Lual13012/rag-document-ChatBot-APP

📑 RAG Document Chatbot (RAG Application)

An offline-capable, interactive Retrieval-Augmented Generation (RAG) chatbot that allows you to upload any PDF document and ask questions about its content. This application uses LangChain for orchestration, Groq (Llama 3.3 70B) for ultra-fast inference, and local Hugging Face BGE Embeddings for precise document retrieval.

🚀 Features

• —PDF Document Parsing: Upload any PDF to instantly split and index its pages.
• —In-Memory Vector Store: Uses Chroma DB natively without bloat to isolate document data seamlessly per session.
• —Local Embeddings: Generates vector embeddings locally using the highly efficient BAAI/bge-small-en-v1.5 model.
• —Llama 3.3 Intelligence: Leverages Groq Cloud API for near-instant, highly context-aware responses.
• —Guardrails: Built-in instructions prevent the LLM from making up answers if the information isn't found in the document.
• —Clean Session Management: Sidebar settings to wipe chat histories cleanly and switch documents effortlessly.

🛠️ Tech Stack

• —Frontend UI: Streamlit
• —LLM Orchestration: LangChain / LangChain Core
• —Inference Engine: ChatGroq (Model: llama-3.3-70b-versatile)
• —Vector Database: Chroma
• —Text Embedding Model: Hugging Face Transformers (bge-small-en-v1.5)