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Build a Document Q&A Bot with RAG: A Step-by-Step Tutorial

1. What is RAG and Why Use It?

• Understand the core concept: retrieving relevant document chunks and feeding them to an LLM for grounded answers.
• Key benefits: reduces hallucination, works with your proprietary data, and scales beyond the LLM's training cutoff.
• Real‑world use cases: internal knowledge bases, customer support, legal document analysis, and education.

2. Setting Up Your Environment

• Install Python 3.10+ and create a virtual environment.
• Install essential libraries: `langchain`, `openai`, `chromadb`, `pypdf` (or `unstructured` for diverse file types).
• Obtain API keys: OpenAI API key (for embeddings and
  

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