🧠 Contextual RAG Chatbot (Groq + FAISS)

run in google colab

This project is a Retrieval-Augmented Generation (RAG) chatbot that uses:

• Groq LLM (llama-3.3-70b-versatile) for reasoning and answering questions
• FAISS for vector search
• Sentence Transformers (all-MiniLM-L6-v2) for embeddings
• Gradio for an interactive chatbot UI
• Contextual Compression Retriever with a custom Groq-based compressor for more precise answers

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📌 Features

• Upload or use a text file (notes.txt) as your knowledge base.
• Splits the text into chunks using RecursiveCharacterTextSplitter.
• Stores chunks in FAISS vector DB with HuggingFace embeddings.
• Retrieves relevant context using FAISS or Compressed Retriever (Groq LLM).
• Answers queries only based on the given context.
• Provides two modes:
  • Compressed: Uses Groq to extract only the most relevant snippets.
  • Raw: Direct retrieval from FAISS without compression.

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