Secure Knowledge-Driven AI Framework

A high-performance Retrieval-Augmented Generation (RAG) chatbot built with FastAPI, LangChain, and FAISS. This system allows users to upload PDF documents and engage in context-aware conversations based on the uploaded data.

Features

• PDF Ingestion: Seamlessly upload and index PDF documents.
• RAG Pipeline: Advanced retrieval using LangChain and FAISS for efficient semantic search.
• Real-time Chat: Interactive web-based chat interface.
• Source Attribution: See exactly which parts of your documents were used to generate answers.
• FastAPI Backend: Robust, typed, and fast API endpoints.

Tech Stack

• Backend: FastAPI, Python
• LLM/RAG: LangChain, OpenAI, Sentence-Transformers
• Vector Database: FAISS
• Frontend: Vanilla JS, HTML, CSS (served via FastAPI)

Setup & Installation

1. Clone the repository:

   git clone <your-repo-url>
   cd chatbot

2. Install dependencies:

   pip install -r backend/requirements.txt

3. Configure Environment Variables: Create a .env file in the root directory and add your API keys:

   OPENAI_API_KEY=your_key_here

4. Run the application:

   uvicorn backend.main:app --reload

5. Access the Chatbot: Open your browser and navigate to http://localhost:8000

Security

This project is designed with security in mind. Ensure that your .env file is never committed to version control (already included in .gitignore).