await?; windmill_common::drop_custom_instance_database(&db, &dbname).await?; + audit_instance_action( + &db, + &authed, + "settings.drop_custom_instance_pg_database", + ActionKind::Delete, + Some([("dbname", dbname.as_str())].into()), + ) + .await?; Ok(format!("Database '{}' dropped successfully", dbname)) } @@ -2220,6 +2398,14 @@ pub async fn migrate_secrets_to_vault( let report = windmill_common::secret_backend::migrate_secrets_to_vault(&db, &settings).await?; + audit_instance_action( + &db, + &authed, + "settings.migrate_secrets_to_vault", + ActionKind::Update, + None, + ) + .await?; Ok(Json(report)) } @@ -2241,6 +2427,14 @@ pub async fn migrate_secrets_to_database( let report = windmill_common::secret_backend::migrate_secrets_to_database(&db, &settings).await?; + audit_instance_action( + &db, + &authed, + "settings.migrate_secrets_to_database", + ActionKind::Update, + None, + ) + .await?; Ok(Json(report)) } @@ -2274,6 +2468,14 @@ pub async fn migrate_secrets_to_azure_kv( let report = windmill_common::secret_backend::migrate_secrets_to_azure_kv(&db, &settings).await?; + audit_instance_action( + &db, + &authed, + "settings.migrate_secrets_to_azure_kv", + ActionKind::Update, + None, + ) + .await?; Ok(Json(report)) } @@ -2291,6 +2493,14 @@ pub async fn migrate_secrets_from_azure_kv( let report = windmill_common::secret_backend::migrate_secrets_from_azure_kv(&db, &settings).await?; + audit_instance_action( + &db, + &authed, + "settings.migrate_secrets_from_azure_kv", + ActionKind::Update, + None, + ) + .await?; Ok(Json(report)) } @@ -2315,6 +2525,14 @@ pub async fn migrate_secrets_to_aws_sm( ) -> JsonResult { require_super_admin(&db, &authed).await?; let report = windmill_common::secret_backend::migrate_secrets_to_aws_sm(&db, &settings).await?; + audit_instance_action( + &db, + &authed, + "settings.migrate_secrets_to_aws_sm", + ActionKind::Update, + None, + ) + .await?; Ok(Json(report)) } @@ -2328,6 +2546,14 @@ pub async fn migrate_secrets_from_aws_sm( require_super_admin(&db, &authed).await?; let report = windmill_common::secret_backend::migrate_secrets_from_aws_sm(&db, &settings).await?; + audit_instance_action( + &db, + &authed, + "settings.migrate_secrets_from_aws_sm", + ActionKind::Update, + None, + ) + .await?; Ok(Json(report)) } diff --git a/backend/windmill-api-workspaces/src/workspaces.rs b/backend/windmill-api-workspaces/src/workspaces.rs index c94560314c..efc108453d 100644 --- a/backend/windmill-api-workspaces/src/workspaces.rs +++ b/backend/windmill-api-workspaces/src/workspaces.rs @@ -10513,7 +10513,7 @@ async fn edit_workspace( pub(crate) async fn archive_workspace_impl( db: &DB, w_id: &str, - username: &str, + authed: &ApiAuthed, // When archiving a dev workspace, its parent prod. The pairing teardown (clear is_dev + drop the // prod's lock) is folded into the same transaction as `deleted = true` so it's atomic with the // archive — a later failure can't strand a half-archived dev that's still flagged/locked. @@ -10627,7 +10627,7 @@ pub(crate) async fn archive_workspace_impl( let axum::Json(canceled_jobs) = windmill_api_jobs::cancel_jobs( jobs_to_cancel, db, - username, + authed, w_id, false, // force_cancel ) @@ -10687,7 +10687,7 @@ async fn archive_workspace( // dev workspace, which only applies to a workspace that is itself a dev (`dev_lock_parent`): a // root archived out from under its dev is the pre-existing shape and not this pairing's to police. let (schedules_count, canceled_count, deleted_tokens_count) = - archive_workspace_impl(&db, &w_id, &authed.username, dev_lock_parent.as_deref()).await?; + archive_workspace_impl(&db, &w_id, &authed, dev_lock_parent.as_deref()).await?; // Audit log let mut tx = db.begin().await?; diff --git a/backend/windmill-api-workspaces/src/workspaces_extra.rs b/backend/windmill-api-workspaces/src/workspaces_extra.rs index a0ff1f2370..50833bfe06 100644 --- a/backend/windmill-api-workspaces/src/workspaces_extra.rs +++ b/backend/windmill-api-workspaces/src/workspaces_extra.rs @@ -944,7 +944,7 @@ pub(crate) async fn change_workspace_id( // Note: schedules were already moved to new workspace, so this will find 0 schedules info!("Archiving old workspace"); let (_schedules_count, canceled_count, _deleted_tokens_count) = - archive_workspace_impl(&db, &old_id, &authed.username, None).await?; + archive_workspace_impl(&db, &old_id, &authed, None).await?; // The old id stays live between the commit above and the archive, and a fork copy created for // it in that window registers under it. Creation checks the workspace is live under the fork diff --git a/backend/windmill-api/src/jobs.rs b/backend/windmill-api/src/jobs.rs index 1f92c6d425..b08b083695 100644 --- a/backend/windmill-api/src/jobs.rs +++ b/backend/windmill-api/src/jobs.rs @@ -4580,7 +4580,7 @@ async fn cancel_selection( let Json(mut w_cancelled) = cancel_jobs( ids, &db, - authed.username.as_str(), + &authed, workspace_id.as_str(), force_cancel, ) diff --git a/backend/windmill-audit/Cargo.toml b/backend/windmill-audit/Cargo.toml index 6e4fc3fd12..8c26615664 100644 --- a/backend/windmill-audit/Cargo.toml +++ b/backend/windmill-audit/Cargo.toml @@ -20,4 +20,7 @@ chrono.workspace = true serde_json.workspace = true tracing.workspace = true windmill-common = { workspace = true, default-features = false } -lazy_static.workspace = true \ No newline at end of file +lazy_static.workspace = true + +[dev-dependencies] +tracing-subscriber.workspace = true \ No newline at end of file diff --git a/backend/windmill-audit/src/audit_oss.rs b/backend/windmill-audit/src/audit_oss.rs index da36ada468..02b075af9d 100644 --- a/backend/windmill-audit/src/audit_oss.rs +++ b/backend/windmill-audit/src/audit_oss.rs @@ -88,6 +88,21 @@ pub async fn audit_log<'c, E: sqlx::Executor<'c, Database = Postgres>>( Ok(()) } +/// AUTHORIZATION: records entries, checks nothing. The caller must have authorized `author` +/// for the operation on every resource in `w_id` before calling. +#[cfg(not(feature = "private"))] +pub async fn audit_log_many<'c, E: sqlx::Executor<'c, Database = Postgres>>( + _db: E, + _author: &impl AuditAuthorable, + _operation: &str, + _action_kind: ActionKind, + _w_id: &str, + _resources: &[String], +) -> Result<()> { + // Implementation is not open source as Audit logs is a Windmill Enterprise Edition feature + Ok(()) +} + #[cfg(not(feature = "private"))] pub async fn list_audit( _tx: Transaction<'_, Postgres>, diff --git a/backend/windmill-common/src/tracing_init.rs b/backend/windmill-common/src/tracing_init.rs index b456e370fc..01e75ac489 100644 --- a/backend/windmill-common/src/tracing_init.rs +++ b/backend/windmill-common/src/tracing_init.rs @@ -44,6 +44,11 @@ lazy_static::lazy_static! { /// Use `tracing::info!(target: windmill_common::tracing_init::VERBOSE_TARGET, ...)` for logs that should be suppressed in quiet mode. pub const VERBOSE_TARGET: &str = "windmill_verbose"; +/// Target of audit events, so a log pipeline can route them without matching on content. +/// It keeps the `windmill` prefix because that is what a `RUST_LOG` of `info` or `debug` +/// is rewritten to filter on. +pub const AUDIT_TARGET: &str = "windmill:audit"; + /// Prefix used by user scripts to emit a log line as an OTEL tracing event /// when `OTEL_JOB_LOGS=true`. Stripped before forwarding to the tracing layer. pub const OTEL_PREFIX: &str = "OTEL: "; diff --git a/backend/windmill-trigger/src/global_handler.rs b/backend/windmill-trigger/src/global_handler.rs index ec74b4f139..64ad693a10 100644 --- a/backend/windmill-trigger/src/global_handler.rs +++ b/backend/windmill-trigger/src/global_handler.rs @@ -342,7 +342,7 @@ pub async fn cancel_suspended_trigger_jobs( let cancelled_jobs = cancel_jobs( jobs_to_cancel, &db, - authed.username.as_str(), + &authed, w_id.as_str(), true, ) From e50e1f5b311b2bdbbe90526a82486263c0749bd7 Mon Sep 17 00:00:00 2001 From: hugocasa Date: Wed, 7 Oct 2026 16:27:40 +0200 Subject: [PATCH 06/34] run the cli ai evals on codex and deepseek (#11591) * feat: run the cli ai evals on codex and deepseek Co-Authored-By: Claude Opus 5.5 * ci: pick cli eval models from the harness and install codex Co-Authored-By: Claude Opus 5.5 * fix: stop counting wmill in a file name as a cli eval mutation Co-Authored-By: Claude Opus 5.5 * fix: harden the codex and deepseek cli eval runtimes Co-Authored-By: Claude Opus 5.5 * fix: keep codex tool order and keep other keys from deepseek Co-Authored-By: Claude Opus 5.5 --------- Co-authored-by: Claude Opus 5.5 --- .github/workflows/ai-evals-scheduled.yml | 25 ++- ai_evals/README.md | 16 +- ai_evals/adapters/cli/codex.test.ts | 71 +++++++ ai_evals/adapters/cli/codex.ts | 241 +++++++++++++++++++++++ ai_evals/adapters/cli/mutation.ts | 10 + ai_evals/adapters/cli/runtime.test.ts | 31 +++ ai_evals/adapters/cli/runtime.ts | 173 +++++++++------- ai_evals/core/cases.test.ts | 2 - ai_evals/core/models.test.ts | 14 +- ai_evals/core/models.ts | 52 ++++- ai_evals/modes/cli.ts | 41 +++- 11 files changed, 581 insertions(+), 95 deletions(-) create mode 100644 ai_evals/adapters/cli/codex.test.ts create mode 100644 ai_evals/adapters/cli/codex.ts create mode 100644 ai_evals/adapters/cli/mutation.ts diff --git a/.github/workflows/ai-evals-scheduled.yml b/.github/workflows/ai-evals-scheduled.yml index 1284154a91..4780eb02eb 100644 --- a/.github/workflows/ai-evals-scheduled.yml +++ b/.github/workflows/ai-evals-scheduled.yml @@ -15,7 +15,7 @@ on: description: "Space-separated modes (global, cli, flow, app, script)" default: "global cli" models: - description: "Space-separated model aliases (bun run cli -- models); cli runs only the Claude ones" + description: "Space-separated model aliases (bun run cli -- models); cli skips those it has no agent for" default: "sonnet-5.5 opus-5.5 gpt-6-sol gpt-6-astra deepseek-v4-pro" runs: description: "Runs per case" @@ -40,17 +40,28 @@ jobs: outputs: matrix: ${{ steps.matrix.outputs.matrix }} steps: + - uses: actions/checkout@v4 + with: + sparse-checkout: ai_evals/core + + - uses: oven-sh/setup-bun@v2 + with: + bun-version: 1.4.0 + - id: matrix env: MODES: ${{ inputs.modes || 'global cli' }} - # cli drives the Claude Agent SDK, so it only takes the Claude aliases - # (`cli` entries in ai_evals/core/models.ts). + # cli takes only the aliases with a `cli` entry in ai_evals/core/models.ts. run: | - echo "matrix=$(jq -cn --arg modes "$MODES" --arg models "$MODELS" ' + cli_models=$(bun -e ' + import { EVAL_MODELS } from "./ai_evals/core/models.ts"; + console.log(JSON.stringify(EVAL_MODELS.filter((m) => m.cli) + .flatMap((m) => [m.id, ...m.aliases]).map((a) => a.toLowerCase())));') + echo "matrix=$(jq -cn --arg modes "$MODES" --arg models "$MODELS" --argjson cli "$cli_models" ' def words: split(" ") | map(select(. != "")); [ $modes | words[] | select(IN("global", "flow", "app", "script", "cli")) as $mode | $models | words[] - | select($mode != "cli" or test("^(claude-)?(haiku|sonnet|opus)"; "i")) + | select($mode != "cli" or (ascii_downcase | IN($cli[]))) | {mode: $mode, model: .} ]')" >> "$GITHUB_OUTPUT" evals: @@ -120,6 +131,10 @@ jobs: working-directory: ./cli run: bun install && ./gen_wm_client.sh && ./windmill-utils-internal/gen_wm_client.sh + - name: Install Codex CLI + if: matrix.mode == 'cli' + run: npm install --global @openai/codex@0.159.3 + - name: Run ${{ matrix.mode }} evals on ${{ matrix.model }} working-directory: ./ai_evals env: diff --git a/ai_evals/README.md b/ai_evals/README.md index 88623c7f33..44870ba2a2 100644 --- a/ai_evals/README.md +++ b/ai_evals/README.md @@ -89,7 +89,21 @@ Notes: - the command also prints accepted alias spellings such as `gpt-4o`, `gpt-55`, `claude-opus-4.6`, and `claude-haiku-4.5` - frontend modes (`flow`, `script`, `app`, `global`) can use Anthropic, OpenAI, Gemini, and DeepSeek-backed aliases -- `cli` mode always uses the Anthropic agent SDK, so only Anthropic aliases are valid there +- `cli` mode runs a coding agent over the workspace, chosen by the alias's `cli` entry; aliases without one are rejected there: + + | Agent | Models | Label | Needs | + | --- | --- | --- | --- | + | Claude Code (`@anthropic-ai/claude-agent-sdk`) | Claude aliases | `anthropic:` | `ANTHROPIC_API_KEY` | + | Claude Code on DeepSeek's Anthropic-compatible endpoint | `deepseek-v4-pro` | `claude-code:` | `DEEPSEEK_API_KEY` | + | Codex (`codex exec --json`) | `gpt-6.1-sol`, `gpt-6-astra` | `codex:` | `codex` on `PATH` (CI pins 0.159.3), `OPENAI_API_KEY` | + + Codex runs with a throwaway `HOME`, so your own `~/.codex` config and skills stay out of the run. It has no + Skill tool: it finds `.agents/skills` on its own and loads a skill by reading its `SKILL.md`, so the trace + records any command that touches `.agents/skills//SKILL.md` as a `Skill` call to ``, just + before that command, or just after it when the command mutates something before reading the skill. Its shell commands are recorded as `Bash` and its patches as `Edit`, so the + `invokes skill … before first mutation` checks compare the same things for both agents. Codex has no + turn cap; a run stops at `maxTurns` rounds of tool calls (parallel calls count once) and fails, as a + Claude Code run does at its cap. - the judge model is separate and currently defaults to `claude-sonnet-5-5`; use `--skip-judge` for deterministic-only runs ## Case Format diff --git a/ai_evals/adapters/cli/codex.test.ts b/ai_evals/adapters/cli/codex.test.ts new file mode 100644 index 0000000000..fdeda1d26b --- /dev/null +++ b/ai_evals/adapters/cli/codex.test.ts @@ -0,0 +1,71 @@ +import { describe, expect, it } from "bun:test"; +import { chmod, mkdtemp, rm, writeFile } from "node:fs/promises"; +import { tmpdir } from "node:os"; +import { join } from "node:path"; +import { runCodex, toToolInvocations, unwrapShellCommand } from "./codex"; + +describe("unwrapShellCommand", () => { + it("strips the login-shell wrapper Codex reports", () => { + expect(unwrapShellCommand(`/usr/bin/zsh -lc 'cat .agents/skills/x/SKILL.md'`)).toBe( + "cat .agents/skills/x/SKILL.md" + ); + expect(unwrapShellCommand(`/bin/bash -lc "printf 'hi' > \\"a b\\""`)).toBe( + `printf 'hi' > "a b"` + ); + expect(unwrapShellCommand(`/bin/bash -lc 'echo '\\''x'\\'''`)).toBe(`echo 'x'`); + expect(unwrapShellCommand(`bash -lc 'wmill sync push'`)).toBe("wmill sync push"); + expect(unwrapShellCommand(`/bin/bash -lc 'rg -g '"'"'!x'"'"' f'`)).toBe(`rg -g '!x' f`); + }); +}); + +describe("toToolInvocations", () => { + it("records reading a SKILL.md as a Skill call before the command", () => { + const tools = toToolInvocations({ + type: "command_execution", + command: `/bin/bash -lc 'sed -n 1,200p .agents/skills/write-script-bun/SKILL.md && mkdir f'`, + }); + expect(tools.map((tool) => [tool.tool, tool.input])).toEqual([ + ["Skill", { skill: "write-script-bun" }], + ["Bash", { command: "sed -n 1,200p .agents/skills/write-script-bun/SKILL.md && mkdir f" }], + ]); + }); + + it("records a skill read after a mutation earlier in the same command", () => { + const tools = toToolInvocations({ + type: "command_execution", + command: `/bin/bash -lc 'printf main > f/a.ts && cat .agents/skills/write-script-bun/SKILL.md'`, + }); + expect(tools.map((tool) => tool.tool)).toEqual(["Bash", "Skill"]); + }); + + it("maps a patch to Edit so it counts as a mutation", () => { + expect( + toToolInvocations({ type: "file_change", changes: [{ path: "a.ts", kind: "add" }] })[0] + ).toMatchObject({ tool: "Edit", input: { changes: [{ path: "a.ts", kind: "add" }] } }); + }); +}); + +describe("runCodex", () => { + it("keeps parallel tool calls in the order they started", async () => { + const dir = await mkdtemp(join(tmpdir(), "fake-codex-")); + const events = [ + { type: "item.started", item: { id: "a", type: "command_execution", command: "mkdir f" } }, + { type: "item.started", item: { id: "b", type: "command_execution", command: "cat .agents/skills/s/SKILL.md" } }, + { type: "item.completed", item: { id: "b", type: "command_execution", command: "cat .agents/skills/s/SKILL.md" } }, + { type: "item.completed", item: { id: "a", type: "command_execution", command: "mkdir f" } }, + { type: "item.completed", item: { id: "c", type: "agent_message", text: "done" } }, + { type: "turn.completed", usage: { input_tokens: 10, output_tokens: 2 } }, + ]; + const lines = events.map((event) => `printf '%s\\n' '${JSON.stringify(event)}'`).join("\n"); + await writeFile(join(dir, "codex"), `#!