LangChain Agent Example: Empower Your Applications with Intelligent Tools
Agents
import { ChatOpenAI } from "@langchain/openai";
import { HumanMessage, AIMessage } from "@langchain/core/messages";
import * as dotenv from "dotenv";
dotenv.config();
async function main() {
const chatModel = new ChatOpenAI({
modelName: "gpt-3.5-turbo",
temperature: 0.7,
openAIApiKey: process.env.OPENAI_API_KEY!,
});
const chatHistory = [
new HumanMessage("What is LangChain?"),
new AIMessage("LangChain is a framework for building applications powered by language models."),
new HumanMessage("What are its key features?"),
];
chatHistory.push(new HumanMessage("Can you provide an example of how to use it?"));
const response = await chatModel.call(chatHistory);
console.log("Chat History Example:");
console.log("Response:", response.text || response);
}
main().catch(console.error);
Explore how to build intelligent agents using LangChain and OpenAI. This tutorial showcases a practical implementation of a LangChain Agent that integrates a custom calculator tool for performing arithmetic operations. Learn how to empower your applications with reactive and task-oriented capabilities, ideal for interactive and dynamic user experiences.
https://js.langchain.com/docs/Conclusion
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