TavilySearchAPIRetriever
Tavily 的搜索 API 是专为 AI 代理(LLMs)构建的搜索引擎,能够快速提供实时、准确且基于事实的结果。
概述
这将帮助您开始使用 Tavily 搜索 API
检索器。如需了解TavilySearchAPIRetriever所有功能和配置的详细文档,请访问API 参考文档。
集成详情
| 检索器 | 来源 | 包 |
|---|---|---|
TavilySearchAPIRetriever | 网络上的信息。 | @langchain/community |
准备工作
您需要使用您的 Tavily
API 密钥填充TAVILY_API_KEY环境变量,或者在构造函数中以apiKey参数传入。通过他们的网站注册获取密钥。
如果您希望从单个查询中获得自动追踪信息,也可以取消以下代码的注释并设置您的LangSmith API 密钥:
// process.env.LANGSMITH_API_KEY = "<YOUR API KEY HERE>";
// process.env.LANGSMITH_TRACING = "true";
安装
此检索器位于@langchain/community包中:
:::提示 请参阅安装集成包的一般说明部分。 :::
- npm
- yarn
- pnpm
npm i @langchain/community @langchain/core
yarn add @langchain/community @langchain/core
pnpm add @langchain/community @langchain/core
实例化
现在我们可以实例化检索器:
import { TavilySearchAPIRetriever } from "@langchain/community/retrievers/tavily_search_api";
const retriever = new TavilySearchAPIRetriever({
k: 3,
});
有关允许参数的完整列表,请参阅官方文档。您可以通过kwargs对象将任何参数传递给 SDK。
用法
const query = "what is the current weather in SF?";
await retriever.invoke(query);
[
Document {
pageContent: "{'location': {'name': 'San Francisco', 'region': 'California', 'country': 'United States of America', 'lat': 37.78, 'lon': -122.42, 'tz_id': 'America/Los_Angeles', 'localtime_epoch': 1722900266, 'localtime': '2024-08-05 16:24'}, 'current': {'last_updated_epoch': 1722899700, 'last_updated': '2024-08-05 16:15', 'temp_c': 16.8, 'temp_f': 62.2, 'is_day': 1, 'condition': {'text': 'Partly Cloudy', 'icon': '//cdn.weatherapi.com/weather/64x64/day/116.png', 'code': 1003}, 'wind_mph': 13.2, 'wind_kph': 21.2, 'wind_degree': 261, 'wind_dir': 'W', 'pressure_mb': 1014.0, 'pressure_in': 29.94, 'precip_mm': 0.0, 'precip_in': 0.0, 'humidity': 74, 'cloud': 60, 'feelslike_c': 16.8, 'feelslike_f': 62.2, 'windchill_c': 16.8, 'windchill_f': 62.2, 'heatindex_c': 16.8, 'heatindex_f': 62.2, 'dewpoint_c': 12.3, 'dewpoint_f': 54.1, 'vis_km': 10.0, 'vis_miles': 6.0, 'uv': 5.0, 'gust_mph': 17.3, 'gust_kph': 27.8}}",
metadata: {
title: 'Weather in San Francisco',
source: 'https://www.weatherapi.com/',
score: 0.9947009,
images: []
},
id: undefined
},
Document {
pageContent: 'Current Weather for Popular Cities . San Francisco, CA 56 ° F Mostly Cloudy; Manhattan, NY warning 85 ° F Fair; Schiller Park, IL (60176) 71 ° F Mostly Cloudy; Boston, MA warning 84 ° F Partly ...',
metadata: {
title: 'San Francisco, CA Hourly Weather Forecast | Weather Underground',
source: 'https://www.wunderground.com/hourly/us/ca/san-francisco/date/2024-08-02',
score: 0.9859904,
images: []
},
id: undefined
},
Document {
pageContent: 'San Francisco CA 37.77°N 122.41°W (Elev. 131 ft) Last Update: 2:42 pm PDT Aug 4, 2024. Forecast Valid: 5pm PDT Aug 4, 2024-6pm PDT Aug 11, 2024 . Forecast Discussion . Additional Resources. Radar & Satellite Image. Hourly Weather Forecast. ... Severe Weather ; Current Outlook Maps ; Drought ; Fire Weather ; Fronts/Precipitation Maps ; Current ...',
metadata: {
title: 'National Weather Service',
source: 'https://forecast.weather.gov/zipcity.php?inputstring=San+Francisco,CA',
score: 0.98141783,
images: []
},
id: undefined
}
]
在链中使用
与其他检索器一样,TavilySearchAPIRetriever 可以通过
链(chains) 集成到 LLM 应用程序中。
我们需要一个 LLM 或聊天模型:
Pick your chat model:
- Groq
- OpenAI
- Anthropic
- Google Gemini
- FireworksAI
- MistralAI
- VertexAI
Install dependencies
- npm
- yarn
- pnpm
npm i @langchain/groq
yarn add @langchain/groq
pnpm add @langchain/groq
Add environment variables
GROQ_API_KEY=your-api-key