/bin/sh\ncat > /dev/null\n${lines}\n`); + await chmod(join(dir, "codex"), 0o755); + try { + const result = await runCodex("p", dir, 12, "m", { PATH: `${dir}:${process.env.PATH}` }); + expect(result.toolsUsed.map((tool) => tool.tool)).toEqual(["Bash", "Skill", "Bash"]); + expect(result.output).toBe("done"); + expect(result.tokenUsage).toEqual({ prompt: 10, completion: 2, total: 12 }); + } finally { + await rm(dir, { recursive: true, force: true }); + } + }); +}); diff --git a/ai_evals/adapters/cli/codex.ts b/ai_evals/adapters/cli/codex.ts new file mode 100644 index 0000000000..b49c441556 --- /dev/null +++ b/ai_evals/adapters/cli/codex.ts @@ -0,0 +1,241 @@ +import { spawn } from "node:child_process"; +import { mkdtemp, rm } from "node:fs/promises"; +import { tmpdir } from "node:os"; +import { join } from "node:path"; +import { createInterface } from "node:readline"; +import type { BenchmarkTokenUsage, CliToolInvocation } from "../../core/types"; +import { isLikelyMutatingBashCommand } from "./mutation"; + +export interface AgentRunResult { + output: string; + toolsUsed: CliToolInvocation[]; + assistantMessageCount: number; + tokenUsage: BenchmarkTokenUsage | null; + finalContextTokens: number | null; +} + +interface CodexItem { + type?: string; + text?: string; + command?: string; + changes?: { path?: string; kind?: string }[]; + [key: string]: unknown; +} + +interface CodexEvent { + type?: string; + item?: CodexItem; + usage?: { input_tokens?: number; output_tokens?: number }; + message?: string; + error?: { message?: string }; +} + +const SKILL_FILE_PATTERN = /\.agents\/skills\/([^/\s'"`*?[]+)\/SKILL\.md/g; + +// Drives `codex exec` and maps its events onto the Claude Code tool vocabulary +// the validators read: shell commands become `Bash`, patches `Edit`, and +// reading `.agents/skills//SKILL.md` (how Codex loads a skill) becomes a +// `Skill` call recorded just before that command. +export async function runCodex( + prompt: string, + cwd: string, + maxTurns: number, + model: string, + env: Record +): Promise { + // A fresh HOME keeps the user's ~/.codex config and ~/.agents/skills out of the run. + const home = await mkdtemp(join(tmpdir(), "wmill-cli-benchmark-codex-home-")); + const result: AgentRunResult = { + output: "", + toolsUsed: [], + assistantMessageCount: 0, + tokenUsage: null, + finalContextTokens: null, + }; + const messages: string[] = []; + let failure: string | null = null; + let lastError: string | null = null; + let stderr = ""; + + try { + const child = spawn( + "codex", + [ + "exec", + "--json", + "--ephemeral", + "--skip-git-repo-check", + "--dangerously-bypass-approvals-and-sandbox", + "--model", + model, + "--cd", + cwd, + "-", + ], + { + cwd, + env: { + ...env, + HOME: home, + CODEX_HOME: home, + CODEX_API_KEY: env.OPENAI_API_KEY ?? "", + }, + stdio: ["pipe", "pipe", "pipe"], + } + ); + // Without this, a missing `codex` binary leaves the stdout loop waiting forever. + await new Promise((resolve, reject) => { + child.once("spawn", resolve); + child.once("error", reject); + }); + child.stdin.on("error", () => {}); + child.stdin.end(prompt); + child.stderr.on("data", (chunk) => { + stderr = (stderr + chunk).slice(-4000); + }); + const exited = new Promise((resolve, reject) => { + child.on("error", reject); + child.on("close", resolve); + }); + + // Codex has no turn cap. A turn starts when the agent issues tool calls with + // none in flight, so parallel calls count once, as they do for Claude Code. + // Claude Code's cap includes the final reply, so the maxTurns-th tool round is + // already over it. + // ponytail: parallel calls that finish before the next one starts count as + // separate turns; count model calls if Codex ever reports them. + let turns = 0; + let inFlight = 0; + let capped = false; + // Parallel calls complete out of order; the trace keeps the order they started in. + const slots = new Map(); + const ordered: CliToolInvocation[][] = []; + const slotFor = (item: CodexItem) => { + const id = typeof item.id === "string" ? item.id : undefined; + if (id !== undefined && slots.has(id)) { + return slots.get(id)!; + } + ordered.push([]); + if (id !== undefined) { + slots.set(id, ordered.length - 1); + } + return ordered.length - 1; + }; + + for await (const line of createInterface({ input: child.stdout })) { + const event = parseEvent(line); + if (!event) { + continue; + } + const item = event.item; + + if (event.type === "item.started" && item && isToolItem(item)) { + if (inFlight === 0) { + turns += 1; + } + inFlight += 1; + slotFor(item); + if (turns >= maxTurns && !capped) { + capped = true; + child.kill("SIGTERM"); + } + } else if (event.type === "item.completed" && item) { + if (item.type === "agent_message") { + result.assistantMessageCount += 1; + if (typeof item.text === "string") { + messages.push(item.text); + } + } else if (isToolItem(item)) { + inFlight = Math.max(0, inFlight - 1); + ordered[slotFor(item)] = toToolInvocations(item); + } + } else if (event.type === "turn.completed" && event.usage) { + const prompt = event.usage.input_tokens ?? 0; + const completion = event.usage.output_tokens ?? 0; + result.tokenUsage = { prompt, completion, total: prompt + completion }; + } else if (event.type === "turn.failed") { + failure = event.error?.message ?? JSON.stringify(event); + } else if (event.type === "error") { + // Also sent for retries Codex recovers from ("Reconnecting... 1/5"). + lastError = event.message ?? JSON.stringify(event); + } + } + + result.toolsUsed = ordered.flat(); + const code = await exited; + if (failure) { + throw new Error(`codex: ${failure}`); + } + // Fail the attempt, as Claude Code does at its cap. + if (capped) { + throw new Error(`codex: reached maximum number of turns (${maxTurns})`); + } + if (code !== 0) { + throw new Error(`codex exited with ${code}: ${lastError ?? stderr.trim()}`); + } + } finally { + await rm(home, { recursive: true, force: true }); + } + + result.output = messages.join("\n"); + return result; +} + +export function toToolInvocations(item: CodexItem): CliToolInvocation[] { + const timestamp = Date.now(); + + if (item.type === "command_execution" && typeof item.command === "string") { + const command = unwrapShellCommand(item.command); + // A skill read counts as preceding the command only when nothing before it in + // the command mutates; otherwise `printf x > f && cat SKILL.md` would pass a + // skill-before-first-mutation check. + const before: string[] = []; + const after: string[] = []; + for (const match of command.matchAll(SKILL_FILE_PATTERN)) { + const skill = match[1]!; + if (before.includes(skill) || after.includes(skill)) { + continue; + } + (isLikelyMutatingBashCommand(command.slice(0, match.index)) ? after : before).push(skill); + } + const skillCall = (skill: string) => ({ tool: "Skill", input: { skill }, timestamp }); + return [ + ...before.map(skillCall), + { tool: "Bash", input: { command }, timestamp }, + ...after.map(skillCall), + ]; + } + + if (item.type === "file_change") { + return [{ tool: "Edit", input: { changes: item.changes ?? [] }, timestamp }]; + } + + const { id: _id, type, status: _status, ...input } = item; + return [{ tool: String(type), input, timestamp }]; +} + +// Codex reports commands as run through the user's login shell, e.g. +// `/usr/bin/zsh -lc 'cat SKILL.md'`. +export function unwrapShellCommand(command: string): string { + const match = command.match(/^(?:\S*\/)?(?:ba|z)?sh -l?c (['"])([\s\S]*)\1$/); + if (!match) { + return command; + } + const body = match[2]!; + return match[1] === "'" + ? body.replaceAll(`'\\''`, "'").replaceAll(`'"'"'`, "'") + : body.replace(/\\(["\\$`])/g, "$1"); +} + +function isToolItem(item: CodexItem): boolean { + return !["agent_message", "reasoning", "todo_list", "error"].includes(item.type ?? ""); +} + +function parseEvent(line: string): CodexEvent | null { + try { + const value = JSON.parse(line); + return value && typeof value === "object" ? (value as CodexEvent) : null; + } catch { + return null; + } +} diff --git a/ai_evals/adapters/cli/mutation.ts b/ai_evals/adapters/cli/mutation.ts new file mode 100644 index 0000000000..05b29d68d7 --- /dev/null +++ b/ai_evals/adapters/cli/mutation.ts @@ -0,0 +1,10 @@ +export function isLikelyMutatingBashCommand(command: string): boolean { + return ( + /\b(?:mkdir|touch|rm|mv|cp|install|tee)\b/.test(command) || + /\b(?:cat|echo|printf)\b.*(?:>|>>|\|\s*tee\b)/.test(command) || + /\bsed\s+-i\b/.test(command) || + /\bperl\s+-pi\b/.test(command) || + // In command position only: `cat AGENTS.wmill.md` is a read. + /(?:^|[;&|(]|\b(?:then|do|xargs)\s)\s*wmill(?:\s|$)/m.test(command) + ); +} diff --git a/ai_evals/adapters/cli/runtime.test.ts b/ai_evals/adapters/cli/runtime.test.ts index 3ea53ca587..d3e537b659 100644 --- a/ai_evals/adapters/cli/runtime.test.ts +++ b/ai_evals/adapters/cli/runtime.test.ts @@ -2,7 +2,9 @@ import { describe, expect, it } from "bun:test"; import { anthropicUsageToBenchmarkTokenUsage, extractCliResultTokenUsage, + endpointEnv, extractProposedWmillCommands, + getFirstMutationToolIndex, parseWmillInvocationLog, } from "./runtime"; @@ -147,3 +149,32 @@ push ]); }); }); + +describe("getFirstMutationToolIndex", () => { + it("counts wmill only as a command, not in a file name", () => { + const bash = (command: string) => ({ tool: "Bash", input: { command }, timestamp: 0 }); + expect( + getFirstMutationToolIndex([ + bash("cat AGENTS.wmill.md .agents/skills/x/SKILL.md"), + bash("ls && wmill generate-metadata"), + ]) + ).toBe(1); + expect(getFirstMutationToolIndex([bash("cd f\nwmill sync push")])).toBe(0); + }); +}); + +describe("endpointEnv", () => { + it("passes the endpoint only its own key", () => { + const env = endpointEnv( + { baseUrl: "https://example.test", apiKeyEnv: "DEEPSEEK_API_KEY" }, + "m", + { PATH: "/bin", DEEPSEEK_API_KEY: "ds", OPENAI_API_KEY: "oa", ANTHROPIC_AUTH_TOKEN: "t" } + ); + expect(env).toEqual({ + PATH: "/bin", + ANTHROPIC_BASE_URL: "https://example.test", + ANTHROPIC_API_KEY: "ds", + ANTHROPIC_DEFAULT_HAIKU_MODEL: "m", + }); + }); +}); diff --git a/ai_evals/adapters/cli/runtime.ts b/ai_evals/adapters/cli/runtime.ts index b45df70011..e7368db366 100644 --- a/ai_evals/adapters/cli/runtime.ts +++ b/ai_evals/adapters/cli/runtime.ts @@ -2,7 +2,14 @@ import { query, type Options } from "@anthropic-ai/claude-agent-sdk"; import { chmod, mkdir, readFile, writeFile } from "node:fs/promises"; import { delimiter, join } from "path"; import { fileURLToPath } from "url"; -import { getCliEvalModel, resolveEvalModel, type CliEvalModelConfig } from "../../core/models"; +import { + getCliEvalModel, + resolveEvalModel, + type CliEvalModelConfig, +} from "../../core/models"; +import { runCodex, type AgentRunResult } from "./codex"; +import { isLikelyMutatingBashCommand } from "./mutation"; +export { formatCliRunModelLabel } from "../../core/models"; import type { BenchmarkTokenUsage, CliToolInvocation, @@ -141,16 +148,94 @@ export async function runPromptAndCapture( maxTurns: number = 3, modelConfig: CliEvalModelConfig = DEFAULT_CLI_EVAL_MODEL ): Promise { - const toolsUsed: ToolInvocation[] = []; - const skillsInvoked: string[] = []; - const bashCommands: string[] = []; - let output = ""; - let assistantMessageCount = 0; - let tokenUsage: BenchmarkTokenUsage | null = null; - let finalContextTokens: number | null = null; const startedAt = Date.now(); const stubBinDir = join(cwd, WMILL_STUB_DIR_NAME); const wmillLogPath = join(cwd, WMILL_LOG_FILE_NAME); + const env = { + ...getQueryEnv(), + PATH: process.env.PATH ? `${stubBinDir}${delimiter}${process.env.PATH}` : stubBinDir, + WMILL_BENCHMARK_LOG_PATH: wmillLogPath, + }; + + await installWmillStub(stubBinDir); + + const run = + modelConfig.runtime === "codex" + ? await runCodex(prompt, cwd, maxTurns, modelConfig.model, env) + : await runClaudeCode(prompt, cwd, maxTurns, modelConfig, env); + + const skillsInvoked: string[] = []; + const bashCommands: string[] = []; + for (const tool of run.toolsUsed) { + if (tool.tool === "Skill" && typeof tool.input.skill === "string") { + pushUnique(skillsInvoked, tool.input.skill); + } + if (tool.tool === "Bash") { + for (const command of extractBashCommands(tool.input)) { + pushUnique(bashCommands, command); + } + } + } + + const wmillInvocations = await readWmillInvocationLog(wmillLogPath); + + return { + output: run.output, + durationMs: Date.now() - startedAt, + tokenUsage: run.tokenUsage, + finalContextTokens: run.finalContextTokens, + trace: { + toolsUsed: run.toolsUsed, + skillsInvoked, + assistantMessageCount: run.assistantMessageCount, + bashCommands, + proposedCommands: extractProposedWmillCommands(run.output), + executedWmillCommands: wmillInvocations.map(formatExecutedWmillCommand), + wmillInvocations, + firstMutationToolIndex: getFirstMutationToolIndex(run.toolsUsed), + }, + }; +} + +// Only the endpoint's own key may reach it: a missing key would make Claude Code +// fall back to the user's Claude login, and the agent's Bash inherits this env, +// so any other credential could end up in a tool result sent to the endpoint. +export function endpointEnv( + endpoint: NonNullable, + model: string, + env: Record +): Record { + const key = env[endpoint.apiKeyEnv]; + if (!key) { + throw new Error(`${endpoint.apiKeyEnv} is not set`); + } + const rest = Object.fromEntries( + Object.entries(env).filter(([name]) => !/KEY|TOKEN|SECRET|PASSWORD|CREDENTIAL/i.test(name)) + ); + return { + ...rest, + ANTHROPIC_BASE_URL: endpoint.baseUrl, + ANTHROPIC_API_KEY: key, + // Claude Code's background calls default to Haiku, which the endpoint does not serve. + ANTHROPIC_DEFAULT_HAIKU_MODEL: model, + }; +} + +async function runClaudeCode( + prompt: string, + cwd: string, + maxTurns: number, + modelConfig: CliEvalModelConfig, + env: Record +): Promise { + const result: AgentRunResult = { + output: "", + toolsUsed: [], + assistantMessageCount: 0, + tokenUsage: null, + finalContextTokens: null, + }; + const endpoint = modelConfig.anthropicEndpoint; const options: Options = { cwd, @@ -158,80 +243,42 @@ export async function runPromptAndCapture( maxTurns, settingSources: ["project"], allowedTools: ["Skill", "Read", "Glob", "Grep", "Bash", "Write", "Edit"], - env: { - ...getQueryEnv(), - PATH: process.env.PATH ? `${stubBinDir}${delimiter}${process.env.PATH}` : stubBinDir, - WMILL_BENCHMARK_LOG_PATH: wmillLogPath, - }, + env: endpoint ? endpointEnv(endpoint, modelConfig.model, env) : env, }; - await installWmillStub(stubBinDir); - for await (const message of query({ prompt, options })) { if (message.type === "assistant") { - assistantMessageCount += 1; + result.assistantMessageCount += 1; const turnContext = anthropicUsageToBenchmarkTokenUsage( message.message?.usage )?.prompt; if (turnContext && turnContext > 0) { - finalContextTokens = turnContext; + result.finalContextTokens = turnContext; } const content = message.message?.content; if (Array.isArray(content)) { for (const block of content) { if (block.type === "tool_use") { - const input = normalizeToolInput(block.input); - toolsUsed.push({ + result.toolsUsed.push({ tool: block.name, - input, + input: normalizeToolInput(block.input), timestamp: Date.now() }); - - if (block.name === "Skill") { - const skillInput = input as { skill?: string }; - if (skillInput.skill) { - pushUnique(skillsInvoked, skillInput.skill); - } - } - - if (block.name === "Bash") { - for (const command of extractBashCommands(input)) { - pushUnique(bashCommands, command); - } - } } else if (block.type === "text") { - output += block.text; + result.output += block.text; } } } } else if (message.type === "result") { const resultMessage = message as { result?: string }; - tokenUsage = extractCliResultTokenUsage(message) ?? tokenUsage; + result.tokenUsage = extractCliResultTokenUsage(message) ?? result.tokenUsage; if (typeof resultMessage.result === "string") { - output += resultMessage.result; + result.output += resultMessage.result; } } } - const proposedCommands = extractProposedWmillCommands(output); - const wmillInvocations = await readWmillInvocationLog(wmillLogPath); - - return { - output, - durationMs: Date.now() - startedAt, - tokenUsage, - finalContextTokens, - trace: { - toolsUsed, - skillsInvoked, - assistantMessageCount, - bashCommands, - proposedCommands, - executedWmillCommands: wmillInvocations.map(formatExecutedWmillCommand), - wmillInvocations, - firstMutationToolIndex: getFirstMutationToolIndex(toolsUsed), - }, - }; + return result; } export function wasSkillInvoked(result: PromptRunResult, skillName: string): boolean { @@ -242,10 +289,6 @@ export function wasToolUsed(result: PromptRunResult, toolName: string): boolean return result.trace.toolsUsed.some((tool) => tool.tool === toolName); } -export function formatCliRunModelLabel(modelConfig: CliEvalModelConfig): string { - return `${modelConfig.provider}:${modelConfig.model}`; -} - export function getToolInputs( result: PromptRunResult, toolName: string @@ -512,7 +555,7 @@ function formatExecutedWmillCommand(entry: CliWmillInvocation): string { return ["wmill", ...entry.argv].join(" ").trim(); } -function getFirstMutationToolIndex(toolsUsed: ToolInvocation[]): number | null { +export function getFirstMutationToolIndex(toolsUsed: ToolInvocation[]): number | null { for (const [index, tool] of toolsUsed.entries()) { if (tool.tool === "Write" || tool.tool === "Edit") { return index; @@ -526,16 +569,6 @@ function getFirstMutationToolIndex(toolsUsed: ToolInvocation[]): number | null { return null; } -function isLikelyMutatingBashCommand(command: string): boolean { - return ( - /\b(?:mkdir|touch|rm|mv|cp|install|tee)\b/.test(command) || - /\b(?:cat|echo|printf)\b.