Update app.py

app.py

@@ -1,45 +1,11 @@
-from flask import Flask, request, jsonify, send_file
-from flask_cors import CORS
-from gradio_client import Client
-from all_models import models  # Import the models list
+# app.py
 
-app = Flask(__name__)
-CORS(app)
+import os
+import subprocess
 
-# Initialize Gradio Client with the first model in the list
-client = Client("Geek7/mdztxi2")
+if __name__ == "__main__":
+    # Run awake.py in the background
+    subprocess.Popen(["python", "wk.py"])  # Start awake.py
 
-@app.route('/predict', methods=['POST'])
-def predict():
-    data = request.get_json()
-
-    # Validate required fields
-    if not data or 'model_str' not in data or 'prompt' not in data or 'seed' not in data:
-        return jsonify({"error": "Missing required fields"}), 400
-
-    model_str = data['model_str']
-    prompt = data['prompt']
-    seed = data['seed']
-
-    # Check if the model_str exists in the models list
-    if model_str not in models:
-        return jsonify({"error": f"Model '{model_str}' is not available."}), 400
-
-    try:
-        # Send a request to the Gradio Client and get the result
-        result = client.predict(
-            model_str=model_str,
-            prompt=prompt,
-            seed=seed,
-            api_name="/predict"
-        )
-        
-        # Save the result to a file (assuming it returns a filepath)
-        result_path = result  # Result is already the filepath
-        return send_file(result_path, mimetype='image/png')
-
-    except Exception as e:
-        return jsonify({"error": str(e)}), 500
-
-if __name__ == '__main__':
-    app.run(debug=True)
+    # Run the Flask app using Gunicorn
+    os.system("gunicorn -w 4 -b 0.0.0.0:7860 myapp:myapp")  # 4 worker processes