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* feat: adopt directory-based docs versioning with Edge channel Switch docs.crewai.com from navigation-only versioning (every version selector entry rendered the same docs/<lang>/* source files) to Mintlify's directory-based versioning so each version selector entry renders its own snapshot. Add an "Edge" channel under docs/edge/<lang>/* that always reflects main HEAD for unreleased work, eliminating pre-release leakage onto frozen release labels. External links to canonical /<lang>/* URLs are preserved via wildcard redirects that always land on the current default version. Layout: - docs/edge/<lang>/* rolling source (you edit here) - docs/edge/enterprise-api.*.yaml - docs/v<X.Y.Z>/<lang>/* frozen, immutable snapshots - docs/v<X.Y.Z>/enterprise-api.*.yaml - docs/images/ shared, append-only - docs/docs.json nav + redirects URLs follow the Mintlify-idiomatic shape: /edge/<lang>/<page> for Edge, /v<X.Y.Z>/<lang>/<page> for every frozen snapshot. The wildcard redirects /<lang>/:slug* -> /<default>/<lang>/:slug* keep stale links working, and every freeze rewrites them (plus all per-section/per-page redirects) so destinations always resolve to the current default without depending on a second redirect hop. Release flow integration (devtools release): - New module crewai_devtools.docs_versioning.freeze() materialises docs/v<X.Y.Z>/ from docs/edge/, rewrites openapi: refs inside the snapshot, inserts the version into every language block in docs.json, and refreshes all redirect destinations. - _update_docs_and_create_pr() in cli.py now calls that freeze during Phase 2 of devtools release. Edge changelogs are updated first (so the snapshot freeze picks them up), then the snapshot is staged alongside docs.json, branched as docs/freeze-v<X.Y.Z>, and the PR is titled [docs-freeze] docs: snapshot and changelog for v<X.Y.Z> — the title prefix the new CI guard reads. - The PR still gates tag, GitHub release, PyPI publish, and the enterprise release as before; no new PRs are added. - Pre-releases (1.X.YaN, 1.X.YbN, ...) skip the snapshot — they ride Edge — and the docs PR title omits the [docs-freeze] prefix. - docs_check (AI-generated docs scaffolding) writes to docs/edge/<lang>/* so newly-generated unreleased docs land in Edge and never accidentally touch a frozen snapshot. Migration scripts (one-shot): - scripts/docs/freeze_historical_versions.py reconstructs all 16 historical snapshots (v1.10.0 .. v1.14.7) from git tags via git archive | tar, rewriting openapi: MDX refs so each snapshot reads its own enterprise-api YAML rather than the live one. - scripts/docs/prefix_version_paths.py one-shot-migrates docs.json: rewrites every page path in 16 versioned blocks to point under docs/v<X.Y.Z>/, inserts a new Edge entry per language, tags v1.14.7 as Latest (default), prunes pages whose target file doesn't exist in the snapshot (e.g. docs/ar/ didn't exist before v1.12.0), and writes the wildcard + per-section redirects. - scripts/docs/freeze_current_edge.py is now a thin CLI wrapper around docs_versioning.freeze for manual one-off freezes (e.g. retroactively snapshotting a forgotten release). CI guards (.github/workflows/docs-snapshots.yml): - Frozen snapshots under docs/v[0-9]*/ are immutable; only PRs whose title contains [docs-freeze] (i.e. release-cut PRs generated by devtools release or the manual wrapper) may modify them. - Images under docs/images/ are append-only since snapshots share a single image directory. Deleting or renaming an image breaks every historical snapshot that still references it. Restored docs/images/crewai-otel-export.png from PR #3673; it was deleted in PR #4908 but v1.10.0 / v1.10.1 snapshots still reference it. Restoring instead of editing the snapshots preserves historical rendering fidelity and validates the new append-only rule retroactively. Tests: - lib/devtools/tests/test_docs_versioning.py covers the freeze: file copy, openapi rewrite, version insertion, default demotion, redirect upserts, per-section redirect rewriting, idempotency, and invalid inputs. Verified locally with mintlify broken-links: 0 broken links across the full site (Edge + 16 frozen versions, 4 locales). AGENTS.md (repo root) is the contributor guide for the new model; RELEASING.md is the release-cut runbook; README's Contribution section links to both. Co-authored-by: Cursor <cursoragent@cursor.com> * style: resolve linter issues --------- Co-authored-by: Cursor <cursoragent@cursor.com>
179 lines
4.8 KiB
Plaintext
179 lines
4.8 KiB
Plaintext
---
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title: "Kickoff Crew"
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description: "Kickoff a Crew on CrewAI AMP"
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icon: "flag-checkered"
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mode: "wide"
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---
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## Overview
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Once you've deployed your crew to the CrewAI AMP platform, you can kickoff executions through the web interface or the API. This guide covers both approaches.
