Update app.py

app.py

@@ -202,11 +202,14 @@ def run_lora(prompt, cfg_scale, steps, selected_index, randomize_seed, seed, asp
     # Load LoRAs based on speed mode
     if speed_mode == "Speed (4 steps)":
         with calculateDuration("Loading Lightning LoRA and style LoRA"):
+            # Load Lightning LoRA first
             pipe.load_lora_weights(
                 LIGHTNING_LORA_REPO, 
                 weight_name=LIGHTNING_LORA_WEIGHT,
                 adapter_name="lightning"
             )
+            
+            # Load the selected style LoRA
             weight_name = selected_lora.get("weights", None)
             pipe.load_lora_weights(
                 lora_path, 
@@ -214,14 +217,19 @@ def run_lora(prompt, cfg_scale, steps, selected_index, randomize_seed, seed, asp
                 low_cpu_mem_usage=True,
                 adapter_name="style"
             )
+            
+            # Set both adapters active with their weights
             pipe.set_adapters(["lightning", "style"], adapter_weights=[1.0, lora_scale])
     elif speed_mode == "Speed (8 steps)":
         with calculateDuration("Loading Lightning LoRA and style LoRA"):
+            # Load Lightning LoRA first
             pipe.load_lora_weights(
                 LIGHTNING_LORA_REPO, 
                 weight_name=LIGHTNING8_LORA_WEIGHT,
                 adapter_name="lightning"
             )
+            
+            # Load the selected style LoRA
             weight_name = selected_lora.get("weights", None)
             pipe.load_lora_weights(
                 lora_path, 
@@ -229,8 +237,11 @@ def run_lora(prompt, cfg_scale, steps, selected_index, randomize_seed, seed, asp
                 low_cpu_mem_usage=True,
                 adapter_name="style"
             )
+            
+            # Set both adapters active with their weights
             pipe.set_adapters(["lightning", "style"], adapter_weights=[1.0, lora_scale])
     else:
+        # Quality mode - only load the style LoRA
         with calculateDuration(f"Loading LoRA weights for {selected_lora['title']}"):
             weight_name = selected_lora.get("weights", None)
             pipe.load_lora_weights(
@@ -254,4 +265,289 @@ def run_lora(prompt, cfg_scale, steps, selected_index, randomize_seed, seed, asp
     
     return final_image, seed
 
-# (resto del código con interfaz Gradio, etc.)
+def get_huggingface_safetensors(link):
+    split_link = link.split("/")
+    if len(split_link) != 2:
+        raise Exception("Invalid Hugging Face repository link format.")
+
+    print(f"Repository attempted: {split_link}")
+    
+    # Load model card
+    model_card = ModelCard.load(link)
+    base_model = model_card.data.get("base_model")
+    print(f"Base model: {base_model}")
+
+    # Validate model type (for Qwen-Image)
+    acceptable_models = {"Qwen/Qwen-Image"}
+    
+    models_to_check = base_model if isinstance(base_model, list) else [base_model]
+    
+    if not any(model in acceptable_models for model in models_to_check):
+        raise Exception("Not a Qwen-Image LoRA!")
+        
+    # Extract image and trigger word
+    image_path = model_card.data.get("widget", [{}])[0].get("output", {}).get("url", None)
+    trigger_word = model_card.data.get("instance_prompt", "")
+    image_url = f"https://huggingface.co/{link}/resolve/main/{image_path}" if image_path else None
+
+    # Initialize Hugging Face file system
+    fs = HfFileSystem()
+    try:
+        list_of_files = fs.ls(link, detail=False)
+        
+        # Find safetensors file
+        safetensors_name = None
+        for file in list_of_files:
+            filename = file.split("/")[-1]
+            if filename.endswith(".safetensors"):
+                safetensors_name = filename
+                break
+
+        if not safetensors_name:
+            raise Exception("No valid *.safetensors file found in the repository.")
