Update app_inference.py

app_inference.py

@@ -43,6 +43,9 @@ body {
 }
 """
 
+hf_token = os.getenv('HF_TOKEN')
+pipe = InferencePipeline(hf_token)
+app = InferenceUtil(hf_token)
 
 def get_choices(hf_token):
     api = HfApi(token=hf_token)
@@ -129,112 +132,103 @@ class InferenceUtil:
             raise type(e)(f'failed to update_model_info, due to: {e}')
 
 
-def create_inference_demo(pipe,  #: InferencePipeline,
-                          hf_token: str | None = None) -> gr.Blocks:
-    with gr.Blocks(css=css) as demo:
-        with gr.Row(elem_classes="gr-row"):
-            with gr.Column():
-                with gr.Group(elem_classes="lora-column"):
-                    gr.Markdown('## Content B-LoRA')
-                    content_checkbox = gr.Checkbox(label='Use Content Only', value=False)
-                    content_lora_model_id = gr.Dropdown(label='Model ID', choices=[])
-                    content_prompt = gr.Text(label='Content instance prompt', interactive=False, max_lines=1)
-                    content_image = gr.Image(label='Content Image', elem_classes="gr-image")
-            with gr.Column():
-                with gr.Group(elem_classes="lora-column"):
-                    gr.Markdown('## Style B-LoRA')
-                    style_checkbox = gr.Checkbox(label='Use Style Only', value=False)
-                    style_lora_model_id = gr.Dropdown(label='Model ID', choices=[])
-                    style_prompt = gr.Text(label='Style instance prompt', interactive=False, max_lines=1)
-                    style_image = gr.Image(label='Style Image', elem_classes="gr-image")
-        with gr.Row(elem_classes="gr-row"):
-            with gr.Column():
-                with gr.Group():
-                    prompt = gr.Textbox(
-                        label='Prompt',
-                        max_lines=1,
-                        placeholder='Example: "A [c] in [s] style"'
-                    )
-                    result = gr.Image(label='Result')
-                    with gr.Accordion('Other Parameters', open=False, elem_classes="gr-accordion"):
-                        content_alpha = gr.Slider(label='Content B-LoRA alpha',
-                                                  minimum=0,
-                                                  maximum=2,
-                                                  step=0.05,
-                                                  value=1)
-                        style_alpha = gr.Slider(label='Style B-LoRA alpha',
-                                                minimum=0,
-                                                maximum=2,
-                                                step=0.05,
-                                                value=1)
-                        seed = gr.Slider(label='Seed',
-                                         minimum=0,
-                                         maximum=100000,
-                                         step=1,
-                                         value=8888)
-                        num_steps = gr.Slider(label='Number of Steps',
+
+with gr.Blocks(css=css) as demo:
+    with gr.Row(elem_classes="gr-row"):
+        with gr.Column():
+            with gr.Group(elem_classes="lora-column"):
+                gr.Markdown('## Content B-LoRA')
+                content_checkbox = gr.Checkbox(label='Use Content Only', value=False)
+                content_lora_model_id = gr.Dropdown(label='Model ID', choices=[])
+                content_prompt = gr.Text(label='Content instance prompt', interactive=False, max_lines=1)
+                content_image = gr.Image(label='Content Image', elem_classes="gr-image")
+        with gr.Column():
+            with gr.Group(elem_classes="lora-column"):
+                gr.Markdown('## Style B-LoRA')
+                style_checkbox = gr.Checkbox(label='Use Style Only', value=False)
+                style_lora_model_id = gr.Dropdown(label='Model ID', choices=[])
+                style_prompt = gr.Text(label='Style instance prompt', interactive=False, max_lines=1)
+                style_image = gr.Image(label='Style Image', elem_classes="gr-image")
+    with gr.Row(elem_classes="gr-row"):
+        with gr.Column():
+            with gr.Group():
+                prompt = gr.Textbox(
+                    label='Prompt',
+                    max_lines=1,
+                    placeholder='Example: "A [c] in [s] style"'
+                )
+                result = gr.Image(label='Result')
+                with gr.Accordion('Other Parameters', open=False, elem_classes="gr-accordion"):
+                    content_alpha = gr.Slider(label='Content B-LoRA alpha',
                                               minimum=0,
-                                              maximum=100,
-                                              step=1,
-                                              value=50)
-                        guidance_scale = gr.Slider(label='CFG Scale',
-                                                   minimum=0,
-                                                   maximum=50,
-                                                   step=0.1,
-                                                   value=7.5)
-
-                    run_button = gr.Button('Generate')
-        demo.load(demo_init, inputs=[],
-                  outputs=[content_lora_model_id, content_prompt, content_image, style_lora_model_id, style_prompt,
