---
title: ALDDS
emoji: 💻
colorFrom: indigo
colorTo: red
sdk: gradio
sdk_version: 6.14.0
python_version: '3.13'
app_file: app.py
pinned: false
---

# ⚖️ Automated Legal Document Digitization System (ALDDS)

![Python](https://img.shields.io/badge/Python-3.13-blue.svg)
![Gradio](https://img.shields.io/badge/Gradio-6.14.0-orange.svg)
![MongoDB](https://img.shields.io/badge/MongoDB-Atlas-green.svg)
![Hugging Face](https://img.shields.io/badge/Deploy-Hugging%20Face-yellow.svg)

Upload a photo of a legal document (bailable warrant, summon, etc.) and seamlessly convert it into structured JSON data. ALDDS handles the OCR, AI parsing, secure storage, and live dispatcher notifications in a single streamlined pipeline.

## 🚀 Pipeline & Architecture

```text
Image Upload → Cloudinary Hosting → Tesseract OCR → NVIDIA LLMs → MongoDB → WhatsApp Alert
```

1. **OCR Extraction**: Uses Tesseract to extract raw text from image uploads.
2. **AI Parsing**: Leverages advanced NVIDIA models (`qwen/qwen3-coder-480b-a35b-instruct`, Llama 3) to parse the unstructured OCR text into a strict 10-field JSON schema.
3. **Secure Storage**: Automatically commits the digital record to a MongoDB database.
4. **Live Dashboard**: A real-time, searchable Police Dashboard built directly into the UI.
5. **Instant Notifications**: Dispatchers can notify Investigating Officers (IOs) instantly via zero-cost WhatsApp `wa.me` links populated from an internal CSV database.

---

## 📋 Features

- **Multi-Model Fallback**: The app cycles through a priority list of NVIDIA LLMs ensuring maximum uptime and reliability during the parsing phase.
- **👮 Live Police Dashboard**: A dedicated tab for station dispatchers to monitor incoming warrants. Includes a real-time MongoDB search filter (by Case No, IO Name, Station, etc.).
- **💬 WhatsApp Integration**: Zero-API-cost notifications. Selecting an officer from the dropdown dynamically pulls their phone number from `officers.csv` and opens a pre-filled WhatsApp window for the dispatcher to send manually.

---

## 🔑 Environment Setup

To run ALDDS locally or in the cloud, you need the following API keys configured in a `.env` file (or as Secrets on Hugging Face).

```env
# Cloudinary (Image Hosting)
CLOUDINARY_CLOUD_NAME=your_cloud_name
CLOUDINARY_API_KEY=your_api_key
CLOUDINARY_API_SECRET=your_api_secret

# NVIDIA API (LLM Parsing)
NVIDIA_API_KEY=your_nvidia_api_key

# MongoDB (Database)
MONGODB_URI=mongodb+srv://username:password@cluster0.../?retryWrites=true&w=majority
```

| Variable | Where to get it |
|---|---|
| `CLOUDINARY_*` | [Cloudinary Console](https://console.cloudinary.com/) → Dashboard |
| `NVIDIA_API_KEY` | [NVIDIA Build](https://build.nvidia.com/) → API Catalog → Get API Key |
| `MONGODB_URI` | [MongoDB Atlas](https://www.mongodb.com/cloud/atlas) → Database → Connect |

---

## 💻 Local Installation Guide

### 1. Install Tesseract OCR (System Binary)
Python's `pytesseract` requires the underlying Tesseract engine to be installed on your OS.

**Windows**
1. Download installer from: https://github.com/UB-Mannheim/tesseract/wiki
2. Run installer (default path: `C:\Program Files\Tesseract-OCR\`)
3. The app is hardcoded to look for this path on Windows.

**Linux (Debian/Ubuntu)**
```bash
sudo apt-get update
sudo apt-get install tesseract-ocr
```

**macOS**
```bash
brew install tesseract
```

### 2. Run the App
```bash
# Clone repository
git clone https://huggingface.co/spaces/LovnishVerma/ALDDS
cd ALDDS

# Install Dependencies
pip install -r requirements.txt

# Run the Server
python app.py
```
The interface will launch at **http://127.0.0.1:7860**.

---

## ☁️ Hugging Face Spaces Deployment

If you are deploying ALDDS to Hugging Face Spaces, follow these critical steps:

1. **Set Up Secrets**: Go to your Space **Settings** -> **Variables and secrets**. Add all variables from your `.env` file as **Secrets**.
2. **System Dependencies**: Hugging Face runs Debian Linux. The repository includes a `packages.txt` file telling Hugging Face to install `tesseract-ocr` and `libtesseract-dev` during the Docker build.
3. **CRLF Warning**: Ensure that `packages.txt` is saved with Unix (`LF`) line endings. If it has Windows (`CRLF`) line endings, the Hugging Face Docker build will fail with a `Package not found` error.
4. **Restart**: Always click **Restart Space** after adding or modifying Secrets so the new environment variables are loaded into the container.

---

## 📊 Extracted JSON Schema

The LLM is strictly prompted to extract the following fields. If a field cannot be found, it defaults to `null`.

| JSON Key | Description |
|---|---|
| `Case_FIR_Number` | FIR or court case reference number |
| `Act_and_Sections` | Applicable IPC/CRPC legal acts and sections |
| `Type_of_Document` | Warrant, summon, notice, etc. |
| `Target_Police_Station` | Police station the document is addressed to |
| `IO_Name_and_Belt_No` | Investigating Officer's name and belt number |
| `IO_Mobile_Number` | IO's contact number |
| `Person_Name_To_Serve` | Name of the person to be served/arrested |
| `Person_Address` | Address of the target person |
| `Court_Name` | Issuing court name |
| `Hearing_Date` | Scheduled hearing or appearance date (DD-MM-YYYY) |

---
*Built to streamline station workflows, eliminate manual data entry, and instantly notify field officers.*