Update app.py

app.py

@@ -5,12 +5,6 @@ from externalmod import gr_Interface_load
 import asyncio
 import os
 from threading import RLock
-from gradio_client import Client
-from flask import Flask, request, jsonify, send_file
-
-
-client = Client("Geek7/mdztxi2")
-
 
 lock = RLock()
 HF_TOKEN = os.environ.get("HF_TOKEN")
@@ -55,31 +49,12 @@ async def infer(model_str, prompt, seed=1, timeout=inference_timeout):
     return None
 
 # Expose Gradio API
-#def generate_api(model_str, prompt, seed=1):
+def generate_api(model_str, prompt, seed=1):
     result = asyncio.run(infer(model_str, prompt, seed))
     if result:
         return result  # Path to generated image
     return None
 
-@app.route('/predict2', methods=['POST'])
-def async_infer_api():
-    data = request.get_json()
-    model_str = data['model_str']
-    prompt = data['prompt']
-    seed = data.get('seed', 1)  # Default seed value to 1 if not provided
-
-    try:
-        # Run the asynchronous inference function
-        result_path = asyncio.run(async_infer(model_str, prompt, seed))
-        if result_path:
-            # Use send_file to return the generated image
-            return send_file(result_path, mimetype='image/png')  # Adjust mimetype as needed
-        else:
-            return jsonify({"error": "Image generation failed."}), 500
-    except Exception as e:
-        return jsonify({"error": str(e)}), 500
-
-
 # Launch Gradio API without frontend
-iface = gr.Interface(fn=async_infer_api , inputs=["text", "text", "number"], outputs="file")
+iface = gr.Interface(fn=generate_api, inputs=["text", "text", "number"], outputs="file")
 iface.launch(show_api=True, share=True)