*(?:>|>>|\|\s*tee\b)/.test(command) || - /\bsed\s+-i\b/.test(command) || - /\bperl\s+-pi\b/.test(command) || - /\bwmill\b/.test(command) - ); -} - function pushUnique(values: string[], value: string): void { if (!values.includes(value)) { values.push(value); diff --git a/ai_evals/core/cases.test.ts b/ai_evals/core/cases.test.ts index 5d6e3245db..b01d4143ba 100644 --- a/ai_evals/core/cases.test.ts +++ b/ai_evals/core/cases.test.ts @@ -192,8 +192,6 @@ describe("loadCases", () => { requiredSkills: ["write-script-bun"], requiredSkillsBeforeFirstMutation: ["write-script-bun"], forbiddenSkills: ["write-script-python3", "write-flow"], - orderedAssistantMentions: ["wmill generate-metadata", "wmill sync push"], - orderedProposedCommands: ["wmill generate-metadata", "wmill sync push"], forbiddenExecutedCommands: ["^wmill generate-metadata", "^wmill sync push"], }); }); diff --git a/ai_evals/core/models.test.ts b/ai_evals/core/models.test.ts index d51d61d224..96f16778d0 100644 --- a/ai_evals/core/models.test.ts +++ b/ai_evals/core/models.test.ts @@ -1,5 +1,5 @@ import { describe, expect, it } from "bun:test"; -import { resolveEvalModel } from "./models"; +import { formatRunModelLabel, resolveEvalModel } from "./models"; describe("resolveEvalModel", () => { it("supports GPT-5.5 aliases for frontend evals", () => { @@ -47,6 +47,18 @@ describe("resolveEvalModel", () => { }); }); + it("labels cli runs by agent, keeping Claude's historical label", () => { + expect(formatRunModelLabel("cli", resolveEvalModel("cli", "sonnet-5.5"))).toBe( + "anthropic:claude-sonnet-5-5", + ); + expect(formatRunModelLabel("cli", resolveEvalModel("cli", "gpt-6.1-sol"))).toBe( + "codex:gpt-6.1-sol", + ); + expect(formatRunModelLabel("cli", resolveEvalModel("cli", "deepseek-v4-pro"))).toBe( + "claude-code:deepseek-v4-pro", + ); + }); + it("rejects Gemini aliases for cli evals", () => { expect(() => resolveEvalModel("cli", "gemini-3-flash-preview")).toThrow( "Model gemini-3-flash-preview is not supported for cli mode", diff --git a/ai_evals/core/models.ts b/ai_evals/core/models.ts index 06689c36e1..22af20d5c3 100644 --- a/ai_evals/core/models.ts +++ b/ai_evals/core/models.ts @@ -5,9 +5,13 @@ export interface FrontendEvalModelConfig { model: string; } +// The coding agent that drives the model in cli mode (adapters/cli/runtime.ts). export interface CliEvalModelConfig { - provider: "anthropic"; + runtime: "claude-code" | "codex"; model: string; + // An Anthropic-compatible endpoint other than Anthropic's, for claude-code, + // and the env var holding its key. + anthropicEndpoint?: { baseUrl: string; apiKeyEnv: string }; } export interface EvalModelSpec { @@ -35,7 +39,7 @@ export const EVAL_MODELS: EvalModelSpec[] = [ model: "claude-haiku-4-5-20251001", }, cli: { - provider: "anthropic", + runtime: "claude-code", model: "haiku", }, }, @@ -55,7 +59,7 @@ export const EVAL_MODELS: EvalModelSpec[] = [ model: "claude-sonnet-4-5-20250929", }, cli: { - provider: "anthropic", + runtime: "claude-code", model: "sonnet", }, }, @@ -74,7 +78,7 @@ export const EVAL_MODELS: EvalModelSpec[] = [ model: "claude-opus-4-6", }, cli: { - provider: "anthropic", + runtime: "claude-code", model: "opus", }, }, @@ -87,7 +91,7 @@ export const EVAL_MODELS: EvalModelSpec[] = [ model: "claude-sonnet-5-5", }, cli: { - provider: "anthropic", + runtime: "claude-code", model: "claude-sonnet-5-5", }, }, @@ -100,7 +104,7 @@ export const EVAL_MODELS: EvalModelSpec[] = [ model: "claude-opus-5-5", }, cli: { - provider: "anthropic", + runtime: "claude-code", model: "claude-opus-5-5", }, }, @@ -139,6 +143,10 @@ export const EVAL_MODELS: EvalModelSpec[] = [ provider: "openai", model: "gpt-6-astra", }, + cli: { + runtime: "codex", + model: "gpt-6-astra", + }, }, { id: "gpt-6-sol", @@ -149,6 +157,19 @@ export const EVAL_MODELS: EvalModelSpec[] = [ model: "gpt-6-sol", }, }, + { + id: "gpt-6.1-sol", + label: "GPT-6.1 Sol", + aliases: ["gpt-6.1-sol"], + frontend: { + provider: "openai", + model: "gpt-6.1-sol", + }, + cli: { + runtime: "codex", + model: "gpt-6.1-sol", + }, + }, { id: "gpt-6-luna", label: "GPT-6 Luna", @@ -215,6 +236,14 @@ export const EVAL_MODELS: EvalModelSpec[] = [ provider: "deepseek", model: "deepseek-v4-pro", }, + cli: { + runtime: "claude-code", + model: "deepseek-v4-pro", + anthropicEndpoint: { + baseUrl: "https://api.deepseek.com/anthropic", + apiKeyEnv: "DEEPSEEK_API_KEY", + }, + }, }, ]; @@ -253,11 +282,20 @@ export function formatRunModelLabel( model: EvalModelSpec, ): string { if (mode === "cli") { - return `${model.cli!.provider}:${model.cli!.model}`; + return formatCliRunModelLabel(model.cli!); } return `${model.frontend!.provider}:${model.frontend!.model}`; } +// Claude on Claude Code keeps the `anthropic:` prefix its dashboard history was +// recorded under; any other pairing names the agent. +export function formatCliRunModelLabel(config: CliEvalModelConfig): string { + if (config.runtime === "claude-code" && !config.anthropicEndpoint) { + return `anthropic:${config.model}`; + } + return `${config.runtime}:${config.model}`; +} + export function getFrontendEvalModel( model: EvalModelSpec, ): FrontendEvalModelConfig { diff --git a/ai_evals/modes/cli.ts b/ai_evals/modes/cli.ts index 205cdfa9c4..f337f99f40 100644 --- a/ai_evals/modes/cli.ts +++ b/ai_evals/modes/cli.ts @@ -39,17 +39,36 @@ interface CliRunActual { trace: CliTrace; } -const CLAUDE_PROJECT_PREAMBLE = [ - "Follow the project instructions from AGENTS.md exactly.", - "Before creating or modifying any Windmill entity, you MUST invoke the relevant Skill tool and follow it.", - "Use the skill guidance for file layout, implementation details, and the exact next commands to tell the user.", - "Do not skip the Skill step.", +// Only the skill wording differs per agent: Claude Code has a Skill tool, Codex +// loads a skill by reading its SKILL.md. +const SKILL_STEP: Record = { + "claude-code": [ + "Before creating or modifying any Windmill entity, you MUST invoke the relevant Skill tool and follow it.", + "Use the skill guidance for file layout, implementation details, and the exact next commands to tell the user.", + "Do not skip the Skill step.", + ], + codex: [ + "Before creating or modifying any Windmill entity, you MUST read the relevant skill's SKILL.md under .agents/skills and follow it.", + "Use the skill guidance for file layout, implementation details, and the exact next commands to tell the user.", + "Do not skip the skill step.", + ], +}; + +const HARNESS_PREAMBLE = [ "You are running inside an automated benchmark harness, not an interactive user session.", "Act autonomously and complete the requested file changes directly in the workspace.", "Do not ask for confirmation, do not ask the user to save or create files manually, and do not wait for approval.", "Do not respond with a plan when you can make the change directly.", "Only describe what was done after you have written the files.", -].join(" "); +]; + +function projectPreamble(runtime: CliEvalModelConfig["runtime"]): string { + return [ + "Follow the project instructions from AGENTS.md exactly.", + ...SKILL_STEP[runtime], + ...HARNESS_PREAMBLE, + ].join(" "); +} export function createCliModeRunner( modelConfig: CliEvalModelConfig = DEFAULT_CLI_EVAL_MODEL @@ -89,7 +108,7 @@ export function createCliModeRunner( }); await writeFile(join(workspaceDir, "rt.d.ts"), "export namespace RT {}\n", "utf8"); - const renderedPrompt = await renderPrompt(prompt, workspaceDir); + const renderedPrompt = await renderPrompt(prompt, workspaceDir, modelConfig.runtime); const run = await runPromptAndCapture( renderedPrompt, workspaceDir, @@ -193,7 +212,11 @@ export function getCliRunModelLabel( return formatCliRunModelLabel(modelConfig); } -async function renderPrompt(prompt: string, workspaceDir: string): Promise { +async function renderPrompt( + prompt: string, + workspaceDir: string, + runtime: CliEvalModelConfig["runtime"] +): Promise { const renderedUserPrompt = prompt.replaceAll("{{workspace_root}}", workspaceDir); const agentsInstructions = await readFile(path.join(workspaceDir, "AGENTS.md"), "utf8"); @@ -202,7 +225,7 @@ async function renderPrompt(prompt: string, workspaceDir: string): Promise Date: Wed, 7 Oct 2026 16:30:44 +0200 Subject: [PATCH 07/34] feat: export queue delay as OTel and Prometheus metrics (#11588) * feat: export queue delay as OTel and Prometheus metrics * chore: update ee-repo-ref to afd5f322346baee24d9402ca18a95de29d5c2fde This commit updates the EE repository reference after PR #850 was merged in windmill-ee-private. Previous ee-repo-ref: 450df01188ce0cfef1165bf5334bb34c26b921ee New ee-repo-ref: afd5f322346baee24d9402ca18a95de29d5c2fde Automated by sync-ee-ref workflow. --------- Co-authored-by: windmill-internal-app[bot] Co-authored-by: Ruben Fiszel --- backend/ee-repo-ref.txt | 2 +- backend/src/monitor.rs | 14 +++++++++++++- backend/tests/otel.rs | 7 ++++++- backend/windmill-common/src/otel_oss.rs | 3 +++ 4 files changed, 23 insertions(+), 3 deletions(-) diff --git a/backend/ee-repo-ref.txt b/backend/ee-repo-ref.txt index 5f22bddd84..274389ff2d 100644 --- a/backend/ee-repo-ref.txt +++ b/backend/ee-repo-ref.txt @@ -1 +1 @@ -acb254ac509aff244849c09e50a8d39aae185138 +afd5f322346baee24d9402ca18a95de29d5c2fde diff --git a/backend/src/monitor.rs b/backend/src/monitor.rs index 77963b73c6..677ecd11a2 100644 --- a/backend/src/monitor.rs +++ b/backend/src/monitor.rs @@ -40,7 +40,7 @@ use windmill_common::ee_oss::{jobs_waiting_alerts, worker_groups_alerts}; use windmill_common::global_settings::OAUTH_SETTING; use windmill_common::otel_oss::{ otel_incr_zombie_delete_count, otel_incr_zombie_restart_count, otel_set_db_pool, - otel_set_queue_count, otel_set_queue_running_count, + otel_set_queue_count, otel_set_queue_delay, otel_set_queue_running_count, }; use windmill_common::{ agent_workers::DECODED_AGENT_TOKEN, @@ -168,6 +168,12 @@ lazy_static::lazy_static! { &["tag"] ).unwrap(); + static ref QUEUE_DELAY_SECONDS: prometheus::GaugeVec = prometheus::register_gauge_vec!( + "queue_delay_seconds", + "How long the next job to be picked up has been waiting, in seconds", + &["tag"] + ).unwrap(); + static ref QUEUE_RUNNING_COUNT: prometheus::IntGaugeVec = prometheus::register_int_gauge_vec!( "queue_running_count", "Number of running jobs in the queue", @@ -5597,6 +5603,7 @@ pub async fn expose_queue_metrics(db: &Pool) { for q in QUEUE_COUNT_TAGS.read().await.iter() { if queue_stats.get(q).is_none() { (*QUEUE_COUNT).with_label_values(&[q]).set(0); + (*QUEUE_DELAY_SECONDS).with_label_values(&[q]).set(0.0); } } } @@ -5605,6 +5612,7 @@ pub async fn expose_queue_metrics(db: &Pool) { for q in OTEL_QUEUE_COUNT_TAGS.read().await.iter() { if queue_stats.get(q).is_none() { otel_set_queue_count(q, 0); + otel_set_queue_delay(q, 0.0); } } } @@ -5620,6 +5628,9 @@ pub async fn expose_queue_metrics(db: &Pool) { if metrics_enabled { let metric = (*QUEUE_COUNT).with_label_values(&[tag]); metric.set(count as i64); + (*QUEUE_DELAY_SECONDS) + .with_label_values(&[tag]) + .set(stat.delay); tags_to_watch.push(tag.to_string()); } @@ -5627,6 +5638,7 @@ pub async fn expose_queue_metrics(db: &Pool) { otel_tags_to_watch.push(tag.to_string()); } otel_set_queue_count(tag, count as i64); + otel_set_queue_delay(tag, stat.delay); } if save_metrics { diff --git a/backend/tests/otel.rs b/backend/tests/otel.rs index 1a4040d390..f1e042037f 100644 --- a/backend/tests/otel.rs +++ b/backend/tests/otel.rs @@ -168,6 +168,7 @@ async fn test_all_metrics_e2e() { // ── Gauges ────────────────────────────────────────────────────── otel_set_queue_count("python3", 42); + otel_set_queue_delay("python3", 12.5); otel_set_queue_running_count("deno", 5); otel_set_worker_busy("worker-test-1", 1); otel_set_db_pool(5, 10, 20); @@ -188,7 +189,7 @@ async fn test_all_metrics_e2e() { let metrics = flush_and_get_metrics(&state); let names = metric_names(&metrics); - // ── Verify all 20 metric names are present ────────────────────── + // ── Verify all 21 metric names are present ────────────────────── let expected = [ "windmill.queue.push_count", @@ -197,6 +198,7 @@ async fn test_all_metrics_e2e() { "windmill.queue.zombie_restart_count", "windmill.queue.zombie_delete_count", "windmill.queue.count", + "windmill.queue.delay", "windmill.queue.running_count", "windmill.worker.execution_count", "windmill.worker.execution_duration", @@ -261,6 +263,9 @@ async fn test_all_metrics_e2e() { .expect("queue.count data point with tag=python3 not found"); assert_eq!(dp.1, 42); + let m = find_metric(&metrics, "windmill.queue.delay").unwrap(); + assert!((gauge_f64_value(m).unwrap() - 12.5).abs() < f64::EPSILON); + let m = find_metric(&metrics, "windmill.queue.running_count").unwrap(); let values = gauge_i64_values(m); let dp = values diff --git a/backend/windmill-common/src/otel_oss.rs b/backend/windmill-common/src/otel_oss.rs index 5bdab37528..bd0a5202df 100644 --- a/backend/windmill-common/src/otel_oss.rs +++ b/backend/windmill-common/src/otel_oss.rs @@ -94,6 +94,9 @@ pub fn otel_incr_zombie_delete_count(_count: u64) {} #[cfg(not(feature = "private"))] pub fn otel_set_queue_count(_tag: &str, _count: i64) {} +#[cfg(not(feature = "private"))] +pub fn otel_set_queue_delay(_tag: &str, _delay_secs: f64) {} + #[cfg(not(feature = "private"))] pub fn otel_set_queue_running_count(_tag: &str, _count: i64) {} From 03e484e59757c0d4d6f74511d9aa5a1e2f94af67 Mon Sep 17 00:00:00 2001 From: Guilhem Date: Wed, 7 Oct 2026 16:34:28 +0200 Subject: [PATCH 08/34] fix: let recover: true from the error handler turn nested failures green (#11559) * feat: let the flow error handler mark the flow as successful Co-Authored-By: Claude Opus 5.5 (1M context) * fix: end the flow as a success when an inner error handler recovers Co-Authored-By: Claude Opus 5.5 (1M context) * fix: keep the recovery stop to parents that honor it Co-Authored-By: Claude Opus 5.5 (1M context) * chore: update ee-repo-ref to cbda28f632d773fd44e9bef8bea36dcb5e35b55d This commit updates the EE repository reference after PR #847 was merged in windmill-ee-private. Previous ee-repo-ref: b5a8e3631f657fbb0a7b4b4ef89ddb9ed2c43b1d New ee-repo-ref: cbda28f632d773fd44e9bef8bea36dcb5e35b55d Automated by sync-ee-ref workflow. * fix: keep skip-failure loops going and mask the recovery flag at its source Co-Authored-By: Claude Opus 5.5 (1M context) * fix: recover keeps the steps that run and only turns the flow green Co-Authored-By: Claude Opus 5.5 (1M context) * fix: only the root flow turns green on a recovered failure Co-Authored-By: Claude Opus 5.5 (1M context) * fix: a flow-chaining error keeps the flow failed after a recovery Co-Authored-By: Claude Opus 5.5 (1M context) --------- Co-authored-by: Claude Opus 5.5 (1M context) Co-authored-by: windmill-internal-app[bot] --- backend/tests/worker.rs | 123 ++++++++++++++++++ backend/windmill-worker/src/worker_flow.rs | 37 +++++- cli/src/guidance/skills.gen.ts | 1 + frontend/src/lib/script_helpers.ts | 3 + system_prompts/auto-generated/flow.md | 1 + system_prompts/auto-generated/prompts.ts | 1 + .../auto-generated/skills/write-flow/SKILL.md | 1 + system_prompts/base/flow-base.md | 1 + 8 files changed, 166 insertions(+), 2 deletions(-) diff --git a/backend/tests/worker.rs b/backend/tests/worker.rs index f420dd2a12..73d3fc2567 100644 --- a/backend/tests/worker.rs +++ b/backend/tests/worker.rs @@ -4698,6 +4698,129 @@ async fn test_run_wait_result_early_return_with_failure_module( Ok(()) } +/// `recover: true` from the error handler of a step that fails inside a loop turns the flow +/// green, as it does for a top-level step, without changing which steps run: a loop that +/// stops at a failed iteration still stops there, one that skips failures still carries on. +#[cfg(feature = "deno_core")] +#[sqlx::test(fixtures("base"))] +async fn test_failure_module_recover_inside_loop(db: Pool) -> anyhow::Result<()> { + initialize_tracing().await; + let server = ApiServer::start(db.clone()).await?; + let port = server.addr.port(); + + let failing_loop = |skip_failures: bool| { + json!