Update README.md

README.md

@@ -1,152 +1,167 @@
-# Digital Doctors Assistant ML API
-
-A FastAPI-based machine learning service that provides two prediction models for healthcare applications:
-
-1. **Risk Assessment Model** - Predicts patient risk levels (Low/Medium/High) based on vitals and health metrics
-2. **Treatment Outcome Model** - Predicts treatment success probability based on patient data and medication
-
-## Features
-
-- RESTful API endpoints for ML predictions
-- Interactive web interface for easy testing
-- ONNX Runtime for fast inference
-- Pre-trained models hosted on HuggingFace
-- Docker support for easy deployment
-
-## Quick Start
-
-### Local Setup
-
-1. Install dependencies:
-```bash
-pip install -r requirements.txt
-```
-
-2. Set your HuggingFace token:
-```bash
-# Windows PowerShell
-$env:HUGGINGFACE_TOKEN="your_token_here"
-
-# Windows CMD
-set HUGGINGFACE_TOKEN=your_token_here
-
-# Linux/Mac
-export HUGGINGFACE_TOKEN=your_token_here
-```
-
-3. Run the server:
-```bash
-uvicorn ml:app --host 0.0.0.0 --port 7860
-```
-
-4. Open your browser:
-- Web Interface: http://localhost:7860
-- API Docs: http://localhost:7860/docs
-- Health Check: http://localhost:7860/health
-
-### Docker Setup
-
-```bash
-docker build -t dda-ml-api .
-docker run -p 7860:7860 -e HUGGINGFACE_TOKEN="your_token_here" dda-ml-api
-```
-
-## API Endpoints
-
-### POST /predict/risk
-Predict patient risk level based on health metrics.
-
-**Request Body:**
-```json
-{
-  "age": 45,
-  "bmi": 28.5,
-  "systolic_bp": 140,
-  "diastolic_bp": 90,
-  "chronic_conditions": "diabetes,hypertension",
-  "severity_score": 7.5
-}
-```
-
-**Response:**
-```json
-{
-  "success": true,
-  "model": "risk_assessment",
-  "prediction": "High",
-  "confidence": 0.85,
-  "probabilities": {
-    "Low": 0.05,
-    "Medium": 0.10,
-    "High": 0.85
-  }
-}
-```
-
-### POST /predict/treatment
-Predict treatment outcome success probability.
-
-**Request Body:**
-```json
-{
-  "patient_age": 55,
-  "severity_score": 6.5,
-  "compliance_rate": 0.85,
-  "medication": "Metformin",
-  "condition": "Diabetes Type 2"
-}
-```
-
-**Response:**
-```json
-{
-  "success": true,
-  "model": "treatment_outcome",
-  "prediction": 1,
-  "success_probability": 78.5,
-  "confidence": 0.78,
-  "probabilities": {
-    "failure": 0.22,
-    "success": 0.78
-  }
-}
-```
-
-## Supported Medications
-
-- Paracetamol
-- Ibuprofen
-- Amoxicillin
-- Ciprofloxacin
-- Metformin
-- Lisinopril
-- Amlodipine
-- Omeprazole
-
-## Supported Conditions
-
-- Common Cold
-- Influenza
-- Pneumonia
-- Bronchitis
-- Hypertension
-- Diabetes Type 2
-- Migraine
-- Gastroenteritis
-
-## Environment Variables
-
-- `HUGGINGFACE_TOKEN` - Required. Your HuggingFace access token for downloading models
-
-## Technology Stack
-
-- FastAPI - Web framework
-- ONNX Runtime - ML inference
-- NumPy - Numerical computing
-- HuggingFace Hub - Model hosting
-- Pydantic - Data validation
-- Uvicorn - ASGI server
-
-## License
-
-MIT
+---
+title: Digital Doctors Assistant ML API
+emoji: 🏥
+colorFrom: blue
+colorTo: purple
+sdk: docker
+pinned: false
+license: mit
+---
+
+# Digital Doctors Assistant ML API
+
+A FastAPI-based machine learning service that provides two prediction models for healthcare applications:
+
+1. **Risk Assessment Model** - Predicts patient risk levels (Low/Medium/High) based on vitals and health metrics
+2. **Treatment Outcome Model** - Predicts treatment success probability based on patient data and medication
+
+## Features
+
+- RESTful API endpoints for ML predictions
+- Interactive web interface for easy testing
+- ONNX Runtime for fast inference
+- Pre-trained models hosted on HuggingFace
+- Docker support for easy deployment
+
+## Quick Start
+
+### Using HuggingFace Space
+
+Simply visit the Space URL and use the web interface to make predictions.
