🤖 RAG Chatbot

A production-ready Python RAG (Retrieval-Augmented Generation) Chatbot with Streamlit UI. Chat normally or upload PDFs to have AI-powered conversations about your documents.

✨ Features

• 💬 Normal Chat Mode: Have natural conversations with the AI
• 📚 RAG Mode: Upload PDFs and ask questions about their content
• 🔄 Auto-Switch: Automatically switches between normal and RAG mode
• 💾 Persistent Storage: Vector embeddings are saved locally
• ⚙️ Configurable: Adjust chunk size and overlap via UI
• ⚡ Super Fast: Uses Groq API for lightning-fast inference (free tier available)

🛠️ Tech Stack

Component	Technology
LLM	Groq (Llama 3.3 / Mixtral)
Embeddings	sentence-transformers (all-MiniLM-L6-v2)
Vector Store	FAISS
PDF Parsing	PyPDF2
UI	Streamlit
Orchestration	LangChain

📋 Prerequisites

1. Python 3.10+

Make sure you have Python 3.10 or higher installed:

python --version

2. Groq API Key (Free)

Get your free API key from Groq Console:

1. Visit https://console.groq.com/keys
2. Sign in or create an account
3. Click "Create API Key"
4. Copy the key for use in the setup

🚀 Installation

1. Clone/Navigate to Project

cd rag_chatbot

2. Create Virtual Environment (Recommended)

# Create virtual environment
python -m venv venv

# Activate it
# Windows:
venv\Scripts\activate

# macOS/Linux:
source venv/bin/activate

3. Install Dependencies

pip install -r requirements.txt

4. Set API Key

Choose one of these methods:

Option A: Environment Variable (Recommended)

# Windows PowerShell:
$env:GROQ_API_KEY = "your-api-key-here"

# Windows Command Prompt:
set GROQ_API_KEY=your-api-key-here

# macOS/Linux:
export GROQ_API_KEY="your-api-key-here"

Option B: Direct in config.py Edit config.py and add your key:

GROQ_API_KEY = "your-api-key-here"

🎮 Running the App

streamlit run app.py

The app will open in your browser at http://localhost:8501

📖 How to Use

Normal Chat Mode

1. Simply type your message in the chat input
2. Press Enter to send
3. The AI will respond naturally

RAG Mode (Chat with PDFs)

1. Upload PDFs: Use the sidebar to upload one or more PDF files
2. Configure Chunking (optional): Adjust chunk size and overlap
3. Process: Click "Process PDFs" to index the documents
4. Ask Questions: Type questions about your documents
5. View Sources: Expand the "Sources" section to see where answers came from

📁 Project Structure

rag_chatbot/
│
├── app.py                      # Streamlit entry point
├── config.py                   # Configuration settings
├── requirements.txt            # Python dependencies
├── README.md                   # This file
│
├── loaders/
│   ├── __init__.py
│   └── pdf_loader.py           # PDF loading & parsing
│
├── embeddings/
│   ├── __init__.py
│   └── embedder.py             # Sentence transformer embeddings
│
├── vectorstore/
│   ├── __init__.py
│   └── store.py                # FAISS vector storage
│
├── retriever/
│   ├── __init__.py
│   └── retriever.py            # Document retrieval
│
├── chat/
│   ├── __init__.py
│   └── conversation.py         # Groq chat integration
│
├── prompts/
│   ├── __init__.py
│   ├── chat_prompt.py          # Normal chat prompts
│   └── rag_prompt.py           # RAG-specific prompts
│
├── utils/
│   ├── __init__.py
│   └── helpers.py              # Utility functions
│
└── data/
    ├── pdfs/                   # Uploaded PDFs (auto-created)
    └── vectorstore/            # Saved embeddings (auto-created)

⚙️ Configuration

Edit config.py to customize:

# Change the Groq model
GROQ_MODEL = "llama-3.3-70b-versatile"  # or "mixtral-8x7b-32768", etc.

# Adjust default chunking
DEFAULT_CHUNK_SIZE = 1000
DEFAULT_CHUNK_OVERLAP = 200

# Modify retrieval settings
TOP_K_DOCUMENTS = 4
SIMILARITY_THRESHOLD = 0.3

🔧 Troubleshooting

API Key Error

Error: Groq API key not found

Solution:

• Make sure you've set the GROQ_API_KEY environment variable
• Or add it directly to config.py
• Get a free key at: https://console.groq.com/keys

Rate Limit Error

Error: Rate limit reached

Solution:

• Groq's free tier has limits on requests per minute (RPM) and tokens per minute (TPM).
• Wait a few seconds before retrying.
• Switch to a smaller model like llama-3.1-8b-instant in config.py if needed.

🤝 Contributing

Contributions are welcome! Feel free to:

1. Fork the repository
2. Create a feature branch
3. Make your changes
4. Submit a pull request

🙏 Acknowledgments

• Groq for lightning-fast AI inference
• Sentence Transformers for embeddings
• FAISS for vector search
• Streamlit for the UI framework
• LangChain for orchestration