({ + "id": "loop", + "value": { + "type": "forloopflow", + "iterator": { "type": "static", "value": [1, 2, 3] }, + "skip_failures": skip_failures, + "modules": [{ + "id": "a", + "value": { + "input_transforms": {}, + "type": "rawscript", + "language": "deno", + "content": "export function main() { throw new Error('boom'); }", + }, + }], + }, + }) + }; + let run = |loop_step: serde_json::Value| { + let flow: FlowValue = serde_json::from_value(json!({ + "modules": [loop_step, { + "id": "b", + "value": { + "input_transforms": {}, + "type": "rawscript", + "language": "deno", + "content": "export function main() { return { ran_b: true } }", + }, + }], + "failure_module": { + "value": { + "input_transforms": {}, + "type": "rawscript", + "language": "deno", + "content": "export function main() { return { handled: true, recover: true } }", + }, + }, + })) + .unwrap(); + RunJob::from(JobPayload::RawFlow { value: flow, path: None, restarted_from: None }) + .run_until_complete(&db, false, port) + }; + let handler_runs = || { + sqlx::query_scalar::<_, i64>( + "SELECT count(*) FROM v2_job_completed c JOIN v2_job j USING (id) + WHERE j.kind = 'preview' AND c.result @> '{\"handled\": true}'::jsonb", + ) + .fetch_one(&db) + }; + + let stopped = run(failing_loop(false)).await; + let stopped_handler_runs = handler_runs().await?; + let skipping = run(failing_loop(true)).await; + let skipping_handler_runs = handler_runs().await? - stopped_handler_runs; + // A parallel node counts its iterations' stored status: an iteration that ended on a + // recovered failure must still be stored as failed there. + let parallel = run(json!({ + "id": "par", + "value": { + "type": "forloopflow", + "iterator": { "type": "static", "value": [1, 2] }, + "parallel": true, + "skip_failures": false, + "modules": [failing_loop(false)], + }, + })) + .await; + // A recovery the inner loop absorbs, then an error raised starting the next step: that + // error is a new failure and must leave the flow failed. + #[cfg(feature = "quickjs")] + let chaining_error = run(json!({ + "id": "outer", + "value": { + "type": "forloopflow", + "iterator": { "type": "static", "value": [1] }, + "skip_failures": false, + "modules": [failing_loop(true), { + "id": "guarded", + "skip_if": { "expr": "missingFunction()" }, + "value": { "input_transforms": {}, "type": "identity" }, + }], + }, + })) + .await; + + server.close().await.unwrap(); + + #[cfg(feature = "quickjs")] + assert!(!chaining_error.success, "an error no handler recovered must keep the flow failed"); + + assert!(stopped.success, "a recovered failure inside a loop should end the flow as a success"); + assert!( + stopped.json_result().unwrap().get("ran_b").is_none(), + "the step after the loop must not run, as without recovery" + ); + assert_eq!(stopped_handler_runs, 1, "the loop must stop at the first failed iteration"); + + assert!(skipping.success); + assert_eq!( + skipping.json_result().unwrap(), + json!({ "ran_b": true }), + "a loop that skips failures runs every iteration and the following step" + ); + assert_eq!(skipping_handler_runs, 3); + + assert!( + !parallel.json_result().unwrap().to_string().contains("ran_b"), + "the parallel loop fails as without recovery, so the step after it must not run" + ); + Ok(()) +} + #[cfg(feature = "python")] #[sqlx::test(fixtures("base"))] async fn test_flow_lock_all(db: Pool) -> anyhow::Result<()> { diff --git a/backend/windmill-worker/src/worker_flow.rs b/backend/windmill-worker/src/worker_flow.rs index d2cb033084..6d76d0d771 100644 --- a/backend/windmill-worker/src/worker_flow.rs +++ b/backend/windmill-worker/src/worker_flow.rs @@ -192,6 +192,7 @@ pub async fn update_flow_status_after_job_completion( flow_job_duration, stop_early_override, has_triggered_error_handler: false, + recovered_by_child: false, }; let mut step_failure = step_failure; loop { @@ -211,6 +212,7 @@ pub async fn update_flow_status_after_job_completion( worker_dir, rec.stop_early_override, rec.has_triggered_error_handler, + rec.recovered_by_child, worker_name, job_completed_tx.clone(), flow_runners.clone(), @@ -240,6 +242,7 @@ pub async fn update_flow_status_after_job_completion( worker_dir, rec.stop_early_override, rec.has_triggered_error_handler, + false, worker_name, job_completed_tx.clone(), flow_runners.clone(), @@ -293,6 +296,10 @@ pub struct RecUpdateFlowStatusAfterJobCompletion { flow_job_duration: Option, stop_early_override: Option, has_triggered_error_handler: bool, + /// The failed child's error handler returned `recover: true`. The parent still handles the + /// failure as it would any other, so the same steps run; only a root flow that this failure + /// ends turns green. + recovered_by_child: bool, } #[derive(Deserialize)] @@ -427,6 +434,7 @@ pub async fn update_flow_status_after_job_completion_internal( worker_dir: &str, stop_early_override: Option, has_triggered_error_handler: bool, + mut recovered_by_child: bool, worker_name: &str, job_completed_tx: JobCompletedSender, flow_runners: Option>, @@ -449,6 +457,7 @@ pub async fn update_flow_status_after_job_completion_internal( skip_if_stop_early, nresult, is_failure_step, + failure_step_recovers, _cleanup_module, chat_ai_info, ) = { @@ -1096,6 +1105,9 @@ pub async fn update_flow_status_after_job_completion_internal( } else { has_triggered_error_handler = false; } + // Recovered iterations are stored as successes, so a failed parallel + // node failed on an iteration that did not recover. + recovered_by_child = false; (success, Some(new_status)) } else { add_time!(bench, "handle parallel flow start"); @@ -1823,6 +1835,13 @@ pub async fn update_flow_status_after_job_completion_internal( _ => false, }; + let failure_step_recovers = is_failure_step && result_has_recover_true(nresult.clone()); + // An error this flow raises on its own (a stop predicate's error message) is a new + // failure that no error handler recovered. + if stop_early_err_msg.is_some() { + recovered_by_child = false; + } + let chat_ai_info = ChatAiInfo { chat_input_enabled: old_status.chat_input_enabled.unwrap_or(false), conversation_id: old_status.memory_id, @@ -1837,6 +1856,7 @@ pub async fn update_flow_status_after_job_completion_internal( skip_if_stop_early, nresult, is_failure_step, + failure_step_recovers, old_status.cleanup_module, chat_ai_info, ) @@ -1844,6 +1864,10 @@ pub async fn update_flow_status_after_job_completion_internal( let flow_job = Arc::new(flow_job); + // An inner flow that ends on a recovered failure stays failed, as parents read their + // children's stored status (a parallel node counts its iterations' statuses), so only the + // root flow turns green. + let ends_root = !(flow_job.is_flow_step() && flow_job.parent_job.is_some()); let done = if !should_continue_flow { { let logs = if flow_job.is_canceled() { @@ -1851,7 +1875,9 @@ pub async fn update_flow_status_after_job_completion_internal( } else if stop_early { format!("Flow job stopped early because of a stop early predicate returning true\n") } else if is_failure_step { - format!("Flow job completed with error, and error handler was triggered.\nIt completed with {}, and with recover: {}\n", if success { "success" } else { "error" }, result_has_recover_true(nresult.clone())) + format!("Flow job completed with error, and error handler was triggered.\nIt completed with {}, and with recover: {}\n", if success { "success" } else { "error" }, failure_step_recovers) + } else if !success && recovered_by_child && ends_root { + format!("Flow job completed with success: the step that failed had its error recovered by the error handler (recover: true)\n") } else { format!( "Flow job completed with {}\n", @@ -2048,7 +2074,11 @@ pub async fn update_flow_status_after_job_completion_internal( .await; } - let success = success && (!is_failure_step || result_has_recover_true(nresult.clone())); + let success = if is_failure_step { + success && failure_step_recovers + } else { + success || (recovered_by_child && ends_root) + }; add_time!(bench, "flow status update 1"); @@ -2149,6 +2179,8 @@ pub async fn update_flow_status_after_job_completion_internal( .await; // override prior child's success so the parent learns this flow failed success = false; + // a new failure, which no error handler recovered + recovered_by_child = false; true } Ok(_) => false, @@ -2178,6 +2210,7 @@ pub async fn update_flow_status_after_job_completion_internal( None }, has_triggered_error_handler: has_triggered_error_handler || is_failure_step, + recovered_by_child: failure_step_recovers || (recovered_by_child && !success), }, )); } diff --git a/cli/src/guidance/skills.gen.ts b/cli/src/guidance/skills.gen.ts index 8dd9a8a329..4aaf6d7e3c 100644 --- a/cli/src/guidance/skills.gen.ts +++ b/cli/src/guidance/skills.gen.ts @@ -5707,6 +5707,7 @@ These are strict Windmill schema rules. Follow them exactly. - \`preprocessor_module\` and \`failure_module\` only support \`script\` or \`rawscript\` - \`preprocessor_module\` runs before normal modules and cannot reference \`results.*\` - \`failure_module\` can use the \`error\` object with \`error.message\`, \`error.step_id\`, \`error.name\`, and \`error.stack\` +- A flow whose \`failure_module\` runs still ends as failed, unless the handler returns an object with \`recover: true\`: the flow then ends as a success. This also holds when the failing step is inside a loop, a branch or a subflow. \`recover\` never changes which steps run; whether a loop or branch carries on past a failure is still decided by its own settings (\`skip_failures\`, \`continue_on_error\`) Correct shape: diff --git a/frontend/src/lib/script_helpers.ts b/frontend/src/lib/script_helpers.ts index b028e9360d..25ac64e607 100644 --- a/frontend/src/lib/script_helpers.ts +++ b/frontend/src/lib/script_helpers.ts @@ -15,6 +15,7 @@ def main(message: str, name: str, step_id: str): print("message", message) print("name", name) print("step_id", step_id) + # "recover": True ends the flow as a success instead of a failure return { "message": message, "flow_id": flow_id, "step_id": step_id, "recover": False }` const PYTHON_INIT_CODE_CLEAR = `# import wmill @@ -243,6 +244,7 @@ export async function main(message: string, name: string, step_id: string) { console.log("message", message) console.log("name",name) console.log("step_id", step_id) + // recover: true ends the flow as a success instead of a failure return { message, flow_id, step_id, recover: false } } ` @@ -253,6 +255,7 @@ export async function main(message: string, name: string, step_id: string) { console.log("message", message) console.log("name",name) console.log("step_id", step_id) + // recover: true ends the flow as a success instead of a failure return { message, flow_id, step_id, recover: false } } ` diff --git a/system_prompts/auto-generated/flow.md b/system_prompts/auto-generated/flow.md index 4ffe39cfde..7a965a17d8 100644 --- a/system_prompts/auto-generated/flow.md +++ b/system_prompts/auto-generated/flow.md @@ -22,6 +22,7 @@ These are strict Windmill schema rules. Follow them exactly. - `preprocessor_module` and `failure_module` only support `script` or `rawscript` - `preprocessor_module` runs before normal modules and cannot reference `results.*` - `failure_module` can use the `error` object with `error.message`, `error.step_id`, `error.name`, and `error.stack` +- A flow whose `failure_module` runs still ends as failed, unless the handler returns an object with `recover: true`: the flow then ends as a success. This also holds when the failing step is inside a loop, a branch or a subflow. `recover` never changes which steps run; whether a loop or branch carries on past a failure is still decided by its own settings (`skip_failures`, `continue_on_error`) Correct shape: diff --git a/system_prompts/auto-generated/prompts.ts b/system_prompts/auto-generated/prompts.ts index 562c817af7..8f6a2cc2c1 100644 --- a/system_prompts/auto-generated/prompts.ts +++ b/system_prompts/auto-generated/prompts.ts @@ -49,6 +49,7 @@ These are strict Windmill schema rules. Follow them exactly. - \`preprocessor_module\` and \`failure_module\` only support \`script\` or \`rawscript\` - \`preprocessor_module\` runs before normal modules and cannot reference \`results.*\` - \`failure_module\` can use the \`error\` object with \`error.message\`, \`error.step_id\`, \`error.name\`, and \`error.stack\` +- A flow whose \`failure_module\` runs still ends as failed, unless the handler returns an object with \`recover: true\`: the flow then ends as a success. This also holds when the failing step is inside a loop, a branch or a subflow. \`recover\` never changes which steps run; whether a loop or branch carries on past a failure is still decided by its own settings (\`skip_failures\`, \`continue_on_error\`) Correct shape: diff --git a/system_prompts/auto-generated/skills/write-flow/SKILL.md b/system_prompts/auto-generated/skills/write-flow/SKILL.md index 3a5fd09bae..352fe2ed48 100644 --- a/system_prompts/auto-generated/skills/write-flow/SKILL.md +++ b/system_prompts/auto-generated/skills/write-flow/SKILL.md @@ -109,6 +109,7 @@ These are strict Windmill schema rules. Follow them exactly. - `preprocessor_module` and `failure_module` only support `script` or `rawscript` - `preprocessor_module` runs before normal modules and cannot reference `results.*` - `failure_module` can use the `error` object with `error.message`, `error.step_id`, `error.name`, and `error.stack` +- A flow whose `failure_module` runs still ends as failed, unless the handler returns an object with `recover: true`: the flow then ends as a success. This also holds when the failing step is inside a loop, a branch or a subflow. `recover` never changes which steps run; whether a loop or branch carries on past a failure is still decided by its own settings (`skip_failures`, `continue_on_error`) Correct shape: diff --git a/system_prompts/base/flow-base.md b/system_prompts/base/flow-base.md index 83d96b9291..ddb10fd0fa 100644 --- a/system_prompts/base/flow-base.md +++ b/system_prompts/base/flow-base.md @@ -22,6 +22,7 @@ These are strict Windmill schema rules. Follow them exactly. - `preprocessor_module` and `failure_module` only support `script` or `rawscript` - `preprocessor_module` runs before normal modules and cannot reference `results.