This comprehensive LangChain project handbook equips Python developers with 15 complete, runnable AI agent builds that go far beyond toy examples. Master retrieval-augmented generation (RAG), LangChain agents, vector stores, prompt engineering, memory management, and multi-agent collaboration through production-grade Python code. Every chapter delivers step-by-step LangChain tutorials with fully explained, adaptable scripts that connect LangChain to real data sources, APIs, and databases. From beginner-friendly LangChain chatbots to advanced autonomous AI applications deployed with FastAPI and Docker, you'll construct customer support bots, research assistants, financial data analyzers, and coordinating multi-agent workflows. Each project emphasizes LangChain RAG techniques, tool integration, reliable output engineering, and scalable deployment-giving you a portfolio of production-ready AI systems that showcase expertise in LangChain agents for production environments.
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