Update app.py

app.py

@@ -1,161 +1,161 @@
-import gradio as gr
-import os 
-import sys
-from pathlib import Path
-from all_models import models
-from externalmod import gr_Interface_load
-from prompt_extend import extend_prompt
-from random import randint
-import asyncio
-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.
-
-inference_timeout = 300
-MAX_SEED = 2**32-1
-current_model = models[0]
-text_gen1 = extend_prompt
-
-models2 = [gr_Interface_load(f"models/{m}", live=False, preprocess=True, postprocess=False, hf_token=HF_TOKEN) for m in models]
-
-def text_it1(inputs, text_gen1=text_gen1):
-        go_t1 = text_gen1(inputs)
-        return(go_t1)
-
-def set_model(current_model):
-    current_model = models[current_model]
-    return gr.update(label=(f"{current_model}"))
-
-def send_it1(inputs, model_choice, neg_input, height, width, steps, cfg, seed):
-        output1 = gen_fn(model_choice, inputs, neg_input, height, width, steps, cfg, seed)
-        return (output1)
-
-# 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
-    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 += " "
-    task = asyncio.create_task(asyncio.to_thread(models2[model_index].fn,
-                               prompt=f'{prompt} {noise}', 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]}")
-        if not task.done(): task.cancel()
-        result = None
-        raise Exception(f"Task timed out: {models2[model_index]}")
-    except Exception as e:
-        print(e)
-        if not task.done(): task.cancel()
-        result = None
-        raise Exception(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())
-        return image
-    return None
-
-def gen_fn(model_index, prompt, nprompt="", height=None, width=None, steps=None, cfg=None, 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]}")
-        result = None
-        raise gr.Error(f"Task aborted: {models2[model_index]}, Error: {e}")
-    finally:
-        loop.close()
-    return result
-
-css="""
-.gradio-container {background-image: linear-gradient(#254150, #1e2f40, #182634) !important;
- color: #ffaa66 !important; font-family: 'IBM Plex Sans', sans-serif !important;}
-h1 {font-size: 6em; color: #ffc99f; margin-top: 30px; margin-bottom: 30px;
- text-shadow: 3px 3px 0 rgba(0, 0, 0, 1) !important;}
-h3 {color: #ffc99f; !important;}
-h4 {display: inline-block; color: #ffffff !important;}
-.wrapper img {font-size: 98% !important; white-space: nowrap !important; text-align: center !important;
-display: inline-block !important; color: #ffffff !important;}
-.wrapper {color: #ffffff !important;}
-.gr-box {background-image: linear-gradient(#182634, #1e2f40, #254150) !important;
- border-top-color: #000000 !important; border-right-color: #ffffff !important;
- border-bottom-color: #ffffff !important; border-left-color: #000000 !important;}
-"""
-
-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>
-        <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;">
-        <br><div class="wrapper">Generate 6 images from 1 prompt at the <u><a href="https://huggingface.co/spaces/Yntec/PrintingPress">PrintingPress</a></u>, and use 6 different models at <u><a href="https://huggingface.co/spaces/Yntec/diffusion80xx">Huggingface Diffusion!</a></u>!
-        </p></p></div>
-        """, elem_classes="gr-box")
-    with gr.Row():
-        with gr.Column(scale=100):
-            # Model selection dropdown
-            model_name1 = gr.Dropdown(label="Select Model", choices=[m for m in models], type="index",
-                                      value=current_model, interactive=True, elem_classes=["gr-box", "gr-input"])
-    with gr.Row():
-        with gr.Column(scale=100):
-            with gr.Group():
-                magic1 = gr.Textbox(label="Your Prompt", lines=4, elem_classes=["gr-box", "gr-input"]) #Positive
-                with gr.Accordion("Advanced", open=False, visible=True):
-                    neg_input = gr.Textbox(label='Negative prompt', lines=1, elem_classes=["gr-box", "gr-input"])
-                    with gr.Row():
-                        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"])
-                        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"])
-            run = gr.Button("Generate Image", variant="primary", elem_classes="gr-button")
-
-    with gr.Row():
-        with gr.Column():
-            output1 = gr.Image(label=(f"{current_model}"), show_download_button=True,
-                               interactive=False, show_share_button=False, format=".png", elem_classes="gr-box")
-                
-    with gr.Row():
-        with gr.Column(scale=50):
-            input_text=gr.Textbox(label="Use this box to extend an idea automagically, by typing some words and clicking Extend Idea", lines=2, elem_classes=["gr-box", "gr-input"])
-            see_prompts=gr.Button("Extend Idea -> overwrite the contents of the `Your Prompt´ box above", variant="primary", elem_classes="gr-button")
-            use_short=gr.Button("Copy the contents of this box to the `Your Prompt´ box above", variant="primary", elem_classes="gr-button")
-    def short_prompt(inputs):
-        return (inputs)
-    
-    model_name1.change(set_model, inputs=model_name1, outputs=[output1])
-    gr.on(
-        triggers=[run.click, magic1.submit],
-        fn=send_it1,
-        inputs=[magic1, model_name1, neg_input, height, width, steps, cfg, seed],
-        outputs=[output1],
-        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)
-    
-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
+import gradio as gr
+import os 
+import sys
+from pathlib import Path
+from all_models import models
+from externalmod import gr_Interface_load
+from prompt_extend import extend_prompt
+from random import randint
+import asyncio
+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.
