RAGs-PDF-Reader 📚🤖

A powerful Retrieval-Augmented Generation (RAG) application that allows you to chat with your PDF documents using state-of-the-art language models. Upload any PDF and ask questions about its content through an intuitive Streamlit web interface.

✨ Features

• 📄 PDF Upload & Processing: Load any PDF document through the web interface
• 🧠 Advanced RAG Pipeline: Uses OpenAI's GPT-OSS models via Hugging Face router
• 💬 Interactive Chat Interface: Ask questions and get intelligent answers about your PDF content
• 📚 Document Chunking: Efficiently splits large documents into manageable chunks
• 🔍 Semantic Search: Uses sentence-transformers for accurate content retrieval
• 💾 Vector Storage: ChromaDB for persistent embedding storage
• 🕒 Chat History: Maintains conversation context across multiple questions
• 🎨 Beautiful UI: Clean and responsive Streamlit interface
• ⚡ Real-time Processing: Fast document processing and question answering

📸 Screenshot

🚀 Complete Installation Guide

Prerequisites

• Python 3.8 or higher (Download Python)
• Git (Download Git)
• Hugging Face API Token (Get one here)

Step 1: Check System Requirements

First, verify your Python installation:

python --version
# or
python3 --version

You should see Python 3.8+ (e.g., "Python 3.9.7" or "Python 3.11.2")

Step 2: Download the Project

Option A: Using Git (Recommended)

git clone https://github.com/aaarif796/RAGs-PDF-Reader.git
cd RAGs-PDF-Reader

Option B: Download ZIP

1. Go to GitHub Repository
2. Click "Code" → "Download ZIP"
3. Extract the ZIP file
4. Navigate to the extracted folder

Step 3: Create Virtual Environment

For Windows:

# Create virtual environment
python -m venv gen_ai

# Activate virtual environment
gen_ai\Scripts\activate

# Verify activation (you should see (gen_ai) in your prompt)

For macOS/Linux:

# Create virtual environment
python3 -m venv gen_ai

# Activate virtual environment
source gen_ai/bin/activate

# Verify activation (you should see (gen_ai) in your prompt)

Using Anaconda (Alternative):

# Create conda environment
conda create -n gen_ai python=3.9 -y

# Activate environment
conda activate gen_ai

Step 4: Install Dependencies

Method 1: Using requirements.txt (Recommended)

# Make sure your virtual environment is activated
pip install -r requirements.txt

Method 2: Manual Installation

If you encounter issues with requirements.txt, install packages individually:

# Core packages
pip install streamlit==1.28.0
pip install langchain
pip install langchain-community
pip install langchain-chroma
pip install langchain-huggingface
pip install langchain-openai
pip install langchain-text-splitters

# Supporting packages
pip install chromadb
pip install sentence-transformers
pip install torch
pip install pypdf
pip install python-dotenv
pip install openai

Step 5: Set Up Environment Variables

Method 1: Create .env file

Create a file named .env in the project root directory:

HUGGINGFACEHUB_API_TOKEN=your_actual_token_here

To get your Hugging Face token:

1. Go to Hugging Face Settings
2. Click "New token"
3. Give it a name (e.g., "RAG-PDF-Reader")
4. Select "Read" permissions
5. Copy the generated token

Method 2: Set Environment Variable Directly

Windows (Command Prompt):

set HUGGINGFACEHUB_API_TOKEN=your_actual_token_here

Windows (PowerShell):

$env:HUGGINGFACEHUB_API_TOKEN="your_actual_token_here"

macOS/Linux:

export HUGGINGFACEHUB_API_TOKEN="your_actual_token_here"

Step 6: Verify Installation

Test if everything is installed correctly:

python -c "import streamlit, langchain, chromadb; print('All packages installed successfully!')"

Step 7: Run the Application

# Make sure you're in the project directory and virtual environment is activated
streamlit run app.py

Expected Output:

You can now view your Streamlit app in your browser.

