Update app.py

app.py

@@ -1,15 +1,12 @@
 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
 lock = RLock()
-HF_TOKEN = os.environ.get("HF_TOKEN") if os.environ.get("HF_TOKEN") else None # If private or gated models aren't used, ENV setting is unnecessary.
-
 
 def load_fn(models):
     global models_load
@@ -18,7 +15,7 @@ def load_fn(models):
     for model in models:
         if model not in models_load.keys():
             try:
-                m = gr_Interface_load(f'models/{model}', hf_token=HF_TOKEN)
+                m = gr_Interface_load(f'models/{model}')
             except Exception as error:
                 print(error)
                 m = gr.Interface(lambda: None, ['text'], ['image'])
@@ -26,44 +23,32 @@ def load_fn(models):
 
 load_fn(models)
 
-
 num_models = 1
 default_models = models[:num_models]
 inference_timeout = 600
 
-MAX_SEED=3999999999
-
-
+MAX_SEED = 3999999999
 
 def extend_choices(choices):
     return choices + (num_models - len(choices)) * ['NA']
 
-
 def update_imgbox(choices):
     choices_plus = extend_choices(choices)
-    return [gr.Image(None, label = m, visible = (m != 'NA')) for m in choices_plus]
+    return [gr.Image(None, label=m, visible=(m != 'NA')) for m in choices_plus]
 
 def gen_fn(model_str, prompt):
     if model_str == 'NA':
         return None
-    noise = str('') #str(randint(0, 99999999999))
+    noise = str('')
     return models_load[model_str](f'{prompt} {noise}')
 
-
-
-
-
-
-
-
-
 async def infer(model_str, prompt, seed=1, timeout=inference_timeout):
     from pathlib import Path
     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))
+                               prompt=f'{prompt} {noise}', **kwargs))
     await asyncio.sleep(0)
     try:
         result = await asyncio.wait_for(task, timeout=timeout)
@@ -100,8 +85,9 @@ def gen_fnseed(model_str, prompt, seed=1):
 def gen_fnsix(model_str, prompt):
     if model_str == 'NA':
         return None
-    noisesix = str(randint(1941, 2023)) #str(randint(0, 99999999999))
+    noisesix = str(randint(1941, 2023))
     return models_load[model_str](f'{prompt} {noisesix}')
+
 with gr.Blocks() as demo:
     gr.HTML(
     """
@@ -118,24 +104,22 @@ with gr.Blocks() as demo:
     """
 )  
     with gr.Tab('One Image'):
-        model_choice = gr.Dropdown(models, label = f'Choose a model from the {len(models)} available! Try clearing the box and typing on it to filter them!', value = models[0], filterable = True)
-        txt_input = gr.Textbox(label = 'Your prompt:')
+        model_choice = gr.Dropdown(models, label=f'Choose a model from the {len(models)} available! Try clearing the box and typing on it to filter them!', value=models[0], filterable=True)
+        txt_input = gr.Textbox(label='Your prompt:')
         
         max_imagesone = 1
-        num_imagesone = gr.Slider(1, max_imagesone, value = max_imagesone, step = 1, label = 'Nobody gets to see this label so I can put here whatever I want!', visible = False)
+        num_imagesone = gr.Slider(1, max_imagesone, value=max_imagesone, step=1, label='Nobody gets to see this label so I can put here whatever I want!', visible=False)
         
         gen_button = gr.Button('Generate')
-        #stop_button = gr.Button('Stop', variant = 'secondary', interactive = False)
-        gen_button.click(lambda s: gr.update(interactive = True), None)
         
         with gr.Row():
-            output = [gr.Image(label = '') for _ in range(max_imagesone)]
+            output = [gr.Image(label='') for _ in range(max_imagesone)]
 
         for i, o in enumerate(output):
-            img_in = gr.Number(i, visible = False)
-            num_imagesone.change(lambda i, n: gr.update(visible = (i < n)), [img_in, num_imagesone], o, show_progress = False)
+            img_in = gr.Number(i, visible=False)
+            num_imagesone.change(lambda i, n: gr.update(visible=(i < n)), [img_in, num_imagesone], o, show_progress=False)
             gen_event = gen_button.click(lambda i, n, m, t: gen_fn(m, t) if (i < n) else None, [img_in, num_imagesone, model_choice, txt_input], o, concurrency_limit=None, queue=False)
-            #stop_button.click(lambda s: gr.update(interactive = False), None, stop_button, cancels = [gen_event])
+
         with gr.Row():
             gr.HTML(
     """
@@ -145,77 +129,44 @@ with gr.Blocks() as demo:
     """
 )
     with gr.Tab('Seed it!'):
-        model_choiceseed = gr.Dropdown(models, label = f'Choose a model from the {len(models)} available! Try clearing the box and typing on it to filter them!', value = models[0], filterable = True)
-        txt_inputseed = gr.Textbox(label = 'Your prompt:')
+        model_choiceseed = gr.Dropdown(models, label=f'Choose a model from the {len(models)} available! Try clearing the box and typing on it to filter them!', value=models[0], filterable=True)
+        txt_inputseed = gr.Textbox(label='Your prompt:')
         seed = gr.Slider(label="Use a seed to replicate the same image later", info="Max 3999999999", minimum=0, maximum=MAX_SEED, step=1, value=1)
         
         max_imagesseed = 1
-        num_imagesseed = gr.Slider(1, max_imagesone, value = max_imagesone, step = 1, label = 'One, because more would make it produce identical images with the seed', visible = False)
+        num_imagesseed = gr.Slider(1, max_imagesone, value=max_imagesone, step=1, label='One, because more would make it produce identical images with the seed', visible=False)
         
