概述
集成细节
| 类别 | 包名称 | 可序列化 | JS支持 | 版本 |
|---|---|---|---|---|
@[TavilyCrawl] | @[langchain-tavily] | ✅ | ✅ |  |
工具特性
| 返回物 | 原生异步 | 返回数据 | 定价 |
|---|---|---|---|
| ❌ | ✅ | 基础URL、页面URL、原始内容、图片、图标 | 每月1,000免费信用 |
配置
集成位于langchain-tavily包中。
pip install -qU langchain-tavily
凭据
还需要设置Tavily API密钥。您可通过此网站创建账户获取API密钥。import getpass
import os
if not os.environ.get("TAVILY_API_KEY"):
os.environ["TAVILY_API_KEY"] = getpass.getpass("Tavily API key:\n")
实例化
工具在实例化时可接受以下参数：max_depth(可选，int)：从起始URL的最大跳转层级。默认为1。max_breadth(可选，int)：每层级最大爬取页面数。默认为20。limit(可选，int)：总爬取页面数上限。默认为50。instructions(可选，str)：自然语言爬取指令。select_paths(可选，list[str])：仅爬取包含以下路径正则的URL。select_domains(可选，list[str])：仅爬取以下域名正则匹配的站点。exclude_paths(可选，list[str])：跳过包含以下路径正则的URL。exclude_domains(可选，list[str])：跳过以下域名正则匹配的站点。allow_external(可选，bool)：允许爬虫跟随外部链接。extract_depth(可选，str)："basic"或"advanced"提取深度。format(可选，str)："markdown"或"text"内容格式。include_images(可选，bool)：是否包含页面发现图片。
from langchain_tavily import TavilyCrawl
tool = TavilyCrawl(
max_depth=1,
max_breadth=20,
limit=50,
# extract_depth="basic",
# format="markdown",
# include_images=False,
# allow_external=False,
)
调用
直接通过参数调用
Tavily爬取工具在调用时可接受以下参数：url(必填)：爬取起始的基础URL。- 其他可设置参数：
instructions,select_paths,select_domains,exclude_paths,exclude_domains,allow_external。
tool.invoke({"url": "https://docs.tavily.com"})
{
"base_url": "https://docs.tavily.com",
"results": [
{
"url": "https://docs.tavily.com/",
"raw_content": "\n\n\n##### Welcome\n\n## Documentation Index\n\nFetch the complete documentation index at: <https://docs.tavily.com/llms.txt>\n\nUse this file to discover all available pages before exploring further.\n\n# Build with Tavily\n\nYour journey to state-of-the-art web search starts right here.\n\n## Python SDK\n\n`pip install tavily-python`\n\n## JavaScript SDK\n\n`npm i @tavily/core`\n`from tavily import TavilyClient\n\ntavily_client = TavilyClient(api_key=\"tvly-YOUR_API_KEY\")\nresponse = tavily_client.search(\"Who is Leo Messi?\")\n\nprint(response)`\n`from tavily import TavilyClient\n\ntavily_client = TavilyClient(api_key=\"tvly-YOUR_API_KEY\")\nresponse = tavily_client.extract(\"https://en.wikipedia.org/wiki/Artificial_intelligence\")\n\nprint(response)`\n`from tavily import TavilyClient\n\ntavily_client = TavilyClient(api_key=\"tvly-YOUR_API_KEY\")\nresponse = tavily_client.crawl(\"https://docs.tavily.com\", instructions=\"Find all pages on the Python SDK\")\n\nprint(response)`\n`from tavily import TavilyClient\n\ntavily_client = TavilyClient(api_key=\"tvly-YOUR_API_KEY\")\nresponse = tavily_client.map(\"https://docs.tavily.com\")\n\nprint(response)`\n`from tavily import TavilyClient\n\ntavily_client = TavilyClient(api_key=\"tvly-YOUR_API_KEY\")\nresponse = tavily_client.research(\"What are the latest developments in AI?\")\n\nprint(response)`\n\n### Developer Resources\n\n## API Credits Overview\n\n## Rate Limits\n\n## Playground",
"favicon": "https://docs.tavily.com/mintlify-assets/_mintlify/favicons/tavilyai/SXaxSfweEU3ftIlh/_generated/favicon/apple-touch-icon.png"
},
{
"url": "https://docs.tavily.com/documentation/about",
"raw_content": "Performance\n\nCommitted to speed and efficiency, our API guarantees real-time and trusted information. Our team works hard to improve Tavily’s performance over time.\n\nIntegration-friendly\n\nWe appreciate the essence of adaptability. That’s why integrating our API with your existing setup is a breeze. You can choose our Python library, JavaScript package or a simple API call. You can also use Tavily through any of our supported partners such as LangChain and LlamaIndex.\n\nTransparent & Informative\n\nOur detailed documentation ensures you’re never left in the dark. From setup basics to nuanced features, we’ve got you covered.