Update app.py

app.py

@@ -41,9 +41,9 @@ def infer(prompt, seed=42, randomize_seed=False, width=1024, height=1024, guidan
 
     # Handle LoRA loading
     # Load LoRA weights and prepare joint_attention_kwargs
-    if lora_id:
+    if lora_id and lora_id.strip() != "":
         pipe.unload_lora_weights()
-        pipe.load_lora_weights(lora_id)
+        pipe.load_lora_weights(lora_id.strip())
         joint_attention_kwargs = {"scale": lora_scale}
     else:
         joint_attention_kwargs = None
@@ -61,7 +61,7 @@ def infer(prompt, seed=42, randomize_seed=False, width=1024, height=1024, guidan
             good_vae=good_vae,  # Assuming good_vae is defined elsewhere
             joint_attention_kwargs=joint_attention_kwargs,  # Fixed parameter name
         ):
-            yield img, seed
+            yield img, seed, seed
     finally:
         # Unload LoRA weights if they were loaded
         if lora_id:
@@ -73,168 +73,181 @@ examples = [
     "an anime illustration of a wiener schnitzel",
 ]
 
-css="""
-#col-container {
-    margin: 0 auto;
-    max-width: 520px;
-}
-"""
+# css="""
+# #col-container {
+#     margin: 0 auto;
+#     max-width: 520px;
+# }
+# """
 
-with gr.Blocks(css=css) as demo:
+# with gr.Blocks(css=css) as demo:
     
-    with gr.Column(elem_id="col-container"):
-        gr.Markdown(f"""# FLUX.1 [dev] LoRA
-12B param rectified flow transformer guidance-distilled from [FLUX.1 [pro]](https://blackforestlabs.ai/)  
-[[non-commercial license](https://huggingface.co/black-forest-labs/FLUX.1-dev/blob/main/LICENSE.md)] [[blog](https://blackforestlabs.ai/announcing-black-forest-labs/)] [[model](https://huggingface.co/black-forest-labs/FLUX.1-dev)]
-        """)
+#     with gr.Column(elem_id="col-container"):
+#         gr.Markdown(f"""# FLUX.1 [dev] LoRA
+# 12B param rectified flow transformer guidance-distilled from [FLUX.1 [pro]](https://blackforestlabs.ai/)  
+# [[non-commercial license](https://huggingface.co/black-forest-labs/FLUX.1-dev/blob/main/LICENSE.md)] [[blog](https://blackforestlabs.ai/announcing-black-forest-labs/)] [[model](https://huggingface.co/black-forest-labs/FLUX.1-dev)]
+#         """)
         
-        with gr.Row():
+#         with gr.Row():
             
-            prompt = gr.Text(
-                label="Prompt",
-                show_label=False,
-                max_lines=1,
-                placeholder="Enter your prompt",
-                container=False,
-            )
+#             prompt = gr.Text(
+#                 label="Prompt",
+#                 show_label=False,
+#                 max_lines=1,
+#                 placeholder="Enter your prompt",
+#                 container=False,
+#             )
             
-            run_button = gr.Button("Run", scale=0)
+#             run_button = gr.Button("Run", scale=0)
         
-        result = gr.Image(label="Result", show_label=False)
+#         result = gr.Image(label="Result", show_label=False)
         
-        with gr.Accordion("Advanced Settings", open=False):
+#         with gr.Accordion("Advanced Settings", open=False):
             
-            seed = gr.Slider(
-                label="Seed",
-                minimum=0,
-                maximum=MAX_SEED,
-                step=1,
-                value=0,
-            )
+#             seed = gr.Slider(
+#                 label="Seed",
+#                 minimum=0,
+#                 maximum=MAX_SEED,
+#                 step=1,
+#                 value=0,
+#             )
             
-            randomize_seed = gr.Checkbox(label="Randomize seed", value=True)
+#             randomize_seed = gr.Checkbox(label="Randomize seed", value=True)
             
-            with gr.Row():
+#             with gr.Row():
                 
-                width = gr.Slider(
-                    label="Width",
-                    minimum=256,
-                    maximum=MAX_IMAGE_SIZE,
-                    step=8,
-                    value=1024,
-                )
+#                 width = gr.Slider(
+#                     label="Width",
+#                     minimum=256,
+#                     maximum=MAX_IMAGE_SIZE,
+#                     step=8,
+#                     value=1024,
+#                 )
                 
-                height = gr.Slider(
-                    label="Height",
-                    minimum=256,
-                    maximum=MAX_IMAGE_SIZE,
-                    step=8,
-                    value=1024,
-                )
+#                 height = gr.Slider(
+#                     label="Height",
+#                     minimum=256,
+#                     maximum=MAX_IMAGE_SIZE,
+#                     step=8,
+#                     value=1024,
+#                 )
             