Instantiate the model
import { ChatGroq } from "@langchain/groq";
const llm = new ChatGroq({
model: "llama-3.3-70b-versatile",
temperature: 0
});
Install dependencies
- npm
- yarn
- pnpm
npm i @langchain/openai
yarn add @langchain/openai
pnpm add @langchain/openai
Add environment variables
OPENAI_API_KEY=your-api-key
Instantiate the model
import { ChatOpenAI } from "@langchain/openai";
const llm = new ChatOpenAI({
model: "gpt-4o-mini",
temperature: 0
});
Install dependencies
- npm
- yarn
- pnpm
npm i @langchain/anthropic
yarn add @langchain/anthropic
pnpm add @langchain/anthropic
Add environment variables
ANTHROPIC_API_KEY=your-api-key
Instantiate the model
import { ChatAnthropic } from "@langchain/anthropic";
const llm = new ChatAnthropic({
model: "claude-3-5-sonnet-20240620",
temperature: 0
});
Install dependencies
- npm
- yarn
- pnpm
npm i @langchain/google-genai
yarn add @langchain/google-genai
pnpm add @langchain/google-genai
Add environment variables
GOOGLE_API_KEY=your-api-key
Instantiate the model
import { ChatGoogleGenerativeAI } from "@langchain/google-genai";
const llm = new ChatGoogleGenerativeAI({
model: "gemini-2.0-flash",
temperature: 0
});
Install dependencies
- npm
- yarn
- pnpm
npm i @langchain/community
yarn add @langchain/community
pnpm add @langchain/community
Add environment variables
FIREWORKS_API_KEY=your-api-key
Instantiate the model
import { ChatFireworks } from "@langchain/community/chat_models/fireworks";
const llm = new ChatFireworks({
model: "accounts/fireworks/models/llama-v3p1-70b-instruct",
temperature: 0
});
Install dependencies
- npm
- yarn
- pnpm
npm i @langchain/mistralai
yarn add @langchain/mistralai
pnpm add @langchain/mistralai
Add environment variables
MISTRAL_API_KEY=your-api-key
Instantiate the model
import { ChatMistralAI } from "@langchain/mistralai";
const llm = new ChatMistralAI({
model: "mistral-large-latest",
temperature: 0
});
Install dependencies
- npm
- yarn
- pnpm
npm i @langchain/google-vertexai
yarn add @langchain/google-vertexai
pnpm add @langchain/google-vertexai
Add environment variables
GOOGLE_APPLICATION_CREDENTIALS=credentials.json
Instantiate the model
import { ChatVertexAI } from "@langchain/google-vertexai";
const llm = new ChatVertexAI({
model: "gemini-1.5-flash",
temperature: 0
});
import { ChatPromptTemplate } from "@langchain/core/prompts";
import {
RunnablePassthrough,
RunnableSequence,
} from "@langchain/core/runnables";
import { StringOutputParser } from "@langchain/core/output_parsers";
import type { Document } from "@langchain/core/documents";
const prompt = ChatPromptTemplate.fromTemplate(`
Answer the question based only on the context provided.
Context: {context}
Question: {question}`);
const formatDocs = (docs: Document[]) => {
return docs.map((doc) => doc.pageContent).join("\n\n");
};
// See https://js.langchain.com/docs/tutorials/rag
const ragChain = RunnableSequence.from([
{
context: retriever.pipe(formatDocs),
question: new RunnablePassthrough(),
},
prompt,
llm,
new StringOutputParser(),
]);
await ragChain.invoke(query);
The current weather in San Francisco is partly cloudy with a temperature of 16.8°C (62.2°F). The wind is coming from the west at 13.2 mph (21.2 kph), and the humidity is at 74%. There is no precipitation, and visibility is 10 km (6 miles).
API 参考文档
如需详细了解所有 TavilySearchAPIRetriever 的功能和配置,请访问 API
参考文档。
Related
- Retriever conceptual guide
- Retriever how-to guides