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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>
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74 lines
2.5 KiB
Plaintext
---
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title: Langtrace Integration
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description: How to monitor cost, latency, and performance of CrewAI Agents using Langtrace, an external observability tool.
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icon: chart-line
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mode: "wide"
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---
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# Langtrace Overview
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Langtrace is an open-source, external tool that helps you set up observability and evaluations for Large Language Models (LLMs), LLM frameworks, and Vector Databases.
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While not built directly into CrewAI, Langtrace can be used alongside CrewAI to gain deep visibility into the cost, latency, and performance of your CrewAI Agents.
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This integration allows you to log hyperparameters, monitor performance regressions, and establish a process for continuous improvement of your Agents.
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## Setup Instructions
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<Steps>
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<Step title="Sign up for Langtrace">
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Sign up by visiting [https://langtrace.ai/signup](https://langtrace.ai/signup).
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</Step>
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<Step title="Create a project">
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Set the project type to `CrewAI` and generate an API key.
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</Step>
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<Step title="Install Langtrace in your CrewAI project">
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Use the following command:
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```bash
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pip install langtrace-python-sdk
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```
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</Step>
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<Step title="Import Langtrace">
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Import and initialize Langtrace at the beginning of your script, before any CrewAI imports:
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```python
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from langtrace_python_sdk import langtrace
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langtrace.init(api_key='<LANGTRACE_API_KEY>')
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# Now import CrewAI modules
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from crewai import Agent, Task, Crew
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```
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</Step>
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</Steps>
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### Features and Their Application to CrewAI
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1. **LLM Token and Cost Tracking**
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- Monitor the token usage and associated costs for each CrewAI agent interaction.
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2. **Trace Graph for Execution Steps**
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- Visualize the execution flow of your CrewAI tasks, including latency and logs.
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- Useful for identifying bottlenecks in your agent workflows.
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3. **Dataset Curation with Manual Annotation**
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- Create datasets from your CrewAI task outputs for future training or evaluation.
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4. **Prompt Versioning and Management**
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- Keep track of different versions of prompts used in your CrewAI agents.
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- Useful for A/B testing and optimizing agent performance.
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5. **Prompt Playground with Model Comparisons**
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- Test and compare different prompts and models for your CrewAI agents before deployment.
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6. **Testing and Evaluations**
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- Set up automated tests for your CrewAI agents and tasks.
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