-            with gr.Row():
-
-                guidance_scale = gr.Slider(
-                    label="Guidance Scale",
-                    minimum=1,
-                    maximum=15,
-                    step=0.1,
-                    value=3.5,
-                )
+#             with gr.Row():
+
+#                 guidance_scale = gr.Slider(
+#                     label="Guidance Scale",
+#                     minimum=1,
+#                     maximum=15,
+#                     step=0.1,
+#                     value=3.5,
+#                 )
   
-                num_inference_steps = gr.Slider(
-                    label="Number of inference steps",
-                    minimum=1,
-                    maximum=50,
-                    step=1,
-                    value=28,
-                )
-
-            with gr.Row():
-                lora_id = gr.Textbox(
-                    label="LoRA Model ID (HuggingFace path)",
-                    placeholder="username/lora-model",
-                    max_lines=1
-                )
-                lora_scale = gr.Slider(
-                    label="LoRA Scale",
-                    minimum=0,
-                    maximum=2,
-                    step=0.01,
-                    value=0.95,
-                )
+#                 num_inference_steps = gr.Slider(
+#                     label="Number of inference steps",
+#                     minimum=1,
+#                     maximum=50,
+#                     step=1,
+#                     value=28,
+#                 )
+
+#             with gr.Row():
+#                 lora_id = gr.Textbox(
+#                     label="LoRA Model ID (HuggingFace path)",
+#                     placeholder="username/lora-model",
+#                     max_lines=1
+#                 )
+#                 lora_scale = gr.Slider(
+#                     label="LoRA Scale",
+#                     minimum=0,
+#                     maximum=2,
+#                     step=0.01,
+#                     value=0.95,
+#                 )
         
-        gr.Examples(
-            examples = examples,
-            fn = infer,
-            inputs = [prompt],
-            outputs = [result, seed],
-            cache_examples="lazy"
-        )
+#         gr.Examples(
+#             examples = examples,
+#             fn = infer,
+#             inputs = [prompt],
+#             outputs = [result, seed],
+#             cache_examples="lazy"
+#         )
 
-    gr.on(
-        triggers=[run_button.click, prompt.submit],
-        fn = infer,
-        inputs = [prompt, seed, randomize_seed, width, height, guidance_scale, num_inference_steps,lora_id,lora_scale],
-        outputs = [result, seed]
-    )
+#     gr.on(
+#         triggers=[run_button.click, prompt.submit],
+#         fn = infer,
+#         inputs = [prompt, seed, randomize_seed, width, height, guidance_scale, num_inference_steps,lora_id,lora_scale],
+#         outputs = [result, seed]
+#     )
 
-demo.launch()
+# demo.launch()
     
+css = """
+#col-container {
+   margin: 0 auto;
+   max-width: 960px;
+}
+.generate-btn {
+   background: linear-gradient(90deg, #4B79A1 0%, #283E51 100%) !important;
+   border: none !important;
+   color: white !important;
+}
+.generate-btn:hover {
+   transform: translateY(-2px);
+   box-shadow: 0 5px 15px rgba(0,0,0,0.2);
+}
+"""
 
