Update app.py

app.py

@@ -1,47 +1,11 @@
-from flask import Flask, request, send_file, jsonify
-from flask_cors import CORS
-from huggingface_hub import InferenceClient
-from PIL import Image
-import io
+# app.py
 
-# Initialize Flask app
-app = Flask(__name__)
-CORS(app)
+import os
+import subprocess
 
-# Your Hugging Face API Token
-API_TOKEN = "your_huggingface_api_key"
+if __name__ == "__main__":
+    # Run awake.py in the background
+    subprocess.Popen(["python", "wk.py"])  # Start awake.py
 
-# Initialize the Inference Client
-client = InferenceClient(model="stabilityai/sd-x2-latent-upscaler", token=API_TOKEN)
-
-@app.route('/upscale', methods=['POST'])
-def upscale_image():
-    try:
-        # Retrieve the image file from the request
-        image_file = request.files.get('image')
-        if not image_file:
-            return jsonify({"error": "No image file provided"}), 400
-
-        # Open the image
-        input_image = Image.open(image_file)
-
-        # Use the Hugging Face Inference Client to upscale the image
-        result = client.image_to_image(
-            image=input_image,
-            prompt="",  # Optional: Add a guiding prompt
-            num_inference_steps=50,  # Adjust as needed
-            guidance_scale=6.0  # Adjust as needed
-        )
-
-        # Save the upscaled image to a BytesIO object
-        img_io = io.BytesIO()
-        result.save(img_io, 'PNG')
-        img_io.seek(0)
-
-        return send_file(img_io, mimetype='image/png')
-    except Exception as e:
-        return jsonify({"error": str(e)}), 500
-
-# Run the app
-if __name__ == '__main__':
-    app.run(host='0.0.0.0', port=5000)
+    # Run the Flask app using Gunicorn
+    os.system("gunicorn -w 4 -b 0.0.0.0:5000 myapp:myapp")  # 4 worker processes