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Zim Docs OCR-to-JSON Extractor

Overview

Welcome to the Zim Docs OCR-to-JSON Extractor! This is a powerful and user-friendly web application built with Gradio, designed to help you upload scanned documents (PDFs) or images (PNG, JPG, etc.). It then uses a vision AI model to perform Optical Character Recognition (OCR) and extract structured information into a JSON format. This tool aims to streamline your process of digitizing and organizing data from various document types, such as driver's licenses, passports, national ID cards, invoices, receipts, and more.

Requirements

To use this application, you'll need:

  • Python 3.7+
  • Gradio
  • Gradio-PDF (gradio_pdf)
  • Requests
  • PyMuPDF (fitz)
  • An API Key from OpenRouter.ai (or any other service compatible with the OpenAI chat completions API format).
    • You should set this key as an environment variable named API_KEY. The Python script uses os.getenv("API_KEY") to retrieve this key. If you're using Hugging Face Spaces, you can set this as a "Secret".

Running the Application

On Hugging Face Spaces:

This application is designed for deployment on Hugging Face Spaces.

  1. Ensure your requirements.txt file in your Hugging Face Space repository lists all necessary dependencies (e.g., gradio, gradio_pdf, requests, PyMuPDF).
  2. You should configure your API_KEY as a "Secret" in your Hugging Face Space settings. The application will then retrieve it using os.getenv("API_KEY").
  3. Once deployed, you can access the application via the URL provided by your Hugging Face Space.
    • Live Demo: You can try out a live demo of this application at: Demo

For Local Development/Testing (Optional):

If you wish to run the application on your local machine:

  1. Make sure you have all dependencies listed under "Requirements" installed in your local Python environment (e.g., by running pip install gradio gradio_pdf requests PyMuPDF).
  2. Set the API_KEY environment variable on your local system.
  3. You can then run the application using the command:
    python app.py
    Replace app.py with the actual name of your Python file. It will typically be available at http://127.0.0.1:7860.

How to Use

  1. Access the Application: Open the URL of your Hugging Face Space where the application is deployed (see Live Demo link above), or your local URL if running it locally.
  2. Upload Your Document:
    • Drag and drop a supported file (PDF, PNG, JPG, etc.) into the designated upload area.
    • Alternatively, click on the upload area to open your file browser and select the document.
  3. View Preview:
    • Once you've uploaded a file, the "Document Preview" tab will attempt to display the image or the first page of your PDF.
  4. Check Extracted Data:
    • The application will automatically process your document.
    • Switch to the "Extracted Data (JSON)" tab to view the structured information extracted by the AI model.
    • If any errors occur during processing (e.g., unsupported file type, API issue), an error message will be displayed in the JSON output area.