Add API endpoints for external inference calls

- Add Flask API with /predict, /health, and /info endpoints
- Add CORS support for cross-origin requests
- Update requirements.txt with flask-cors dependency
- Update README with comprehensive API documentation
- Include Python example for easy integration

README.md

@@ -26,12 +26,52 @@ This is a custom handler for the Grammarly CoEdIT model, providing grammar corre
 
 ## API Usage
 
-The Space provides a REST API endpoint at `/predict`:
+The Space provides multiple REST API endpoints:
 
+### Main Inference Endpoint
 ```bash
-curl -X POST "https://your-space-url.hf.space/predict" \
+curl -X POST "https://sxtran-grammar-corrector-app.hf.space/predict" \
      -H "Content-Type: application/json" \
-     -d '{"inputs": ["Fix the grammar: When I grow up, I start to understand what he said is quite right."]}'
+     -d '{
+       "inputs": ["Fix the grammar: When I grow up, I start to understand what he said is quite right."],
+       "parameters": {
+         "num_return_sequences": 1,
+         "temperature": 1.0
+       }
+     }'
+```
+
+### Health Check
+```bash
+curl -X GET "https://sxtran-grammar-corrector-app.hf.space/health"
+```
+
+### API Information
+```bash
+curl -X GET "https://sxtran-grammar-corrector-app.hf.space/info"
+```
+
+### Python Example
+```python
+import requests
+
+# API endpoint
+url = "https://sxtran-grammar-corrector-app.hf.space/predict"
+
+# Request data
+data = {
+    "inputs": ["Fix the grammar: When I grow up, I start to understand what he said is quite right."],
+    "parameters": {
+        "num_return_sequences": 1,
+        "temperature": 1.0
+    }
+}
+
+# Make request
+response = requests.post(url, json=data)
+result = response.json()
+
+print(result)
 ```
 
 ## Response Format

app.py

@@ -6,6 +6,8 @@ import gradio as gr
 import sys
 import os
 import json
+from flask import Flask, request, jsonify
+from flask_cors import CORS
 
 # Add current directory to path so we can import handler
 sys.path.append(os.path.dirname(os.path.abspath(__file__)))
@@ -138,7 +140,102 @@ def create_interface():
     
     return demo
 
+# Create Flask app for API endpoints
+app = Flask(__name__)
+CORS(app)  # Enable CORS for cross-origin requests
+
+@app.route('/predict', methods=['POST'])
+def api_predict():
+    """API endpoint for inference calls from external applications"""
+    try:
+        # Get JSON data from request
+        data = request.get_json()
+        
+        if not data:
+            return jsonify({
+                "success": False,
+                "error": "No JSON data provided"
+            }), 400
+        
+        # Extract inputs and parameters
+        inputs = data.get('inputs', [])
+        parameters = data.get('parameters', {})
+        
+        # If inputs is a single string, wrap it in a list
+        if isinstance(inputs, str):
+            inputs = [inputs]
+        
+        if not inputs:
+            return jsonify({
+                "success": False,
+                "error": "No inputs provided"
+            }), 400
+        
+        # Process through handler
+        result = handler({
+            "inputs": inputs,
+            "parameters": parameters
+        })
+        
+        return jsonify(result)
+        
+    except Exception as e:
+        return jsonify({
+            "success": False,
+            "error": f"Error processing request: {str(e)}"
+        }), 500
+
+@app.route('/health', methods=['GET'])
+def health_check():
+    """Health check endpoint"""
+    return jsonify({
+        "status": "healthy",
+        "handler_initialized": handler is not None
+    })
+
+@app.route('/info', methods=['GET'])
+def api_info():
+    """API information endpoint"""
+    return jsonify({
+        "name": "CoEdIT Grammar Corrector API",
+        "version": "1.0.0",
+        "description": "API for grammar correction and text enhancement using Grammarly CoEdIT model",
+        "endpoints": {
+            "/predict": "POST - Main inference endpoint",
+            "/health": "GET - Health check",
+            "/info": "GET - API information"
+        },
+        "input_format": {
+            "inputs": "List of strings or single string to process",
+            "parameters": {
+                "num_return_sequences": "Number of variations to generate (default: 1)",
+                "temperature": "Sampling temperature (default: 1.0)"
+            }
+        },
+        "example_request": {
+            "inputs": ["Fix the grammar: When I grow up, I start to understand what he said is quite right."],
+            "parameters": {
+                "num_return_sequences": 1,
+                "temperature": 1.0
+            }
+        }
+    })
+
 # Create the interface
 if __name__ == "__main__":
     demo = create_interface()
+    
+    # Launch both Gradio and Flask
+    # Gradio will run on port 7860, Flask on port 7861
+    import threading
+    
+    def run_flask():
+        app.run(host="0.0.0.0", port=7861, debug=False)
+    
+    # Start Flask in a separate thread
+    flask_thread = threading.Thread(target=run_flask)
+    flask_thread.daemon = True
+    flask_thread.start()
+    
+    # Launch Gradio
     demo.launch(server_name="0.0.0.0", server_port=7860)

requirements.txt

@@ -1,6 +1,7 @@
 torch>=2.0.0
 transformers>=4.30.0
 flask>=2.3.0
+flask-cors>=4.0.0
 requests>=2.31.0
 safetensors>=0.3.0
 gradio>=4.0.0