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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>
94 lines
3.4 KiB
Plaintext
94 lines
3.4 KiB
Plaintext
---
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title: CSV RAG Search
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description: The `CSVSearchTool` is a powerful RAG (Retrieval-Augmented Generation) tool designed for semantic searches within a CSV file's content.
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icon: file-csv
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mode: "wide"
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---
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# `CSVSearchTool`
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<Note>
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**Experimental**: We are still working on improving tools, so there might be unexpected behavior or changes in the future.
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</Note>
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## Description
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This tool is used to perform a RAG (Retrieval-Augmented Generation) search within a CSV file's content. It allows users to semantically search for queries in the content of a specified CSV file.
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This feature is particularly useful for extracting information from large CSV datasets where traditional search methods might be inefficient. All tools with "Search" in their name, including CSVSearchTool,
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are RAG tools designed for searching different sources of data.
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## Installation
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Install the crewai_tools package
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```shell
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pip install 'crewai[tools]'
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```
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## Example
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```python Code
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from crewai_tools import CSVSearchTool
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# Initialize the tool with a specific CSV file.
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# This setup allows the agent to only search the given CSV file.
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tool = CSVSearchTool(csv='path/to/your/csvfile.csv')
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# OR
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# Initialize the tool without a specific CSV file.
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# Agent will need to provide the CSV path at runtime.
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tool = CSVSearchTool()
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```
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## Arguments
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The following parameters can be used to customize the `CSVSearchTool`'s behavior:
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| Argument | Type | Description |
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|:---------------|:---------|:-------------------------------------------------------------------------------------------------------------------------------------|
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| **csv** | `string` | _Optional_. The path to the CSV file you want to search. This is a mandatory argument if the tool was initialized without a specific CSV file; otherwise, it is optional. |
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## Custom model and embeddings
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By default, the tool uses OpenAI for both embeddings and summarization. To customize the model, you can use a config dictionary as follows:
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```python Code
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from chromadb.config import Settings
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tool = CSVSearchTool(
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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", # or "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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## Security
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### Path Validation
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File paths provided to this tool are validated against the current working directory. Paths that resolve outside the working directory are rejected with a `ValueError`.
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To allow paths outside the working directory (for example, in tests or trusted pipelines), set the environment variable:
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```shell
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CREWAI_TOOLS_ALLOW_UNSAFE_PATHS=true
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```
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### URL Validation
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URL inputs are validated: `file://` URIs and requests targeting private or reserved IP ranges are blocked to prevent server-side request forgery (SSRF) attacks.
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``` |