+
+inference_timeout = 300
+MAX_SEED = 2**32-1
+current_model = models[0]
+text_gen1 = extend_prompt
+
+models2 = [gr_Interface_load(f"models/{m}", live=False, preprocess=True, postprocess=False, hf_token=HF_TOKEN) for m in models]
+
+def text_it1(inputs, text_gen1=text_gen1):
+        go_t1 = text_gen1(inputs)
+        return(go_t1)
+
+def set_model(current_model):
+    current_model = models[current_model]
+    return gr.update(label=(f"{current_model}"))
+
+def send_it1(inputs, model_choice, neg_input, height, width, steps, cfg, seed):
+        output1 = gen_fn(model_choice, inputs, neg_input, height, width, steps, cfg, seed)
+        return (output1)
+
+# 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
+    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 += " "
+    task = asyncio.create_task(asyncio.to_thread(models2[model_index].fn,
+                               prompt=f'{prompt} {noise}', 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]}")
+        if not task.done(): task.cancel()
+        result = None
+        raise Exception(f"Task timed out: {models2[model_index]}")
+    except Exception as e:
+        print(e)
+        if not task.done(): task.cancel()
+        result = None
+        raise Exception(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())
+        return image
+    return None
+
+def gen_fn(model_index, prompt, nprompt="", height=None, width=None, steps=None, cfg=None, 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]}")
+        result = None
+        raise gr.Error(f"Task aborted: {models2[model_index]}, Error: {e}")
+    finally:
+        loop.close()
+    return result
+
+css="""
+.gradio-container {background-image: linear-gradient(#254150, #1e2f40, #182634) !important;
+ color: #ffaa66 !important; font-family: 'IBM Plex Sans', sans-serif !important;}
+h1 {font-size: 6em; color: #ffc99f; margin-top: 30px; margin-bottom: 30px;
+ text-shadow: 3px 3px 0 rgba(0, 0, 0, 1) !important;}
+h3 {color: #ffc99f; !important;}
+h4 {display: inline-block; color: #ffffff !important;}
+.wrapper img {font-size: 98% !important; white-space: nowrap !important; text-align: center !important;
+display: inline-block !important; color: #ffffff !important;}
+.wrapper {color: #ffffff !important;}
+.gr-box {background-image: linear-gradient(#182634, #1e2f40, #254150) !important;
+ border-top-color: #000000 !important; border-right-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:
+    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>
+        <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;">
+        <br><div class="wrapper">Generate 6 images from 1 prompt at the <u><a href="https://huggingface.co/spaces/Yntec/PrintingPress">PrintingPress</a></u>, and use 6 different models at <u><a href="https://huggingface.co/spaces/Yntec/diffusion80xx">Huggingface Diffusion!</a></u>!
+        </p></p></div>
+        """, elem_classes="gr-box")
+    with gr.Row():
+        with gr.Column(scale=100):
+            # Model selection dropdown
+            model_name1 = gr.Dropdown(label="Select Model", choices=[m for m in models], type="index",
+                                      value=current_model, interactive=True, elem_classes=["gr-box", "gr-input"])
+    with gr.Row():
+        with gr.Column(scale=100):
+            with gr.Group():
+                magic1 = gr.Textbox(label="Your Prompt", lines=4, elem_classes=["gr-box", "gr-input"]) #Positive
+                with gr.Accordion("Advanced", open=False, visible=True):
+                    neg_input = gr.Textbox(label='Negative prompt', lines=1, elem_classes=["gr-box", "gr-input"])
+                    with gr.Row():
+                        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"])
+                        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"])
+            run = gr.Button("Generate Image", variant="primary", elem_classes="gr-button")
+
+    with gr.Row():
+        with gr.Column():
+            output1 = gr.Image(label=(f"{current_model}"), show_download_button=True,
+                               interactive=False, show_share_button=False, format=".png", elem_classes="gr-box")
+                
+    with gr.Row():
+        with gr.Column(scale=50):
+            input_text=gr.Textbox(label="Use this box to extend an idea automagically, by typing some words and clicking Extend Idea", lines=2, elem_classes=["gr-box", "gr-input"])
+            see_prompts=gr.Button("Extend Idea -> overwrite the contents of the `Your Prompt´ box above", variant="primary", elem_classes="gr-button")
+            use_short=gr.Button("Copy the contents of this box to the `Your Prompt´ box above", variant="primary", elem_classes="gr-button")
+    def short_prompt(inputs):
+        return (inputs)
+    
+    model_name1.change(set_model, inputs=model_name1, outputs=[output1])
+    gr.on(
+        triggers=[run.click, magic1.submit],
+        fn=send_it1,
+        inputs=[magic1, model_name1, neg_input, height, width, steps, cfg, seed],
+        outputs=[output1],
+        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)
+    
+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