📄 PDF Table Extraction & Summarization

Welcome to the PDF Table Extraction & Summarization project! This application allows you to effortlessly upload PDF documents, extract tables from them, and generate concise summaries using advanced AI models. Built with Streamlit, this tool offers a seamless and interactive user experience.

🚀 Features

• 📤 Upload PDFs: Easily upload your PDF documents through a user-friendly interface.
• 👀 Preview PDFs: View the content of your PDFs directly within the application.
• 📊 Extract Tables: Automatically detect and extract tables from your uploaded PDFs.
• 📝 Summarize Tables: Generate insightful summaries of each extracted table using AI-powered summarization.
• 🧹 Automatic Cleanup: Ensures temporary files are deleted after processing to maintain security and efficiency.

🛠️ Installation

Follow these steps to set up the project locally:

1. 🔀 Clone the Repository:

   git clone https://github.com/PUndead/Analyzing-Income-Statement-BalanceSheet-Table-with-OpenAI.git

2. 📥 Install Required System Dependencies:

   ⚠️ Python Compatibility: This project requires Python version 3.9 to 3.11 (3.10 recommended). Python 3.13 is not supported by some dependencies.

   Version Notes:

   • ✅ Python 3.9: Fully compatible
   • ✅ Python 3.10: Recommended version (best stability)
   • ✅ Python 3.11: Compatible but some packages might need additional setup
   • ❌ Python 3.8: Too old, missing required features
   • ❌ Python 3.12+: Not supported by key dependencies

   First, ensure you have the correct Python version:

   # Check Python version
   python --version  # Windows
   python3 --version  # macOS/Linux

   Windows:

   # Install Python 3.10 if needed
   winget install Python.Python.3.10
   
   # Create virtual environment with Python 3.10
   py -3.10 -m venv venv
   
   # Activate virtual environment
   venv\Scripts\activate
   
   # Upgrade pip
   python -m pip install --upgrade pip
   
   # Verify Python version
   python --version  # Should show Python 3.10.x

   macOS/Linux:

   # Install Python 3.10 if needed
   brew install [email protected]
   
   # Create virtual environment with Python 3.10
   python3.10 -m venv venv
   
   # Activate virtual environment
   source venv/bin/activate
   
   # Upgrade pip
   pip3 install --upgrade pip
   
   # Verify Python version
   python3 --version  # Should show Python 3.10.x

   If you have multiple Python versions installed, you can also use these alternative paths:

   # Windows alternative
   C:\Python310\python -m venv venv
   
   # macOS alternative (Intel)
   /usr/local/opt/[email protected]/bin/python3.10 -m venv venv
   
   # macOS alternative (Apple Silicon)
   /opt/homebrew/opt/[email protected]/bin/python3.10 -m venv venv

   If you encounter any PyTorch-related errors:

   1. Visit PyTorch Get Started
   2. Select your operating system and preferences
   3. Use the provided installation command before installing other requirements

   Windows:

   # Install Poppler
   winget install poppler
   # OR download from: http://blog.alivate.com.au/poppler-windows/
   
   # Install Tesseract
   winget install tesseract-ocr
   # OR download installer from: https://github.com/UB-Mannheim/tesseract/wiki

   macOS:

   First, install Homebrew if you haven't already:

   # Install Homebrew
   /bin/bash -c "$(curl -fsSL https://raw.githubusercontent.com/Homebrew/install/HEAD/install.sh)"
   
   # After installation, add Homebrew to your PATH:
   # For Intel Macs
   echo 'eval "$(/usr/local/bin/brew shellenv)"' >> ~/.zshrc
   # For Apple Silicon Macs
   echo 'eval "$(/opt/homebrew/bin/brew shellenv)"' >> ~/.zshrc
   
   # Reload your shell configuration
   source ~/.zshrc

   Then install the required dependencies:

   # Install Poppler
   brew install poppler
   
   # Install Tesseract
   brew install tesseract

3. 📦 Install Dependencies:

   pip install -r requirements.txt

4. 🔑 Configure Hugging Face:

   a. Create a Hugging Face account at https://huggingface.co/

   b. Generate an access token:

   • Go to https://huggingface.co/settings/tokens
   • Click "New token"
   • Name your token and select "read" role
   • Copy the generated token

   c. Login using the CLI:

   Windows:

   huggingface-cli login
   # Enter your token when prompted

   macOS/Linux:

   huggingface-cli login
   # Enter your token when prompted

   d. Set up environment variable:

   Windows:

   setx HUGGING_FACE_TOKEN "your_token_here"

   macOS/Linux:

   echo "export HUGGING_FACE_TOKEN='your_token_here'" >> ~/.zshrc
   # OR for bash
   echo "export HUGGING_FACE_TOKEN='your_token_here'" >> ~/.bashrc

🖥️ Usage

Run the Streamlit application using the following command:

streamlit run app.py

Once the application starts, follow these steps:

1. 📂 Upload Your PDF:

   • Navigate to the sidebar and use the file uploader to select your PDF document.

2. 🔍 Preview the PDF:

   • After uploading, the application will display a preview of your PDF.

3. 📑 Extract Tables:

   • The app will automatically extract tables from the PDF. View them in expandable sections.

4. 📝 Summarize Tables:

   • Generate and view summaries for each extracted table.

📁 Project Structure

pdf-table-extraction/

├── app.py
├── requirements.txt
├── utils/
│ ├── table_extraction.py
│ └── summarization.py
├── README.md
└── assets/
└── icons/

• app.py: The main Streamlit application file.
• requirements.txt: Lists all the project dependencies.
• utils/: Contains utility modules for table extraction and summarization.
• assets/: (Optional) Directory to store images, icons, or other assets.

🧰 Dependencies

The project relies on the following key libraries:

• Streamlit: For building the interactive web application.
• Pandas: For data manipulation and analysis.
• PyPDF2: For reading and handling PDF files.
• Mistralai: For AI-powered summarization (ensure it's correctly installed and configured).

Full List of Dependencies:

streamlit pandas PyPDF2 mistralai

🌐 Contributing

Contributions are welcome! Please follow these steps to contribute:

1. Fork the Repository

2. Create a New Branch:

   git checkout -b feature/YourFeature

3. Commit Your Changes:

   git commit -m "Add your message here"

4. Push to the Branch:

   git push origin feature/YourFeature

5. Open a Pull Request

📝 License

This project is licensed under the MIT License.

📧 Contact

For any inquiries or feedback, please reach out to SHRIPAD DHAS.

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