Update app.py

app.py

@@ -234,70 +234,111 @@ def run_lora(prompt, image_input, image_strength, cfg_scale, steps, selected_ind
         if randomize_seed:
             seed = random.randint(0, MAX_SEED)
 
-    try:
-        if image_input is not None:
-            final_image, file_path, base64_str = generate_image_to_image(prompt_mash, image_input, image_strength, steps, cfg_scale, width, height, lora_scale, seed)
-            return final_image, file_path, base64_str
+    if image_input is not None:
+        final_image, file_path, base64_str = generate_image_to_image(prompt_mash, image_input, image_strength, steps, cfg_scale, width, height, lora_scale, seed)
+        return final_image, file_path, base64_str
 
-        else:
-            image_generator = generate_image(prompt_mash, steps, seed, cfg_scale, width, height, lora_scale, progress)
-            final_image = None
-            for image in image_generator:
-                final_image = image
-
-            # Save and encode final image
-            temp_file = tempfile.NamedTemporaryFile(delete=False, suffix=".png")
-            final_image.save(temp_file.name, "PNG")
-            with open(temp_file.name, "rb") as f:
-                base64_str = base64.b64encode(f.read()).decode("utf-8")
-
-            return final_image, temp_file.name, base64_str
-
-    except Exception as e:
-        raise gr.Error(f"Error during image generation: {e}")
-
-# Define the Gradio interface
-def interface():
-    with gr.Blocks() as demo:
-        gr.Markdown("# Image Generator with LoRA and Downloadable Outputs")
-
-        with gr.Row():
-            prompt = gr.Textbox(label="Prompt")
-            image_input = gr.Image(type="filepath", label="Optional Input Image")
-
-        with gr.Row():
-            cfg_scale = gr.Slider(label="CFG Scale", minimum=1, maximum=20, step=0.5, value=7)
-            steps = gr.Slider(label="Steps", minimum=1, maximum=50, step=1, value=25)
-
-        with gr.Row():
-            randomize_seed = gr.Checkbox(label="Randomize Seed", value=True)
-            seed = gr.Number(label="Seed", value=0, precision=0)
-
-        with gr.Row():
-            width = gr.Slider(label="Width", minimum=256, maximum=1024, step=64, value=512)
-            height = gr.Slider(label="Height", minimum=256, maximum=1024, step=64, value=512)
-
-        with gr.Row():
-            lora_scale = gr.Slider(label="LoRA Scale", minimum=0.1, maximum=2.0, step=0.1, value=1.0)
-
-        generate_btn = gr.Button("Generate")
-        result_image = gr.Image(label="Generated Image")
-        download_link = gr.File(label="Download Image")
-        base64_output = gr.Textbox(label="Base64 Encoded String")
-
-        def run_interface(prompt, image_input, cfg_scale, steps, randomize_seed, seed, width, height, lora_scale):
-            if randomize_seed:
-                seed = random.randint(0, MAX_SEED)
-            final_image, file_path, base64_str = run_lora(prompt, image_input, 0.75, cfg_scale, steps, 0, randomize_seed, seed, width, height, lora_scale)
-            return final_image, file_path, base64_str
-
-        generate_btn.click(
-            run_interface,
-            inputs=[prompt, image_input, cfg_scale, steps, randomize_seed, seed, width, height, lora_scale],
-            outputs=[result_image, download_link, base64_output]
-        )
-
-    demo.launch()
-
-if __name__ == "__main__":
-    interface()
+    else:
+        image_generator = generate_image(prompt_mash, steps, seed, cfg_scale, width, height, lora_scale, progress)
+        final_image = None
+        for image in image_generator:
+            final_image = image
+
+        # Save and encode final image
+        temp_file = tempfile.NamedTemporaryFile(delete=False, suffix=".png")
+        final_image.save(temp_file.name, "PNG")
+        with open(temp_file.name, "rb") as f:
+            base64_str = base64.b64encode(f.read()).decode("utf-8")
+
+        return final_image, temp_file.name, base64_str
+
+css = '''
+#gen_btn{height: 100%}
+#gen_column{align-self: stretch}
+#title{text-align: center}
+#title h1{font-size: 3em; display:inline-flex; align-items:center}
+#title img{width: 100px; margin-right: 0.5em}
+#gallery .grid-wrap{height: 10vh}
+#lora_list{background: var(--block-background-fill);padding: 0 1em .3em; font-size: 90%}
+.card_internal{display: flex;height: 100px;margin-top: .5em}
