Tavily Search

Tavily's Search API 是一个专门为AI代理（LLMs）构建的搜索引擎，能够快速提供实时、准确和事实性的结果。

概述

集成详情

类	包	可序列化	JS支持	最新包
TavilySearchResults	langchain-community	❌	✅

工具特性

返回工件	原生异步	返回数据	定价
✅	✅	标题, URL, 内容, 答案	每月1,000次免费搜索

设置

集成位于lang-community包中。我们还需要安装tavily-python包。

%pip install -qU "langchain-community>=0.2.11" tavily-python

凭证

我们还需要设置我们的Tavily API密钥。您可以通过访问此网站并创建一个账户来获取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")

设置LangSmith以获得一流的可观察性也是有益的（但不是必需的）：

# os.environ["LANGCHAIN_TRACING_V2"] = "true"
# os.environ["LANGCHAIN_API_KEY"] = getpass.getpass()

实例化

这里我们展示如何实例化一个Tavily搜索工具的实例，使用

from langchain_community.tools import TavilySearchResults

tool = TavilySearchResults(
    max_results=5,
    search_depth="advanced",
    include_answer=True,
    include_raw_content=True,
    include_images=True,
    # include_domains=[...],
    # exclude_domains=[...],
    # name="...",            # overwrite default tool name
    # description="...",     # overwrite default tool description
    # args_schema=...,       # overwrite default args_schema: BaseModel
)

API Reference:TavilySearchResults

调用

直接使用参数调用

TavilySearchResults 工具接受一个单一的 "query" 参数，该参数应该是一个自然语言查询：

tool.invoke({"query": "What happened at the last wimbledon"})

[{'url': 'https://www.theguardian.com/sport/live/2023/jul/16/wimbledon-mens-singles-final-2023-carlos-alcaraz-v-novak-djokovic-live?page=with:block-64b3ff568f08df28470056bf',
  'content': 'Carlos Alcaraz recovered from a set down to topple Djokovic 1-6, 7-6(6), 6-1, 3-6, 6-4 and win his first Wimbledon title in a battle for the ages'},
 {'url': 'https://www.nytimes.com/athletic/live-blogs/wimbledon-2024-live-updates-alcaraz-djokovic-mens-final-result/kJJdTKhOgkZo/',
  'content': "It was Djokovic's first straight-sets defeat at Wimbledon since the 2013 final, when he lost to Andy Murray. Below, The Athletic 's writers, Charlie Eccleshare and Matt Futterman, analyze the ..."},
 {'url': 'https://www.foxsports.com.au/tennis/wimbledon/fk-you-stars-explosion-stuns-wimbledon-as-massive-final-locked-in/news-story/41cf7d28a12845cdab6be4150a22a170',
  'content': 'The last time Djokovic and Wimbledon met was at the French Open in June when the Serb claimed victory in a third round tie which ended at 3:07 in the morning. On Friday, however, Djokovic was ...'},
 {'url': 'https://www.cnn.com/2024/07/09/sport/novak-djokovic-wimbledon-crowd-quarterfinals-spt-intl/index.html',
  'content': 'Novak Djokovic produced another impressive performance at Wimbledon on Monday to cruise into the quarterfinals, but the 24-time grand slam champion was far from happy after his win.'},
 {'url': 'https://www.cnn.com/2024/07/05/sport/andy-murray-wimbledon-farewell-ceremony-spt-intl/index.html',
  'content': "It was an emotional night for three-time grand slam champion Andy Murray on Thursday, as the 37-year-old's Wimbledon farewell began with doubles defeat.. Murray will retire from the sport this ..."}]

使用ToolCall调用

我们也可以使用模型生成的ToolCall来调用工具，在这种情况下，将返回一个ToolMessage：

# This is usually generated by a model, but we'll create a tool call directly for demo purposes.
model_generated_tool_call = {
    "args": {"query": "euro 2024 host nation"},
    "id": "1",
    "name": "tavily",
    "type": "tool_call",
}
tool_msg = tool.invoke(model_generated_tool_call)

