npm install @langchain/tavily

process.env.TAVILY_API_KEY = "YOUR_API_KEY";

import { TavilySearch } from "@langchain/tavily";

const tool = new TavilySearch({
  maxResults: 5,
  // You can set other constructor parameters here, e.g.:
  // topic: "general",
  // includeAnswer: false,
  // includeRawContent: false,
  // includeImages: false,
  // searchDepth: "basic",
});

// Invoke with a query
const results = await tool.invoke({
  query: "what is the current weather in SF?",
});

console.log(results);

import { TavilyExtract } from "@langchain/tavily";

const tool = new TavilyExtract({
  // Constructor parameters:
  // extractDepth: "basic",
  // includeImages: false,
});

// Invoke with a list of URLs
const results = await tool.invoke({
  urls: ["https://en.wikipedia.org/wiki/Lionel_Messi"],
});

console.log(results);

import { TavilyResearch } from "@langchain/tavily";

const tool = new TavilyResearch({
  // Optional constructor defaults:
  // model: "auto",
  // stream: false,
  // citationFormat: "numbered",
  // apiBaseUrl: "https://api.tavily.com",
});

// Invoke with a research task
const result = await tool.invoke({
  input: "Research the latest developments in AI",
  model: "mini",
  citationFormat: "apa",
});

console.log(result);

import { TavilyGetResearch } from "@langchain/tavily";

const tool = new TavilyGetResearch({
  // Optional constructor parameters:
  // apiBaseUrl: "https://api.tavily.com",
});

// Invoke with a request_id returned from TavilyResearch
const result = await tool.invoke({
  requestId: "your-request-id-here",
});

console.log(result);

import { TavilyCrawl } from "@langchain/tavily";

const tool = new TavilyCrawl({
  // Constructor parameters:
  // extractDepth: "basic",
  // format: "markdown",
  // maxDepth: 3,
  // maxBreadth: 50,
  // limit: 100,
  // includeImages: false,
  // allowExternal: false,
});

// Invoke with a URL and optional parameters
const results = await tool.invoke({
  url: "https://docs.tavily.com/",
  instructions: "Find information about the LangChain integration.",
});

console.log(results);

import { TavilyMap } from "@langchain/tavily";

const tool = new TavilyMap({
  // Constructor parameters:
  // maxDepth: 3,
  // maxBreadth: 50,
  // limit: 100,
  // allowExternal: false,
});

// Invoke with a URL and optional parameters
const results = await tool.invoke({
  url: "https://docs.tavily.com/",
});

console.log(results);