+.card_internal img{margin-right: 1em}
+.styler{--form-gap-width: 0px !important}
+#progress{height:30px}
+#progress .generating{display:none}
+.progress-container {width: 100%;height: 30px;background-color: #f0f0f0;border-radius: 15px;overflow: hidden;margin-bottom: 20px}
+.progress-bar {height: 100%;background-color: #4f46e5;width: calc(var(--current) / var(--total) * 100%);transition: width 0.5s ease-in-out}
+'''
+font=[gr.themes.GoogleFont("Source Sans Pro"), "Arial", "sans-serif"]
+with gr.Blocks(theme=gr.themes.Soft(font=font), css=css, delete_cache=(60, 60)) as app:
+    title = gr.HTML(
+        """<h1><img src=\"https://huggingface.co/spaces/multimodalart/flux-lora-the-explorer/resolve/main/flux_lora.png\" alt=\"LoRA\"> FLUX LoRA the Explorer</h1>""",
+        elem_id="title",
+    )
+    selected_index = gr.State(None)
+    with gr.Row():
+        with gr.Column(scale=3):
+            prompt = gr.Textbox(label="Prompt", lines=1, placeholder="Type a prompt after selecting a LoRA")
+        with gr.Column(scale=1, elem_id="gen_column"):
+            generate_button = gr.Button("Generate", variant="primary", elem_id="gen_btn")
+    with gr.Row():
+        with gr.Column():
+            selected_info = gr.Markdown("")
+            gallery = gr.Gallery(
+                [(item["image"], item["title"]) for item in loras],
+                label="LoRA Gallery",
+                allow_preview=False,
+                columns=3,
+                elem_id="gallery",
+                show_share_button=False
+            )
+            with gr.Group():
+                custom_lora = gr.Textbox(label="Custom LoRA", info="LoRA Hugging Face path", placeholder="multimodalart/vintage-ads-flux")
+                gr.Markdown("[Check the list of FLUX LoRas](https://huggingface.co/models?other=base_model:adapter:black-forest-labs/FLUX.1-dev)", elem_id="lora_list")
+            custom_lora_info = gr.HTML(visible=False)
+            custom_lora_button = gr.Button("Remove custom LoRA", visible=False)
+        with gr.Column():
+            progress_bar = gr.Markdown(elem_id="progress",visible=False)
+            result = gr.Image(label="Generated Image")
+            download_link = gr.File(label="Download Image")
+            base64_output = gr.Textbox(label="Base64 Encoded Image")
+
+    with gr.Row():
+        with gr.Accordion("Advanced Settings", open=False):
+            with gr.Row():
+                input_image = gr.Image(label="Input image", type="filepath")
+                image_strength = gr.Slider(label="Denoise Strength", info="Lower means more image influence", minimum=0.1, maximum=1.0, step=0.01, value=0.75)
+            with gr.Column():
+                with gr.Row():
+                    cfg_scale = gr.Slider(label="CFG Scale", minimum=1, maximum=20, step=0.5, value=3.5)
+                    steps = gr.Slider(label="Steps", minimum=1, maximum=50, step=1, value=28)
+                
+                with gr.Row():
+                    width = gr.Slider(label="Width", minimum=256, maximum=1536, step=64, value=1024)
+                    height = gr.Slider(label="Height", minimum=256, maximum=1536, step=64, value=1024)
+                
+                with gr.Row():
+                    randomize_seed = gr.Checkbox(True, label="Randomize seed")
+                    seed = gr.Slider(label="Seed", minimum=0, maximum=MAX_SEED, step=1, value=0, randomize=True)
+                    lora_scale = gr.Slider(label="LoRA Scale", minimum=0, maximum=3, step=0.01, value=0.95)
+
+    gallery.select(
+        update_selection,
+        inputs=[width, height],
+        outputs=[prompt, selected_info, selected_index, width, height]
+    )
+    custom_lora.input(
+        add_custom_lora,
+        inputs=[custom_lora],
+        outputs=[custom_lora_info, custom_lora_button, gallery, selected_info, selected_index, prompt]
+    )
+    custom_lora_button.click(
+        remove_custom_lora,
+        outputs=[custom_lora_info, custom_lora_button, gallery, selected_info, selected_index, custom_lora]
+    )
+    generate_button.click(
+        run_lora,
+        inputs=[prompt, input_image, image_strength, cfg_scale, steps, selected_index, randomize_seed, seed, width, height, lora_scale],
+        outputs=[result, download_link, base64_output]
+    )
+app.queue()
+app.launch()