Build a Local RAG System with LangChain and ChromaDB

RAG lets LLMs answer questions based on your private data. Build one that runs entirely locally with privacy, no API costs, and full control. Architecture includes Document Loader for PDF/Word/TXT/Markdown, Text Splitter, Embedding Model using BGE, Vector DB with ChromaDB, and LLM Interface supporting OpenAI or Ollama. Full code includes 400+ lines with RAGSystem class and Gradio web UI.