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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>
86 lines
2.9 KiB
Plaintext
86 lines
2.9 KiB
Plaintext
---
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title: "Tavily Get Research Tool"
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description: "Retrieve the status and results of an existing Tavily research task"
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icon: "clipboard-list"
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mode: "wide"
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---
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The `TavilyGetResearchTool` lets CrewAI agents check an existing Tavily research task by `request_id`. Use it when a research task was started earlier and you need to retrieve its current status or final results.
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If you need to start a new research job, use the [Tavily Research Tool](/en/tools/search-research/tavilyresearchtool). This tool is specifically for looking up an existing Tavily research request after you already have its `request_id`.
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## Installation
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To use the `TavilyGetResearchTool`, install the `tavily-python` library alongside `crewai-tools`:
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```shell
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uv add 'crewai[tools]' tavily-python
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```
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## Environment Variables
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Set your Tavily API key:
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```bash
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export TAVILY_API_KEY='your_tavily_api_key'
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```
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Get an API key at [https://app.tavily.com/](https://app.tavily.com/) (sign up, then create a key).
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## Example Usage
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```python
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from crewai_tools import TavilyGetResearchTool
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tavily_get_research_tool = TavilyGetResearchTool()
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status_result = tavily_get_research_tool.run(
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request_id="your-research-request-id"
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)
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print(status_result)
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```
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## Common Workflow
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Use `TavilyGetResearchTool` when your application or another service has already created a Tavily research task and saved its `request_id`.
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Typical cases include:
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- Polling for completion after kicking off research in a background job.
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- Looking up the latest status of a long-running research task.
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- Fetching final research output from a previously created Tavily request.
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## Configuration Options
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The `TavilyGetResearchTool` accepts the following argument when calling the `run` method:
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- `request_id` (str): **Required.** The existing Tavily research request ID to retrieve.
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## Async Usage
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Use `_arun` when your application is already running inside an async event loop:
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```python
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from crewai_tools import TavilyGetResearchTool
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tavily_get_research_tool = TavilyGetResearchTool()
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status_result = await tavily_get_research_tool._arun(
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request_id="your-research-request-id"
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)
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```
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## Features
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- **Research status retrieval**: Fetch the current status of an existing Tavily research task.
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- **Result retrieval**: Return available research output once Tavily has completed the task.
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- **Sync and async**: Use either `_run`/`run` or `_arun` depending on your application's runtime.
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- **JSON output**: Returns Tavily responses as formatted JSON strings.
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## Response Format
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The tool returns a JSON string containing the current research task status and any available results from Tavily. The exact response shape depends on the task state returned by Tavily, so incomplete tasks may return status information before the final research output is available.
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Refer to the [Tavily API documentation](https://docs.tavily.com/) for full details on the Research API.
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