Update app.py

app.py

@@ -1,6 +1,6 @@
 import gradio as gr
 from all_models import models
-# from externalmod import gr_Interface_load, save_image, randomize_seed
+from externalmod import gr_Interface_load, save_image, randomize_seed
 import asyncio
 import os
 from threading import RLock
@@ -11,52 +11,7 @@ negPreSetPrompt = "[deformed | disfigured], poorly drawn, [bad : wrong] anatomy,
 
 lock = RLock()
 
-HF_TOKEN = os.environ.get("HF_TOKEN") if os.environ.get("HF_TOKEN") else None
-
-num_models = 12
-max_images = 12
-inference_timeout = 400
-default_models = models[:num_models]
-MAX_SEED = 2**32-1
-
-def gr_Interface_load(
-    name: str,
-    src: str | None = None,
-    hf_token: str | None = None,
-    alias: str | None = None,
-    **kwargs, # ignore
-) -> Blocks:
-    try:
-        return load_blocks_from_repo(name, src, hf_token, alias)
-    except Exception as e:
-        print(e)
-        return gradio.Interface(lambda: None, ['text'], ['image'])
-
-
-def save_image(image, savefile, modelname, prompt, nprompt, height=0, width=0, steps=0, cfg=0, seed=-1):
-    from PIL import Image, PngImagePlugin
-    import json
-    try:
-        metadata = {"prompt": prompt, "negative_prompt": nprompt, "Model": {"Model": modelname.split("/")[-1]}}
-        if steps > 0: metadata["num_inference_steps"] = steps
-        if cfg > 0: metadata["guidance_scale"] = cfg
-        if seed != -1: metadata["seed"] = seed
-        if width > 0 and height > 0: metadata["resolution"] = f"{width} x {height}"
-        metadata_str = json.dumps(metadata)
-        info = PngImagePlugin.PngInfo()
-        info.add_text("metadata", metadata_str)
-        image.save(savefile, "PNG", pnginfo=info)
-        return str(Path(savefile).resolve())
-    except Exception as e:
-        print(f"Failed to save image file: {e}")
-        raise Exception(f"Failed to save image file:") from e
-
-def randomize_seed():
-    from random import seed, randint
-    MAX_SEED = 2**32-1
-    seed()
-    rseed = randint(0, MAX_SEED)
-    return rseed
+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 get_current_time():
     now = datetime.now()
@@ -76,20 +31,31 @@ def load_fn(models):
                 m = gr.Interface(lambda: None, ['text'], ['image'])
             models_load.update({model: m})
 
+
 load_fn(models)
 
+num_models = 12
+max_images = 12
+inference_timeout = 400
+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
@@ -139,6 +105,7 @@ def gen_fn(model_str, prompt, nprompt="", height=0, width=0, steps=0, cfg=0, see
         loop.close()
     return result
 
+
 def add_gallery(image, model_str, gallery):
     if gallery is None: gallery = []
     with lock:
@@ -150,7 +117,6 @@ js="""
 """
 
 with gr.Blocks(fill_width=True, head=js) as demo:
-    gr.HTML("")  
     with gr.Tab(str(num_models) + ' Models'):
         with gr.Column(scale=2):
             with gr.Group():
@@ -213,7 +179,7 @@ with gr.Blocks(fill_width=True, head=js) as demo:
                         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/2, step=1, label='Number of images')
+            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)