benman1/generative_ai_with_langchain
Jupyter notebook-based code examples demonstrating how to build production LLM applications and advanced agents with LangChain and LangGraph.

This repository contains Jupyter notebooks that walk through building production-ready LLM applications and advanced agents using Python, LangChain, and LangGraph. The material covers integrating with multiple LLM providers including OpenAI, Anthropic Claude, DeepSeek, and Hugging Face models, as well as deploying with tools like Ollama and llama.cpp. Topics include RAG, agent orchestration, prompt engineering, and enterprise deployment patterns.