Zip File Metadata Extractor

This project is a Python application that extracts metadata from files within a zip archive and generates JSON files containing the extracted metadata. It uses Azure OpenAI's language model to analyze and extract relevant information from the file contents.

Features

• Extracts metadata from various file types within a zip archive
• Generates JSON files for each processed file, containing structured metadata
• Handles zip file contents efficiently
• Uses Azure OpenAI's language model for intelligent metadata extraction
• Provides two user interface options:
  1. Custom HTML UI (app.py)
  2. Streamlit-based UI (test.py)

Prerequisites

• Python 3.12
• pipenv

Installation

1. Clone this repository:

   git clone https://github.com/jc2409/jsonify.git
   cd jsonify
   

2. Install dependencies using pipenv:

   pipenv install
   

3. Set up your Azure OpenAI API credentials: Create a .env file in the project root and add your Azure OpenAI API key and version:

   AZURE_OPENAI_API_KEY=your_api_key_here
   AZURE_OPENAI_API_VERSION=your_api_version_here
   

Usage

1. Activate the virtual environment:

   pipenv shell
   

2. Choose your preferred UI option:

   Option 1: Custom HTML UI (app.py)

   Run the Flask application:

   python app.py
   

   Access the application by navigating to http://localhost:5000 in your web browser.

   Option 2: Streamlit UI (test.py)

   Run the Streamlit application:

   streamlit run test.py
   

   Your default web browser should open automatically to the Streamlit app. If not, access it at the URL provided in the terminal.

3. Upload a zip file through the web interface.

4. Process the zip file and view the extracted metadata.

5. Download the generated JSON files containing the metadata.

Customization

• You can modify the FileMetadata class in the Python scripts to adjust the metadata fields extracted from each file.
• The extract_text function can be expanded to handle additional file types for text extraction.
• To customize the Custom HTML UI, edit the HTML templates in the templates folder and update app.py accordingly.
• For Streamlit UI modifications, edit test.py directly.