\n\n## \n\nHow does the Search API work? [...] With LLM hallucinations, it’s crucial to optimize for RAG with the right context and information. This is where Tavily comes in, delivering accurate and precise information for your RAG applications.\n\n## \n\nGetting started\n\nSign up for Tavily to get your API key. You get 1,000 free API Credits every month. No credit card required.\n\n## Get your free API key You get 1,000 free API Credits every month. No credit card required.\n\nHead to our API Playground to familiarize yourself with our API.To get started with Tavily’s APIs and SDKs using code, head to our Quickstart Guide and follow the steps.\n\nGot questions? Stumbled upon an issue? Simply intrigued? Don’t hesitate! Our support team is always on standby, eager to assist. Join us, dive deep, and redefine your search experience! Contact us! [...] # About - Tavily Docs\n\nSkip to main content\n\nTavily Docs home pageImage 1: light logoImage 2: dark logo\n\nSearch...\n\nCtrl K Ask AI\n\n Support\n Get an API key\n Get an API key\n\nSearch...\n\nNavigation\n\nGetting Started\n\nAbout\n\nHomeIntroductionAPI & SDKsEcosystemExamplesChangelogHelp\n\n API Playground\n Community\n Blog\n\n##### Getting Started\n\n About\n Quickstart\n Credits & Pricing\n Rate Limits\n\n##### FAQ\n\n Frequently Asked Questions\n\nOn this page\n\n Who are we?\n What is the Tavily Search Engine?\n Why choose Tavily?\n How does the Search API work?\n Getting started\n\nGetting Started\n\n# About\n\nCopy page\n\nWelcome to Tavily!\n\nCopy page\n\nLooking for a step-by-step tutorial to get started in under 5 minutes? Head to our Quickstart guide and start coding!\n\n## \n\nWho are we?",
"favicon": "https://docs.tavily.com/mintlify-assets/_mintlify/favicons/tavilyai/SXaxSfweEU3ftIlh/_generated/favicon/apple-touch-icon.png"
},
{
"url": "https://docs.tavily.com/documentation/api-reference/introduction",
"raw_content": "# Introduction - Tavily Docs\n\nSkip to main content\n\nTavily Docs home pageImage 1: light logoImage 2: dark logo\n\nSearch...\n\n⌘K Ask AI\n\n Support\n Get an API key\n Get an API key\n\nSearch...\n\nNavigation\n\nAPI Reference\n\nIntroduction\n\nHomeIntroductionAPI & SDKsEcosystemExamplesChangelogHelp\n\n API Playground\n Community\n Blog\n\n##### API Reference\n\n Introduction\n POST Search\n POST Extract\n POST Crawl\n POST Map\n Research \n GET Usage\n\n##### Enterprise API Reference\n\n API Key Generator \n\n##### Python SDK\n\n Quickstart\n SDK Reference\n\n##### JavaScript SDK\n\n Quickstart\n SDK Reference\n\n##### Best Practices\n\n Search\n Extract\n Crawl\n Research\n API Key Management\n\nOn this page\n\n Base URL\n Authentication\n Endpoints\n Project Tracking\n\nAPI Reference [...] When using the SDKs, you can specify a project using the `project_id` parameter when instantiating the client, or by setting the `TAVILY_PROJECT` environment variable.\n\nTavily Search Next\n\n⌘I\n\nTavily Docs home pageImage 3: light logoImage 4: dark logo\n\nlinkedinxgithubyoutube\n\nResources\n\nAboutTavily Search CrawlerTavily Status\n\nLegal\n\nSecurity & CompliancePrivacy PolicyWebsite Terms of UsePlatform Terms of UseCookie Notice\n\nlinkedinxgithubyoutube\n\nPowered by This documentation is built and hosted on Mintlify, a developer documentation platform\n\nAssistant\n\nResponses are generated using AI and may contain mistakes. [...] API Reference\n\n# Introduction\n\nCopy page\n\nEasily integrate our APIs with your services.\n\nCopy page\n\n> ## Documentation Index\n> \n> \n> Fetch the complete documentation index at: \n> \n> \n> Use this file to discover all available pages before exploring further.