+
+### Run Locally with Docker
+
+```bash
+docker run -it -p 7860:7860 \
+  -e HUGGINGFACE_TOKEN="your_token_here" \
+  registry.hf.space/your-username-your-space-name:latest
+```
+
+### Local Setup (Without Docker)
+
+1. Install dependencies:
+```bash
+pip install -r requirements.txt
+```
+
+2. Set your HuggingFace token:
+```bash
+# Windows PowerShell
+$env:HUGGINGFACE_TOKEN="your_token_here"
+
+# Windows CMD
+set HUGGINGFACE_TOKEN=your_token_here
+
+# Linux/Mac
+export HUGGINGFACE_TOKEN=your_token_here
+```
+
+3. Run the server:
+```bash
+uvicorn ml:app --host 0.0.0.0 --port 7860
+```
+
+4. Open your browser:
+- Web Interface: http://localhost:7860
+- API Docs: http://localhost:7860/docs
+- Health Check: http://localhost:7860/health
+
+## API Endpoints
+
+### POST /predict/risk
+Predict patient risk level based on health metrics.
+
+**Request Body:**
+```json
+{
+  "age": 45,
+  "bmi": 28.5,
+  "systolic_bp": 140,
+  "diastolic_bp": 90,
+  "chronic_conditions": "diabetes,hypertension",
+  "severity_score": 7.5
+}
+```
+
+**Response:**
+```json
+{
+  "success": true,
+  "model": "risk_assessment",
+  "prediction": "High",
+  "confidence": 0.85,
+  "probabilities": {
+    "Low": 0.05,
+    "Medium": 0.10,
+    "High": 0.85
+  }
+}
+```
+
+### POST /predict/treatment
+Predict treatment outcome success probability.
+
+**Request Body:**
+```json
+{
+  "patient_age": 55,
+  "severity_score": 6.5,
+  "compliance_rate": 0.85,
+  "medication": "Metformin",
+  "condition": "Diabetes Type 2"
+}
+```
+
+**Response:**
+```json
+{
+  "success": true,
+  "model": "treatment_outcome",
+  "prediction": 1,
+  "success_probability": 78.5,
+  "confidence": 0.78,
+  "probabilities": {
+    "failure": 0.22,
+    "success": 0.78
+  }
+}
+```
+
+## Supported Medications
+
+- Paracetamol
+- Ibuprofen
+- Amoxicillin
+- Ciprofloxacin
+- Metformin
+- Lisinopril
+- Amlodipine
+- Omeprazole
+
+## Supported Conditions
+
+- Common Cold
+- Influenza
+- Pneumonia
+- Bronchitis
+- Hypertension
+- Diabetes Type 2
+- Migraine
+- Gastroenteritis
+
+## Environment Variables
+
+- `HUGGINGFACE_TOKEN` - Required. Your HuggingFace access token for downloading models
+
+## Technology Stack
+
+- FastAPI - Web framework
+- ONNX Runtime - ML inference
+- NumPy - Numerical computing
+- HuggingFace Hub - Model hosting
+- Pydantic - Data validation
+- Uvicorn - ASGI server
+
+## License
+
+MIT