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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>
158 lines
8.4 KiB
Plaintext
158 lines
8.4 KiB
Plaintext
---
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title: "Webhook Automation"
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description: "Automate CrewAI AMP workflows using webhooks with platforms like ActivePieces, Zapier, and Make.com"
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icon: "webhook"
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mode: "wide"
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---
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CrewAI AMP allows you to automate your workflow using webhooks. This article will guide you through the process of setting up and using webhooks to kickoff your crew execution, with a focus on integration with ActivePieces, a workflow automation platform similar to Zapier and Make.com.
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## Setting Up Webhooks
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<Steps>
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<Step title="Accessing the Kickoff Interface">
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- Navigate to the CrewAI AMP dashboard
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- Look for the `/kickoff` section, which is used to start the crew execution
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<Frame>
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<img src="/images/enterprise/kickoff-interface.png" alt="Kickoff Interface" />
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</Frame>
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</Step>
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<Step title="Configuring the JSON Content">
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In the JSON Content section, you'll need to provide the following information:
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- **inputs**: A JSON object containing:
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- `company`: The name of the company (e.g., "tesla")
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- `product_name`: The name of the product (e.g., "crewai")
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- `form_response`: The type of response (e.g., "financial")
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- `icp_description`: A brief description of the Ideal Customer Profile
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- `product_description`: A short description of the product
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- `taskWebhookUrl`, `stepWebhookUrl`, `crewWebhookUrl`: URLs for various webhook endpoints (ActivePieces, Zapier, Make.com or another compatible platform)
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</Step>
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<Step title="Integrating with ActivePieces">
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In this example we will be using ActivePieces. You can use other platforms such as Zapier and Make.com
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To integrate with ActivePieces:
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1. Set up a new flow in ActivePieces
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2. Add a trigger (e.g., `Every Day` schedule)
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<Frame>
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<img src="/images/enterprise/activepieces-trigger.png" alt="ActivePieces Trigger" />
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</Frame>
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3. Add an HTTP action step
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- Set the action to `Send HTTP request`
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- Use `POST` as the method
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- Set the URL to your CrewAI AMP kickoff endpoint
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- Add necessary headers (e.g., `Bearer Token`)
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<Frame>
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<img src="/images/enterprise/activepieces-headers.png" alt="ActivePieces Headers" />
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</Frame>
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- In the body, include the JSON content as configured in step 2
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<Frame>
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<img src="/images/enterprise/activepieces-body.png" alt="ActivePieces Body" />
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</Frame>
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- The crew will then kickoff at the pre-defined time.
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</Step>
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<Step title="Setting Up the Webhook">
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1. Create a new flow in ActivePieces and name it
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<Frame>
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<img src="/images/enterprise/activepieces-flow.png" alt="ActivePieces Flow" />
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</Frame>
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2. Add a webhook step as the trigger:
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- Select `Catch Webhook` as the trigger type
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- This will generate a unique URL that will receive HTTP requests and trigger your flow
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<Frame>
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<img src="/images/enterprise/activepieces-webhook.png" alt="ActivePieces Webhook" />
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</Frame>
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- Configure the email to use crew webhook body text
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<Frame>
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<img src="/images/enterprise/activepieces-email.png" alt="ActivePieces Email" />
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</Frame>
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</Step>
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</Steps>
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## Webhook Output Examples
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**Note:** Any `meta` object provided in your kickoff request will be included in all webhook payloads, allowing you to track requests and maintain context across the entire crew execution lifecycle.
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<Tabs>
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<Tab title="Step Webhook">
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`stepWebhookUrl` - Callback that will be executed upon each agent inner thought
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```json
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{
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"prompt": "Research the financial industry for potential AI solutions",
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"thought": "I need to conduct preliminary research on the financial industry",
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"tool": "research_tool",
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"tool_input": "financial industry AI solutions",
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"result": "**Preliminary Research Report on the Financial Industry for crewai Enterprise Solution**\n1. Industry Overview and Trends\nThe financial industry in ....\nConclusion:\nThe financial industry presents a fertile ground for implementing AI solutions like crewai, particularly in areas such as digital customer engagement, risk management, and regulatory compliance. Further engagement with the lead is recommended to better tailor the crewai solution to their specific needs and scale.",
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"kickoff_id": "97eba64f-958c-40a0-b61c-625fe635a3c0",
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"meta": {
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"requestId": "travel-req-123",
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"source": "web-app"
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}
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}
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```
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</Tab>
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<Tab title="Task Webhook">
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`taskWebhookUrl` - Callback that will be executed upon the end of each task
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```json
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{
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"description": "Using the information gathered from the lead's data, conduct preliminary research on the lead's industry, company background, and potential use cases for crewai. Focus on finding relevant data that can aid in scoring the lead and planning a strategy to pitch them crewai.",
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"name": "Industry Research Task",
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"expected_output": "Detailed research report on the financial industry",
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"summary": "The financial industry presents a fertile ground for implementing AI solutions like crewai, particularly in areas such as digital customer engagement, risk management, and regulatory compliance. Further engagement with the lead is recommended to better tailor the crewai solution to their specific needs and scale.",
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"agent": "Research Agent",
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"output": "**Preliminary Research Report on the Financial Industry for crewai Enterprise Solution**\n1. Industry Overview and Trends\nThe financial industry in ....\nConclusion:\nThe financial industry presents a fertile ground for implementing AI solutions like crewai, particularly in areas such as digital customer engagement, risk management, and regulatory compliance.",
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"output_json": {
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"industry": "financial",
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"key_opportunities": ["digital customer engagement", "risk management", "regulatory compliance"]
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},
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"kickoff_id": "97eba64f-958c-40a0-b61c-625fe635a3c0",
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"meta": {
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"requestId": "travel-req-123",
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"source": "web-app"
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}
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}
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```
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</Tab>
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<Tab title="Crew Webhook">
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`crewWebhookUrl` - Callback that will be executed upon the end of the crew execution
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```json
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{
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"kickoff_id": "97eba64f-958c-40a0-b61c-625fe635a3c0",
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"result": "**Final Analysis Report**\n\nLead Score: Customer service enhancement and compliance are particularly relevant.\n\nTalking Points:\n- Highlight how crewai's AI solutions can transform customer service\n- Discuss crewai's potential for sustainability goals\n- Emphasize compliance capabilities\n- Stress adaptability for various operation scales",
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"result_json": {
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"lead_score": "Customer service enhancement, and compliance are particularly relevant.",
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"talking_points": [
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"Highlight how crewai's AI solutions can transform customer service with automated, personalized experiences and 24/7 support, improving both customer satisfaction and operational efficiency.",
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"Discuss crewai's potential to help the institution achieve its sustainability goals through better data analysis and decision-making, contributing to responsible investing and green initiatives.",
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"Emphasize crewai's ability to enhance compliance with evolving regulations through efficient data processing and reporting, reducing the risk of non-compliance penalties.",
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"Stress the adaptability of crewai to support both extensive multinational operations and smaller, targeted projects, ensuring the solution grows with the institution's needs."
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]
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},
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"token_usage": {
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"total_tokens": 1250,
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"prompt_tokens": 800,
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"completion_tokens": 450
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},
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"meta": {
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"requestId": "travel-req-123",
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"source": "web-app"
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}
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}
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```
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</Tab>
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</Tabs>
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