🧠 RAG-Based ChatBot (Offline)

📖 Overview

This project implements a Retrieval-Augmented Generation (RAG) chatbot that answers questions based on user-provided PDF documents.

• 📄 Dynamic knowledge base — user uploads PDFs which are split into paragraphs
• ⚙️ Embeddings using Sentence Transformers — converts text into vectors
• 🧱 FAISS-based retrieval — efficiently finds the most relevant paragraphs
• 🤖 Text generation using Flan-T5 — generates answers using retrieved context
• 💻 Local inference — runs on CPU, Apple MPS, or NVIDIA CUDA GPU
• 🖥️ Gradio UI — web interface for uploading PDFs and asking questions
• 🛠️ Lazy model loading — model loads only on first query for faster startup

---

🖼️ Application Screenshot

Below is a preview of the Gradio Interface used for real-time classification:

🧩 Libraries

• PyTorch – model and inference
• Transformers – Flan-T5 text generation
• sentence-transformers – embeddings
• faiss – vector retrieval
• numpy – numerical operations
• PyPDF2 – PDF parsing
• gradio – UI interface

---

⚙️ Requirements

• Python 3.13+
• Recommended editor: VS Code

---

📦 Installation

• Clone the repository

git clone https://github.com/hurkanugur/RAG-Based-ChatBot.git

• Navigate to the RAG-Based-ChatBot directory

cd RAG-Based-ChatBot

• Install dependencies

pip install -r requirements.txt

---

🔧 Setup Python Environment in VS Code

1. View → Command Palette → Python: Create Environment
2. Choose Venv and your Python version
3. Select requirements.txt to install dependencies
4. Click OK

---

📂 Project Structure

assets/
└── app_screenshot.png            # Application screenshot

src/
├── config.py                     # Paths, model settings...
├── device_manager.py             # Selects and manages compute device
├── embeddings.py                 # Local embedding model
├── retriever.py                  # FAISS-based retrieval
├── generator.py                  # Text generation model
├── pdf_loader.py                 # PDF parsing
└── ui.py                         # Gradio UI

main/
└── main.py                       # Entry point for chatbot

requirements.txt                  # Python dependencies

---

📂 System Architecture

User PDF Upload
    ↓
PDF Loader (split into paragraphs)
    ↓
Sentence Transformer Embeddings
    ↓
FAISS Retriever (top-k relevant paragraphs)
    ↓
Flan-T5 Generator (with retrieved context)
    ↓
Answer displayed in Gradio UI

---

📂 Run the Application

Navigate to the project directory:

cd RAG-Based-ChatBot

Run the app:

python -m main.main

or

python3 -m main.main