Generative AI Document Summarizer

A tool for summarizing PDF documents using various AI models including OpenAI, Azure OpenAI, and Llama.

Features

• Extract text from PDF documents
• Generate summaries using different AI models:
  • OpenAI (GPT-4)
  • Azure OpenAI
  • Llama (local model)
• Create formatted Word documents with the summaries
• Customizable section templates

Installation

1. Clone the repository:

git clone https://github.com/hermesdev0131/Generative_AI_Document_Summarizer.git
cd Generative_AI_Document_Summarizer

2. Install the required dependencies:

pip install -r requirements.txt

3. Configure your environment variables by creating a .env file:

# Model type: "openai", "azure", or "llama"
MODEL_TYPE=openai

# OpenAI configuration (used when MODEL_TYPE=openai)
OPENAI_API_KEY=your_openai_api_key_here

# Azure OpenAI configuration (used when MODEL_TYPE=azure)
AZURE_OPENAI_API_KEY=your_azure_api_key_here
AZURE_OPENAI_ENDPOINT=https://your-resource-name.openai.azure.com/
AZURE_OPENAI_DEPLOYMENT_NAME=your-deployment-name

# Llama configuration (used when MODEL_TYPE=llama)
LLAMA_MODEL_PATH=/path/to/your/models/model.gguf

Usage

1. Place your PDF documents in the input_doc directory.

2. Run the main script:

python main.py

3. The summarized documents will be saved as Word files in the output_doc directory.

Configuration

Model Selection

You can choose between three different AI models by setting the MODEL_TYPE environment variable in your .env file:

• openai: Uses the OpenAI GPT-4 model
• azure: Uses Azure OpenAI services
• llama: Uses a local Llama model

Template Customization

You can customize the template sections by modifying the template_sections.py file or by providing a template document in the template_doc directory.

Requirements

• Python 3.8+
• Required packages (see requirements.txt)
• For Llama model: A compatible GGUF model file

License

MIT License