Update app.py

app.py

@@ -43,19 +43,11 @@ def update_imgbox(choices):
     choices_plus = extend_choices(choices[:num_models])
     return [gr.Image(None, label=m, visible=(m!='NA')) for m in choices_plus]
 
-async def infer(model_str, prompt, negative_prompt, width, height, steps, cfg, strength, seed, method, timeout=inference_timeout):
+async def infer(model_str, prompt, seed=1, timeout=inference_timeout):
     from pathlib import Path
-    kwargs = {
-        "seed": seed,
-        "negative_prompt": negative_prompt,
-        "width": width,
-        "height": height,
-        "steps": steps,
-        "cfg": cfg,
-        "strength": strength,
-        "method": method
-    }
+    kwargs = {}
     noise = ""
+    kwargs["seed"] = seed
     task = asyncio.create_task(asyncio.to_thread(models_load[model_str].fn,
                                prompt=f'{prompt} {noise}', **kwargs, token=HF_TOKEN))
     await asyncio.sleep(0)
@@ -75,12 +67,12 @@ async def infer(model_str, prompt, negative_prompt, width, height, steps, cfg, s
     return None
 
 
-def gen_fnseed(model_str, prompt, negative_prompt, width, height, steps, cfg, strength, seed, method):
+def gen_fnseed(model_str, prompt, seed=1):
     if model_str == 'NA':
         return None
     try:
         loop = asyncio.new_event_loop()
-        result = loop.run_until_complete(infer(model_str, prompt, negative_prompt, width, height, steps, cfg, strength, seed, method, inference_timeout))
+        result = loop.run_until_complete(infer(model_str, prompt, seed, inference_timeout))
     except (Exception, asyncio.CancelledError) as e:
         print(e)
         print(f"Task aborted: {model_str}")
@@ -122,7 +114,7 @@ with gr.Blocks(theme="Nymbo/Nymbo_Theme") as demo:
             strength = gr.Slider(label="Strength", value=0.7, minimum=0, maximum=1, step=0.001)
         with gr.Row():
             # Slider for setting the seed for reproducibility
-            adv_seed = gr.Slider(label="Seed", value=-1, minimum=-1, maximum=1000000000, step=1)
+            seed = gr.Slider(label="Seed", value=-1, minimum=-1, maximum=1000000000, step=1)
         with gr.Row():
             # Radio buttons for selecting the sampling method
             method = gr.Radio(label="Sampling method", value="DPM++ 2M Karras", choices=["DPM++ 2M Karras", "DPM++ SDE Karras", "Euler", "Euler a", "Heun", "DDIM"])
@@ -145,7 +137,7 @@ with gr.Blocks(theme="Nymbo/Nymbo_Theme") as demo:
                         
             for m, o in zip(current_models, output):
                 gen_event = gr.on(triggers=[gen_button.click, txt_input.submit], fn=gen_fnseed,
-                            inputs=[m, txt_input, negative_prompt, width, height, steps, cfg, strength, seed, method], outputs=[o], concurrency_limit=None, queue=False)
+                            inputs=[m, txt_input, seed], outputs=[o], concurrency_limit=None, queue=False)
                 #stop_button.click(lambda s: gr.update(interactive = False), None, stop_button, cancels = [gen_event])
         with gr.Accordion('Model selection'):
             model_choice = gr.CheckboxGroup(models, label = f'Choose up to {int(num_models)} different models from the {len(models)} available!', value=default_models, interactive=True)