Update app.py

app.py

@@ -1,77 +1,11 @@
-from flask import Flask, request, jsonify, send_file
-import gradio as gr
-from random import randint
-from all_models import models
-from externalmod import gr_Interface_load
-import asyncio
-import os
-from threading import RLock
-from PIL import Image
-
-app = Flask(__name__)
-
-lock = RLock()
-HF_TOKEN = os.environ.get("HF_TOKEN")
-
-# Load models
-def load_fn(models):
-    global models_load
-    models_load = {}
-    
-    for model in models:
-        if model not in models_load.keys():
-            try:
-                m = gr_Interface_load(f'models/{model}', hf_token=HF_TOKEN)
-            except Exception as error:
-                print(error)
-                m = gr.Interface(lambda: None, ['text'], ['image'])
-            models_load.update({model: m})
-
-load_fn(models)
 
-num_models = 6
-MAX_SEED = 3999999999
-default_models = models[:num_models]
-inference_timeout = 600
-
-# Gradio inference function
-async def infer(model_str, prompt, seed=1, timeout=inference_timeout):
-    kwargs = {"seed": seed}
-    task = asyncio.create_task(asyncio.to_thread(models_load[model_str].fn, prompt=prompt, **kwargs, token=HF_TOKEN))
-    await asyncio.sleep(0)
-    try:
-        result = await asyncio.wait_for(task, timeout=timeout)
-    except (Exception, asyncio.TimeoutError) as e:
-        print(e)
-        print(f"Task timed out: {model_str}")
-        if not task.done(): 
-            task.cancel()
-        result = None
-    if task.done() and result is not None:
-        with lock:
-            png_path = "generated_image.png"
-            result.save(png_path)  # Save the result as an image
-        return png_path
-    return None
-
-# API function to perform inference
-@app.route('/generate-image', methods=['POST'])
-def generate_image():
-    data = request.get_json()
-    model_str = data['model_str']
-    prompt = data['prompt']
-    seed = data.get('seed', 1)
-
-    # Run Gradio inference
-    result_path = asyncio.run(infer(model_str, prompt, seed))
-    
-    if result_path:
-        # Send back the generated image file
-        return send_file(result_path, mimetype='image/png')
-    else:
-        return jsonify({"error": "Failed to generate image."}), 500
 
+import os
+import subprocess
 
-# Add this block to make sure your app runs when called
 if __name__ == "__main__":
-    app.run(host='0.0.0.0', port=7860)  # Run directly
+    # Run awake.py in the background
+    subprocess.Popen(["python", "wk.py"])  # Start awake.py
+
+    # Run the Flask app using Gunicorn
+    os.system("gunicorn -w 4 -b 0.0.0.0:7860 myapp:myapp")  # 4 worker processes