Q-A-Chatbot-with-RAG

🛠 Features

• Upload and load multiple PDF documents
• Split documents into chunks for better semantic search
• Embed documents using HuggingFace Sentence Transformers
• Store embeddings in FAISS vector store for fast similarity search
• Integrate with Groq LLM (llama-3.1-8b-instant) for generating answers
• Streamlit web interface for interactive Q&A
• Optional display of source documents (context) used in answers
• Fully local embedding support (no external API costs)

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💻 Tech Stack

• Python 3.10+
• LangChain
• LangChain-HuggingFace embeddings
• FAISS for vector storage
• Streamlit for UI
• Groq API for LLM