mirror of
https://github.com/crewAIInc/crewAI.git
synced 2026-07-02 13:48:09 +00:00
* 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>
151 lines
5.5 KiB
Plaintext
151 lines
5.5 KiB
Plaintext
---
|
|
title: Ferramenta S3 Writer
|
|
description: A `S3WriterTool` permite que agentes CrewAI escrevam conteúdo em arquivos em buckets Amazon S3.
|
|
icon: aws
|
|
mode: "wide"
|
|
---
|
|
|
|
# `S3WriterTool`
|
|
|
|
## Descrição
|
|
|
|
A `S3WriterTool` foi projetada para escrever conteúdo em arquivos em buckets Amazon S3. Esta ferramenta permite que agentes CrewAI criem ou atualizem arquivos no S3, tornando-a ideal para fluxos de trabalho que exigem armazenamento de dados, salvamento de arquivos de configuração ou persistência de qualquer outro conteúdo no armazenamento AWS S3.
|
|
|
|
## Instalação
|
|
|
|
Para usar esta ferramenta, você precisa instalar as dependências necessárias:
|
|
|
|
```shell
|
|
uv add boto3
|
|
```
|
|
|
|
## Passos para Começar
|
|
|
|
Para usar a `S3WriterTool` de forma eficaz, siga estes passos:
|
|
|
|
1. **Instale as Dependências**: Instale os pacotes necessários usando o comando acima.
|
|
2. **Configure as Credenciais AWS**: Defina suas credenciais AWS como variáveis de ambiente.
|
|
3. **Inicialize a Ferramenta**: Crie uma instância da ferramenta.
|
|
4. **Especifique o Caminho no S3 e o Conteúdo**: Forneça o caminho no S3 onde deseja gravar o arquivo e o conteúdo a ser escrito.
|
|
|
|
## Exemplo
|
|
|
|
O exemplo a seguir demonstra como usar a `S3WriterTool` para gravar conteúdo em um arquivo em um bucket S3:
|
|
|
|
```python Code
|
|
from crewai import Agent, Task, Crew
|
|
from crewai_tools.aws.s3 import S3WriterTool
|
|
|
|
# Initialize the tool
|
|
s3_writer_tool = S3WriterTool()
|
|
|
|
# Define an agent that uses the tool
|
|
file_writer_agent = Agent(
|
|
role="File Writer",
|
|
goal="Write content to files in S3 buckets",
|
|
backstory="An expert in storing and managing files in cloud storage.",
|
|
tools=[s3_writer_tool],
|
|
verbose=True,
|
|
)
|
|
|
|
# Example task to write a report
|
|
write_task = Task(
|
|
description="Generate a summary report of the quarterly sales data and save it to {my_bucket}.",
|
|
expected_output="Confirmation that the report was successfully saved to S3.",
|
|
agent=file_writer_agent,
|
|
)
|
|
|
|
# Create and run the crew
|
|
crew = Crew(agents=[file_writer_agent], tasks=[write_task])
|
|
result = crew.kickoff(inputs={"my_bucket": "s3://my-bucket/reports/quarterly-summary.txt"})
|
|
```
|
|
|
|
## Parâmetros
|
|
|
|
A `S3WriterTool` aceita os seguintes parâmetros quando utilizada por um agente:
|
|
|
|
- **file_path**: Obrigatório. O caminho do arquivo S3 no formato `s3://bucket-name/file-name`.
|
|
- **content**: Obrigatório. O conteúdo a ser escrito no arquivo.
|
|
|
|
## Credenciais AWS
|
|
|
|
A ferramenta requer credenciais AWS para acessar os buckets S3. Você pode configurar essas credenciais usando variáveis de ambiente:
|
|
|
|
- **CREW_AWS_REGION**: A região AWS onde seu bucket S3 está localizado. O padrão é `us-east-1`.
|
|
- **CREW_AWS_ACCESS_KEY_ID**: Sua AWS access key ID.
|
|
- **CREW_AWS_SEC_ACCESS_KEY**: Sua AWS secret access key.
|
|
|
|
## Uso
|
|
|
|
Ao usar a `S3WriterTool` com um agente, o agente precisará fornecer tanto o caminho do arquivo no S3 quanto o conteúdo a ser gravado:
|
|
|
|
```python Code
|
|
# Example of using the tool with an agent
|
|
file_writer_agent = Agent(
|
|
role="File Writer",
|
|
goal="Write content to files in S3 buckets",
|
|
backstory="An expert in storing and managing files in cloud storage.",
|
|
tools=[s3_writer_tool],
|
|
verbose=True,
|
|
)
|
|
|
|
# Create a task for the agent to write a specific file
|
|
write_config_task = Task(
|
|
description="""
|
|
Create a configuration file with the following database settings:
|
|
- host: db.example.com
|
|
- port: 5432
|
|
- username: app_user
|
|
- password: secure_password
|
|
|
|
Save this configuration as JSON to {my_bucket}.
|
|
""",
|
|
expected_output="Confirmation that the configuration file was successfully saved to S3.",
|
|
agent=file_writer_agent,
|
|
)
|
|
|
|
# Run the task
|
|
crew = Crew(agents=[file_writer_agent], tasks=[write_config_task])
|
|
result = crew.kickoff(inputs={"my_bucket": "s3://my-bucket/config/db-config.json"})
|
|
```
|
|
|
|
## Tratamento de Erros
|
|
|
|
A `S3WriterTool` inclui tratamento de erros para problemas comuns no S3:
|
|
|
|
- Formato de caminho S3 inválido
|
|
- Problemas de permissão (ex: sem acesso de gravação ao bucket)
|
|
- Problemas com credenciais AWS
|
|
- Bucket inexistente
|
|
|
|
Quando ocorre um erro, a ferramenta retorna uma mensagem de erro que inclui detalhes sobre o problema.
|
|
|
|
## Detalhes de Implementação
|
|
|
|
A `S3WriterTool` utiliza o AWS SDK para Python (boto3) para interagir com o S3:
|
|
|
|
```python Code
|
|
class S3WriterTool(BaseTool):
|
|
name: str = "S3 Writer Tool"
|
|
description: str = "Writes content to a file in Amazon S3 given an S3 file path"
|
|
|
|
def _run(self, file_path: str, content: str) -> str:
|
|
try:
|
|
bucket_name, object_key = self._parse_s3_path(file_path)
|
|
|
|
s3 = boto3.client(
|
|
's3',
|
|
region_name=os.getenv('CREW_AWS_REGION', 'us-east-1'),
|
|
aws_access_key_id=os.getenv('CREW_AWS_ACCESS_KEY_ID'),
|
|
aws_secret_access_key=os.getenv('CREW_AWS_SEC_ACCESS_KEY')
|
|
)
|
|
|
|
s3.put_object(Bucket=bucket_name, Key=object_key, Body=content.encode('utf-8'))
|
|
return f"Successfully wrote content to {file_path}"
|
|
except ClientError as e:
|
|
return f"Error writing file to S3: {str(e)}"
|
|
```
|
|
|
|
## Conclusão
|
|
|
|
A `S3WriterTool` oferece uma maneira direta de gravar conteúdo em arquivos em buckets Amazon S3. Ao permitir que agentes criem e atualizem arquivos no S3, ela facilita fluxos de trabalho que exigem armazenamento de arquivos em nuvem. Esta ferramenta é particularmente útil para persistência de dados, gerenciamento de configurações, geração de relatórios e qualquer tarefa que envolva armazenar informações no AWS S3. |