SearchApi 工具

SearchApi 工具将您的代理和链连接到互联网。

搜索 API 的包装器。当您需要回答有关当前事件的问题时，此工具非常方便。

用法

输入应为搜索查询。

提示

请参阅 此部分以获取有关安装集成包的一般说明.

npm

npm install @langchain/openai

Yarn

yarn add @langchain/openai

pnpm

pnpm add @langchain/openai

import { ChatOpenAI } from "@langchain/openai";
import { AgentExecutor } from "langchain/agents";
import { ChatPromptTemplate } from "@langchain/core/prompts";
import { RunnableSequence } from "@langchain/core/runnables";
import { AgentFinish, AgentAction } from "@langchain/core/agents";
import { BaseMessageChunk } from "@langchain/core/messages";
import { SearchApi } from "@langchain/community/tools/searchapi";

const model = new ChatOpenAI({
  temperature: 0,
});
const tools = [
  new SearchApi(process.env.SEARCHAPI_API_KEY, {
    engine: "google_news",
  }),
];
const prefix = ChatPromptTemplate.fromMessages([
  [
    "ai",
    "Answer the following questions as best you can. In your final answer, use a bulleted list markdown format.",
  ],
  ["human", "{input}"],
]);
// Replace this with your actual output parser.
const customOutputParser = (
  input: BaseMessageChunk
): AgentAction | AgentFinish => ({
  log: "test",
  returnValues: {
    output: input,
  },
});
// Replace this placeholder agent with your actual implementation.
const agent = RunnableSequence.from([prefix, model, customOutputParser]);
const executor = AgentExecutor.fromAgentAndTools({
  agent,
  tools,
});
const res = await executor.invoke({
  input: "What's happening in Ukraine today?",
});
console.log(res);

API 参考

• ChatOpenAI 来自 @langchain/openai
• AgentExecutor 来自 langchain/agents
• ChatPromptTemplate 来自 @langchain/core/prompts
• RunnableSequence 来自 @langchain/core/runnables
• AgentFinish 来自 @langchain/core/agents
• AgentAction 来自 @langchain/core/agents
• BaseMessageChunk 来自 @langchain/core/messages
• SearchApi 来自 @langchain/community/tools/searchapi

相关

• 工具 概念指南
• 工具 操作指南