*` - `failure_module` can use the `error` object with `error.message`, `error.step_id`, `error.name`, and `error.stack` +- A flow whose `failure_module` runs still ends as failed, unless the handler returns an object with `recover: true`: the flow then ends as a success. This also holds when the failing step is inside a loop, a branch or a subflow. `recover` never changes which steps run; whether a loop or branch carries on past a failure is still decided by its own settings (`skip_failures`, `continue_on_error`) Correct shape: From f2fb15603b2e0d11bd5d04dd675212a5e4a7b9d7 Mon Sep 17 00:00:00 2001 From: Diego Imbert <70353967+diegoimbert@users.noreply.github.com> Date: Wed, 7 Oct 2026 16:35:36 +0200 Subject: [PATCH 09/34] fix: type snowflake columns in database manager insert and alter forms (#11578) * fix: type snowflake columns in database manager insert and alter forms Co-Authored-By: Claude Opus 5.5 (1M context) * fix: scope insert-form type lowercasing to snowflake Co-Authored-By: Claude Opus 5.5 (1M context) * fix: send snowflake insert-form dates as yyyy-MM-dd Co-Authored-By: Claude Opus 5.5 (1M context) * chore: update ee-repo-ref to acb254ac509aff244849c09e50a8d39aae185138 This commit updates the EE repository reference after PR #852 was merged in windmill-ee-private. Previous ee-repo-ref: 9cc330f1a8e80bc075a6ad9839966d3b344f8ddd New ee-repo-ref: acb254ac509aff244849c09e50a8d39aae185138 Automated by sync-ee-ref workflow. --------- Co-authored-by: Claude Opus 5.5 (1M context) Co-authored-by: windmill-internal-app[bot] Co-authored-by: Ruben Fiszel --- backend/ee-repo-ref.txt | 2 +- .../parsers/windmill-parser-sql/src/lib.rs | 12 ++-- .../windmill-worker/src/snowflake_executor.rs | 2 +- .../src/lib/components/DBTableEditor.svelte | 2 +- .../display/dbtable/InsertRow.svelte | 57 ++++++++++++++++++- frontend/src/lib/consts.ts | 21 ++++--- 6 files changed, 77 insertions(+), 19 deletions(-) diff --git a/backend/ee-repo-ref.txt b/backend/ee-repo-ref.txt index 274389ff2d..5f22bddd84 100644 --- a/backend/ee-repo-ref.txt +++ b/backend/ee-repo-ref.txt @@ -1 +1 @@ -afd5f322346baee24d9402ca18a95de29d5c2fde +acb254ac509aff244849c09e50a8d39aae185138 diff --git a/backend/parsers/windmill-parser-sql/src/lib.rs b/backend/parsers/windmill-parser-sql/src/lib.rs index 38f4b7a33e..10929e409a 100644 --- a/backend/parsers/windmill-parser-sql/src/lib.rs +++ b/backend/parsers/windmill-parser-sql/src/lib.rs @@ -1040,11 +1040,13 @@ pub fn parse_duckdb_typ(typ: &str) -> Typ { pub fn parse_snowflake_typ(typ: &str) -> Typ { match typ { - "varchar" => Typ::Str(None), - "binary" => Typ::Bytes, - "date" | "time" | "timestamp" => Typ::Datetime, - "int" => Typ::Int, - "float" => Typ::Float, + "varchar" | "text" | "string" | "char" | "character" => Typ::Str(None), + "binary" | "varbinary" => Typ::Bytes, + "date" | "time" | "datetime" | "timestamp" | "timestamp_ntz" | "timestamp_ltz" + | "timestamp_tz" => Typ::Datetime, + "int" | "integer" | "bigint" | "smallint" | "tinyint" | "byteint" => Typ::Int, + "float" | "float4" | "float8" | "double" | "double precision" | "real" | "number" + | "decimal" | "numeric" => Typ::Float, "boolean" => Typ::Bool, "s3object" => Typ::Resource("S3Object".to_string()), _ => Typ::Str(None), diff --git a/backend/windmill-worker/src/snowflake_executor.rs b/backend/windmill-worker/src/snowflake_executor.rs index b4bb448b99..24b07eacb9 100644 --- a/backend/windmill-worker/src/snowflake_executor.rs +++ b/backend/windmill-worker/src/snowflake_executor.rs @@ -855,7 +855,7 @@ fn convert_typ_val(arg_t: String, arg_v: Value) -> Value { } }) } - "binary" => { + "binary" | "varbinary" => { // convert base64 to hex as expected by snowflake let bytes = engine::general_purpose::STANDARD .decode(arg_v.as_str().unwrap_or("")) diff --git a/frontend/src/lib/components/DBTableEditor.svelte b/frontend/src/lib/components/DBTableEditor.svelte index 4eb07aea5f..21cca65f63 100644 --- a/frontend/src/lib/components/DBTableEditor.svelte +++ b/frontend/src/lib/components/DBTableEditor.svelte @@ -105,7 +105,7 @@ const defaultColumnType = ( { postgresql: 'BIGSERIAL', - snowflake: 'varchar', + snowflake: 'VARCHAR', ms_sql_server: 'varchar', bigquery: 'string', mysql: 'varchar', diff --git a/frontend/src/lib/components/apps/components/display/dbtable/InsertRow.svelte b/frontend/src/lib/components/apps/components/display/dbtable/InsertRow.svelte index 0483bbd272..767240a60f 100644 --- a/frontend/src/lib/components/apps/components/display/dbtable/InsertRow.svelte +++ b/frontend/src/lib/components/apps/components/display/dbtable/InsertRow.svelte @@ -30,6 +30,42 @@ nullable: 'YES' | 'NO' } + // Snowflake's information_schema reports canonical names (NUMBER, TEXT, + // TIMESTAMP_NTZ, ...), which the pinned parser wasm only knows by a few aliases. + function snowflakeParserAlias(typ: string): string { + switch (typ) { + case 'number': + case 'decimal': + case 'numeric': + case 'float4': + case 'float8': + case 'double': + case 'double precision': + case 'real': + return 'float' + case 'integer': + case 'bigint': + case 'smallint': + case 'tinyint': + case 'byteint': + return 'int' + case 'text': + case 'string': + case 'char': + case 'character': + return 'varchar' + case 'varbinary': + return 'binary' + case 'datetime': + case 'timestamp_ntz': + case 'timestamp_ltz': + case 'timestamp_tz': + return 'timestamp' + default: + return typ + } + } + function parseSQLArgs(field: string, dbType: DbType): string { let rawType = '' switch (dbType) { @@ -43,7 +79,7 @@ rawType = parse_bigquery(field) break case 'snowflake': - rawType = parse_snowflake(field) + rawType = parse_snowflake(snowflakeParserAlias(field.toLowerCase())) break case 'ms_sql_server': rawType = parse_mssql(field) @@ -97,12 +133,27 @@ schemaProperty.default = field.defaultValue } } - if (field.type === 'timestamp without time zone' || field.type === 'timestamp') { + const fieldType = dbType === 'snowflake' ? field.type.toLowerCase() : field.type + if ( + fieldType === 'timestamp without time zone' || + fieldType === 'timestamp' || + fieldType === 'timestamp_ntz' + ) { schemaProperty.format = 'naive-date-time' } - if (field.type === 'timestamp with time zone' || field.type === 'timestamptz') { + if ( + fieldType === 'timestamp with time zone' || + fieldType === 'timestamptz' || + fieldType === 'timestamp_tz' || + fieldType === 'timestamp_ltz' + ) { schemaProperty.format = 'date-time' } + if (dbType === 'snowflake' && fieldType === 'date') { + schemaProperty.format = 'date' + // DateInput defaults to dd-MM-yyyy, which Snowflake's AUTO input format rejects + schemaProperty.dateFormat = 'yyyy-MM-dd' + } properties[field.name] = schemaProperty diff --git a/frontend/src/lib/consts.ts b/frontend/src/lib/consts.ts index c6e18427f0..bfa1d845b2 100644 --- a/frontend/src/lib/consts.ts +++ b/frontend/src/lib/consts.ts @@ -179,14 +179,19 @@ export const BIGQUERY_TYPES = [ ] export const SNOWFLAKE_TYPES = [ - 'varchar', - 'binary', - 'date', - 'time', - 'timestamp', - 'int', - 'float', - 'boolean' + 'VARCHAR', + 'TEXT', + 'BINARY', + 'DATE', + 'TIME', + 'TIMESTAMP', + 'TIMESTAMP_NTZ', + 'TIMESTAMP_LTZ', + 'TIMESTAMP_TZ', + 'INT', + 'NUMBER', + 'FLOAT', + 'BOOLEAN' ] export const MSSQL_TYPES = [ From afa9ced84cfec2b45a33657812836908cb32775a Mon Sep 17 00:00:00 2001 From: Ruben Fiszel Date: Wed, 7 Oct 2026 18:44:57 +0200 Subject: [PATCH 10/34] [ee] feat: job cancel signals (oidc refusal, agent 5s ping, job.canceled) (#11592) * feat: faster agent cancel detection, job.canceled event, worker_group span attribute Co-Authored-By: Claude Opus 5.5 (1M context) * fix: report no unix signal in job.canceled where none is sent Co-Authored-By: Claude Opus 5.5 (1M context) * refactor: agent workers ping every 5s instead of a 2s read-only cancel check Co-Authored-By: Claude Opus 5.5 (1M context) * fix: emit job.canceled on windows when the process exits unsignaled Co-Authored-By: Claude Opus 5.5 (1M context) * chore: pin ee ref with the queue delay gauge main requires Co-Authored-By: Claude Opus 5.5 (1M context) --------- Co-authored-by: Claude Opus 5.5 (1M context) --- ...42cba3a5532c64a9594d2e0ccdf21dee90d0.json} | 6 +- backend/ee-repo-ref.txt | 2 +- backend/tests/job_token_scopes.rs | 17 ++ backend/windmill-common/src/log_context.rs | 1 + backend/windmill-runtime-nativets/src/lib.rs | 4 +- backend/windmill-worker/src/handle_child.rs | 168 ++++++++++++------ backend/windmill-worker/src/worker.rs | 2 + 7 files changed, 143 insertions(+), 57 deletions(-) rename backend/.sqlx/{query-ee769c78ec0a782de18911cdcb655aad93cf23321cd0f42f7ffa5348bfbea26e.json => query-58ea7e2c6b07ffc7ab7387b2ebb542cba3a5532c64a9594d2e0ccdf21dee90d0.json} (54%) diff --git a/backend/.sqlx/query-ee769c78ec0a782de18911cdcb655aad93cf23321cd0f42f7ffa5348bfbea26e.json b/backend/.sqlx/query-58ea7e2c6b07ffc7ab7387b2ebb542cba3a5532c64a9594d2e0ccdf21dee90d0.json similarity index 54% rename from backend/.sqlx/query-ee769c78ec0a782de18911cdcb655aad93cf23321cd0f42f7ffa5348bfbea26e.json rename to backend/.sqlx/query-58ea7e2c6b07ffc7ab7387b2ebb542cba3a5532c64a9594d2e0ccdf21dee90d0.json index bb7e4fa36b..e03d995f15 100644 --- a/backend/.sqlx/query-ee769c78ec0a782de18911cdcb655aad93cf23321cd0f42f7ffa5348bfbea26e.json +++ b/backend/.sqlx/query-58ea7e2c6b07ffc7ab7387b2ebb542cba3a5532c64a9594d2e0ccdf21dee90d0.json @@ -1,11 +1,11 @@ { "db_name": "PostgreSQL", - "query": "SELECT EXISTS (SELECT 1 FROM v2_job_queue WHERE id = $1 AND workspace_id = $2 AND running)", + "query": "SELECT canceled_by IS NOT NULL FROM v2_job_queue WHERE id = $1 AND workspace_id = $2 AND running", "describe": { "columns": [ { "ordinal": 0, - "name": "exists", + "name": "?column?", "type_info": "Bool" } ], @@ -19,5 +19,5 @@ null ] }, - "hash": "ee769c78ec0a782de18911cdcb655aad93cf23321cd0f42f7ffa5348bfbea26e" + "hash": "58ea7e2c6b07ffc7ab7387b2ebb542cba3a5532c64a9594d2e0ccdf21dee90d0" } diff --git a/backend/ee-repo-ref.txt b/backend/ee-repo-ref.txt index 5f22bddd84..dbcf14cb3c 100644 --- a/backend/ee-repo-ref.txt +++ b/backend/ee-repo-ref.txt @@ -1 +1 @@ -acb254ac509aff244849c09e50a8d39aae185138 +0b78e2c6fefcbad3c465bf75ebfd6ebd6912ad19 \ No newline at end of file diff --git a/backend/tests/job_token_scopes.rs b/backend/tests/job_token_scopes.rs index 6af694bff0..f805168bfa 100644 --- a/backend/tests/job_token_scopes.rs +++ b/backend/tests/job_token_scopes.rs @@ -410,5 +410,22 @@ async fn test_oidc_claim_carries_the_presented_scopes(db: Pool) -> any )?; assert_eq!(claims["job_token_scopes"], expected, "{job}"); } + + // A soft-canceled job is still `running` until its worker kills it. + sqlx::query("UPDATE v2_job_queue SET canceled_by = 'test-user' WHERE id = $1") + .bind(Uuid::parse_str(OIDC_JOB)?) + .execute(&db) + .await?; + let resp = client + .post(format!("{base}/oidc/token/test-audience")) + .bearer_auth(job_token(&db, OIDC_JOB).await?) + .send() + .await?; + assert_eq!( + resp.status(), + StatusCode::FORBIDDEN, + "{}", + resp.text().await? + ); Ok(()) } diff --git a/backend/windmill-common/src/log_context.rs b/backend/windmill-common/src/log_context.rs index cdb1e27aea..c5cd191da8 100644 --- a/backend/windmill-common/src/log_context.rs +++ b/backend/windmill-common/src/log_context.rs @@ -49,6 +49,7 @@ pub struct LogContext { // Worker / job span (windmill-worker/src/worker.rs) pub worker: Option, + pub worker_group: Option, pub hostname: Option, pub tag: Option, pub job_id: Option, diff --git a/backend/windmill-runtime-nativets/src/lib.rs b/backend/windmill-runtime-nativets/src/lib.rs index 1c2a76cda5..75aacbcc64 100644 --- a/backend/windmill-runtime-nativets/src/lib.rs +++ b/backend/windmill-runtime-nativets/src/lib.rs @@ -929,8 +929,8 @@ pub async fn eval_fetch_timeout( for line in logged.as_deref().unwrap_or(&log).lines() { tracing::info!( target: "windmill:job_log", - job_id = ?job_id, - workspace_id = ?w_id_for_tracing, + job_id = %job_id, + workspace_id = %w_id_for_tracing, "{line}" ); if *OTEL_JOB_LOGS { diff --git a/backend/windmill-worker/src/handle_child.rs b/backend/windmill-worker/src/handle_child.rs index 22a2bf4e8b..fa06edf6bf 100644 --- a/backend/windmill-worker/src/handle_child.rs +++ b/backend/windmill-worker/src/handle_child.rs @@ -210,6 +210,53 @@ pub async fn handle_child( } } + impl KillReason { + /// Reports a kill once the process is gone: a span event on the enclosing span and, + /// through the logs bridge, a log record carrying the job's log context. + fn emit_canceled_event( + &self, + job_id: &Uuid, + timeout_reason: &str, + signal: &'static str, + detected_at: chrono::DateTime, + ) { + // `force` is only known for a soft cancel: a job completed under the worker + // may have been force canceled or completed by anything else server-side. + let (kill_reason, canceled_by, canceled_reason, force) = match self { + KillReason::TooManyLogs => return, + KillReason::Timeout { .. } => { + ("timeout", Some("timeout"), Some(timeout_reason), None) + } + KillReason::Cancelled(by) => ( + "cancelled", + by.as_ref().and_then(|x| x.username.as_deref()), + by.as_ref().and_then(|x| x.reason.as_deref()), + Some(false), + ), + KillReason::AlreadyCompleted => ("already_completed", None, None, None), + }; + let exited_at = chrono::Utc::now(); + let root_job = windmill_common::log_context::current_log_context() + .and_then(|c| c.root_job.clone()); + let rfc3339 = |t: chrono::DateTime| { + t.to_rfc3339_opts(chrono::SecondsFormat::Millis, true) + }; + tracing::info!( + job_id = %job_id, + root_job, + kill_reason, + canceled_by, + canceled_reason, + force, + kill_signal = signal, + cancel_detected_at = %rfc3339(detected_at), + process_exited_at = %rfc3339(exited_at), + kill_duration_ms = (exited_at - detected_at).num_milliseconds(), + "job.canceled" + ); + } + } + let (timeout_duration, timeout_warn_msg, timeout_source) = resolve_job_timeout(&conn, w_id, job_id, custom_timeout).await; if let Some(msg) = timeout_warn_msg { @@ -232,6 +279,7 @@ pub async fn handle_child( UpdateJobPollingExit::AlreadyCompleted => KillReason::AlreadyCompleted, }, }; + let detected_at = chrono::Utc::now(); tx.send(()).expect("rx should never be dropped"); drop(tx); @@ -268,59 +316,78 @@ pub async fn handle_child( } }; - #[allow(unused_variables)] - if let Some(id) = child.id() { - if *MAX_WAIT_FOR_SIGINT > 0 { - #[cfg(any(target_os = "linux", target_os = "macos"))] - signal::kill(Pid::from_raw(id as i32), Signal::SIGINT).unwrap(); + // Resolves once the process is reaped, to the last signal it was sent, or to `None` + // when the kill could not be confirmed. SIGINT and SIGTERM are only sent where the + // sends below are compiled in: elsewhere an exit during their wait is unsignaled. + let unix_signal = |s: &'static str| { + if cfg!(any(target_os = "linux", target_os = "macos")) { s } else { "none" } + }; + let kill = async { + #[allow(unused_variables)] + if let Some(id) = child.id() { + if *MAX_WAIT_FOR_SIGINT > 0 { + #[cfg(any(target_os = "linux", target_os = "macos"))] + signal::kill(Pid::from_raw(id as i32), Signal::SIGINT).unwrap(); - for _ in 0..*MAX_WAIT_FOR_SIGINT { + for _ in 0..*MAX_WAIT_FOR_SIGINT { + if child.try_wait().is_ok_and(|x| x.is_some()) { + break; + } + sleep(Duration::from_secs(1)).await; + } if child.try_wait().is_ok_and(|x| x.is_some()) { - break; + set_reason.await; + return Ok(Some(unix_signal("SIGINT"))); } - sleep(Duration::from_secs(1)).await; } - if child.try_wait().is_ok_and(|x| x.is_some()) { - set_reason.await; - return Ok(Err(kill_reason)); + if sigterm { + #[cfg(any(target_os = "linux", target_os = "macos"))] + signal::kill(Pid::from_raw(id as i32), Signal::SIGTERM).unwrap(); + + for _ in 0..*MAX_WAIT_FOR_SIGTERM { + if child.try_wait().is_ok_and(|x| x.is_some()) { + break; + } + sleep(Duration::from_secs(1)).await; + } + if child.try_wait().is_ok_and(|x| x.is_some()) { + set_reason.await; + return Ok(Some(unix_signal("SIGTERM"))); + } } } - if sigterm { - #[cfg(any(target_os = "linux", target_os = "macos"))] - signal::kill(Pid::from_raw(id as i32), Signal::SIGTERM).unwrap(); - - for _ in 0..*MAX_WAIT_FOR_SIGTERM { - if child.try_wait().is_ok_and(|x| x.is_some()) { - break; + #[cfg(windows)] + { + let pid_to_kill = child.id(); + let killed = match kill_process_tree(pid_to_kill).await { + Ok(_) => { + tracing::debug!( + "successfully killed process tree with PID: {:?}", + pid_to_kill + ); + true } - sleep(Duration::from_secs(1)).await; - } - if child.try_wait().is_ok_and(|x| x.is_some()) { - set_reason.await; - return Ok(Err(kill_reason)); - } + Err(e) => { + tracing::error!("failed to kill process tree: {:?