Update app.py

app.py

@@ -233,118 +233,71 @@ def run_lora(prompt, image_input, image_strength, cfg_scale, steps, selected_ind
     with calculateDuration("Randomizing seed"):
         if randomize_seed:
             seed = random.randint(0, MAX_SEED)
-            
-    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)
-    
-        # Consume the generator to get the final image
-        final_image = None
-        step_counter = 0
-        for image in image_generator:
-            step_counter += 1
-            final_image = image
-            progress_bar = f'<div class="progress-container"><div class="progress-bar" style="--current: {step_counter}; --total: {steps};"></div></div>'
-            yield image, seed, None, None, gr.update(value=progress_bar, visible=True)
-            
-        # Save the final image and encode to Base64
-        temp_file = tempfile.NamedTemporaryFile(delete=False, suffix=".png")
-        final_image.save(temp_file.name, "PNG")
-        with open(temp_file.name, "rb") as f:
-            img_base64 = 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, seed, progress_bar]
-    )
-app.queue()
-app.launch()
 
+    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
+
+        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()