\n\n## \n\nBase URL\n\nThe base URL for all requests to the Tavily API is:\n\n```\n\n```\n\n## \n\nAuthentication\n\nAll Tavily endpoints are authenticated using API keys. Get your free API key.\n\n```\ncurl -X POST \\\n -H \"Content-Type: application/json\" \\\n -H \"Authorization: Bearer tvly-YOUR_API_KEY\" \\\n -d '{\"query\": \"Who is Leo Messi?\"}'\n```\n\n## \n\nEndpoints\n\n`/search`Tavily’s powerful web search API.\n\n`/extract`Tavily’s powerful content extraction API.\n\n`/crawl` , `/map`Tavily’s intelligent sitegraph navigation and extraction tools.",
"favicon": "https://docs.tavily.com/mintlify-assets/_mintlify/favicons/tavilyai/SXaxSfweEU3ftIlh/_generated/favicon/apple-touch-icon.png"
},
{
"url": "https://github.com/tavily-ai",
"raw_content": "JavaScript1.8k239 \n2. tavily-pythontavily-python Public \nThe Tavily Python SDK allows for easy interaction with the Tavily API, offering the full range of our search, extract, crawl, map, and research functionalities directly from your Python programs. E…\n\nPython1.2k148 \n3. skillsskills Public \nPython23321 \n4. meeting-prep-agentmeeting-prep-agent Public \nPrepare for meetings with company and attendee research notes, integrated with Google Calendar through MCP\n\nPython19334 \n5. tavily-jstavily-js Public \nOfficial TypeScript/JavaScript library for Tavily.\n\nTypeScript839 \n6. tavily-chattavily-chat Public \nConversational agent that fuses chat data with live web results through Tavily search, extract, and crawl.\n\nTypeScript7216 \n\n### Repositories\n\nLoading\n\nType\n\nSelect type [...] ### Repositories\n\nLoading\n\nType\n\nSelect type\n\nAll Public Sources Forks Archived Mirrors Templates \n\nLanguage\n\nSelect language\n\nAll JavaScript Jupyter Notebook Python TypeScript \n\nSort\n\nSelect order\n\nLast updated Name Stars \n\nShowing 10 of 33 repositories [...] langchain-tavily Public ### Uh oh! There was an error while loading. [Please reload this page.]( past year of commit activity Python22MIT 1511 Updated Apr 16, 2026 \n langchainjs Public Forked from langchain-ai/langchainjs\n🦜🔗 Build context-aware reasoning applications ### Uh oh! There was an error while loading. [Please reload this page.]( past year of commit activity TypeScript 0 MIT 3,20800 Updated Apr 16, 2026",
"favicon": "https://github.githubassets.com/favicons/favicon.svg"
}
],
"response_time": 13.45
}
通过ToolCall调用
也可通过模型生成的ToolCall进行调用，此时将返回ToolMessage：model_generated_tool_call = {
"args": {"url": "https://docs.tavily.com", "instructions": "Find API reference pages"},
"id": "1",
"name": "tavily_crawl",
"type": "tool_call",
}
tool_msg = tool.invoke(model_generated_tool_call)
print(tool_msg.content[:400])
在智能体中应用
通过将工具绑定到模型，可直接在智能体中使用爬取工具。智能体可动态设置参数以控制爬取范围和深度。if not os.environ.get("OPENAI_API_KEY"):
os.environ["OPENAI_API_KEY"] = getpass.getpass("OPENAI_API_KEY:\n")
from langchain.chat_models import init_chat_model
model = init_chat_model(model="gpt-5.5", model_provider="openai", temperature=0)
from langchain_tavily import TavilyCrawl
from langchain.agents import create_agent
tavily_crawl_tool = TavilyCrawl(max_depth=1, max_breadth=10, limit=10)
agent = create_agent(model, [tavily_crawl_tool])
user_input = "Crawl https://docs.tavily.com and find the API reference for the search endpoint."
stream = agent.stream_events({"messages": user_input}, version="v3")
for snapshot in stream.values:
snapshot["messages"][-1].pretty_print()
API参考
所有Tavily Crawl API特性和配置的详细文档请访问API参考：docs.tavily.com/documentation/api-reference/endpoint/crawl官方原文：src/oss/python/integrations/tools/tavily_crawl.mdx · 非官方翻译，译文由 AI 生成，以英文原文为准。