-
-
-# with gr.Blocks(css=css) as app:
-#     gr.HTML("<center><h1>FLUX.1-Dev with LoRA support</h1></center>")
-#     with gr.Column(elem_id="col-container"):
-#         with gr.Row():
-#             with gr.Column():
-#                 with gr.Row():
-#                     text_prompt = gr.Textbox(label="Prompt", placeholder="Enter a prompt here", lines=3, elem_id="prompt-text-input")
-#                 with gr.Row():
-#                     custom_lora = gr.Textbox(label="Custom LoRA", info="LoRA Hugging Face path (optional)", placeholder="multimodalart/vintage-ads-flux")
-#                 with gr.Row():
-#                     with gr.Accordion("Advanced Settings", open=False):
-#                         lora_scale = gr.Slider(
-#                             label="LoRA Scale",
-#                             minimum=0,
-#                             maximum=2,
-#                             step=0.01,
-#                             value=0.95,
-#                         )
-#                         with gr.Row():
-#                             width = gr.Slider(label="Width", value=1024, minimum=64, maximum=1216, step=8)
-#                             height = gr.Slider(label="Height", value=1024, minimum=64, maximum=1216, step=8)
-#                         seed = gr.Slider(label="Seed", value=-1, minimum=-1, maximum=4294967296, step=1)
-#                         randomize_seed = gr.Checkbox(label="Randomize seed", value=True)
-#                         with gr.Row():
-#                             steps = gr.Slider(label="Inference steps steps", value=28, minimum=1, maximum=100, step=1)
-#                             cfg = gr.Slider(label="Guidance Scale", value=3.5, minimum=1, maximum=20, step=0.5)
-#                         # method = gr.Radio(label="Sampling method", value="DPM++ 2M Karras", choices=["DPM++ 2M Karras", "DPM++ SDE Karras", "Euler", "Euler a", "Heun", "DDIM"])
-
-#                 with gr.Row():
-#                     # text_button = gr.Button("Run", variant='primary', elem_id="gen-button")
-#                     text_button = gr.Button("✨ Generate Image", variant='primary', elem_classes=["generate-btn"])
-#             with gr.Column():
-#                 with gr.Row():
-#                     image_output = gr.Image(type="pil", label="Image Output", elem_id="gallery")
-#                 with gr.Row():
-#                     seed_output = gr.Textbox(label="Seed Used", show_copy_button = True)
+with gr.Blocks(css=css) as app:
+    gr.HTML("<center><h1>FLUX.1-Dev with LoRA support</h1></center>")
+    with gr.Column(elem_id="col-container"):
+        with gr.Row():
+            with gr.Column():
+                with gr.Row():
+                    text_prompt = gr.Textbox(label="Prompt", placeholder="Enter a prompt here", lines=3, elem_id="prompt-text-input")
+                with gr.Row():
+                    custom_lora = gr.Textbox(label="Custom LoRA", info="LoRA Hugging Face path (optional)", placeholder="multimodalart/vintage-ads-flux")
+                with gr.Row():
+                    with gr.Accordion("Advanced Settings", open=False):
+                        lora_scale = gr.Slider(
+                            label="LoRA Scale",
+                            minimum=0,
+                            maximum=2,
+                            step=0.01,
+                            value=0.95,
+                        )
+                        with gr.Row():
+                            width = gr.Slider(label="Width", value=1024, minimum=64, maximum=1216, step=8)
+                            height = gr.Slider(label="Height", value=1024, minimum=64, maximum=1216, step=8)
+                        seed = gr.Slider(label="Seed", value=-1, minimum=-1, maximum=4294967296, step=1)
+                        randomize_seed = gr.Checkbox(label="Randomize seed", value=True)
+                        with gr.Row():
+                            steps = gr.Slider(label="Inference steps steps", value=28, minimum=1, maximum=100, step=1)
+                            cfg = gr.Slider(label="Guidance Scale", value=3.5, minimum=1, maximum=20, step=0.5)
+                        # method = gr.Radio(label="Sampling method", value="DPM++ 2M Karras", choices=["DPM++ 2M Karras", "DPM++ SDE Karras", "Euler", "Euler a", "Heun", "DDIM"])
+
+                with gr.Row():
+                    # text_button = gr.Button("Run", variant='primary', elem_id="gen-button")
+                    text_button = gr.Button("✨ Generate Image", variant='primary', elem_classes=["generate-btn"])
+            with gr.Column():
+                with gr.Row():
+                    image_output = gr.Image(type="pil", label="Image Output", elem_id="gallery")
+                with gr.Row():
+                    seed_output = gr.Textbox(label="Seed Used", show_copy_button = True)
         
-#         # gr.Markdown(article_text)
-#         with gr.Column():
-#             gr.Examples(
-#                 examples = examples,
-#                 inputs = [text_prompt],
-#             )
-#     gr.on(
-#         triggers=[text_button.click, text_prompt.submit],
-#         fn = infer,
-#         inputs=[text_prompt, seed, randomize_seed, width, height, cfg, steps, custom_lora, lora_scale], 
-#         outputs=[image_output,seed_output, seed]
-#     )
+        # gr.Markdown(article_text)
+        with gr.Column():
+            gr.Examples(
+                examples = examples,
+                inputs = [text_prompt],
+            )
+    gr.on(
+        triggers=[text_button.click, text_prompt.submit],
+        fn = infer,
+        inputs=[text_prompt, seed, randomize_seed, width, height, cfg, steps, custom_lora, lora_scale], 
+        outputs=[image_output,seed_output, seed]
+    )
         
-#         # text_button.click(query, inputs=[custom_lora, text_prompt, steps, cfg, randomize_seed, seed, width, height], outputs=[image_output,seed_output, seed])
-#         # text_button.click(infer, inputs=[text_prompt, seed, randomize_seed, width, height, cfg, steps, custom_lora, lora_scale], outputs=[image_output,seed_output, seed])
+        # text_button.click(query, inputs=[custom_lora, text_prompt, steps, cfg, randomize_seed, seed, width, height], outputs=[image_output,seed_output, seed])
+        # text_button.click(infer, inputs=[text_prompt, seed, randomize_seed, width, height, cfg, steps, custom_lora, lora_scale], outputs=[image_output,seed_output, seed])
 
-# app.launch(share=True)
+app.launch(share=True)