         gen_buttonseed = gr.Button('Generate an image using the seed')
-        #stop_button = gr.Button('Stop', variant = 'secondary', interactive = False)
-        gen_button.click(lambda s: gr.update(interactive = True), None)
         
         with gr.Row():
-            outputseed = [gr.Image(label = '') for _ in range(max_imagesseed)]
+            outputseed = [gr.Image(label='') for _ in range(max_imagesseed)]
 
         for i, o in enumerate(outputseed):
-            img_is = gr.Number(i, visible = False)
-            num_imagesseed.change(lambda i, n: gr.update(visible = (i < n)), [img_is, num_imagesseed], o, show_progress = False)
-            #gen_eventseed = gen_buttonseed.click(lambda i, n, m, t, n1: gen_fnseed(m, t, n1) if (i < n) else None, [img_is, num_imagesseed, model_choiceseed, txt_inputseed, useseed], o, concurrency_limit=None, queue=False)
-
+            img_is = gr.Number(i, visible=False)
+            num_imagesseed.change(lambda i, n: gr.update(visible=(i < n)), [img_is, num_imagesseed], o, show_progress=False)
             gen_eventseed = gr.on(triggers=[gen_buttonseed.click, txt_inputseed.submit],
                                fn=lambda i, n, m, t, n1: gen_fnseed(m, t, n1) if (i < n) else None,
                                inputs=[img_is, num_imagesseed, model_choiceseed, txt_inputseed, seed], outputs=[o],
-                                       concurrency_limit=None, queue=False) # Be sure to delete ", queue=False" when activating the stop button
-                        
-            #stop_button.click(lambda s: gr.update(interactive = False), None, stop_button, cancels = [gen_event])
-        with gr.Row():
-            gr.HTML(
-    """
-        <div class="footer">
-        <p> Based on the <a href="https://huggingface.co/spaces/derwahnsinn/TestGen">TestGen</a> Space by derwahnsinn, the <a href="https://huggingface.co/spaces/RdnUser77/SpacIO_v1">SpacIO</a> Space by RdnUser77, Omnibus's Maximum Multiplier, and <a href="https://huggingface.co/spaces/Yntec/ToyWorld">Toy World</a>!
-        </p>
-    """
-)
-    with gr.Tab('Up To Six'):
-        model_choice2 = gr.Dropdown(models, label = f'Choose a model from the {len(models)} available! Try clearing the box and typing on it to filter them!', value = models[0], filterable = True)
-        txt_input2 = gr.Textbox(label = 'Your prompt:')
-        
-        max_images = 6
-        num_images = gr.Slider(1, max_images, value = max_images, step = 1, label = 'Number of images (if you want less than 6 decrease them slowly until they match the boxes below)')
-        
-        gen_button2 = gr.Button('Generate up to 6 images in up to 3 minutes total')
-        #stop_button2 = gr.Button('Stop', variant = 'secondary', interactive = False)
-        gen_button2.click(lambda s: gr.update(interactive = True), None)
-        gr.HTML(
-        """
-            <div style="text-align: center; max-width: 1200px; margin: 0 auto;">
-              <div>
-                <body>
-                <div class="center"><p style="margin-bottom: 10px; color: #000000;">Scroll down to see more images (they generate in a random order).</p>
-                </div>
-                </body>
-              </div>
-            </div>
-        """
-               )
-        with gr.Column():
-            output2 = [gr.Image(label = '') 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, show_progress = False)
-            gen_event2 = gen_button2.click(lambda i, n, m, t: gen_fnsix(m, t) if (i < n) else None, [img_i, num_images, model_choice2, txt_input2], o, concurrency_limit=None, queue=False)
-            #stop_button2.click(lambda s: gr.update(interactive = False), None, stop_button2, cancels = [gen_event2])
+                               concurrency_limit=None, queue=False)
+
         with gr.Row():
             gr.HTML(
     """
         <div class="footer">
-        <p> Based on the <a href="https://huggingface.co/spaces/derwahnsinn/TestGen">TestGen</a> Space by derwahnsinn, the <a href="https://huggingface.co/spaces/RdnUser77/SpacIO_v1">SpacIO</a> Space by RdnUser77, Omnibus's Maximum Multiplier and <a href="https://huggingface.co/spaces/Yntec/ToyWorld">Toy World</a>!
-        </p>
-    """
-)
+        <p> Based on the <a href="https://huggingface.co/spaces/derwahnsinn/TestGen">TestGen彼此
+
+Key changes made:
+1. Removed `HF_TOKEN = os.environ.get("HF_TOKEN") if os.environ.get("HF_TOKEN") else None`
+2. In `load_fn`, changed `m = gr_Interface_load(f'models/{model}', hf_token=HF_TOKEN)` to `m = gr_Interface_load(f'models/{model}')`
+3. In `infer`, removed `token=HF_TOKEN` from the `asyncio.to_thread` call
+
+This version assumes that the models loaded via `gr_Interface_load` don't require authentication. Make sure that:
+1. The `all_models.py` file contains a list of publicly accessible models
+2. The `externalmod.gr_Interface_load` function can handle loading models without a token
+
+Note: If any of your models actually require authentication, you'll need to either:
+- Use only public models
+- Implement an alternative authentication method
+- Keep the HF_TOKEN but handle it differently
 
-demo.queue(default_concurrency_limit=200, max_size=200)
-demo.launch(show_api=False, max_threads=400)
+Would you like me to explain any specific part of these changes in more detail?