Langchain Multi Agent Example

LangChain Multi-Agent Example

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Comprehensive tutorial and code examples for building multi-agent systems with LangChain

🚀 Overview

This repository provides a complete, production-ready example of building multi-agent systems using LangChain. It demonstrates how to create specialized AI agents that can collaborate to solve complex tasks through orchestration patterns.

🎯 What You'll Learn

• Agent Architecture: Design patterns for AI agents
• Multi-Agent Orchestration: Coordinate multiple agents effectively
• Tool Integration: Equip agents with external tools and APIs
• Memory Management: Implement conversation and context memory
• Error Handling: Build robust multi-agent systems
• Performance Optimization: Optimize for cost and speed

✨ Features

• Complete Working Examples: Copy-paste ready code
• Step-by-Step Tutorials: From basic to advanced patterns
• Production Best Practices: Security, testing, deployment
• Real-World Use Cases: Practical applications
• TypeScript: Full type safety
• Jest Tests: Comprehensive test coverage

📋 Prerequisites

• Node.js 18+ installed
• Basic knowledge of TypeScript
• Understanding of async/await patterns
• API keys for OpenAI and/or Anthropic

🚦 Quick Start

1. Clone and Install

git clone https://github.com/groovy-web/langchain-multi-agent-example.git
cd langchain-multi-agent-example
npm install

2. Set Up Environment

cp .env.example .env

Edit `.env` and add your API keys:

OPENAI_API_KEY=sk-your-openai-key
ANTHROPIC_API_KEY=sk-ant-your-anthropic-key
TAVILY_API_KEY=tvly-your-tavily-key  # For search
SERPER_API_KEY=your-serper-key