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.

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Established

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.

AI engineering machine learning operations generative AI development LLM application development data science
No Package No Dependents
Maintenance 13 / 25
Adoption 10 / 25
Maturity 16 / 25
Community 25 / 25

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Stars

1,287

Forks

535

Language

Jupyter Notebook

License

MIT

Last pushed

Mar 09, 2026

Commits (30d)

1

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