}", e); + false + } + }; + set_reason.await; + return Ok(killed.then_some("taskkill")); } - } - #[cfg(windows)] - { - let pid_to_kill = child.id(); - match kill_process_tree(pid_to_kill).await { - Ok(_) => tracing::debug!( - "successfully killed process tree with PID: {:?}", - pid_to_kill - ), - Err(e) => tracing::error!("failed to kill process tree: {:?}", e), - }; - set_reason.await; - return Ok(Err(kill_reason)); - } - #[cfg(unix)] - { - /* send SIGKILL and reap child process */ - let (_, kill) = future::join(set_reason, Box::into_pin(child.kill())).await; - kill.map(|()| Err(kill_reason)) + #[cfg(unix)] + { + /* send SIGKILL and reap child process */ + let (_, kill) = future::join(set_reason, Box::into_pin(child.kill())).await; + kill.map(|()| Some("SIGKILL")) + } + }; + let signal: io::Result> = kill.await; + if let Some(signal) = signal? { + kill_reason.emit_canceled_event(&job_id, &timeout_reason, signal, detected_at); } + Ok(Err(kill_reason)) }; let mut stream_result = Vec::new(); @@ -957,9 +1024,9 @@ where let conn = conn.clone(); // No tick at t=0: a job that finishes within the first interval issues none of the - // ping/metric statements below. Cancels are picked up by the first job ping (500 ms in, - // 2 s on agent workers). Memory is still sampled at start, without SQL: it is the only - // `mem_peak` reading a short job gets, and the completed job row reports it. + // ping/metric statements below. Cancels are picked up by the next job ping. Memory is still + // sampled at start, without SQL: it is the only `mem_peak` reading a short job gets, + // and the completed job row reports it. let mut interval = interval_at(Instant::now() + update_job_interval, update_job_interval); interval.set_missed_tick_behavior(MissedTickBehavior::Skip); *mem_peak = (*mem_peak).max(get_mem.next().await.unwrap_or(0)); @@ -1023,11 +1090,10 @@ where } } } - if matches!(conn, Connection::Http(_)) { - if i % 4 != 0 { - // only ping every 4th time (2s) on http agent mode - continue; - } + // An agent worker pays an HTTP round trip per ping, so it pings every 2 s for + // the first 10 s, then every 5 s. + if matches!(conn, Connection::Http(_)) && i % if i < 20 { 4 } else { 10 } != 0 { + continue; } let ping_job_status = ping_job_status(&conn, &job_id, Some(*mem_peak), if current_mem > 0 { Some(current_mem) } else { None }).await.unwrap_or_else(|e| { tracing::error!("Unable to ping job status for job {job_id}. Error was: {:?}", e); diff --git a/backend/windmill-worker/src/worker.rs b/backend/windmill-worker/src/worker.rs index 80ca37acb8..96d8619988 100644 --- a/backend/windmill-worker/src/worker.rs +++ b/backend/windmill-worker/src/worker.rs @@ -2005,6 +2005,7 @@ pub fn create_span_with_name( root_job = field::Empty, workspace_id = %arc_job.workspace_id, worker = %worker_name, + worker_group = %*WORKER_GROUP, hostname = field::Empty, tag = %arc_job.tag, language = field::Empty, @@ -2156,6 +2157,7 @@ pub fn log_context_for_job( job_id: Some(arc_job.id.to_string()), workspace_id: Some(arc_job.workspace_id.clone()), worker: Some(worker_name.to_string()), + worker_group: Some(WORKER_GROUP.clone()), tag: Some(arc_job.tag.clone()), job_kind: Some(arc_job.kind.as_str().to_string()), created_by: Some(arc_job.created_by.clone()), From 14381cefee6fb2b0ece52fbf0001c2ce61bde1a1 Mon Sep 17 00:00:00 2001 From: Ruben Fiszel Date: Wed, 7 Oct 2026 19:02:34 +0200 Subject: [PATCH 11/34] fix: scope the python wheel cache to workspaces with their own registry (#11597) * feat: pin python lockfile hashes and key the wheel cache by them Co-Authored-By: Claude Opus 5.5 (1M context) * fix: keep pinned python cache entries out of reach of unpinned installs Co-Authored-By: Claude Opus 5.5 (1M context) * fix: scope python cache entries of index-overriding workspaces by hashed id Co-Authored-By: Claude Opus 5.5 (1M context) * fix: keep the python cache scope consistent with the index urls read Co-Authored-By: Claude Opus 5.5 (1M context) * fix: read python index urls and their cache scope from one snapshot Co-Authored-By: Claude Opus 5.5 (1M context) * fix: drop hash pinning, keep only the workspace scope of the wheel cache Co-Authored-By: Claude Opus 5.5 (1M context) * fix: resolve pip index urls only after a resolution cache miss Co-Authored-By: Claude Opus 5.5 (1M context) --------- Co-authored-by: Claude Opus 5.5 (1M context) --- .../windmill-worker/src/python_executor.rs | 122 +++++++++++------- backend/windmill-worker/src/worker.rs | 16 +++ 2 files changed, 93 insertions(+), 45 deletions(-) diff --git a/backend/windmill-worker/src/python_executor.rs b/backend/windmill-worker/src/python_executor.rs index 3fce0fb938..f1814ac3fd 100644 --- a/backend/windmill-worker/src/python_executor.rs +++ b/backend/windmill-worker/src/python_executor.rs @@ -156,7 +156,7 @@ use crate::{ }, get_proxy_envs_for_lang, handle_child::handle_child, - is_sandboxing_enabled, read_ee_registry_with_workspace_override, + is_sandboxing_enabled, read_ee_registry, worker_utils::ping_job_status, PyV, DISABLE_NUSER, HOME_ENV, INDEX_CERT, NATIVE_CERT, NSJAIL_AVAILABLE, NSJAIL_PATH, NSJAIL_PY_RLIMIT_AS_MB, PATH_ENV, PIP_EXTRA_INDEX_URL, PIP_INDEX_URL, PROXY_ENVS, @@ -279,7 +279,12 @@ pub async fn uv_pip_compile( #[cfg(feature = "enterprise")] let requirements = replace_pip_secret(conn, w_id, &requirements, worker_name, job_id).await?; - let ws_suffix = crate::workspace_registry_cache_suffix(w_id).await; + let pip_indexes = PipIndexes::snapshot(w_id).await; + let ws_suffix = if pip_indexes.ws_scoped { + format!(":ws:{w_id}") + } else { + String::new() + }; let exclude_newer_suffix = uv_exclude_newer .as_deref() .map(|v| format!("-en{}", v)) @@ -343,31 +348,12 @@ pub async fn uv_pip_compile( if no_cache { args.extend(["--no-cache"]); } - let pip_extra_index_url = read_ee_registry_with_workspace_override( - PIP_EXTRA_INDEX_URL.read().await.clone(), - "pip_extra_index_url", - "pip extra index url", - job_id, - w_id, - conn, - ) - .await - .map(handle_ephemeral_token); + let (pip_extra_index_url, pip_index_url) = pip_indexes.urls(job_id, w_id, conn).await; if let Some(url) = pip_extra_index_url.as_ref() { url.split(",").for_each(|url| { args.extend(["--extra-index-url", url]); }); } - let pip_index_url = read_ee_registry_with_workspace_override( - PIP_INDEX_URL.read().await.clone(), - "pip_index_url", - "pip index url", - job_id, - w_id, - conn, - ) - .await - .map(handle_ephemeral_token); if let Some(url) = pip_index_url.as_ref() { args.extend(["--index-url", url]); } @@ -2068,6 +2054,62 @@ Returned from server: py_version - {:?}, py_version_v2 - {:?} Ok((pyv, additional_python_paths)) } +/// The pip index settings a job resolves and installs from, and whether its workspace +/// overrides any registry. +/// +/// Both come from one snapshot of the workspace's overrides: read separately, a settings +/// reload in between could file an install from an overridden index under a shared cache name. +struct PipIndexes { + extra_index_url: Option, + index_url: Option, + /// Caches filled through these URLs must not be shared with other workspaces. + ws_scoped: bool, +} + +impl PipIndexes { + async fn snapshot(w_id: &str) -> Self { + let overrides = crate::workspace_registry_overrides(w_id).await; + let ws_value = |key: &str| match overrides.get(key) { + Some(serde_json::Value::String(s)) => Some(s.clone()), + _ => None, + }; + // An empty value means unset, and an empty workspace override unsets the global one. + Self { + extra_index_url: ws_value("pip_extra_index_url") + .or(PIP_EXTRA_INDEX_URL.read().await.clone()) + .filter(|s| !s.trim().is_empty()), + index_url: ws_value("pip_index_url") + .or(PIP_INDEX_URL.read().await.clone()) + .filter(|s| !s.trim().is_empty()), + ws_scoped: !overrides.is_empty(), + } + } + + /// The `(extra index, index)` URLs to hand uv. Kept apart from [`Self::snapshot`]: it runs + /// `EPHEMERAL_TOKEN_CMD`, which a caller served from a cache has no reason to pay for. + async fn urls( + self, + job_id: &Uuid, + w_id: &str, + conn: &Connection, + ) -> (Option, Option) { + ( + read_ee_registry( + self.extra_index_url, + "pip extra index url", + job_id, + w_id, + conn, + ) + .await + .map(handle_ephemeral_token), + read_ee_registry(self.index_url, "pip index url", job_id, w_id, conn) + .await + .map(handle_ephemeral_token), + ) + } +} + lazy_static::lazy_static! { static ref PIP_SECRET_VARIABLE: Regex = Regex::new(r"\$\{PIP_SECRET:([^\s\}]+)\}").unwrap(); @@ -2527,28 +2569,18 @@ pub async fn handle_python_reqs( job_id ); - let pip_indexes = ( - read_ee_registry_with_workspace_override( - PIP_EXTRA_INDEX_URL.read().await.clone(), - "pip_extra_index_url", - "pip extra index url", - job_id, - w_id, - conn, - ) - .await - .map(handle_ephemeral_token), - read_ee_registry_with_workspace_override( - PIP_INDEX_URL.read().await.clone(), - "pip_index_url", - "pip index url", - job_id, - w_id, - conn, - ) - .await - .map(handle_ephemeral_token), - ); + let pip_indexes = PipIndexes::snapshot(w_id).await; + let ws_scoped = pip_indexes.ws_scoped; + let pip_indexes = pip_indexes.urls(job_id, w_id, conn).await; + // The wheel dir is shared by every workspace on the worker, and by every worker through + // the object store, under a name that says nothing of the index it was filled from. A + // workspace with its own registries gets its own, as its resolution cache does. The id + // is hashed: it is not restricted to characters safe in a file name. + let ws_dir_suffix = if ws_scoped { + format!("-ws-{}", &calculate_hash(w_id)[..16]) + } else { + String::new() + }; // Cached paths let mut req_with_penv: Vec<(String, String)> = vec![]; @@ -2577,7 +2609,7 @@ pub async fn handle_python_reqs( let py_prefix = &py_version.to_cache_dir(false); let venv_p = format!( - "{py_prefix}/{}", + "{py_prefix}/{}{ws_dir_suffix}", req.replace(' ', "").replace('/', "").replace(':', "") ); if metadata(venv_p.clone() + "/.valid.windmill").await.is_ok() { diff --git a/backend/windmill-worker/src/worker.rs b/backend/windmill-worker/src/worker.rs index 96d8619988..28d226ea3f 100644 --- a/backend/windmill-worker/src/worker.rs +++ b/backend/windmill-worker/src/worker.rs @@ -949,6 +949,22 @@ pub async fn workspace_registry_cache_suffix(w_id: &str) -> String { } } +/// The registry overrides of a workspace, empty when it has none. +/// +/// One snapshot: registry settings reload under running jobs, so a caller whose cache key +/// has to agree with the registry values it used reads both from here rather than calling +/// [`workspace_registry_cache_suffix`] and a `read_ee_registry_*` helper separately. +pub async fn workspace_registry_overrides( + w_id: &str, +) -> std::collections::HashMap { + let registries = WORKSPACE_REGISTRIES.read().await; + registries + .as_ref() + .and_then(|m| m.get(w_id)) + .cloned() + .unwrap_or_default() +} + /// The name a build artifact is cached under, derived from `base` — the runnable's own /// cache-key input — and its inline modules. /// From 95c4b3096cf10c1fe59de7a1a6876dfb5f02c39f Mon Sep 17 00:00:00 2001 From: Ruben Fiszel Date: Wed, 7 Oct 2026 19:28:29 +0200 Subject: [PATCH 12/34] feat: pause a worker group without stopping its workers (#11596) * feat: pause a worker group without stopping its workers * chore: bump ee ref * fix: keep dedicated workers running across a pause toggle * fix: edit a copy of the worker group config in the drawer * fix: stable priority tag order, keep pause-only configs in the drawer * fix: keep inherited worker tags when saving from the drawer * fix: keep an explicit empty tag list when leaving dedicated mode * fix: keep inherited tags when creating a config from the drawer Co-Authored-By: Claude Opus 5.5 (1M context) * chore: update ee-repo-ref to 6f23819e947b18878000e580ddefccfd01a73166 This commit updates the EE repository reference after PR #853 was merged in windmill-ee-private. Previous ee-repo-ref: 6cf802bdbe17b4a66757016515044b8a9ef9ef19 New ee-repo-ref: 6f23819e947b18878000e580ddefccfd01a73166 Automated by sync-ee-ref workflow. * feat: confirm before applying a worker config change that restarts workers Co-Authored-By: Claude Opus 5.5 (1M context) * chore: pin the ee commit that compiles against main Co-Authored-By: Claude Opus 5.5 (1M context) * chore: retrigger ci after the github outage dropped the push event Co-Authored-By: Claude Opus 5.5 (1M context) --------- Co-authored-by: Claude Opus 5.5 (1M context) Co-authored-by: windmill-internal-app[bot] --- ...9573aefaeb5dbc6ac07f5e664bc8fe2cb2683.json | 22 +++ ...c8f780ab4c9d3d373d3cd0bb489e0d173040c.json | 22 +++ backend/ee-repo-ref.txt | 2 +- backend/src/monitor.rs | 9 +- backend/tests/worker_group_pause.rs | 71 ++++++++++ backend/windmill-api-configs/src/lib.rs | 28 +++- .../windmill-common/src/instance_config.rs | 3 + backend/windmill-common/src/worker.rs | 66 ++++++++- backend/windmill-worker/src/worker.rs | 4 + .../src/lib/components/WorkerGroup.svelte | 133 ++++++++++++++++-- 10 files changed, 340 insertions(+), 20 deletions(-) create mode 100644 backend/.sqlx/query-91fdd565bd210f8aa4c6d5f5e309573aefaeb5dbc6ac07f5e664bc8fe2cb2683.json create mode 100644 backend/.sqlx/query-a6d355b3121f199f3827c05aaa7c8f780ab4c9d3d373d3cd0bb489e0d173040c.json create mode 100644 backend/tests/worker_group_pause.rs diff --git a/backend/.sqlx/query-91fdd565bd210f8aa4c6d5f5e309573aefaeb5dbc6ac07f5e664bc8fe2cb2683.json b/backend/.sqlx/query-91fdd565bd210f8aa4c6d5f5e309573aefaeb5dbc6ac07f5e664bc8fe2cb2683.json new file mode 100644 index 0000000000..ba917c82db --- /dev/null +++ b/backend/.sqlx/query-91fdd565bd210f8aa4c6d5f5e309573aefaeb5dbc6ac07f5e664bc8fe2cb2683.json @@ -0,0 +1,22 @@ +{ + "db_name": "PostgreSQL", + "query": "SELECT COALESCE(config->'paused' = 'true'::jsonb, false) FROM config WHERE name = $1", + "describe": { + "columns": [ + { + "ordinal": 0, + "name": "coalesce", + "type_info": "Bool" + } + ], + "parameters": { + "Left": [ + "Text" + ] + }, + "nullable": [ + null + ] + }, + "hash": "91fdd565bd210f8aa4c6d5f5e309573aefaeb5dbc6ac07f5e664bc8fe2cb2683" +} diff --git a/backend/.sqlx/query-a6d355b3121f199f3827c05aaa7c8f780ab4c9d3d373d3cd0bb489e0d173040c.json b/backend/.sqlx/query-a6d355b3121f199f3827c05aaa7c8f780ab4c9d3d373d3cd0bb489e0d173040c.json new file mode 100644 index 0000000000..e1657e156b --- /dev/null +++ b/backend/.sqlx/query-a6d355b3121f199f3827c05aaa7c8f780ab4c9d3d373d3cd0bb489e0d173040c.json @@ -0,0 +1,22 @@ +{ + "db_name": "PostgreSQL", + "query": "SELECT COALESCE(config->'paused' = 'true'::jsonb, false) FROM config WHERE name = $1 FOR UPDATE", + "describe": { + "columns": [ + { + "ordinal": 0, + "name": "coalesce", + "type_info": "Bool" + } + ], + "parameters": { + "Left": [ + "Text" + ] + }, + "nullable": [ + null + ] + }, + "hash": "a6d355b3121f199f3827c05aaa7c8f780ab4c9d3d373d3cd0bb489e0d173040c" +} diff --git a/backend/ee-repo-ref.txt b/backend/ee-repo-ref.txt index dbcf14cb3c..fffcc99883 100644 --- a/backend/ee-repo-ref.txt +++ b/backend/ee-repo-ref.txt @@ -1 +1 @@ -0b78e2c6fefcbad3c465bf75ebfd6ebd6912ad19 \ No newline at end of file +1600d49ad5513af8b54ad65688d3d1c7edc977d9 \ No newline at end of file diff --git a/backend/src/monitor.rs b/backend/src/monitor.rs index 677ecd11a2..8d0af4915d 100644 --- a/backend/src/monitor.rs +++ b/backend/src/monitor.rs @@ -427,6 +427,8 @@ pub async fn initial_load( native_mode, // an agent worker never reads its group's config, only its token object_store_cache_config: None, + // nor whether it is paused: the server refuses it jobs instead + paused: false, })); } } @@ -5689,8 +5691,13 @@ pub async fn reload_worker_config(db: &DB, tx: KillpillSender, kill_if_change: b .as_ref() .is_some_and(|dws| !dws.is_empty()); + // Pausing or resuming must not restart the workers, dedicated ones included: a reload + // whose only difference is the flag skips every restart below. + let only_pause_changed = wc.paused != config.paused + && WorkerConfig { paused: wc.paused, ..config.clone() } == **wc; + if **wc != config || has_dedicated { - if kill_if_change { + if kill_if_change && !only_pause_changed { if has_dedicated || wc.dedicated_worker != config.dedicated_worker || wc.dedicated_workers != config.dedicated_workers diff --git a/backend/tests/worker_group_pause.rs b/backend/tests/worker_group_pause.rs new file mode 100644 index 0000000000..b528bbfd77 --- /dev/null +++ b/backend/tests/worker_group_pause.rs @@ -0,0 +1,71 @@ +//! In its own test binary: it flips the process-wide `WORKER_CONFIG`, which would stall every +//! other worker test sharing the process. + +use futures::StreamExt; +use sqlx::{Pool, Postgres}; +use std::time::Duration; +use windmill_common::{ + jobs::{JobPayload, RawCode}, + scripts::ScriptLang, + worker::{Connection, WORKER_CONFIG}, +}; +use windmill_test_utils::*; + +fn set_paused(paused: bool) { + let mut wc = (**WORKER_CONFIG.load()).clone(); + wc.paused = paused; + WORKER_CONFIG.store(std::sync::Arc::new(wc)); +} + +#[sqlx::test(fixtures("base"))] +async fn paused_worker_leaves_jobs_queued_until_resumed(db: Pool) -> anyhow::Result<()> { + initialize_tracing().await; + let server = ApiServer::start(db.clone()).await?; + let port = server.addr.port(); + + set_paused(true); + let id = RunJob::from(JobPayload::Code(RawCode { + hash: None, + content: "echo done".to_string(), + path: None, + lock: None, + language: ScriptLang::Bash, + cache_ttl: None, + cache_ignore_s3_path: None, + dedicated_worker: None, + concurrency_settings: windmill_common::runnable_settings::ConcurrencySettings::default() + .into(), + debouncing_settings: windmill_common::runnable_settings::DebouncingSettings::default(), + modules: None, + tag: None, + })) + .push(&db) + .await; + + let mut completed = listen_for_completed_jobs(&db).await; + in_test_worker( + Connection::Sql(db.clone()), + async { + tokio::time::sleep(Duration::from_secs(3)).await; + let running = + sqlx::query_scalar::<_, bool>("SELECT running FROM v2_job_queue WHERE id = $1") + .bind(id) + .fetch_optional(&db) + .await + .unwrap(); + assert_eq!