Upload 2 files

app.py

@@ -119,11 +119,11 @@ with gr.Blocks(theme='Nymbo/Nymbo_Theme', fill_width=True, css=CSS) as demo:
                 neg_input = gr.Textbox(label='Negative prompt:', lines=1)
                 with gr.Accordion("Advanced", open=False, visible=True):
                     with gr.Row():
-                        width = gr.Number(label="Width", info="If 0, the default value is used.", maximum=1216, step=32, value=0)
-                        height = gr.Number(label="Height", info="If 0, the default value is used.", maximum=1216, step=32, value=0)
+                        width = gr.Slider(label="Width", info="If 0, the default value is used.", maximum=1216, step=32, value=0)
+                        height = gr.Slider(label="Height", info="If 0, the default value is used.", maximum=1216, step=32, value=0)
                     with gr.Row():
-                        steps = gr.Number(label="Number of inference steps", info="If 0, the default value is used.", maximum=100, step=1, value=0)
-                        cfg = gr.Number(label="Guidance scale", info="If 0, the default value is used.", maximum=30.0, step=0.1, value=0)
+                        steps = gr.Slider(label="Number of inference steps", info="If 0, the default value is used.", maximum=100, step=1, value=0)
+                        cfg = gr.Slider(label="Guidance scale", info="If 0, the default value is used.", maximum=30.0, step=0.1, value=0)
                         seed = gr.Slider(label="Seed", info="Randomize Seed if -1.", minimum=-1, maximum=MAX_SEED, step=1, value=-1)
             with gr.Row():
                 gen_button = gr.Button(f'Generate up to {int(num_models)} images in up to 3 minutes total', scale=3)
@@ -166,11 +166,11 @@ with gr.Blocks(theme='Nymbo/Nymbo_Theme', fill_width=True, css=CSS) as demo:
                 neg_input2 = gr.Textbox(label='Negative prompt:', lines=1)
                 with gr.Accordion("Advanced", open=False, visible=True):
                     with gr.Row():
-                        width2 = gr.Number(label="Width", info="If 0, the default value is used.", maximum=1216, step=32, value=0)
-                        height2 = gr.Number(label="Height", info="If 0, the default value is used.", maximum=1216, step=32, value=0)
+                        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.Number(label="Number of inference steps", info="If 0, the default value is used.", maximum=100, step=1, value=0)
-                        cfg2 = gr.Number(label="Guidance scale", info="If 0, the default value is used.", maximum=30.0, step=0.1, value=0)
+                        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)
             num_images = gr.Slider(1, max_images, value=max_images, step=1, label='Number of images')
             with gr.Row():
@@ -202,5 +202,5 @@ with gr.Blocks(theme='Nymbo/Nymbo_Theme', fill_width=True, css=CSS) as demo:
 
     gr.Markdown("Based on the [TestGen](https://huggingface.co/spaces/derwahnsinn/TestGen) Space by derwahnsinn, the [SpacIO](https://huggingface.co/spaces/RdnUser77/SpacIO_v1) Space by RdnUser77 and Omnibus's Maximum Multiplier!")
 
-demo.queue()
-demo.launch()
+demo.queue(default_concurrency_limit=200, max_size=200)
+demo.launch(show_api=False, max_threads=400)

externalmod.py

@@ -531,7 +531,11 @@ def gr_Interface_load(
     alias: str | None = None,
     **kwargs,
 ) -> Blocks:
-    return load_blocks_from_repo(name, src, hf_token, alias)
+    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 list_uniq(l):