Hyperbrowser 网络抓取工具
Hyperbrowser 是一个用于运行和扩展无头浏览器的平台。它让您能够大规模启动和管理浏览器会话,并为任何网页抓取需求提供易于使用的解决方案,例如抓取单个页面或爬取整个网站。
主要功能
- 即时可伸缩性 - 在几秒钟内启动数百个浏览器会话,无需基础设施烦恼
- 简单集成 - 与 Puppeteer 和 Playwright 等流行工具无缝协作
- 强大的 API - 易于使用的 API,用于抓取/爬取任何网站等
- 绕过反机器人措施 - 内置隐身模式、广告拦截、自动验证码解决和轮换代理
本 Notebook 提供了 Hyperbrowser 网页工具的快速入门概述。
欲了解更多 Hyperbrowser 信息,请访问 Hyperbrowser 官网,或查阅 Hyperbrowser 文档。
主要功能
抓取
Hyperbrowser 提供了强大的抓取功能,让您能够从任何网页提取数据。抓取工具可以将网页内容转换为 Markdown 或 HTML 等结构化格式,便于处理和分析数据。
爬取
爬取功能使您能够自动浏览网站的多个页面。您可以设置页面限制等参数,以控制爬虫探索网站的广度,并收集其访问的每个页面的数据。
提取
Hyperbrowser 的提取功能利用 AI 根据您定义的 Schema 从网页中提取特定信息。这使您能够将非结构化网页内容转换为符合您确切要求的结构化数据。
概述
集成详情
工具 | 包 | 本地 | 可序列化 | JS 支持 |
---|---|---|---|---|
爬取工具 | langchain-hyperbrowser | ❌ | ❌ | ❌ |
抓取工具 | langchain-hyperbrowser | ❌ | ❌ | ❌ |
提取工具 | langchain-hyperbrowser | ❌ | ❌ | ❌ |
设置
要访问 Hyperbrowser 网页工具,您需要安装 langchain-hyperbrowser
集成包,并创建一个 Hyperbrowser 账户并获取 API 密钥。
凭证
前往 Hyperbrowser 注册并生成 API 密钥。完成后,请设置 HYPERBROWSER_API_KEY 环境变量
export HYPERBROWSER_API_KEY=<your-api-key>
安装
安装 langchain-hyperbrowser。
%pip install -qU langchain-hyperbrowser
实例化
爬取工具
HyperbrowserCrawlTool
是一个强大的工具,可以从给定 URL 开始爬取整个网站。它支持可配置的页面限制和抓取选项。
from langchain_hyperbrowser import HyperbrowserCrawlTool
tool = HyperbrowserCrawlTool()
抓取工具
HyperbrowserScrapeTool
是一个可以从网页抓取内容的工具。它支持 Markdown 和 HTML 输出格式,以及元数据提取。
from langchain_hyperbrowser import HyperbrowserScrapeTool
tool = HyperbrowserScrapeTool()
提取工具
HyperbrowserExtractTool
是一个强大的工具,它利用 AI 从网页中提取结构化数据。它可以根据预定义的 Schema 提取信息。
from langchain_hyperbrowser import HyperbrowserExtractTool
tool = HyperbrowserExtractTool()
调用
基本用法
爬取工具
from langchain_hyperbrowser import HyperbrowserCrawlTool
result = HyperbrowserCrawlTool().invoke(
{
"url": "https://example.com",
"max_pages": 2,
"scrape_options": {"formats": ["markdown"]},
}
)
print(result)
{'data': [CrawledPage(metadata={'url': 'https://www.example.com/', 'title': 'Example Domain', 'viewport': 'width=device-width, initial-scale=1', 'sourceURL': 'https://example.com'}, html=None, markdown='Example Domain\n\n# Example Domain\n\nThis domain is for use in illustrative examples in documents. You may use this\ndomain in literature without prior coordination or asking for permission.\n\n[More information...](https://www.iana.org/domains/example)', links=None, screenshot=None, url='https://example.com', status='completed', error=None)], 'error': None}
抓取工具
from langchain_hyperbrowser import HyperbrowserScrapeTool
result = HyperbrowserScrapeTool().invoke(
{"url": "https://example.com", "scrape_options": {"formats": ["markdown"]}}
)
print(result)
{'data': ScrapeJobData(metadata={'url': 'https://www.example.com/', 'title': 'Example Domain', 'viewport': 'width=device-width, initial-scale=1', 'sourceURL': 'https://example.com'}, html=None, markdown='Example Domain\n\n# Example Domain\n\nThis domain is for use in illustrative examples in documents. You may use this\ndomain in literature without prior coordination or asking for permission.\n\n[More information...](https://www.iana.org/domains/example)', links=None, screenshot=None), 'error': None}
提取工具
from langchain_hyperbrowser import HyperbrowserExtractTool
from pydantic import BaseModel
class SimpleExtractionModel(BaseModel):
title: str
result = HyperbrowserExtractTool().invoke(
{
"url": "https://example.com",
"schema": SimpleExtractionModel,
}
)
print(result)
{'data': {'title': 'Example Domain'}, 'error': None}
带自定义选项
带自定义选项的爬取工具
result = HyperbrowserCrawlTool().run(
{
"url": "https://example.com",
"max_pages": 2,