Local URL: http://localhost:8501
Network URL: http://192.168.1.xxx:8501

Step 8: Use the Application

1. Open your browser and go to http://localhost:8501
2. Click "🤖 Initialize Chatbot" (wait for success message)
3. Upload a PDF file using the file uploader
4. Click "📄 Load PDF" (wait for processing to complete)
5. Ask questions about your PDF in the text area
6. Click "🚀 Ask Question" to get answers

🛠️ Troubleshooting Installation Issues

Common Problems and Solutions

Problem 1: Python Command Not Found

# Try these alternatives:
python3 --version
py --version
python3.9 --version

Problem 2: Permission Errors (Windows)

# Run as administrator or use:
python -m pip install --user -r requirements.txt

Problem 3: Virtual Environment Issues

# Deactivate current environment
deactivate

# Remove old environment
rm -rf gen_ai  # Linux/Mac
rmdir /s gen_ai  # Windows

# Create new environment
python -m venv gen_ai_new

Problem 4: Package Installation Failures

# Upgrade pip first
pip install --upgrade pip

# Install packages one by one
pip install streamlit
pip install langchain
# ... continue with others

Problem 5: ChromaDB Issues

# Install system dependencies (Ubuntu/Debian)
sudo apt-get update
sudo apt-get install build-essential

# For macOS
xcode-select --install

# Alternative: Use SQLite backend
pip install chromadb[sqlite]

Problem 6: Token Issues

# Check if token is set
python -c "import os; print(os.environ.get('HUGGINGFACEHUB_API_TOKEN', 'Token not found'))"

# Test token validity
python -c "from huggingface_hub import HfApi; api = HfApi(); print('Token valid!' if api.whoami() else 'Invalid token')"

Memory Requirements

• Minimum RAM: 8GB
• Recommended RAM: 16GB+
• Storage: 2GB free space (for model downloads)

Port Issues

If port 8501 is already in use:

streamlit run app.py --server.port 8502

🔄 Updating the Project

To get the latest version:

# Navigate to project directory
cd RAGs-PDF-Reader

# Pull latest changes
git pull origin main

# Update dependencies
pip install -r requirements.txt --upgrade

🗂️ Project Structure

RAGs-PDF-Reader/
├── app.py                 # Main Streamlit application
├── pdf_chatbot.py        # Core chatbot class implementation
├── requirements.txt      # Python dependencies
├── .env                  # Environment variables (create this)
├── README.md            # This file
├── chroma_db_temp/      # ChromaDB storage (auto-created)
└── gen_ai/             # Virtual environment (auto-created)

💻 System-Specific Instructions

Windows Users

• Use python instead of python3
• Use backslashes \ in paths
• Consider using PowerShell instead of Command Prompt
• May need Visual Studio Build Tools for some packages

macOS Users

• May need to install Xcode Command Line Tools
• Use python3 explicitly
• Homebrew can help with system dependencies:

  brew install python

Linux Users

• Install system dependencies:

  sudo apt-get update
  sudo apt-get install python3-pip python3-venv build-essential

• Use python3 and pip3 explicitly

Docker Alternative (Advanced)

For consistent environments across all systems:

# Dockerfile
FROM python:3.9-slim

WORKDIR /app
COPY requirements.txt .
RUN pip install -r requirements.txt

COPY . .
EXPOSE 8501

CMD ["streamlit", "run", "app.py"]

# Build and run
docker build -t rag-pdf-reader .
docker run -p 8501:8501 -e HUGGINGFACEHUB_API_TOKEN=your_token rag-pdf-reader

📄 License

This project is licensed under the MIT License - see the LICENSE file for details.

🙏 Acknowledgments

• LangChain for the RAG framework
• Streamlit for the web interface
• Hugging Face for model hosting and APIs
• OpenAI for the GPT-OSS models
• ChromaDB for vector storage

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Made with ❤️ by aaarif796

If this project helped you, please consider giving it a ⭐!