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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>
127 lines
6.6 KiB
Plaintext
127 lines
6.6 KiB
Plaintext
---
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title: "Automação com Webhook"
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description: "Automatize fluxos de trabalho do CrewAI AMP usando webhooks com plataformas como ActivePieces, Zapier e Make.com"
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icon: "webhook"
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mode: "wide"
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---
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O CrewAI AMP permite que você automatize seu fluxo de trabalho usando webhooks. Este artigo irá guiá-lo no processo de configuração e uso de webhooks para iniciar a execução do crew, com foco na integração com o ActivePieces, uma plataforma de automação de fluxos de trabalho semelhante ao Zapier e Make.com.
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## Configurando Webhooks
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<Steps>
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<Step title="Acessando a Interface de Kickoff">
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- Navegue até o painel do CrewAI AMP
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- Procure pela seção `/kickoff`, que é usada para iniciar a execução do crew
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<Frame>
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<img src="/images/enterprise/kickoff-interface.png" alt="Interface Kickoff" />
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</Frame>
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</Step>
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<Step title="Configurando o Conteúdo JSON">
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Na seção de Conteúdo JSON, você deverá fornecer as seguintes informações:
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- **inputs**: Um objeto JSON contendo:
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- `company`: O nome da empresa (ex.: "tesla")
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- `product_name`: O nome do produto (ex.: "crewai")
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- `form_response`: O tipo de resposta (ex.: "financial")
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- `icp_description`: Uma breve descrição do Perfil de Cliente Ideal
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- `product_description`: Uma breve descrição do produto
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- `taskWebhookUrl`, `stepWebhookUrl`, `crewWebhookUrl`: URLs para diversos endpoints de webhook (ActivePieces, Zapier, Make.com ou outra plataforma compatível)
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</Step>
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<Step title="Integração com ActivePieces">
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Neste exemplo usaremos o ActivePieces. Você pode utilizar outras plataformas, como Zapier e Make.com.
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Para integrar com o ActivePieces:
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1. Crie um novo flow no ActivePieces
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2. Adicione um gatilho (ex.: agendamento `Every Day`)
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<Frame>
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<img src="/images/enterprise/activepieces-trigger.png" alt="Gatilho ActivePieces" />
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</Frame>
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3. Adicione uma etapa de ação HTTP
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- Configure a ação como `Send HTTP request`
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- Use o método `POST`
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- Defina a URL para o endpoint de kickoff do CrewAI AMP
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- Adicione os headers necessários (ex.: `Bearer Token`)
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<Frame>
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<img src="/images/enterprise/activepieces-headers.png" alt="Headers ActivePieces" />
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</Frame>
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- No corpo, inclua o conteúdo JSON conforme configurado na etapa 2
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<Frame>
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<img src="/images/enterprise/activepieces-body.png" alt="Body ActivePieces" />
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</Frame>
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- O crew será iniciado no horário pré-definido.
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</Step>
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<Step title="Configurando o Webhook">
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1. Crie um novo flow no ActivePieces e nomeie-o
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<Frame>
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<img src="/images/enterprise/activepieces-flow.png" alt="Flow ActivePieces" />
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</Frame>
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2. Adicione uma etapa de webhook como gatilho:
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- Selecione `Catch Webhook` como tipo de gatilho
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- Isso irá gerar uma URL única que receberá requisições HTTP e disparará seu flow
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<Frame>
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<img src="/images/enterprise/activepieces-webhook.png" alt="Webhook ActivePieces" />
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</Frame>
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- Configure o e-mail para usar o corpo de texto do webhook do crew
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<Frame>
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<img src="/images/enterprise/activepieces-email.png" alt="Email ActivePieces" />
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</Frame>
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</Step>
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</Steps>
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## Exemplos de Output do Webhook
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**Nota:** Qualquer objeto `meta` fornecido na sua requisição de kickoff será incluído em todos os payloads de webhook, permitindo rastrear requisições e manter contexto durante todo o ciclo de vida da execução do crew.
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<Tabs>
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<Tab title="Step Webhook">
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`stepWebhookUrl` - Callback executado a cada pensamento interno do agente
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```json
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{
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"action": "**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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"task_id": "97eba64f-958c-40a0-b61c-625fe635a3c0"
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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 executado ao final de cada 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.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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"task_id": "97eba64f-958c-40a0-b61c-625fe635a3c0"
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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 executado ao final da execução do crew
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```json
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{
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"task_id": "97eba64f-958c-40a0-b61c-625fe635a3c0",
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"result": {
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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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}
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```
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</Tab>
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</Tabs>
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