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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>
111 lines
3.5 KiB
Plaintext
111 lines
3.5 KiB
Plaintext
---
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title: "Exa Search Tool"
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description: "Search the web using the Exa Search API to find the most relevant results for any query, with options for full page content, highlights, and summaries."
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icon: "magnifying-glass"
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mode: "wide"
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---
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The `EXASearchTool` lets CrewAI agents search the web using the [Exa](https://exa.ai/) search API. It returns the most relevant results for any query, with options for full page content and AI-generated summaries.
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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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## Environment Variables
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Set your Exa API key as an environment variable:
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```bash
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export EXA_API_KEY='your_exa_api_key'
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```
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Get an API key from the [Exa dashboard](https://dashboard.exa.ai/api-keys).
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## Example Usage
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Here's how to use the `EXASearchTool` within a CrewAI agent:
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```python
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import os
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from crewai import Agent, Task, Crew
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from crewai_tools import EXASearchTool
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# Initialize the tool
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exa_tool = EXASearchTool()
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# Create an agent that uses the tool
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researcher = Agent(
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role='Research Analyst',
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goal='Find the latest information on any topic',
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backstory='An expert researcher who finds the most relevant and up-to-date information.',
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tools=[exa_tool],
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verbose=True
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)
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# Create a task for the agent
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research_task = Task(
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description='Find the top 3 recent breakthroughs in quantum computing.',
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expected_output='A summary of the top 3 breakthroughs with source URLs.',
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agent=researcher
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)
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# Form the crew and kick it off
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crew = Crew(
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agents=[researcher],
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tasks=[research_task],
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verbose=True
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)
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result = crew.kickoff()
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print(result)
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```
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## Configuration Options
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The `EXASearchTool` accepts the following parameters during initialization:
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- `type` (str, optional): The search type to use. Defaults to `"auto"`. Options: `"auto"`, `"instant"`, `"fast"`, `"deep"`.
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- `content` (bool, optional): Whether to include full page content in results. Defaults to `False`.
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- `summary` (bool, optional): Whether to include AI-generated summaries of each result. Requires `content=True`. Defaults to `False`.
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- `api_key` (str, optional): Your Exa API key. Falls back to the `EXA_API_KEY` environment variable if not provided.
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- `base_url` (str, optional): Custom API server URL. Falls back to the `EXA_BASE_URL` environment variable if not provided.
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When calling the tool (or when an agent invokes it), the following search parameters are available:
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- `search_query` (str): **Required**. The search query string.
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- `start_published_date` (str, optional): Filter results published after this date (ISO 8601 format, e.g. `"2024-01-01"`).
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- `end_published_date` (str, optional): Filter results published before this date (ISO 8601 format).
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- `include_domains` (list[str], optional): A list of domains to restrict the search to.
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## Advanced Usage
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You can configure the tool with custom parameters for richer results:
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```python
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# Get full page content with AI summaries
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exa_tool = EXASearchTool(
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content=True,
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summary=True,
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type="deep"
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)
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# Use it in an agent
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agent = Agent(
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role="Deep Researcher",
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goal="Conduct thorough research with full content and summaries",
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tools=[exa_tool]
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)
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```
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## Features
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- **Semantic Search**: Find results based on meaning, not just keywords
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- **Full Content Retrieval**: Get the full text of web pages alongside search results
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- **AI Summaries**: Get concise, AI-generated summaries of each result
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- **Date Filtering**: Limit results to specific time periods with published date filters
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- **Domain Filtering**: Restrict searches to specific domains
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