-                           style_image, prompt], queue=False, show_progress="hidden")
-        content_lora_model_id.change(
-            fn=app.update_model_info,
-            inputs=content_lora_model_id,
-            outputs=[
-                content_prompt,
-                content_image,
-            ])
-        style_lora_model_id.change(
-            fn=app.update_model_info,
-            inputs=style_lora_model_id,
-            outputs=[
-                style_prompt,
-                style_image,
-            ])
-        style_prompt.change(
-            fn=lambda content_blora_prompt,
-                      style_blora_prompt: f'{content_blora_prompt} in {style_blora_prompt[0].lower() + style_blora_prompt[1:]} style' if style_blora_prompt else content_blora_prompt,
-            inputs=[content_prompt, style_prompt],
-            outputs=prompt,
-        )
-        content_prompt.change(
-            fn=lambda content_blora_prompt,
-                      style_blora_prompt: f'{content_blora_prompt} in {style_blora_prompt[0].lower() + style_blora_prompt[1:]} style' if content_blora_prompt else style_blora_prompt,
-            inputs=[content_prompt, style_prompt],
-            outputs=prompt,
-        )
-        content_checkbox.change(toggle_column, inputs=[content_checkbox],
-                                outputs=[style_lora_model_id])
-        style_checkbox.change(toggle_column, inputs=[style_checkbox],
-                              outputs=[content_lora_model_id])
-        inputs = [
-            content_lora_model_id,
-            style_lora_model_id,
-            prompt,
-            content_alpha,
-            style_alpha,
-            seed,
-            num_steps,
-            guidance_scale,
-        ]
-        prompt.submit(fn=pipe.run, inputs=inputs, outputs=result)
-        run_button.click(fn=pipe.run, inputs=inputs, outputs=result)
-    return demo
-
-
-if __name__ == '__main__':
-    hf_token = os.getenv('HF_TOKEN')
-    pipe = InferencePipeline(hf_token)
-    app = InferenceUtil(hf_token)
-    demo = create_inference_demo(pipe, hf_token)
-    demo.queue(max_size=10).launch(share=False)
+                                              maximum=2,
+                                              step=0.05,
+                                              value=1)
+                    style_alpha = gr.Slider(label='Style B-LoRA alpha',
+                                            minimum=0,
+                                            maximum=2,
+                                            step=0.05,
+                                            value=1)
+                    seed = gr.Slider(label='Seed',
+                                     minimum=0,
+                                     maximum=100000,
+                                     step=1,
+                                     value=8888)
+                    num_steps = gr.Slider(label='Number of Steps',
+                                          minimum=0,
+                                          maximum=100,
+                                          step=1,
+                                          value=50)
+                    guidance_scale = gr.Slider(label='CFG Scale',
+                                               minimum=0,
+                                               maximum=50,
+                                               step=0.1,
+                                               value=7.5)
+                run_button = gr.Button('Generate')
+    demo.load(demo_init, inputs=[],
+              outputs=[content_lora_model_id, content_prompt, content_image, style_lora_model_id, style_prompt,
+                       style_image, prompt], queue=False, show_progress="hidden")
+    content_lora_model_id.change(
+        fn=app.update_model_info,
+        inputs=content_lora_model_id,
+        outputs=[
+            content_prompt,
+            content_image,
+        ])
+    style_lora_model_id.change(
+        fn=app.update_model_info,
+        inputs=style_lora_model_id,
+        outputs=[
+            style_prompt,
+            style_image,
+        ])
+    style_prompt.change(
+        fn=lambda content_blora_prompt,
+                  style_blora_prompt: f'{content_blora_prompt} in {style_blora_prompt[0].lower() + style_blora_prompt[1:]} style' if style_blora_prompt else content_blora_prompt,
+        inputs=[content_prompt, style_prompt],
+        outputs=prompt,
+    )
+    content_prompt.change(
+        fn=lambda content_blora_prompt,
+                  style_blora_prompt: f'{content_blora_prompt} in {style_blora_prompt[0].lower() + style_blora_prompt[1:]} style' if content_blora_prompt else style_blora_prompt,
+        inputs=[content_prompt, style_prompt],
+        outputs=prompt,
+    )
+    content_checkbox.change(toggle_column, inputs=[content_checkbox],
+                            outputs=[style_lora_model_id])
+    style_checkbox.change(toggle_column, inputs=[style_checkbox],
+                          outputs=[content_lora_model_id])
+    inputs = [
+        content_lora_model_id,
+        style_lora_model_id,
+        prompt,
+        content_alpha,
+        style_alpha,
+        seed,
+        num_steps,
+        guidance_scale,
+    ]
+    prompt.submit(fn=pipe.run, inputs=inputs, outputs=result)
+    run_button.click(fn=pipe.run, inputs=inputs, outputs=result)
+
+demo.queue(max_size=10).launch(share=False)