Files
crewAI/docs/edge/en/enterprise/guides/kickoff-crew.mdx
Lucas Gomide a237ebabba feat: adopt directory-based docs versioning with Edge channel (#6202)
* 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>
2026-06-17 11:56:59 -04:00

179 lines
4.8 KiB
Plaintext

---
title: "Kickoff Crew"
description: "Kickoff a Crew on CrewAI AMP"
icon: "flag-checkered"
mode: "wide"
---
## Overview
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.
## Method 1: Using the Web Interface
### Step 1: Navigate to Your Deployed Crew
1. Log in to [CrewAI AMP](https://app.crewai.com)
2. Click on the crew name from your projects list
3. You'll be taken to the crew's detail page
<Frame>![Crew Dashboard](/images/enterprise/crew-dashboard.png)</Frame>
### Step 2: Initiate Execution
From your crew's detail page, you have two options to kickoff an execution:
#### Option A: Quick Kickoff
1. Click the `Kickoff` link in the Test Endpoints section
2. Enter the required input parameters for your crew in the JSON editor
3. Click the `Send Request` button
<Frame>![Kickoff Endpoint](/images/enterprise/kickoff-endpoint.png)</Frame>
#### Option B: Using the Visual Interface
1. Click the `Run` tab in the crew detail page
2. Enter the required inputs in the form fields
3. Click the `Run Crew` button
<Frame>![Run Crew](/images/enterprise/run-crew.png)</Frame>
### Step 3: Monitor Execution Progress
After initiating the execution:
1. You'll receive a response containing a `kickoff_id` - **copy this ID**
2. This ID is essential for tracking your execution
<Frame>![Copy Task ID](/images/enterprise/copy-task-id.png)</Frame>
### Step 4: Check Execution Status
To monitor the progress of your execution:
1. Click the "Status" endpoint in the Test Endpoints section
2. Paste the `kickoff_id` into the designated field
3. Click the "Get Status" button
<Frame>![Get Status](/images/enterprise/get-status.png)</Frame>
The status response will show:
- Current execution state (`running`, `completed`, etc.)
- Details about which tasks are in progress
- Any outputs produced so far
### Step 5: View Final Results
Once execution is complete:
1. The status will change to `completed`
2. You can view the full execution results and outputs
3. For a more detailed view, check the `Executions` tab in the crew detail page
## Method 2: Using the API
You can also kickoff crews programmatically using the CrewAI AMP REST API.
### Authentication
All API requests require a bearer token for authentication:
```bash
curl -H "Authorization: Bearer YOUR_CREW_TOKEN" https://your-crew-url.crewai.com
```
Your bearer token is available on the Status tab of your crew's detail page.
### Checking Crew Health
Before executing operations, you can verify that your crew is running properly:
```bash
curl -H "Authorization: Bearer YOUR_CREW_TOKEN" https://your-crew-url.crewai.com
```
A successful response will return a message indicating the crew is operational:
```
Healthy%
```
### Step 1: Retrieve Required Inputs
First, determine what inputs your crew requires:
```bash
curl -X GET \
-H "Authorization: Bearer YOUR_CREW_TOKEN" \
https://your-crew-url.crewai.com/inputs
```
The response will be a JSON object containing an array of required input parameters, for example:
```json
{ "inputs": ["topic", "current_year"] }
```
This example shows that this particular crew requires two inputs: `topic` and `current_year`.
### Step 2: Kickoff Execution
Initiate execution by providing the required inputs:
```bash
curl -X POST \
-H "Content-Type: application/json" \
-H "Authorization: Bearer YOUR_CREW_TOKEN" \
-d '{"inputs": {"topic": "AI Agent Frameworks", "current_year": "2025"}}' \
https://your-crew-url.crewai.com/kickoff
```
The response will include a `kickoff_id` that you'll need for tracking:
```json
{ "kickoff_id": "abcd1234-5678-90ef-ghij-klmnopqrstuv" }
```
### Step 3: Check Execution Status
Monitor the execution progress using the kickoff_id:
```bash
curl -X GET \
-H "Authorization: Bearer YOUR_CREW_TOKEN" \
https://your-crew-url.crewai.com/status/abcd1234-5678-90ef-ghij-klmnopqrstuv
```
## Handling Executions
### Long-Running Executions
For executions that may take a long time:
1. Consider implementing a polling mechanism to check status periodically
2. Use webhooks (if available) for notification when execution completes
3. Implement error handling for potential timeouts
### Execution Context
The execution context includes:
- Inputs provided at kickoff
- Environment variables configured during deployment
- Any state maintained between tasks
### Debugging Failed Executions
If an execution fails:
1. Check the "Executions" tab for detailed logs
2. Review the "Traces" tab for step-by-step execution details
3. Look for LLM responses and tool usage in the trace details
<Card title="Need Help?" icon="headset" href="mailto:support@crewai.com">
Contact our support team for assistance with execution issues or questions
about the Enterprise platform.
</Card>