+
+    except Exception as e:
+        print(e)
+        raise Exception("You didn't include a valid Hugging Face repository with a *.safetensors LoRA")
+    
+    return split_link[1], link, safetensors_name, trigger_word, image_url
+
+def check_custom_model(link):
+    print(f"Checking a custom model on: {link}")
+    
+    if link.endswith('.safetensors'):
+        if 'huggingface.co' in link:
+            parts = link.split('/')
+            try:
+                hf_index = parts.index('huggingface.co')
+                username = parts[hf_index + 1]
+                repo_name = parts[hf_index + 2]
+                repo = f"{username}/{repo_name}"
+                
+                safetensors_name = parts[-1]
+                
+                try:
+                    model_card = ModelCard.load(repo)
+                    trigger_word = model_card.data.get("instance_prompt", "")
+                    image_path = model_card.data.get("widget", [{}])[0].get("output", {}).get("url", None)
+                    image_url = f"https://huggingface.co/{repo}/resolve/main/{image_path}" if image_path else None
+                except:
+                    trigger_word = ""
+                    image_url = None
+                
+                return repo_name, repo, safetensors_name, trigger_word, image_url
+            except:
+                raise Exception("Invalid safetensors URL format")
+    
+    if link.startswith("https://"):
+        if link.startswith("https://huggingface.co") or link.startswith("https://www.huggingface.co"):
+            link_split = link.split("huggingface.co/")
+            return get_huggingface_safetensors(link_split[1])
+    else: 
+        return get_huggingface_safetensors(link)
+
+def add_custom_lora(custom_lora):
+    global loras
+    if custom_lora:
+        try:
+            title, repo, path, trigger_word, image = check_custom_model(custom_lora)
+            print(f"Loaded custom LoRA: {repo}")
+            
+            # Get model card examples for custom LoRA
+            model_card_examples = ""
+            try:
+                model_card = ModelCard.load(repo)
+                widget_data = model_card.data.get("widget", [])
+                if widget_data and len(widget_data) > 0:
+                    examples_html = '<div style="margin-top: 10px;">'
+                    examples_html += '<h4 style="margin-bottom: 8px; font-size: 0.9em;">Sample Images:</h4>'
+                    examples_html += '<div style="display: grid; grid-template-columns: repeat(4, 1fr); gap: 8px;">'
+                    
+                    for i, example in enumerate(widget_data[:4]):
+                        if "output" in example and "url" in example["output"]:
+                            image_url = f"https://huggingface.co/{repo}/resolve/main/{example['output']['url']}"
+                            caption = example.get("text", f"Example {i+1}")
+                            examples_html += f'''
+                            <div style="text-align: center;">
+                                <img src="{image_url}" style="width: 100%; height: auto; border-radius: 4px;" />
+                                <p style="font-size: 0.7em; margin: 2px 0;">{caption[:30]}{'...' if len(caption) > 30 else ''}</p>
+                            </div>
+                            '''
+                    
+                    examples_html += '</div></div>'
+                    model_card_examples = examples_html
+            except Exception as e:
+                print(f"Could not load model card examples for custom LoRA: {e}")
+            
+            card = f'''
+            <div class="custom_lora_card">
+              <span>Loaded custom LoRA:</span>
+              <div class="card_internal">
+                <img src="{image}" />
+                <div>
+                    <h3>{title}</h3>
+                    <small>{"Using: <code><b>"+trigger_word+"</code></b> as the trigger word" if trigger_word else "No trigger word found. If there's a trigger word, include it in your prompt"}<br></small>
+                </div>
+              </div>
+              {model_card_examples}
+            </div>
+            '''
+            existing_item_index = next((index for (index, item) in enumerate(loras) if item['repo'] == repo), None)
+            if existing_item_index is None:
+                new_item = {
+                    "image": image,
+                    "title": title,
+                    "repo": repo,
+                    "weights": path,
+                    "trigger_word": trigger_word
+                }
+                print(new_item)
