Update app.py

app.py

@@ -1,11 +1,8 @@
 import gradio as gr
-import os 
-import sys
-from pathlib import Path
+import os
 from all_models import models
-from externalmod import gr_Interface_load
+from externalmod import gr_Interface_load, save_image, randomize_seed
 from prompt_extend import extend_prompt
-from random import randint
 import asyncio
 from threading import RLock
 lock = RLock()
@@ -32,53 +29,47 @@ def send_it1(inputs, model_choice, neg_input, height, width, steps, cfg, seed):
 
 # https://huggingface.co/docs/api-inference/detailed_parameters
 # https://huggingface.co/docs/huggingface_hub/package_reference/inference_client
-async def infer(model_index, prompt, nprompt="", height=None, width=None, steps=None, cfg=None, seed=-1, timeout=inference_timeout):
-    from pathlib import Path
+async def infer(model_index, prompt, nprompt="", height=0, width=0, steps=0, cfg=0, seed=-1, timeout=inference_timeout):
     kwargs = {}
-    if height is not None and height >= 256: kwargs["height"] = height
-    if width is not None and width >= 256: kwargs["width"] = width
-    if steps is not None and steps >= 1: kwargs["num_inference_steps"] = steps
-    if cfg is not None and cfg > 0: cfg = kwargs["guidance_scale"] = cfg
-    noise = ""
-    if seed >= 0: kwargs["seed"] = seed
-    else:
-        rand = randint(1, 500)
-        for i in range(rand):
-            noise += " "
+    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: kwargs["seed"] = randomize_seed()
+    else: kwargs["seed"] = seed
     task = asyncio.create_task(asyncio.to_thread(models2[model_index].fn,
-                               prompt=f'{prompt} {noise}', negative_prompt=nprompt, **kwargs, token=HF_TOKEN))
+                               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"Task timed out: {models2[model_index]}")
+        print(f"Task timed out: {models[model_index]}")
         if not task.done(): task.cancel()
         result = None
-        raise Exception(f"Task timed out: {models2[model_index]}")
+        raise Exception(f"Task timed out: {models[model_index]}") from e
     except Exception as e:
         print(e)
         if not task.done(): task.cancel()
         result = None
-        raise Exception(e)
+        raise Exception() from e
     if task.done() and result is not None and not isinstance(result, tuple):
         with lock:
             png_path = "image.png"
-            result.save(png_path)
-            image = str(Path(png_path).resolve())
+            image = save_image(result, png_path, models[model_index], prompt, nprompt, height, width, steps, cfg, seed)
         return image
     return None
 
-def gen_fn(model_index, prompt, nprompt="", height=None, width=None, steps=None, cfg=None, seed=-1):
+def gen_fn(model_index, 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_index, prompt, nprompt,
                                          height, width, steps, cfg, seed, inference_timeout))
     except (Exception, asyncio.CancelledError) as e:
         print(e)
-        print(f"Task aborted: {models2[model_index]}")
+        print(f"Task aborted: {models[model_index]}")
         result = None
-        raise gr.Error(f"Task aborted: {models2[model_index]}, Error: {e}")
+        raise gr.Error(f"Task aborted: {models[model_index]}, Error: {e}")
     finally:
         loop.close()
     return result
@@ -98,13 +89,13 @@ display: inline-block !important; color: #ffffff !important;}
  border-bottom-color: #ffffff !important; border-left-color: #000000 !important;}
 """
 
-with gr.Blocks(theme='Yntec/YntecDarkTheme', fill_width=True, css=css) as myface:
+with gr.Blocks(theme='John6666/YntecDark', fill_width=True, css=css) as myface:
     gr.HTML(f"""
         <div style="text-align: center; max-width: 1200px; margin: 0 auto;">
         <div class="center"><h1>Blitz Diffusion</h1></div>
         <p style="margin-bottom: 1px; color: #ffaa66;">
         <h3>{int(len(models))} Stable Diffusion models, but why? For your enjoyment!</h3></p>
-        <br><div class="wrapper">9.3 <img src="https://huggingface.co/Yntec/DucHaitenLofi/resolve/main/NEW.webp" alt="NEW!" style="width:32px;height:16px;">This has become a legacy backup copy of old <u><a href="https://huggingface.co/spaces/Yntec/ToyWorld">ToyWorld</a></u>'s UI! Newer models added dailty over there! 25+ new models since last update!</div>
+        <br><div class="wrapper">9.19 <img src="https://huggingface.co/Yntec/DucHaitenLofi/resolve/main/NEW.webp" alt="NEW!" style="width:32px;height:16px;">This has become a legacy backup copy of old <u><a href="https://huggingface.co/spaces/Yntec/ToyWorld">ToyWorld</a></u>'s UI! Newer models added dailty over there! 18 new models since last update!</div>
         <p style="margin-bottom: 1px; font-size: 98%">
         <br><h4>If a model is already loaded each new image takes less than <b>10</b> seconds to generate!</h4></p>
         <p style="margin-bottom: 1px; color: #ffffff;">
@@ -126,9 +117,10 @@ with gr.Blocks(theme='Yntec/YntecDarkTheme', fill_width=True, css=css) as myface
                         width = gr.Slider(label="Width", info="If 0, the default value is used.", maximum=1216, step=32, value=0, elem_classes=["gr-box", "gr-input"])
                         height = gr.Slider(label="Height", info="If 0, the default value is used.", maximum=1216, step=32, value=0, elem_classes=["gr-box", "gr-input"])
                     with gr.Row():
-                        steps = gr.Slider(label="Number of inference steps", info="If 0, the default value is used.", maximum=100, step=1, value=0, elem_classes=["gr-box", "gr-input"])
-                        cfg = gr.Slider(label="Guidance scale", info="If 0, the default value is used.", maximum=30.0, step=0.1, value=0, elem_classes=["gr-box", "gr-input"])
+                        steps = gr.Slider(label="Number of inference steps", info="If 0, the default value is used.", maximum=33, step=1, value=0, elem_classes=["gr-box", "gr-input"])
+                        cfg = gr.Slider(label="Guidance scale", info="If 0, the default value is used.", maximum=30.0, step=0.1, value=-1, elem_classes=["gr-box", "gr-input"])
                         seed = gr.Slider(label="Seed", info="Randomize Seed if -1.", minimum=-1, maximum=MAX_SEED, step=1, value=-1, elem_classes=["gr-box", "gr-input"])
+                        seed_rand = gr.Button("Randomize Seed 🎲", size="sm", variant="secondary")
             run = gr.Button("Generate Image", variant="primary", elem_classes="gr-button")
 
     with gr.Row():
@@ -153,9 +145,10 @@ with gr.Blocks(theme='Yntec/YntecDarkTheme', fill_width=True, css=css) as myface
         concurrency_limit=None,
         queue=False,
     )
-    use_short.click(short_prompt, inputs=[input_text], outputs=magic1, queue=False)
-    see_prompts.click(text_it1, inputs=[input_text], outputs=magic1, queue=False)
+    use_short.click(short_prompt, inputs=[input_text], outputs=magic1)
+    see_prompts.click(text_it1, inputs=[input_text], outputs=magic1)
+    seed_rand.click(randomize_seed, None, [seed], queue=False)
     
 myface.queue(default_concurrency_limit=200, max_size=200)
 myface.launch(show_api=False, max_threads=400)
-# https://github.com/gradio-app/gradio/issues/6339
+# https://github.com/gradio-app/gradio/issues/6339