benman1/generative_ai_with_langchain resource

Health v2 · maintenance only

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1411 stars · 583 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

Companion code repository for the Packt book 'Generative AI with LangChain, Second Edition', containing Jupyter notebook examples for building production-ready LLM applications and agents with Python, LangChain, and LangGraph. It covers multi-agent architectures, RAG pipelines, reasoning techniques, testing, evaluation, and deployment of LLM systems.

Use cases

• learn to build LLM applications with LangChain
• build multi-agent systems with LangGraph
• implement RAG pipelines with re-ranking and hybrid search
• learn agent design patterns and error handling
• evaluate and test LLM applications
• deploy generative AI apps to production
• work with OpenAI, Claude, and Ollama models in Python

When to choose

• you are reading the book and want runnable code examples
• you want hands-on notebooks covering LangChain and LangGraph
• you want practical coverage of RAG, agents, and LLM deployment

When to avoid

• you need a production library rather than educational example code
• you want a framework-agnostic guide without LangChain
• you need a maintained software dependency for a production system

Facets

learning-resource · maturity active

agent-framework rag llm-inference prompt-engineering chatbot large-language-models machine-learning tutorials python cross-platform langchain langgraph book-companion jupyter-notebooks openai huggingface ollama multi-agent-systems generative-ai ai-agents retrieval-augmented-generation

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For agents

markdown · JSON · MCP: product_card(name="benman1/generative_ai_with_langchain")