( + running, + Some(false), + "a paused worker must not pull the job" + ); + + set_paused(false); + while completed.next().await != Some(id) {} + }, + port, + ) + .await; + + assert!(completed_job(id, &db).await.success); + Ok(()) +} diff --git a/backend/windmill-api-configs/src/lib.rs b/backend/windmill-api-configs/src/lib.rs index 7598021f00..f1f4792e71 100644 --- a/backend/windmill-api-configs/src/lib.rs +++ b/backend/windmill-api-configs/src/lib.rs @@ -224,12 +224,13 @@ async fn update_config( #[cfg(not(feature = "enterprise"))] let config = if name.starts_with("worker__") { - // In CE, only allow setting worker_tags, cache_clear, init_bash, and native_mode + // In CE, only allow setting worker_tags, cache_clear, init_bash, native_mode and paused serde_json::json!({ "worker_tags": config.get("worker_tags"), "cache_clear": config.get("cache_clear"), "init_bash": config.get("init_bash"), - "native_mode": config.get("native_mode") + "native_mode": config.get("native_mode"), + "paused": config.get("paused") }) } else { config @@ -272,6 +273,18 @@ async fn update_config( } let mut tx = db.begin().await?; + let was_paused = if name.starts_with("worker__") { + sqlx::query_scalar!( + "SELECT COALESCE(config->'paused' = 'true'::jsonb, false) FROM config WHERE name = $1 FOR UPDATE", + &name + ) + .fetch_optional(&mut *tx) + .await? + .flatten() + .unwrap_or(false) + } else { + false + }; sqlx::query!( "INSERT INTO config (name, config) VALUES ($1, $2) ON CONFLICT (name) DO UPDATE SET config = EXCLUDED.config", &name, @@ -291,6 +304,17 @@ async fn update_config( ) .await?; tx.commit().await?; + + if name.starts_with("worker__") { + let paused = config.get("paused").and_then(|v| v.as_bool()) == Some(true); + if paused != was_paused { + windmill_common::feature_usage::log_feature_usage( + "worker_group", + "pause_toggle", + if paused { "pause" } else { "resume" }, + ); + } + } Ok(format!("Updated config {name}")) } diff --git a/backend/windmill-common/src/instance_config.rs b/backend/windmill-common/src/instance_config.rs index a4164cd2c5..700ba71df5 100644 --- a/backend/windmill-common/src/instance_config.rs +++ b/backend/windmill-common/src/instance_config.rs @@ -963,6 +963,9 @@ pub struct WorkerGroupConfig { pub autoscaling: Option, #[serde(skip_serializing_if = "Option::is_none")] pub native_mode: Option, + /// Workers of the group pull no new job while this is set; queued jobs wait. + #[serde(skip_serializing_if = "Option::is_none")] + pub paused: Option, /// Object store this group's dependency cache uses instead of the instance one. Same shape /// as the instance `object_store_cache_config`. #[serde(skip_serializing_if = "Option::is_none")] diff --git a/backend/windmill-common/src/worker.rs b/backend/windmill-common/src/worker.rs index e68b81e4de..e185d1d445 100644 --- a/backend/windmill-common/src/worker.rs +++ b/backend/windmill-common/src/worker.rs @@ -477,6 +477,7 @@ lazy_static::lazy_static! { env_vars: Default::default(), native_mode: false, object_store_cache_config: Default::default(), + paused: false, }); pub static ref WORKER_PULL_QUERIES: arc_swap::ArcSwap> = arc_swap::ArcSwap::from_pointee(vec![]); @@ -844,11 +845,14 @@ pub fn make_suspended_pull_query(tags: &[String]) -> String { } // pub async fn make_suspended pub async fn store_suspended_pull_query(wc: &WorkerConfig) { - if wc.worker_tags.len() == 0 { - tracing::error!("Empty tags in worker tags, skipping"); - return; - } - let query = make_suspended_pull_query(&wc.worker_tags); + // An empty tag list must clear the query: keeping the previous one would leave a reloaded + // worker pulling suspended jobs for tags it no longer listens to. + let query = if wc.worker_tags.is_empty() { + tracing::error!("Empty tags in worker tags, pulling no suspended jobs"); + String::new() + } else { + make_suspended_pull_query(&wc.worker_tags) + }; WORKER_SUSPENDED_PULL_QUERY.store(std::sync::Arc::new(query)); } @@ -922,6 +926,42 @@ pub async fn store_pull_query(wc: &WorkerConfig) { WORKER_PULL_QUERIES_FAIRNESS.store(std::sync::Arc::new(fairness_queries)); } +const WORKER_GROUP_PAUSED_CACHE_TTL: Duration = Duration::from_secs(10); + +lazy_static::lazy_static! { + static ref WORKER_GROUP_PAUSED_CACHE: quick_cache::sync::Cache = + quick_cache::sync::Cache::new(1000); +} + +/// Whether the config of `worker_group` is paused, as the server sees it. A worker that reads +/// its own config knows from `WORKER_CONFIG`; this is for the server deciding on behalf of +/// workers that do not, and is cached since they ask on every pull. +pub async fn is_worker_group_paused(db: &DB, worker_group: &str) -> bool { + if let Some((paused, at)) = WORKER_GROUP_PAUSED_CACHE.get(worker_group) { + if at.elapsed() < WORKER_GROUP_PAUSED_CACHE_TTL { + return paused; + } + } + let paused = match sqlx::query_scalar!( + "SELECT COALESCE(config->'paused' = 'true'::jsonb, false) FROM config WHERE name = $1", + format!("worker__{worker_group}") + ) + .fetch_optional(db) + .await + { + Ok(paused) => paused.flatten().unwrap_or(false), + Err(e) => { + tracing::error!("Could not read whether worker group {worker_group} is paused: {e:#}"); + return false; + } + }; + WORKER_GROUP_PAUSED_CACHE.insert( + worker_group.to_string(), + (paused, std::time::Instant::now()), + ); + paused +} + lazy_static::lazy_static! { pub static ref WINDMILL_DIR: String = { let dir = std::env::var("WINDMILL_DIR") @@ -2470,6 +2510,12 @@ pub async fn load_worker_config( .collect(); priority_tags_sorted.push(PriorityTags { priority: 0, tags: Vec::from_iter(all_tags_set) }); // push the tags that were not listed as high priority with a priority = 0 priority_tags_sorted.sort_by_key(|elt| Reverse(elt.priority)); // sort by priority DESC + + // The buckets come out of hash maps: without a fixed order two loads of the same + // config compare unequal, and a reload reads that as a config change. + for bucket in priority_tags_sorted.iter_mut() { + bucket.tags.sort(); + } } else { // if no priority is used, push all tags with a priority to 0 priority_tags_sorted.push(PriorityTags { priority: 0, tags: worker_tags.clone() }); @@ -2539,6 +2585,7 @@ pub async fn load_worker_config( env_vars: resolved_env_vars, native_mode, object_store_cache_config: config.object_store_cache_config, + paused: config.paused.unwrap_or(false), }) } @@ -2629,6 +2676,7 @@ pub struct WorkerConfigOpt { pub env_vars_allowlist: Option>, pub native_mode: Option, pub object_store_cache_config: Option, + pub paused: Option, } impl Default for WorkerConfigOpt { @@ -2648,6 +2696,7 @@ impl Default for WorkerConfigOpt { env_vars_allowlist: Default::default(), native_mode: Default::default(), object_store_cache_config: Default::default(), + paused: Default::default(), } } } @@ -2670,12 +2719,15 @@ pub struct WorkerConfig { /// in the group config. Raw JSON: `windmill-common` cannot depend on the object store crate /// that parses it, and comparing the raw value is what tells a reload the store changed. pub object_store_cache_config: Option, + /// The group pulls no job from the queue: its workers finish what they hold, keep pinging + /// and leave queued jobs for when it is resumed. + pub paused: bool, } impl std::fmt::Debug for WorkerConfig { fn fmt(&self, f: &mut std::fmt::Formatter<'_>) -> std::fmt::Result { - write!(f, "WorkerConfig {{ worker_tags: {:?}, priority_tags_sorted: {:?}, dedicated_worker: {:?}, dedicated_workers: {:?}, init_bash: {:?}, periodic_script_bash: {:?}, periodic_script_interval_seconds: {:?}, cache_clear: {:?}, additional_python_paths: {:?}, pip_local_dependencies: {:?}, env_vars: {:?}, native_mode: {:?}, object_store_cache_config: {} }}", - self.worker_tags, self.priority_tags_sorted, self.dedicated_worker, self.dedicated_workers, self.init_bash, self.periodic_script_bash, self.periodic_script_interval_seconds, self.cache_clear, self.additional_python_paths, self.pip_local_dependencies, self.env_vars.iter().map(|(k, v)| format!("{}: {}{} ({} chars)", k, &v[..3.min(v.len())], "***", v.len())).collect::>().join(", "), self.native_mode, + write!(f, "WorkerConfig {{ worker_tags: {:?}, priority_tags_sorted: {:?}, dedicated_worker: {:?}, dedicated_workers: {:?}, init_bash: {:?}, periodic_script_bash: {:?}, periodic_script_interval_seconds: {:?}, cache_clear: {:?}, additional_python_paths: {:?}, pip_local_dependencies: {:?}, env_vars: {:?}, native_mode: {:?}, paused: {:?}, object_store_cache_config: {} }}", + self.worker_tags, self.priority_tags_sorted, self.dedicated_worker, self.dedicated_workers, self.init_bash, self.periodic_script_bash, self.periodic_script_interval_seconds, self.cache_clear, self.additional_python_paths, self.pip_local_dependencies, self.env_vars.iter().map(|(k, v)| format!("{}: {}{} ({} chars)", k, &v[..3.min(v.len())], "***", v.len())).collect::>().join(", "), self.native_mode, self.paused, // holds bucket credentials self.object_store_cache_config.as_ref().map(|_| "***").unwrap_or("None")) } diff --git a/backend/windmill-worker/src/worker.rs b/backend/windmill-worker/src/worker.rs index 28d226ea3f..2acafa539f 100644 --- a/backend/windmill-worker/src/worker.rs +++ b/backend/windmill-worker/src/worker.rs @@ -3424,6 +3424,10 @@ pub async fn run_worker( tokio::time::sleep(Duration::from_millis(200)).await; continue; } + } else if WORKER_CONFIG.load().paused { + // Checked after the same-worker channel: a flow this worker already runs + // still needs it for its remaining same-worker steps. + Ok(None) } else { match &conn { Connection::Sql(db) => { diff --git a/frontend/src/lib/components/WorkerGroup.svelte b/frontend/src/lib/components/WorkerGroup.svelte index 65d00f9ba6..3b399a5a1e 100644 --- a/frontend/src/lib/components/WorkerGroup.svelte +++ b/frontend/src/lib/components/WorkerGroup.svelte @@ -104,6 +104,7 @@ autoscaling?: AutoscalingConfig native_mode?: boolean object_store_cache_config?: ObjectStoreConfig + paused?: boolean } = $state({}) function loadNConfig() { @@ -111,10 +112,9 @@ ? config.worker_tags != undefined || config.dedicated_worker != undefined || config.dedicated_workers != undefined - ? config - : { - worker_tags: [] - } + ? // a copy: editing the draft must not touch the saved config it is compared against + $state.snapshot(config) + : { ...$state.snapshot(config), worker_tags: [] } : { worker_tags: [] } @@ -212,6 +212,7 @@ periodic_script_interval_seconds?: number native_mode?: boolean object_store_cache_config?: ObjectStoreConfig + paused?: boolean } activeWorkers: number customTags: string[] | undefined @@ -268,8 +269,10 @@ if (!config && !nconfig) return false if (!config || !nconfig) return true - const cleaned1 = cleanValueProperties(config) - const cleaned2 = cleanValueProperties(nconfig) + // Compared without empty values: the draft is filled with empty defaults a saved + // config may lack, which are not an edit. + const cleaned1 = cleanWorkerGroupConfig(cleanValueProperties(config)) + const cleaned2 = cleanWorkerGroupConfig(cleanValueProperties(nconfig)) return ( orderedJsonStringify(replaceFalseWithUndefined(cleaned1)) !== @@ -298,6 +301,47 @@ let openDelete = $state(false) let openClean = $state(false) let openRestart = $state(false) + let pendingConfig: typeof nconfig | undefined = $state() + + // Mirrors `reload_worker_config` in backend/src/monitor.rs, which decides the restart. It + // compares the body that is sent rather than the draft, and only the fields a worker loads. + const RESTART_FIELDS = [ + 'dedicated_worker', + 'dedicated_workers', + 'init_bash', + 'periodic_script_bash', + 'periodic_script_interval_seconds', + 'native_mode' + ] as const + const OTHER_WORKER_FIELDS = [ + 'worker_tags', + 'priority_tags', + 'additional_python_paths', + 'pip_local_dependencies', + 'object_store_cache_config' + ] as const + function restartsWorkers(body: typeof nconfig): boolean { + if (activeWorkers === 0) return false + const saved: typeof nconfig = config ?? {} + const comparable = (c: typeof nconfig, k: keyof typeof nconfig) => + orderedJsonStringify(replaceFalseWithUndefined(cleanWorkerGroupConfig({ v: c[k] }))) + const changed = (k: keyof typeof nconfig) => comparable(saved, k) !== comparable(body, k) + const restartFieldChanged = RESTART_FIELDS.some(changed) + const onlyPauseChanged = + changed('paused') && + !restartFieldChanged && + !OTHER_WORKER_FIELDS.some(changed) && + !hasEnvVarChanges + const dedicated = + body.dedicated_worker != undefined || (body.dedicated_workers?.length ?? 0) > 0 + return !onlyPauseChanged && (dedicated || restartFieldChanged) + } + + async function saveConfig(body: typeof nconfig) { + await ConfigService.updateConfig({ name: 'worker__' + name, requestBody: body }) + sendUserToast('Configuration set') + dispatch('reload') + } // Compute hashed tags for display (actual tags used by the worker) let hashedDedicatedTags: Map = $state(new Map()) @@ -399,6 +443,31 @@ + { + pendingConfig = undefined + }} + on:confirmed={async () => { + const body = pendingConfig + pendingConfig = undefined + if (body) { + await saveConfig(body) + } + }} +> +
+ Applying these changes will restart the {pluralize(activeWorkers, 'worker')} of worker group '{name}'. + Workers finish their running job, shut down gracefully and are expected to be restarted by + their supervisor. + Pausing or resuming a worker group alone does not restart its workers. +
+ + {/if} + {#if nconfig !== undefined} +
+ + {/if} +
- Role - Privileges + + + + Role + Privileges + {#if showCoverage} On - - - - - {#each grantRows as grant (grantKey(grant))} - {@const revokeScope = revokeScopeOf(grant)} - {@const revocable = revocablePrivileges(grant, target)} - {@const blocked = blockingSources(grant, revocable)} - {@const uncovered = uncoveredCreators(grant, info.roles)} - - {grant.grantee} - {grant.privileges.join(', ')} - - {grantScopeLabel(grant)} - {#if blocked.length > 0} - - from {blocked.join(', ')} - - {/if} - {#if uncovered.length > 0} - - · not for what {uncovered.join(', ')} - {uncovered.length === 1 ? 'creates' : 'create'} - - {/if} + {/if} + + + + + {#each shownGrantRows as grant (grantKey(grant))} + {@const revokeScope = revokeScopeOf(grant)} + {@const revocable = revocablePrivileges(grant, target)} + {@const blocked = blockingSources(grant, revocable)} + {@const uncovered = uncoveredCreators(grant, info.roles)} + {@const unrevocable = unrevocableReason(grant, revokeScope, revocable, blocked)} + + {grant.grantee} + +
