Add health check endpoint and improve error handling in prediction API

Dockerfile

@@ -9,4 +9,4 @@ COPY ./label_encoder.pkl /code/label_encoder.pkl
 
 RUN pip install --no-cache-dir --upgrade -r /code/requirements.txt
 
-CMD ["gunicorn", "--bind", "0.0.0.0:7860", "app:app"]
+CMD ["gunicorn", "--bind", "0.0.0.0:7860", "--workers", "1", "--timeout", "180", "app:app"]

app.py

@@ -30,9 +30,21 @@ def predict(input_data):
     return decoded_predictions[0]
 
 
+@app.route('/', methods=['GET'])
+def health_check():
+    """Health check endpoint."""
+    return jsonify({'status': 'healthy', 'message': 'CropSmartAI API is running'})
+
 @app.route('/predict', methods=['POST'])
 def get_prediction():
     """Receive input data, preprocess, and return crop prediction."""
+    if not request.json:
+        return jsonify({'error': 'No input data provided'}), 400
+        
+    required_fields = ['N', 'P', 'K', 'temperature', 'humidity', 'ph', 'rainfall']
+    if not all(field in request.json for field in required_fields):
+        return jsonify({'error': 'Missing required fields'}), 400
+
     try:
         print("here")
         # Get the input JSON data from the request
@@ -50,8 +62,10 @@ def get_prediction():
         # Return the prediction as a JSON response
         return jsonify({'crop': predicted_label})
     except Exception as e:
-        return jsonify({'error': str(e)}), 400
+        response = jsonify({'error': f'Prediction error: {str(e)}'})
+        return response, 500
 
 
 if __name__ == '__main__':
-    app.run(debug=True)
+    # Update to use port 7860 to match Hugging Face Spaces requirements
+    app.run(host='0.0.0.0', port=7860, debug=False)