Update app.py

app.py

@@ -14,7 +14,7 @@ HF_TOKEN = os.environ.get("HF_TOKEN") if os.environ.get("HF_TOKEN") else None
 def load_fn(models):
     global models_load
     models_load = {}
-    
+
     for model in models:
         if model not in models_load:
             try:
@@ -23,7 +23,7 @@ def load_fn(models):
                 print(f"Loaded model: {model}")
             except Exception as error:
                 print(f"Error loading model {model}: {error}")
-                m = gr.Interface(lambda: None, ['text'], ['image'])
+                m = None  # Avoid using gr.Interface here
             models_load[model] = m
 
 print("Loading models...")
@@ -45,49 +45,54 @@ def update_imgbox(choices):
     return [gr.Image(None, label=m, visible=(m != 'NA')) for m in choices_plus]
 
 async def infer(model_str, prompt, seed=1, timeout=inference_timeout):
+    if model_str not in models_load or models_load[model_str] is None:
+        print(f"Model {model_str} is not available.")
+        return None
+    
     kwargs = {"seed": seed}
     print(f"Starting inference: {model_str} | Prompt: '{prompt}' | Seed: {seed}")
-    task = asyncio.create_task(asyncio.to_thread(models_load[model_str].fn, prompt=prompt, **kwargs, token=HF_TOKEN))
+
     try:
-        result = await asyncio.wait_for(task, timeout=timeout)
+        result = await asyncio.wait_for(
+            asyncio.to_thread(models_load[model_str].fn, prompt=prompt, **kwargs),
+            timeout=timeout
+        )
+        if result:
+            save_path = "image.png"
+            with lock:
+                result.save(save_path)
+            return save_path
     except Exception as e:
         print(f"Error during inference: {e}")
-        if not task.done():
-            task.cancel()
-        return None
-    if task.done() and result:
-        with lock:
-            result.save("image.png")
-            return "image.png"
+    
     return None
 
 def gen_fnseed(model_str, prompt, seed=1):
     if model_str == 'NA':
         return None
-    loop = asyncio.new_event_loop()
-    result = loop.run_until_complete(infer(model_str, prompt, seed))
-    loop.close()
-    return result
+    return asyncio.run(infer(model_str, prompt, seed))
 
 print("Creating Gradio interface...")
 with gr.Blocks(theme="gradio/soft") as demo:
     gr.HTML("<center><h1>TEXT-IMAGE-USING-MULTIMODELS</h1></center>")
+
     with gr.Tab():
         txt_input = gr.Textbox(label='Your prompt:', lines=4)
         gen_button = gr.Button('Generate')
         seed = gr.Slider("Seed", minimum=0, maximum=MAX_SEED, step=1, value=starting_seed)
         seed_rand = gr.Button("Randomize Seed 🎲")
         seed_rand.click(randomize_seed, None, [seed])
+
         output = [gr.Image(label=m) for m in default_models]
         current_models = [gr.Textbox(m, visible=False) for m in default_models]
-        
+
         for m, o in zip(current_models, output):
             gen_button.click(gen_fnseed, [m, txt_input, seed], o)
-        
+
         with gr.Accordion('Model selection'):
             model_choice = gr.CheckboxGroup(models, label=f'Choose up to {num_models} models', value=default_models)
             model_choice.change(update_imgbox, model_choice, output)
             model_choice.change(extend_choices, model_choice, current_models)
 
-demo.queue(default_concurrency_limit=200, max_size=200)
+demo.queue(default_concurrency_limit=500, max_size=500)
 demo.launch(show_api=False, max_threads=400)