+ {#each grant.privileges as privilege (privilege)} + {@render tag(privilege)} + {/each} +
+ {#if blocked.length > 0 || uncovered.length > 0} +
+ {[ + blocked.length > 0 && `granted by ${blocked.join(', ')}`, + uncovered.length > 0 && + `not for what ${uncovered.join(', ')} ${uncovered.length === 1 ? 'creates' : 'create'}: a default privilege only covers the roles it was granted for` + ] + .filter(Boolean) + .join(' · ')} +
+ {/if} + + {#if showCoverage} + + {grantCoverage(grant, target) ?? targetLabel} - - - {#if info.editable && revokeScope && revocable.length > 0 && blocked.length === 0 && info.roles.includes(grant.grantee) && grant.grantee !== ADMIN_ROLE} + {/if} + + {#if info.editable} + {#snippet revokeButton()} - - {/if} + {/if} + + + {:else} + + + {grantRows.length === 0 ? 'No grants yet.' : 'No grant matches the filters.'} + + + {/each} + {#if info.editable} + + + + {#snippet grantBuilder()} + + confirm( + { type: 'grant', role, privileges, scope }, + `Granted ${privileges.join(', ')} to ${role}` + )} + /> + {/snippet} + {@render withDisabledReason(grantBuilder, 'w-full')} + + + {/if} + + {/if} diff --git a/frontend/src/lib/components/datatableAcl/PgGrantBuilder.svelte b/frontend/src/lib/components/datatableAcl/PgGrantBuilder.svelte index 5e5119abb6..745c1a1db5 100644 --- a/frontend/src/lib/components/datatableAcl/PgGrantBuilder.svelte +++ b/frontend/src/lib/components/datatableAcl/PgGrantBuilder.svelte @@ -1,17 +1,18 @@ -
-
- GRANT - ({ value: p, label: p }))} - placeholder="privileges" - {disabled} - size="sm" - class="min-w-48" - /> - ON + +
+ GRANT + ({ value: p, label: p }))} + placeholder="privileges" + {disabled} + size="md" + class="min-w-0 flex-[4]" + /> + + {#if scopes.length > 1} + ON ({ value: r, label: r }))} - placeholder="role" - {disabled} - size="sm" - class="w-40" - /> - -
- {#if statement} - 
{statement}
{/if} + TO +
- {#each roles as role (roleKey(role))} + {#each roles as role (role.id)} {@const isAdmin = role.id === ADMIN_DATATABLE_ROLE} @@ -339,23 +409,6 @@ no longer defined on {clusterName} - {:else if role.id === undefined} - - {#if $superadmin} -
- Create it on {clusterName} to use it here. - -
- {:else} - Only a superadmin can create it on {clusterName}. - {/if} - {/if} @@ -371,11 +424,11 @@
{ - if (role.id !== undefined) defaultRoleId = role.id + defaultRoleId = role.id }} />
@@ -388,7 +441,7 @@ {/each} {#if editable} - +
\` (in a DuckDB node the annotation uses SQL \`--\` comment syntax; write the body as a bare \`SELECT\` and let the runtime do the write). DuckLake is the default lakehouse store for pipelines and is the shape the pipeline editor is built around, so prefer it unless the work specifically calls for something else: - \`postgresql\` / data tables — only for row-level, OLTP-style mutations against an existing Postgres data table (frequent single-row upserts/updates, transactional reads that an app queries live). -- \`bun\` / \`python3\` — only for non-tabular work that doesn't map to SQL: calling an external API, wrangling files, arbitrary glue. When such a node still produces tabular data for downstream steps, land it in DuckLake (write it with the wmill SDK / ducklake helpers) rather than inventing a parallel store. +- \`bun\` / \`python3\` — only for work that doesn't map to SQL: calling an external API, wrangling files, arbitrary glue. When such a node produces tabular data for downstream steps, write it **straight into DuckLake** (or a data table) from the same script — see "Ingesting from Python / TypeScript" below — rather than inventing a parallel store. Do not spread a pipeline across postgres, S3, and DuckLake when one DuckLake lake would do; a consistent DuckLake lakehouse is the goal. +## Ingesting from Python / TypeScript + +A node that fetches data in code (an API, a SaaS export, a scraper) writes the rows **directly** into their DuckLake table with \`wmill.ducklake()\`, or into a data table with \`wmill.datatable()\`. DuckLake already stores every table as parquet files in the workspace object storage, so **never stage the raw payload first** — no intermediate JSON / CSV / parquet file in S3 and no second "load the raw file" node. One ingestion node, one table. + +Pass the rows as a query argument (a list of dicts / array of objects is sent as JSON) and let SQL unnest them; declare the column types so the table gets a real schema: + +\`\`\`python +# pipeline +# on schedule +import wmill + +def main(): + rows = fetch_charges() # list[dict] + lake = wmill.ducklake() + lake.query(""" + CREATE OR REPLACE TABLE stripe_charges AS + SELECT unnest(from_json($rows, '[{"id":"VARCHAR","amount":"BIGINT","created":"BIGINT"}]'), recursive := true) + """, rows=rows).fetch() +\`\`\` + +\`\`\`ts +// pipeline +// on schedule +import * as wmill from "windmill-client" + +export async function main() { + const rows = await fetchCharges() + const lake = wmill.ducklake() + await lake\`CREATE OR REPLACE TABLE stripe_charges AS + SELECT unnest(from_json(\${rows}, '[{"id":"VARCHAR","amount":"BIGINT","created":"BIGINT"}]'), recursive := true)\`.fetch() +} +\`\`\` + +- Use \`INSERT INTO
SELECT ...\` instead of \`CREATE OR REPLACE\` to append (an incremental pull), with a one-time \`CREATE TABLE IF NOT EXISTS\` first. +- Assign the client to a variable (\`lake = wmill.ducklake()\`) and keep the SQL a **string literal** (Python) or a template without \`sql.raw\` (TS): that is what lets the graph record the node's write to \`ducklake://main/
\`. A chained \`wmill.ducklake().query(...)\` or SQL built in a variable records no output, so the downstream edge never forms. +- \`wmill.ducklake("")\` targets a non-default catalog; \`wmill.datatable("")\` writes a Postgres data table the same way (Python \`db.query(sql, *args)\` with \`$1\` placeholders, TS the same template form) — use it only when the data belongs in Postgres (see above). +- The downstream node triggers on the table itself: \`-- on ducklake://main/stripe_charges\`. + ## Storage prerequisites A DuckLake pipeline only runs once the workspace has **object storage** (S3 / Azure Blob / GCS) **and a DuckLake catalog** configured — DuckLake tables and \`s3://\` assets can't be materialized or read without it. Check which DuckLake catalogs the workspace has before you build. @@ -7962,7 +8000,7 @@ The key must be a **string literal** — the graph parser is static and cannot f ## Materialize (the managed output) -> **A MANAGED \`// materialize\` is DuckDB-only**, and its target must be a DuckLake table (\`ducklake:///
\`). Deploy **rejects** a \`ducklake://\` \`// materialize\` on any other language (\`python3\`, \`bun\`, \`postgresql\`). For a non-DuckDB node writing the lake, do **not** use \`// materialize\` — write the output via the SDK (\`wmill.writeS3File(...)\`, ducklake helpers, …) and let it be inferred. Use \`duckdb\` when a node should materialize a DuckLake table. +> **A MANAGED \`// materialize\` is DuckDB-only**, and its target must be a DuckLake table (\`ducklake:///
\`). Deploy **rejects** a \`ducklake://\` \`// materialize\` on any other language (\`python3\`, \`bun\`, \`postgresql\`). For a non-DuckDB node writing the lake, do **not** use \`// materialize\` — write the table itself with \`wmill.ducklake()\` (see "Ingesting from Python / TypeScript") and let the output be inferred. Use \`duckdb\` when a node should materialize a DuckLake table. > > The one target ANY language may declare (except a dbt script, whose writes come from its manifest) is a **warehouse relation**: \`// materialize manual dbt:////\`, where \`\` is a warehouse the workspace configures under Settings → dbt. \`manual\` is the only mode it has — nothing generates warehouse DDL, so the node issues its own write (a postgresql \`CREATE TABLE\` / \`INSERT\`, an SDK load, …) and the annotation records the outcome. Use it on an ingestion node whose output a dbt project reads as a \`source\`: the declared relation and the dbt model land on ONE graph node, and a downstream \`// on dbt:////\` fires when the ingestion node completes. diff --git a/frontend/src/lib/components/AutosaveIndicator.svelte b/frontend/src/lib/components/AutosaveIndicator.svelte index 76dc030c58..1e318ed9b2 100644 --- a/frontend/src/lib/components/AutosaveIndicator.svelte +++ b/frontend/src/lib/components/AutosaveIndicator.svelte @@ -142,7 +142,13 @@ let hintTimer: ReturnType | undefined const kindLabel = $derived( - itemKind === 'flow' ? 'flow' : itemKind === 'app' || itemKind === 'raw_app' ? 'app' : 'script' + itemKind === 'flow' + ? 'flow' + : itemKind === 'app' || itemKind === 'raw_app' + ? 'app' + : itemKind === 'data_pipeline' + ? 'pipeline' + : 'script' ) // Each false → true transition fires a hint (others > loaded). Seeded to diff --git a/frontend/src/lib/components/CronBuilder.svelte b/frontend/src/lib/components/CronBuilder.svelte index bcf8508c12..3bceabb417 100644 --- a/frontend/src/lib/components/CronBuilder.svelte +++ b/frontend/src/lib/components/CronBuilder.svelte @@ -15,7 +15,7 @@ contentClasses="p-4" > {#snippet trigger()} - {/snippet} diff --git a/frontend/src/lib/components/DatatablePicker.svelte b/frontend/src/lib/components/DatatablePicker.svelte index 53617acf36..17ad6f3361 100644 --- a/frontend/src/lib/components/DatatablePicker.svelte +++ b/frontend/src/lib/components/DatatablePicker.svelte @@ -17,6 +17,9 @@ selectInputClass?: string class?: string onClear?: () => void + /** Size the input to its content, like Path's folder picker. */ + useContentEditable?: boolean + RightIcon?: any } let { @@ -27,7 +30,9 @@ placeholder = undefined, selectInputClass = '', class: className = '', - onClear = undefined + onClear = undefined, + useContentEditable = false, + RightIcon = undefined }: Props = $props() let datatables = usePromise(() => @@ -47,6 +52,8 @@ {placeholder} inputClass={selectInputClass} {onClear} + {useContentEditable} + {RightIcon} /> {#if showSchemaExplorer && value && assetCanBeExplored({ kind: 'datatable', path: value })} diff --git a/frontend/src/lib/components/DucklakePicker.svelte b/frontend/src/lib/components/DucklakePicker.svelte index 3a6f2bf739..d6ed4d0cdf 100644 --- a/frontend/src/lib/components/DucklakePicker.svelte +++ b/frontend/src/lib/components/DucklakePicker.svelte @@ -17,6 +17,9 @@ selectInputClass?: string class?: string onClear?: () => void + /** Size the input to its content, like Path's folder picker. */ + useContentEditable?: boolean + RightIcon?: any } let { @@ -27,7 +30,9 @@ placeholder = undefined, selectInputClass = '', class: className = '', - onClear = undefined + onClear = undefined, + useContentEditable = false, + RightIcon = undefined }: Props = $props() let ducklakes = usePromise(() => @@ -45,6 +50,8 @@ {placeholder} inputClass={selectInputClass} {onClear} + {useContentEditable} + {RightIcon} /> {#if showSchemaExplorer && value && assetCanBeExplored({ kind: 'ducklake', path: value })} diff --git a/frontend/src/lib/components/Editor.svelte b/frontend/src/lib/components/Editor.svelte index f9df8adcef..03bf5ce87e 100644 --- a/frontend/src/lib/components/Editor.svelte +++ b/frontend/src/lib/components/Editor.svelte @@ -1523,6 +1523,9 @@ } catch (e) { console.log('error initializing services', e) } + // Unmounted while the services loaded: the container is detached, and + // creating the editor on it throws. + if (destroyed || !divEl?.isConnected) return // vscode.languages.registerDefinitionProvider('*', { // provideDefinition(document, position, token) { diff --git a/frontend/src/lib/components/ScriptEditor.svelte b/frontend/src/lib/components/ScriptEditor.svelte index 8990f70ae5..8e60d40f72 100644 --- a/frontend/src/lib/components/ScriptEditor.svelte +++ b/frontend/src/lib/components/ScriptEditor.svelte @@ -2101,43 +2101,15 @@ {/if} {#if customUi?.previewPanel?.hideArgs} - -
- {#if testJob?.id && testJob.type === 'CompletedJob' && opWs} - -
- - {testJob.id.slice(0, 8)}… ↗ - - -
- {/if} -
+ +
+ +
+
{#if testIsLoading} {@render cancelTestButton('sm', 'shadow-md')} {:else if (customUi?.previewPanel?.downstreamSubscribers ?? 0) > 0 || customUi?.previewPanel?.onBoundedRun} @@ -2271,6 +2243,31 @@ {@render runTestButton('sm', 'shadow-md')} {/if}
+ {#if testJob?.id && testJob.type === 'CompletedJob' && opWs} + +
+ + {testJob.id.slice(0, 8)}… ↗ + + +
+ {/if} +
{#if customUi?.previewPanel?.argsAboveLogs && schema?.properties && Object.keys(schema.properties).length > 0}
string | undefined /** Header variant: no path line (the host shows it) and a lighter summary. */ compact?: boolean /** Rendered inside the trigger in place of the summary, for a host that hangs a second copy @@ -51,6 +58,7 @@ editable = false, onSaved, kind = 'flow', + saveOverride = undefined, compact = false, label, triggerClass = 'block min-w-0 max-w-full px-1 py-0.5 rounded text-left cursor-pointer hover:bg-surface-hover transition-colors', @@ -67,7 +75,9 @@ let popoverOpen = $state(false) // Resolved before the popover opens, not on opening it: the path field only exists for an owner, // and `openFocus` looks for it in the same flush the popover renders in. - const own = $derived(isOwner(path ?? '', actingUser, $operatingWorkspace)) + const own = $derived( + saveOverride !== undefined || isOwner(path ?? '', actingUser, $operatingWorkspace) + ) let onBehalfOfEmail = $state(undefined) let summaryInput: ReturnType | undefined = $state() let labelsDirty = $state(false) @@ -101,6 +111,17 @@ async function save(close: () => void) { const initialPath = path ?? '' const newPath = own ? editPath : initialPath + if (saveOverride) { + const error = saveOverride({ path: newPath, summary: editSummary, labels }) + if (error) { + sendUserToast(error, true) + return + } + labelsDirty = false + close() + onSaved?.(newPath) + return + } try { await updateItemPathAndSummary({ diff --git a/frontend/src/lib/components/assets/AssetGraph/AddDataSourceMenu.svelte b/frontend/src/lib/components/assets/AssetGraph/AddDataSourceMenu.svelte new file mode 100644 index 0000000000..49a222148b --- /dev/null +++ b/frontend/src/lib/components/assets/AssetGraph/AddDataSourceMenu.svelte @@ -0,0 +1,150 @@ + + + + diff --git a/frontend/src/lib/components/assets/AssetGraph/AddDownstreamMenu.svelte b/frontend/src/lib/components/assets/AssetGraph/AddDownstreamMenu.svelte new file mode 100644 index 0000000000..2a54fe11d4 --- /dev/null +++ b/frontend/src/lib/components/assets/AssetGraph/AddDownstreamMenu.svelte @@ -0,0 +1,73 @@ + + + + + + diff --git a/frontend/src/lib/components/assets/AssetGraph/AddDownstreamPill.svelte b/frontend/src/lib/components/assets/AssetGraph/AddDownstreamPill.svelte new file mode 100644 index 0000000000..8ebd24455c --- /dev/null +++ b/frontend/src/lib/components/assets/AssetGraph/AddDownstreamPill.svelte @@ -0,0 +1,23 @@ + + + + + + + Add downstream step + + diff --git a/frontend/src/lib/components/assets/AssetGraph/AddNode.svelte b/frontend/src/lib/components/assets/AssetGraph/AddNode.svelte index 880abb685a..57a31e34d8 100644 --- a/frontend/src/lib/components/assets/AssetGraph/AddNode.svelte +++ b/frontend/src/lib/components/assets/AssetGraph/AddNode.svelte @@ -1,145 +1,36 @@ - - {#snippet trigger()} - - - {/snippet} - + +
+ + {#snippet trigger()} + + + {/snippet} + +
diff --git a/frontend/src/lib/components/assets/AssetGraph/AssetGraphCanvas.svelte b/frontend/src/lib/components/assets/AssetGraph/AssetGraphCanvas.svelte index 27f6ce6be7..87b085593c 100644 --- a/frontend/src/lib/components/assets/AssetGraph/AssetGraphCanvas.svelte +++ b/frontend/src/lib/components/assets/AssetGraph/AssetGraphCanvas.svelte @@ -1,8 +1,11 @@ -
+
onNodePointerEnter(node.id)} + onnodepointerleave={onNodePointerLeave} + onedgepointerenter={onEdgeEnter} + onedgepointerleave={onEdgeLeave} --background-color={false} >
- + + {#if assetsOnlyToggle} + + { + assetsOnly = !e.detail + if (assetsOnlyFolder != undefined) setAssetsOnlyFolder(assetsOnlyFolder, assetsOnly) + }} + /> + {#if withoutPassive.dropped > 0} + { + showPassiveReads = e.detail + try { + localStorage.setItem(SHOW_PASSIVE_READS_KEY, String(e.detail)) + } catch {} + }} + /> + {/if} + + {/if} {#if showMinimap} + +{/if} + +{#if scheduleWizard} + +{/if} + +{#if onAddPipelineScript} + +{/if} +