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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>
97 lines
3.3 KiB
Plaintext
97 lines
3.3 KiB
Plaintext
---
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title: Brave Search
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description: O `BraveSearchTool` foi projetado para pesquisar na internet usando a Brave Search API.
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icon: searchengin
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mode: "wide"
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---
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# `BraveSearchTool`
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## Descrição
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Esta ferramenta foi desenvolvida para realizar buscas na web utilizando a Brave Search API. Ela permite que você pesquise na internet com uma consulta especificada e recupere resultados relevantes. A ferramenta suporta a personalização do número de resultados e buscas específicas por país.
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## Instalação
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Para incorporar esta ferramenta ao seu projeto, siga as instruções de instalação abaixo:
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```shell
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pip install 'crewai[tools]'
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```
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## Passos para Começar
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Para utilizar o `BraveSearchTool` de forma eficaz, siga estes passos:
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1. **Instalação do Pacote**: Confirme que o pacote `crewai[tools]` está instalado no seu ambiente Python.
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2. **Obtenção da Chave de API**: Obtenha uma chave de API do Brave Search registrando-se em [Brave Search API](https://api.search.brave.com/app/keys).
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3. **Configuração do Ambiente**: Armazene a chave de API obtida em uma variável de ambiente chamada `BRAVE_API_KEY` para facilitar seu uso pela ferramenta.
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## Exemplo
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O exemplo a seguir demonstra como inicializar a ferramenta e executar uma busca com uma determinada consulta:
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```python Code
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from crewai_tools import BraveSearchTool
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# Inicialize a ferramenta para capacidades de busca na internet
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tool = BraveSearchTool()
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# Execute uma busca
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results = tool.run(search_query="CrewAI agent framework")
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print(results)
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```
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## Parâmetros
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O `BraveSearchTool` aceita os seguintes parâmetros:
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- **search_query**: Obrigatório. A consulta de pesquisa que você deseja usar para pesquisar na internet.
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- **country**: Opcional. Especifique o país dos resultados da pesquisa. O padrão é string vazia.
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- **n_results**: Opcional. Número de resultados de pesquisa a serem retornados. O padrão é `10`.
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- **save_file**: Opcional. Se os resultados da pesquisa devem ser salvos em um arquivo. O padrão é `False`.
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## Exemplo com Parâmetros
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Veja um exemplo demonstrando como usar a ferramenta com parâmetros adicionais:
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```python Code
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from crewai_tools import BraveSearchTool
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# Inicialize a ferramenta com parâmetros personalizados
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tool = BraveSearchTool(
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country="US",
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n_results=5,
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save_file=True
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)
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# Execute uma busca
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results = tool.run(search_query="Latest AI developments")
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print(results)
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```
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## Exemplo de Integração com Agente
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Veja como integrar o `BraveSearchTool` com um agente CrewAI:
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```python Code
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from crewai import Agent
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from crewai.project import agent
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from crewai_tools import BraveSearchTool
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# Inicialize a ferramenta
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brave_search_tool = BraveSearchTool()
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# Defina um agente com o BraveSearchTool
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@agent
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def researcher(self) -> Agent:
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return Agent(
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config=self.agents_config["researcher"],
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allow_delegation=False,
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tools=[brave_search_tool]
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)
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```
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## Conclusão
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Ao integrar o `BraveSearchTool` em projetos Python, os usuários ganham a capacidade de realizar buscas em tempo real e relevantes na internet diretamente de suas aplicações. A ferramenta oferece uma interface simples para a poderosa Brave Search API, facilitando a recuperação e o processamento programático dos resultados de pesquisa. Seguindo as orientações de configuração e uso fornecidas, a incorporação desta ferramenta em projetos é simplificada e direta. |