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## Method 1: Using the Web Interface
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### Step 1: Navigate to Your Deployed Crew
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1. Log in to [CrewAI AMP](https://app.crewai.com)
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2. Click on the crew name from your projects list
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3. You'll be taken to the crew's detail page
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<Frame></Frame>
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### Step 2: Initiate Execution
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From your crew's detail page, you have two options to kickoff an execution:
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#### Option A: Quick Kickoff
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1. Click the `Kickoff` link in the Test Endpoints section
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2. Enter the required input parameters for your crew in the JSON editor
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3. Click the `Send Request` button
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<Frame></Frame>
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#### Option B: Using the Visual Interface
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1. Click the `Run` tab in the crew detail page
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2. Enter the required inputs in the form fields
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3. Click the `Run Crew` button
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<Frame></Frame>
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### Step 3: Monitor Execution Progress
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After initiating the execution:
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1. You'll receive a response containing a `kickoff_id` - **copy this ID**
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2. This ID is essential for tracking your execution
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<Frame></Frame>
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### Step 4: Check Execution Status
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To monitor the progress of your execution:
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1. Click the "Status" endpoint in the Test Endpoints section
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2. Paste the `kickoff_id` into the designated field
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3. Click the "Get Status" button
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<Frame></Frame>
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The status response will show:
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- Current execution state (`running`, `completed`, etc.)
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- Details about which tasks are in progress
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- Any outputs produced so far
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### Step 5: View Final Results
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Once execution is complete:
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1. The status will change to `completed`
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2. You can view the full execution results and outputs
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3. For a more detailed view, check the `Executions` tab in the crew detail page
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## Method 2: Using the API
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You can also kickoff crews programmatically using the CrewAI AMP REST API.
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### Authentication
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All API requests require a bearer token for authentication:
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```bash
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curl -H "Authorization: Bearer YOUR_CREW_TOKEN" https://your-crew-url.crewai.com
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```
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Your bearer token is available on the Status tab of your crew's detail page.
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### Checking Crew Health
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Before executing operations, you can verify that your crew is running properly:
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```bash
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curl -H "Authorization: Bearer YOUR_CREW_TOKEN" https://your-crew-url.crewai.com
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```
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A successful response will return a message indicating the crew is operational:
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```
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Healthy%
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```
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### Step 1: Retrieve Required Inputs
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First, determine what inputs your crew requires:
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```bash
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curl -X GET \
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-H "Authorization: Bearer YOUR_CREW_TOKEN" \
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https://your-crew-url.crewai.com/inputs
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```
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The response will be a JSON object containing an array of required input parameters, for example:
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```json
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{ "inputs": ["topic", "current_year"] }
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```
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This example shows that this particular crew requires two inputs: `topic` and `current_year`.
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### Step 2: Kickoff Execution
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Initiate execution by providing the required inputs:
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```bash
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curl -X POST \
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-H "Content-Type: application/json" \
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-H "Authorization: Bearer YOUR_CREW_TOKEN" \
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-d '{"inputs": {"topic": "AI Agent Frameworks", "current_year": "2025"}}' \
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https://your-crew-url.crewai.com/kickoff
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```
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The response will include a `kickoff_id` that you'll need for tracking:
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```json
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{ "kickoff_id": "abcd1234-5678-90ef-ghij-klmnopqrstuv" }
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```
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### Step 3: Check Execution Status
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Monitor the execution progress using the kickoff_id:
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```bash
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curl -X GET \
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-H "Authorization: Bearer YOUR_CREW_TOKEN" \
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https://your-crew-url.crewai.com/status/abcd1234-5678-90ef-ghij-klmnopqrstuv
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```
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## Handling Executions
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### Long-Running Executions
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For executions that may take a long time:
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1. Consider implementing a polling mechanism to check status periodically
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2. Use webhooks (if available) for notification when execution completes
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3. Implement error handling for potential timeouts
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### Execution Context
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The execution context includes:
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- Inputs provided at kickoff
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- Environment variables configured during deployment
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- Any state maintained between tasks
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### Debugging Failed Executions
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If an execution fails:
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1. Check the "Executions" tab for detailed logs
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2. Review the "Traces" tab for step-by-step execution details
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3. Look for LLM responses and tool usage in the trace details
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<Card title="Need Help?" icon="headset" href="mailto:support@crewai.com">
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Contact our support team for assistance with execution issues or questions
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about the Enterprise platform.
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</Card>
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