benman1/generative_ai_with_langchain
Build production-ready LLM applications and advanced agents using Python, LangChain, and LangGraph. This is the companion repository for the book on generative AI with LangChain.
This project provides practical code examples for building advanced applications and autonomous agents using large language models (LLMs). It guides you through creating systems that can understand complex requests, interact with tools, and generate sophisticated outputs. If you're an AI engineer, machine learning practitioner, or data scientist looking to move your LLM prototypes into reliable, enterprise-grade production systems, this resource is for you.
1,287 stars. Actively maintained with 1 commit in the last 30 days.
Use this if you need to develop, deploy, and scale robust LLM applications, especially those involving multi-agent architectures or advanced retrieval-augmented generation (RAG) pipelines.
Not ideal if you are looking for a conceptual overview of generative AI without hands-on coding examples or if your primary interest is not in building production-ready LLM systems.
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MIT
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Last pushed
Mar 09, 2026
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