"scrape_options": {
"formats": ["markdown", "html"],
},
"session_options": {"use_proxy": True, "solve_captchas": True},
}
)
print(result)
{'data': [CrawledPage(metadata={'url': 'https://www.example.com/', 'title': 'Example Domain', 'viewport': 'width=device-width, initial-scale=1', 'sourceURL': 'https://example.com'}, html=None, markdown='Example Domain\n\n# Example Domain\n\nThis domain is for use in illustrative examples in documents. You may use this\ndomain in literature without prior coordination or asking for permission.\n\n[More information...](https://www.iana.org/domains/example)', links=None, screenshot=None, url='https://example.com', status='completed', error=None)], 'error': None}
带自定义选项的抓取工具
result = HyperbrowserScrapeTool().run(
{
"url": "https://example.com",
"scrape_options": {
"formats": ["markdown", "html"],
},
"session_options": {"use_proxy": True, "solve_captchas": True},
}
)
print(result)
{'data': ScrapeJobData(metadata={'url': 'https://www.example.com/', 'title': 'Example Domain', 'viewport': 'width=device-width, initial-scale=1', 'sourceURL': 'https://example.com'}, html='<html><head>\n <title>Example Domain</title>\n\n <meta charset="utf-8">\n <meta http-equiv="Content-type" content="text/html; charset=utf-8">\n <meta name="viewport" content="width=device-width, initial-scale=1">\n \n</head>\n\n<body>\n<div>\n <h1>Example Domain</h1>\n <p>This domain is for use in illustrative examples in documents. You may use this\n domain in literature without prior coordination or asking for permission.</p>\n <p><a href="https://www.iana.org/domains/example">More information...</a></p>\n</div>\n\n\n</body></html>', markdown='Example Domain\n\n# Example Domain\n\nThis domain is for use in illustrative examples in documents. You may use this\ndomain in literature without prior coordination or asking for permission.\n\n[More information...](https://www.iana.org/domains/example)', links=None, screenshot=None), 'error': None}
带自定义 Schema 的提取工具
from typing import List
from pydantic import BaseModel
class ProductSchema(BaseModel):
title: str
price: float
class ProductsSchema(BaseModel):
products: List[ProductSchema]
result = HyperbrowserExtractTool().run(
{
"url": "https://dummyjson.com/products?limit=10",
"schema": ProductsSchema,
"session_options": {"session_options": {"use_proxy": True}},
}
)
print(result)
{'data': {'products': [{'price': 9.99, 'title': 'Essence Mascara Lash Princess'}, {'price': 19.99, 'title': 'Eyeshadow Palette with Mirror'}, {'price': 14.99, 'title': 'Powder Canister'}, {'price': 12.99, 'title': 'Red Lipstick'}, {'price': 8.99, 'title': 'Red Nail Polish'}, {'price': 49.99, 'title': 'Calvin Klein CK One'}, {'price': 129.99, 'title': 'Chanel Coco Noir Eau De'}, {'price': 89.99, 'title': "Dior J'adore"}, {'price': 69.99, 'title': 'Dolce Shine Eau de'}, {'price': 79.99, 'title': 'Gucci Bloom Eau de'}]}, 'error': None}
异步用法
所有工具都支持异步用法
from typing import List
from langchain_hyperbrowser import (
HyperbrowserCrawlTool,
HyperbrowserExtractTool,
HyperbrowserScrapeTool,
)
from pydantic import BaseModel
class ExtractionSchema(BaseModel):
popular_library_name: List[str]
async def web_operations():
# Crawl
crawl_tool = HyperbrowserCrawlTool()
crawl_result = await crawl_tool.arun(
{
"url": "https://example.com",
"max_pages": 5,
"scrape_options": {"formats": ["markdown"]},
}
)
# Scrape
scrape_tool = HyperbrowserScrapeTool()
scrape_result = await scrape_tool.arun(
{"url": "https://example.com", "scrape_options": {"formats": ["markdown"]}}