+                loras.append(new_item)
+                existing_item_index = len(loras) - 1  # Get the actual index after adding
+                
+            return gr.update(visible=True, value=card), gr.update(visible=True), gr.Gallery(selected_index=None), f"Custom: {path}", existing_item_index, trigger_word
+        except Exception as e:
+            full_traceback = traceback.format_exc()
+            print(f"Full traceback:\n{full_traceback}")
+            gr.Warning(f"Invalid LoRA: either you entered an invalid link, or a non-Qwen-Image LoRA, this was the issue: {e}")
+            return gr.update(visible=True, value=f"Invalid LoRA: either you entered an invalid link, a non-Qwen-Image LoRA"), gr.update(visible=True), gr.update(), "", None, ""
+    else:
+        return gr.update(visible=False), gr.update(visible=False), gr.update(), "", None, ""
+
+def remove_custom_lora():
+    return gr.update(visible=False), gr.update(visible=False), gr.update(), "", None, ""
+
+run_lora.zerogpu = True
+
+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}
+#speed_status{padding: .5em; border-radius: 5px; margin: 1em 0}
+'''
+
+with gr.Blocks(theme=gr.themes.Soft(), css=css, delete_cache=(60, 60)) as app:
+    title = gr.HTML(
+        """<img src=\"https://qianwen-res.oss-cn-beijing.aliyuncs.com/Qwen-Image/qwen_image_logo.png\" alt=\"Qwen-Image\" style=\"width: 280px; margin: 0 auto\">        
+        <h3 style=\"margin-top: -10px\">LoRA🦜 ChoquinLabs Explorer</h3>""",
+        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("")
+            examples_component = gr.Examples(examples=[], inputs=[prompt], label="Sample Prompts", visible=False)
+            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="username/qwen-image-custom-lora")
+                gr.Markdown("[Check Qwen-Image LoRAs](https://huggingface.co/models?other=base_model:adapter:Qwen/Qwen-Image)", elem_id="lora_list")
+            custom_lora_info = gr.HTML(visible=False)
+            custom_lora_button = gr.Button("Remove custom LoRA", visible=False)
+        
+        with gr.Column():
+            result = gr.Image(label="Generated Image")
+            
+            with gr.Row():
+                speed_mode = gr.Radio(
+                    label="Generation Mode",
+                    choices=["Speed (4 steps)", "Speed (8 steps)", "Quality (45 steps)"],
+                    value="Speed (4 steps)",
+                    info="Speed mode uses Lightning LoRA for faster generation"
+                )
+            
+            speed_status = gr.Markdown("Quality mode active", elem_id="speed_status")
+
+    with gr.Row():
+        with gr.Accordion("Advanced Settings", open=False):
+            with gr.Column():
+                with gr.Row():
+                    aspect_ratio = gr.Radio(
+                        label="Aspect Ratio",
+                        choices=["1:1", "16:9", "9:16", "4:3", "3:4", "3:2", "2:3", "3:1", "2:1"],
+                        value="16:9"
+                    )
+                    
+                with gr.Row():
+                    cfg_scale = gr.Slider(
+                        label="Guidance Scale (True CFG)", 
+                        minimum=1.0, 
+                        maximum=5.0, 
+                        step=0.1, 
+                        value=3.5,
+                        info="Lower for speed mode, higher for quality"
+                    )
+                    steps = gr.Slider(
+                        label="Steps", 
+                        minimum=4, 
+                        maximum=50, 
+                        step=1, 
+                        value=45,
+                        info="Automatically set by speed mode"
+                    )
+                
+                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=1.0)
+
+    # Event handlers
+    gallery.select(
+        update_selection,
+        inputs=[aspect_ratio],
+        outputs=[prompt, selected_info, selected_index, aspect_ratio]
+    )
+    
+    speed_mode.change(
+        handle_speed_mode,
+        inputs=[speed_mode],
+        outputs=[speed_status, steps, cfg_scale]
+    )
+    
+    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]
+    )
+    
+    gr.on(
+        triggers=[generate_button.click, prompt.submit],
+        fn=run_lora,
+        inputs=[prompt, cfg_scale, steps, selected_index, randomize_seed, seed, aspect_ratio, lora_scale, speed_mode],
+        outputs=[result, seed]
+    )
+ 
+    app.load(
+        fn=handle_speed_mode,
+        inputs=[gr.State("Speed (4 steps)")],
+        outputs=[speed_status, steps, cfg_scale]
+    )
+
+app.queue()
+app.launch()