🏥 Doclyst Backend

A Flask-powered medical report analysis API that transforms complex medical documents into patient-friendly explanations.

✨ Overview

Doclyst Backend processes medical reports (blood tests, X-rays, ECGs) and returns clear, simple explanations that anyone can understand—without providing medical advice or diagnoses.

🛠️ Tech Stack

• PaddleOCR — OCR text extraction
• OCR Space — Alternative OCR service
• ERNIE — Large language model for analysis
• Groq — LLM inference
• Flask — Python web framework

🏗️ Architecture

┌─────────────────┐
│  Medical Report │  (PDF / PNG / JPG)
└────────┬────────┘
         ▼
┌─────────────────┐
│   Flask API     │  POST /analyze
└────────┬────────┘
         ▼
┌─────────────────┐
│  🔤 PaddleOCR   │  Text Extraction
└────────┬────────┘
         ▼
┌─────────────────┐
│   🧠 ERNIE      │  Medical Explanation
└────────┬────────┘
         ▼
┌─────────────────┐
│  JSON Response  │  Status + Summary + Findings
└─────────────────┘

🚀 Quick Start

Prerequisites

• Python 3.9+
• pip

Installation

# Clone and navigate
cd Doclyst-Backend

# Create virtual environment
python -m venv .venv

# Activate (Windows)
.venv\Scripts\activate

# Activate (Linux/Mac)
source .venv/bin/activate

# Install dependencies
pip install -r requirements.txt

Configuration

# Copy environment template
cp .env.example .env

# Edit .env with your API keys

Environment Variables:

Run Server

# Development
python app.py

# Production
gunicorn app:app

Server runs at http://localhost:5000

📡 API Reference

POST /analyze

Analyze one or more medical report files.

Request:

Content-Type: multipart/form-data
Field: file (supports multiple files)

Response:

{
  "overallStatus": "ATTENTION",
  "summary": "Most of your results look good. A few values need attention.",
  "tests": [
    {
      "name": "Hemoglobin",
      "value": "10.2 g/dL",
      "range": "12.0 - 17.5 g/dL",
      "explanation": "Your hemoglobin is slightly below the typical range, which may cause tiredness.",
      "status": "warning"
    }
  ],
  "disclaimer": "Doclyst does not provide medical advice. This explanation is for understanding only."
}

Status Levels:

GET /health

Health check endpoint.

{"status": "healthy", "service": "doclyst-backend"}

📁 Project Structure

Doclyst-Backend/
├── app.py                  # Flask application entry
├── config.py               # Configuration management
├── routes/
│   └── analyze.py          # API endpoints
├── services/
│   ├── ocr_service.py      # OCR integration
│   ├── ernie_service.py    # LLM integration
│   ├── medical_parser.py   # Data structuring
│   └── risk_engine.py      # Urgency assessment
├── utils/
│   ├── file_utils.py       # File handling
│   └── text_cleaner.py     # Text normalization
├── requirements.txt
└── README.md

🧪 Supported Reports

🔒 Safety & Compliance

Doclyst prioritizes patient safety:

• Explanation, not diagnosis — We clarify results, never diagnose conditions
• Clear disclaimers — Every response includes a medical disclaimer
• No data storage — Reports are processed and immediately discarded
• No personalization — Analysis is based solely on report content

"We help patients understand, not decide."

🧪 Testing

# Test with cURL
curl -X POST http://localhost:5000/analyze \
  -F "file=@your_report.jpg"

# Test multiple files
curl -X POST http://localhost:5000/analyze \
  -F "file=@page1.jpg" \
  -F "file=@page2.jpg"

🚢 Deployment

Render (Recommended)

1. Push to GitHub
2. Connect repo on render.com
3. Configure:
   • Build Command: pip install -r requirements.txt
   • Start Command: gunicorn app:app
4. Add environment variables

📄 License

MIT License