# 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](https://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](https://huggingface.co/spaces/NyashaK/DocOCR2JSON)

**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:
    ```bash
    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.