Update app.py

app.py

@@ -1,22 +1,21 @@
 import gradio as gr
+from handle_models import load_fn,infer,gen_fn
 from all_models import models
-#from _prompt import thePrompt, howManyModelsToUse
 from externalmod import gr_Interface_load, save_image, randomize_seed
 import asyncio
 import os
 from threading import RLock
 from datetime import datetime
-import gradio as gr
+from handlemodelradio import extend_choices,update_imgbox,random_choices
 #anything but huggingface_hub==0.26.2 will result in token error
 from huggingface_hub import HfApi, whoami
 howManyModelsToUse = 20
+num_models = howManyModelsToUse
+max_images = howManyModelsToUse
+inference_timeout = 60
+default_models = models[:num_models]
+MAX_SEED = 2**32-1
 thePrompt ="group of 3boys kissing in bathtub while interracial daddy gives a boy a handjob"
-
-
-
-
-
-
 preSetPrompt = thePrompt
 negPreSetPrompt = "[deformed | disfigured], poorly drawn, [bad : wrong] anatomy, [extra | missing | floating | disconnected] limb, (mutated hands and fingers), blurry, text, fuzziness, asian, african, collage, composite, combined image"
 lock = RLock()
@@ -29,7 +28,6 @@ username = user_info["name"]
 #models = api.list_models(author=username, token=HF_TOKEN)
 mymodels = list(api.list_models(author=username, token=HF_TOKEN))
 model_ids = [m.modelId for m in mymodels]
-
 if not model_ids:
     raise ValueError(f"No models found for user '{username}'")
 # --- Step 3: Build Gradio UI
@@ -43,94 +41,8 @@ def get_current_time():
     now = datetime.now()
     current_time = now.strftime("%y-%m-%d %H:%M:%S")
     return current_time
-
-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 = howManyModelsToUse
-max_images = howManyModelsToUse
-inference_timeout = 60
-default_models = models[:num_models]
-MAX_SEED = 2**32-1
-
-
-def extend_choices(choices):
-    return choices[:num_models] + (num_models - len(choices[:num_models])) * ['NA']
-
-
-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]
-
-
-def random_choices():
-    import random
-    random.seed()
-    return random.choices(models, k=num_models)
-
-
-async def infer(model_str, prompt, nprompt="", height=0, width=0, steps=0, cfg=0, seed=-1, timeout=inference_timeout):
-    kwargs = {}
-    if height > 0: kwargs["height"] = height
-    if width > 0: kwargs["width"] = width
-    if steps > 0: kwargs["num_inference_steps"] = steps
-    if cfg > 0: cfg = kwargs["guidance_scale"] = cfg
-
-    if seed == -1:
-        theSeed = randomize_seed()
-    else: 
-        theSeed = seed
-    kwargs["seed"] = theSeed
-        
-    task = asyncio.create_task(asyncio.to_thread(models_load[model_str].fn, prompt=prompt, negative_prompt=nprompt, **kwargs, token=HF_TOKEN))
-    await asyncio.sleep(0)
-    try:
-        result = await asyncio.wait_for(task, timeout=timeout)
-    except asyncio.TimeoutError as e:
-        print(e)
-        print(f"infer: Task timed out: {model_str}")
-        if not task.done(): task.cancel()
-        result = None
-        raise Exception(f"Task timed out: {model_str}") from e
-    except Exception as e:
-        print(e)
-        print(f"infer: exception: {model_str}")
-        if not task.done(): task.cancel()
-        result = None
-        raise Exception() from e
-    if task.done() and result is not None and not isinstance(result, tuple):
-        with lock:
-            png_path =  model_str.replace("/", "_") + " - " + get_current_time() + "_" + str(theSeed) + ".png"
-            image = save_image(result, png_path, model_str, prompt, nprompt, height, width, steps, cfg, theSeed)
-        return image
-    return None
-
-def gen_fn(model_str, prompt, nprompt="", height=0, width=0, steps=0, cfg=0, seed=-1):
-    try:
-        loop = asyncio.new_event_loop()
-        result = loop.run_until_complete(infer(model_str, prompt, nprompt,
-                                         height, width, steps, cfg, seed, inference_timeout))
-    except (Exception, asyncio.CancelledError) as e:
-        print(e)
-        print(f"gen_fn: Task aborted: {model_str}")
-        result = None
-        raise gr.Error(f"Task aborted: {model_str}, Error: {e}")
-    finally:
-        loop.close()
-    return result
-
 