)
# Extract
extract_tool = HyperbrowserExtractTool()
extract_result = await extract_tool.arun(
{
"url": "https://npmjs.net.cn",
"schema": ExtractionSchema,
}
)
return crawl_result, scrape_result, extract_result
results = await web_operations()
print(results)
---------------------------------------------------------------------------
``````output
NameError Traceback (most recent call last)
``````output
Cell In[6], line 10
1 from langchain_hyperbrowser import (
2 HyperbrowserCrawlTool,
3 HyperbrowserExtractTool,
4 HyperbrowserScrapeTool,
5 )
7 from pydantic import BaseModel
---> 10 class ExtractionSchema(BaseModel):
11 popular_library_name: List[str]
14 async def web_operations():
15 # Crawl
``````output
Cell In[6], line 11, in ExtractionSchema()
10 class ExtractionSchema(BaseModel):
---> 11 popular_library_name: List[str]
``````output
NameError: name 'List' is not defined
在代理中使用
以下是如何在代理中使用任何网页工具的方法
from langchain_hyperbrowser import HyperbrowserCrawlTool
from langchain_openai import ChatOpenAI
from langgraph.prebuilt import create_react_agent
# Initialize the crawl tool
crawl_tool = HyperbrowserCrawlTool()
# Create the agent with the crawl tool
llm = ChatOpenAI(temperature=0)
agent = create_react_agent(llm, [crawl_tool])
user_input = "Crawl https://example.com and get content from up to 5 pages"
for step in agent.stream(
{"messages": user_input},
stream_mode="values",
):
step["messages"][-1].pretty_print()
================================[1m Human Message [0m=================================
Crawl https://example.com and get content from up to 5 pages
==================================[1m Ai Message [0m==================================
Tool Calls:
hyperbrowser_crawl_data (call_G2ofdHOqjdnJUZu4hhbuga58)
Call ID: call_G2ofdHOqjdnJUZu4hhbuga58
Args:
url: https://example.com
max_pages: 5
scrape_options: {'formats': ['markdown']}
=================================[1m Tool Message [0m=================================
Name: hyperbrowser_crawl_data
{'data': [CrawledPage(metadata={'url': 'https://www.example.com/', 'title': 'Example Domain', 'viewport': 'width=device-width, initial-scale=1', 'sourceURL': 'https://example.com'}, html=None, markdown='Example Domain\n\n# Example Domain\n\nThis domain is for use in illustrative examples in documents. You may use this\ndomain in literature without prior coordination or asking for permission.\n\n[More information...](https://www.iana.org/domains/example)', links=None, screenshot=None, url='https://example.com', status='completed', error=None)], 'error': None}
==================================[1m Ai Message [0m==================================
I have crawled the website [https://example.com](https://example.com) and retrieved content from the first page. Here is the content in markdown format:
\`\`\`
Example Domain
# Example Domain
This domain is for use in illustrative examples in documents. You may use this
domain in literature without prior coordination or asking for permission.
[More information...](https://www.iana.org/domains/example)
\`\`\`
If you would like to crawl more pages or need additional information, please let me know!
配置选项
通用选项
所有工具都支持这些基本配置选项
url
: 要处理的网址session_options
: 浏览器会话配置use_proxy
: 是否使用代理solve_captchas
: 是否自动解决 CAPTCHAaccept_cookies
: 是否接受 Cookie
工具特定选项
爬取工具
max_pages
: 最大爬取页面数scrape_options
: 抓取每个页面的选项formats
: 输出格式列表(Markdown、HTML)
抓取工具
scrape_options
: 抓取页面的选项formats
: 输出格式列表(Markdown、HTML)
提取工具
schema
: 定义要提取结构的 Pydantic 模型extraction_prompt
: 用于提取的自然语言提示
更多详情,请参阅相应的 API 参考