Files
crewAI/docs/edge/pt-BR/tools/web-scraping/hyperbrowserloadtool.mdx
Lucas Gomide a237ebabba feat: adopt directory-based docs versioning with Edge channel (#6202)
* 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>
2026-06-17 11:56:59 -04:00

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---
title: Hyperbrowser Load Tool
description: O `HyperbrowserLoadTool` permite realizar web scraping e crawling utilizando o Hyperbrowser.
icon: globe
mode: "wide"
---
# `HyperbrowserLoadTool`
## Descrição
O `HyperbrowserLoadTool` permite realizar web scraping e crawling utilizando o [Hyperbrowser](https://hyperbrowser.ai), uma plataforma para executar e escalar browsers headless. Essa ferramenta possibilita extrair dados de uma única página ou rastrear um site inteiro, retornando o conteúdo em markdown ou HTML corretamente formatado.
Principais Características:
- Escalabilidade Instantânea Inicie centenas de sessões de browser em segundos sem se preocupar com infraestrutura
- Integração Simples Funciona perfeitamente com ferramentas populares como Puppeteer e Playwright
- APIs Poderosas APIs fáceis de usar para scraping/crawling de qualquer site
- Supera Medidas Anti-Bot Inclui modo stealth, bloqueio de anúncios, resolução automática de CAPTCHA e proxies rotativos
## Instalação
Para utilizar esta ferramenta, você precisa instalar o SDK do Hyperbrowser:
```shell
uv add hyperbrowser
```
## Passos para Começar
Para usar efetivamente o `HyperbrowserLoadTool`, siga estes passos:
1. **Cadastre-se**: Vá até o [Hyperbrowser](https://app.hyperbrowser.ai/) para criar uma conta e gerar uma chave de API.
2. **Chave de API**: Defina a variável de ambiente `HYPERBROWSER_API_KEY` ou passe-a diretamente no construtor da ferramenta.
3. **Instale o SDK**: Instale o SDK do Hyperbrowser usando o comando acima.
## Exemplo
O exemplo a seguir demonstra como inicializar a ferramenta e utilizá-la para extrair dados de um site:
```python Code
from crewai_tools import HyperbrowserLoadTool
from crewai import Agent
# Initialize the tool with your API key
tool = HyperbrowserLoadTool(api_key="your_api_key") # Or use environment variable
# Define an agent that uses the tool
@agent
def web_researcher(self) -> Agent:
'''
This agent uses the HyperbrowserLoadTool to scrape websites
and extract information.
'''
return Agent(
config=self.agents_config["web_researcher"],
tools=[tool]
)
```
## Parâmetros
O `HyperbrowserLoadTool` aceita os seguintes parâmetros:
### Parâmetros do Construtor
- **api_key**: Opcional. Sua chave de API do Hyperbrowser. Se não fornecida, será lida da variável de ambiente `HYPERBROWSER_API_KEY`.
### Parâmetros de Execução
- **url**: Obrigatório. A URL do site a ser extraído ou rastreado.
- **operation**: Opcional. A operação a ser realizada no site. Pode ser 'scrape' ou 'crawl'. O padrão é 'scrape'.
- **params**: Opcional. Parâmetros adicionais para a operação de scraping ou crawling.
## Parâmetros Suportados
Para informações detalhadas sobre todos os parâmetros suportados, acesse:
- [Parâmetros de Scrape](https://docs.hyperbrowser.ai/reference/sdks/python/scrape#start-scrape-job-and-wait)
- [Parâmetros de Crawl](https://docs.hyperbrowser.ai/reference/sdks/python/crawl#start-crawl-job-and-wait)
## Formato de Retorno
A ferramenta retorna o conteúdo nos seguintes formatos:
- Para operações **scrape**: O conteúdo da página no formato markdown ou HTML.
- Para operações **crawl**: O conteúdo de cada página separado por divisores, incluindo a URL de cada página.
## Conclusão
O `HyperbrowserLoadTool` oferece uma maneira poderosa de realizar scraping e crawling em sites, lidando com cenários complexos como medidas anti-bot, CAPTCHAs e muito mais. Aproveitando a plataforma do Hyperbrowser, essa ferramenta permite que agentes acessem e extraiam conteúdo da web de forma eficiente.