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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>
80 lines
3.1 KiB
Plaintext
80 lines
3.1 KiB
Plaintext
---
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title: Pesquisa RAG em DOCX
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description: A `DOCXSearchTool` é uma ferramenta RAG projetada para busca semântica em documentos DOCX.
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icon: file-word
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mode: "wide"
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---
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# `DOCXSearchTool`
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<Note>
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Ainda estamos trabalhando na melhoria das ferramentas, portanto pode haver comportamentos inesperados ou alterações no futuro.
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</Note>
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## Descrição
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A `DOCXSearchTool` é uma ferramenta RAG desenvolvida para buscas semânticas dentro de documentos DOCX.
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Ela permite que os usuários pesquisem e extraiam informações relevantes de arquivos DOCX de forma eficiente, utilizando buscas baseadas em consultas.
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Esta ferramenta é inestimável para análise de dados, gestão da informação e tarefas de pesquisa,
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otimizando o processo de encontrar informações específicas em grandes coleções de documentos.
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## Instalação
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Instale o pacote crewai_tools executando o seguinte comando no seu terminal:
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```shell
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uv pip install docx2txt 'crewai[tools]'
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```
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## Exemplo
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O exemplo a seguir demonstra a inicialização da DOCXSearchTool para buscar dentro do conteúdo de qualquer arquivo DOCX ou com o caminho de um arquivo DOCX específico.
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```python Code
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from crewai_tools import DOCXSearchTool
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# Inicialize a ferramenta para buscar dentro do conteúdo de qualquer arquivo DOCX
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tool = DOCXSearchTool()
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# OU
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# Inicialize a ferramenta com um arquivo DOCX específico,
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# assim o agente só poderá buscar dentro do conteúdo do arquivo DOCX especificado
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tool = DOCXSearchTool(docx='path/to/your/document.docx')
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```
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## Argumentos
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Os seguintes parâmetros podem ser usados para customizar o comportamento da `DOCXSearchTool`:
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| Argumento | Tipo | Descrição |
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|:---------------|:----------|:------------------------------------------------------------------------------------------------------------------------------------|
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| **docx** | `string` | _Opcional_. Um argumento que especifica o caminho para o arquivo DOCX que você deseja pesquisar. Se não for fornecido durante a inicialização, a ferramenta permite a especificação posterior do caminho de qualquer arquivo DOCX para busca. |
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## Modelo e embeddings personalizados
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Por padrão, a ferramenta utiliza o OpenAI tanto para embeddings quanto para sumarização. Para customizar o modelo, você pode usar um dicionário de configuração como no exemplo:
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```python Code
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from chromadb.config import Settings
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tool = DOCXSearchTool(
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config={
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"embedding_model": {
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"provider": "openai",
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"config": {
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"model": "text-embedding-3-small",
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# "api_key": "sk-...",
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},
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},
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"vectordb": {
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"provider": "chromadb", # ou "qdrant"
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"config": {
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# "settings": Settings(persist_directory="/content/chroma", allow_reset=True, is_persistent=True),
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# from qdrant_client.models import VectorParams, Distance
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# "vectors_config": VectorParams(size=384, distance=Distance.COSINE),
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}
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},
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}
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)
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``` |