 '''
  
@@ -160,7 +72,6 @@ with gr.Blocks(fill_width=True) as demo:
             with gr.Row():
                 gen_button = gr.Button(f'Generate up to {int(num_models)} images', variant='primary', scale=3, elem_classes=["butt"])
                 random_button = gr.Button(f'Randomize Models', variant='secondary', scale=1)
-
         with gr.Column(scale=1):
             with gr.Group():
                 with gr.Row():
@@ -168,56 +79,17 @@ with gr.Blocks(fill_width=True) as demo:
                               interactive=False, width=112, height=112, show_share_button=False, format="png",
                               visible=True) 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_event = gr.on(triggers=[gen_button.click, txt_input.submit], fn=gen_fn,
                               inputs=[m, txt_input, neg_input, height, width, steps, cfg, seed], outputs=[o],
                               concurrency_limit=None, queue=False)
-            
-
         with gr.Column(scale=4):
             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)
                 model_choice.change(update_imgbox, model_choice, output)
                 model_choice.change(extend_choices, model_choice, current_models)
                 random_button.click(random_choices, None, model_choice)
-
-    with gr.Tab('Single model'):
-        with gr.Column(scale=2):
-            model_choice2 = gr.Dropdown(models, label='Choose model', value=models[0])
-            with gr.Group():
-                txt_input2 = gr.Textbox(label='Your prompt:', value = preSetPrompt, lines=3, autofocus=1)
-                with gr.Accordion("Advanced", open=False, visible=True):
-                    with gr.Row():
-                        neg_input2 = gr.Textbox(label='Negative prompt:', value=negPreSetPrompt, lines=1)
-                    with gr.Row():                        
-                        width2 = gr.Slider(label="Width", info="If 0, the default value is used.", maximum=1216, step=32, value=0)
-                        height2 = gr.Slider(label="Height", info="If 0, the default value is used.", maximum=1216, step=32, value=0)
-                    with gr.Row():
-                        steps2 = gr.Slider(label="Number of inference steps", info="If 0, the default value is used.", maximum=100, step=1, value=0)
-                        cfg2 = gr.Slider(label="Guidance scale", info="If 0, the default value is used.", maximum=30.0, step=0.1, value=0)
-                        seed2 = gr.Slider(label="Seed", info="Randomize Seed if -1.", minimum=-1, maximum=MAX_SEED, step=1, value=-1)
-                        seed_rand2 = gr.Button("Randomize Seed", size="sm", variant="secondary")
-                        seed_rand2.click(randomize_seed, None, [seed2], queue=False)
-            num_images = gr.Slider(1, max_images, value=max_images, step=1, label='Number of images')
-            with gr.Row():
-                gen_button2 = gr.Button('Let the machine halucinate', variant='primary', scale=2, elem_classes=["butt"])
-
-        with gr.Column(scale=1):
-            with gr.Group():
-                with gr.Row():
-                    output2 = [gr.Image(label='', show_download_button=True,
-                               interactive=False, width=112, height=112, visible=True, format="png",
-                               show_share_button=False, show_label=False) for _ in range(max_images)]
-
-        for i, o in enumerate(output2):
-            img_i = gr.Number(i, visible=False)
-            num_images.change(lambda i, n: gr.update(visible = (i < n)), [img_i, num_images], o, queue=False)
-            gen_event2 = gr.on(triggers=[gen_button2.click, txt_input2.submit],
-                               fn=lambda i, n, m, t1, t2, n1, n2, n3, n4, n5: gen_fn(m, t1, t2, n1, n2, n3, n4, n5) if (i < n) else None,
-                               inputs=[img_i, num_images, model_choice2, txt_input2, neg_input2,
-                                       height2, width2, steps2, cfg2, seed2], outputs=[o],
-                                       concurrency_limit=None, queue=False)
+    
             
 
 demo.launch(show_api=False, max_threads=400)