mirror of
https://github.com/crewAIInc/crewAI.git
synced 2026-07-02 05:38:12 +00:00
a237ebabba
* 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>
73 lines
2.9 KiB
Plaintext
73 lines
2.9 KiB
Plaintext
---
|
|
title: Integração com Langtrace
|
|
description: Como monitorar custo, latência e desempenho dos Agentes CrewAI usando o Langtrace, uma ferramenta externa de observabilidade.
|
|
icon: chart-line
|
|
mode: "wide"
|
|
---
|
|
|
|
# Visão Geral do Langtrace
|
|
|
|
O Langtrace é uma ferramenta externa e open-source que auxilia na configuração de observabilidade e avaliações para Modelos de Linguagem de Grande Porte (LLMs), frameworks de LLM e Bancos de Dados Vetoriais.
|
|
Apesar de não ser integrado diretamente ao CrewAI, o Langtrace pode ser utilizado em conjunto com o CrewAI para fornecer uma visibilidade aprofundada sobre o custo, latência e desempenho dos seus Agentes CrewAI.
|
|
Essa integração permite o registro de hiperparâmetros, o monitoramento de regressões de desempenho e o estabelecimento de um processo de melhoria contínua dos seus Agentes.
|
|
|
|
|
|
|
|
|
|
|
|
## Instruções de Configuração
|
|
|
|
<Steps>
|
|
<Step title="Crie uma conta no Langtrace">
|
|
Cadastre-se acessando [https://langtrace.ai/signup](https://langtrace.ai/signup).
|
|
</Step>
|
|
<Step title="Crie um projeto">
|
|
Defina o tipo do projeto como `CrewAI` e gere uma chave de API.
|
|
</Step>
|
|
<Step title="Instale o Langtrace no seu projeto CrewAI">
|
|
Use o seguinte comando:
|
|
|
|
```bash
|
|
pip install langtrace-python-sdk
|
|
```
|
|
</Step>
|
|
<Step title="Importe o Langtrace">
|
|
Importe e inicialize o Langtrace no início do seu script, antes de quaisquer imports do CrewAI:
|
|
|
|
```python
|
|
from langtrace_python_sdk import langtrace
|
|
langtrace.init(api_key='<SUA_CHAVE_LANGTRACE>')
|
|
|
|
# Agora importe os módulos do CrewAI
|
|
from crewai import Agent, Task, Crew
|
|
```
|
|
</Step>
|
|
</Steps>
|
|
|
|
### Funcionalidades e Sua Aplicação no CrewAI
|
|
|
|
1. **Rastreamento de Token e Custo do LLM**
|
|
|
|
- Monitore o uso de tokens e os custos associados para cada interação dos agentes CrewAI.
|
|
|
|
2. **Gráfico de Trace para Etapas de Execução**
|
|
|
|
- Visualize o fluxo de execução das suas tarefas CrewAI, incluindo latência e logs.
|
|
- Útil para identificar gargalos nos fluxos de trabalho dos seus agentes.
|
|
|
|
3. **Curadoria de Dataset com Anotação Manual**
|
|
|
|
- Crie conjuntos de dados a partir das saídas das suas tarefas CrewAI para futuros treinamentos ou avaliações.
|
|
|
|
4. **Versionamento e Gerenciamento de Prompt**
|
|
|
|
- Acompanhe as diferentes versões de prompts utilizados em seus agentes CrewAI.
|
|
- Útil para testes A/B e otimização de desempenho dos agentes.
|
|
|
|
5. **Playground de Prompt com Comparações de Modelos**
|
|
|
|
- Teste e compare diferentes prompts e modelos para seus agentes CrewAI antes da implantação.
|
|
|
|
6. **Testes e Avaliações**
|
|
|
|
- Configure testes automatizados para seus agentes e tarefas CrewAI. |