# The content is a JSON string of results
print(tool_msg.content[:400])

[{"url": "https://www.radiotimes.com/tv/sport/football/euro-2024-location/", "content": "Euro 2024 host cities. Germany have 10 host cities for Euro 2024, topped by the country's capital Berlin. Berlin. Cologne. Dortmund. Dusseldorf. Frankfurt. Gelsenkirchen. Hamburg."}, {"url": "https://www.sportingnews.com/ca/soccer/news/list-euros-host-nations-uefa-european-championship-countries/85f8069d69c9f4

# The artifact is a dict with richer, raw results
{k: type(v) for k, v in tool_msg.artifact.items()}

{'query': str,
 'follow_up_questions': NoneType,
 'answer': str,
 'images': list,
 'results': list,
 'response_time': float}

import json

# Abbreviate the results for demo purposes
print(json.dumps({k: str(v)[:200] for k, v in tool_msg.artifact.items()}, indent=2))

{
  "query": "euro 2024 host nation",
  "follow_up_questions": "None",
  "answer": "Germany will be the host nation for Euro 2024, with the tournament scheduled to take place from June 14 to July 14. The matches will be held in 10 different cities across Germany, including Berlin, Co",
  "images": "['https://i.ytimg.com/vi/3hsX0vLatNw/maxresdefault.jpg', 'https://img.planetafobal.com/2021/10/sedes-uefa-euro-2024-alemania-fg.jpg', 'https://editorial.uefa.com/resources/0274-14fe4fafd0d4-413fc8a7b7",
  "results": "[{'title': 'Where is Euro 2024? Country, host cities and venues', 'url': 'https://www.radiotimes.com/tv/sport/football/euro-2024-location/', 'content': \"Euro 2024 host cities. Germany have 10 host cit",
  "response_time": "3.97"
}

链式调用

我们可以通过首先将其绑定到工具调用模型，然后调用它来在链中使用我们的工具：

Select chat model:

pip install -qU langchain-openai

import getpass
import os

if not os.environ.get("OPENAI_API_KEY"):
  os.environ["OPENAI_API_KEY"] = getpass.getpass("Enter API key for OpenAI: ")

from langchain_openai import ChatOpenAI

llm = ChatOpenAI(model="gpt-4o-mini")

import datetime

from langchain_core.prompts import ChatPromptTemplate
from langchain_core.runnables import RunnableConfig, chain

today = datetime.datetime.today().strftime("%D")
prompt = ChatPromptTemplate(
    [
        ("system", f"You are a helpful assistant. The date today is {today}."),
        ("human", "{user_input}"),
        ("placeholder", "{messages}"),
    ]
)

# specifying tool_choice will force the model to call this tool.
llm_with_tools = llm.bind_tools([tool])

llm_chain = prompt | llm_with_tools


@chain
def tool_chain(user_input: str, config: RunnableConfig):
    input_ = {"user_input": user_input}
    ai_msg = llm_chain.invoke(input_, config=config)
    tool_msgs = tool.batch(ai_msg.tool_calls, config=config)
    return llm_chain.invoke({**input_, "messages": [ai_msg, *tool_msgs]}, config=config)


tool_chain.invoke("who won the last womens singles wimbledon")

API Reference:ChatPromptTemplate | RunnableConfig | chain

AIMessage(content="The last women's singles champion at Wimbledon was Markéta Vondroušová, who won the title in 2023.", response_metadata={'token_usage': {'completion_tokens': 26, 'prompt_tokens': 802, 'total_tokens': 828}, 'model_name': 'gpt-4o-2024-05-13', 'system_fingerprint': 'fp_4e2b2da518', 'finish_reason': 'stop', 'logprobs': None}, id='run-2bfeec6e-8f04-477e-bf51-9500f18bd514-0', usage_metadata={'input_tokens': 802, 'output_tokens': 26, 'total_tokens': 828})

这是本次运行的LangSmith 跟踪。

API参考

有关所有TavilySearchResults功能和配置的详细文档，请访问API参考：https://python.langchain.com/api_reference/community/tools/langchain_community.tools.tavily_search.tool.TavilySearchResults.html

工具概念指南
工具操作指南

概述​

集成详情​

工具特性​

设置​

凭证​

实例化​

调用​

直接使用参数调用​

使用ToolCall调用​

链式调用​

API参考​

相关​

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概述