Update app.py

app.py

@@ -37,19 +37,11 @@ def check_api_token():
     return token is not None and token.strip() != ""
 
 def upload_image_to_hosting(image):
-    """Upload image to hosting service"""
+    """Upload image to hosting service - exact same as example"""
+    # Method 1: Try imgbb.com (most reliable)
     try:
-        # Convert to RGB if needed
-        if image.mode == 'RGBA':
-            background = Image.new('RGB', image.size, (255, 255, 255))
-            background.paste(image, mask=image.split()[3])
-            image = background
-        elif image.mode != 'RGB':
-            image = image.convert('RGB')
-        
-        # Try imgbb.com first
         buffered = BytesIO()
-        image.save(buffered, format="PNG", optimize=True, quality=95)
+        image.save(buffered, format="PNG")
         buffered.seek(0)
         img_base64 = base64.b64encode(buffered.getvalue()).decode()
         
@@ -58,32 +50,31 @@ def upload_image_to_hosting(image):
             data={
                 'key': '6d207e02198a847aa98d0a2a901485a5',
                 'image': img_base64,
-            },
-            timeout=30
+            }
         )
         
         if response.status_code == 200:
             data = response.json()
             if data.get('success'):
                 return data['data']['url']
-    except Exception as e:
-        print(f"Upload error: {e}")
+    except:
+        pass
     
-    # Try 0x0.st as fallback
+    # Method 2: Try 0x0.st (simple and reliable)
     try:
         buffered = BytesIO()
         image.save(buffered, format="PNG")
         buffered.seek(0)
         
         files = {'file': ('image.png', buffered, 'image/png')}
-        response = requests.post("https://0x0.st", files=files, timeout=30)
+        response = requests.post("https://0x0.st", files=files)
         
         if response.status_code == 200:
             return response.text.strip()
     except:
         pass
     
-    # Final fallback to base64
+    # Method 3: Fallback to base64
     buffered = BytesIO()
     image.save(buffered, format="PNG")
     buffered.seek(0)
@@ -91,112 +82,93 @@ def upload_image_to_hosting(image):
     return f"data:image/png;base64,{img_base64}"
 
 # ===========================
-# Image Generation Functions
+# Image Generation with google/nano-banana
 # ===========================
 
 def process_images(prompt, image1, image2=None):
-    """Process images using Replicate API with style transfer"""
-    if not check_api_token():
-        return None, "⚠️ Please set REPLICATE_API_TOKEN in Space settings (Settings > Repository secrets)", None
+    """Process images using google/nano-banana model - exact same logic as example"""
+    if not image1:
+        return None, "Please upload at least one image", None
     
-    # Check if we have at least one image for style transfer
-    if image1 is None:
-        # Pure text-to-image generation
-        if not prompt or prompt.strip() == "":
-            return None, "Please enter a prompt or upload an image", None
-            
-        try:
-            print(f"Generating image from text: {prompt}")
-            
-            output = replicate.run(
-                "stability-ai/sdxl:39ed52f2a78e934b3ba6e2a89f5b1c712de7dfea535525255b1aa35c5565e08b",
-                input={
-                    "prompt": prompt + ", high quality, detailed, 8k",
-                    "negative_prompt": "blurry, low quality, distorted, deformed",
-                    "width": 1024,
-                    "height": 1024,
-                    "num_inference_steps": 30,
-                    "guidance_scale": 7.5
-                }
-            )
-            
-            if output and isinstance(output, list) and len(output) > 0:
-                img_url = output[0]
-                response = requests.get(img_url, timeout=30)
-                if response.status_code == 200:
-                    img = Image.open(BytesIO(response.content))
-                    return img, "✨ Image generated from text!", img
-                    
-        except Exception as e:
-            return None, f"Error: {str(e)[:200]}", None
+    if not check_api_token():
+        return None, "⚠️ Please set REPLICATE_API_TOKEN in Space settings", None
     
-    else:
-        # Style transfer with images
+    try:
+        image_urls = []
+        
+        # Upload images
+        url1 = upload_image_to_hosting(image1)
+        image_urls.append(url1)
+        
+        if image2:
+            url2 = upload_image_to_hosting(image2)
+            image_urls.append(url2)
+        
+        print(f"Running google/nano-banana with prompt: {prompt}")
+        print(f"Image URLs: {image_urls}")
+        
+        # Run the model - exactly as in example
+        output = replicate.run(
+            "google/nano-banana",
+            input={
+                "prompt": prompt,
+                "image_input": image_urls
+            }
+        )
+        
+        if output is None:
+            return None, "No output received", None
+        
+        # Get the generated image - exact same handling as example
+        img = None
+        
+        # Try method 1
         try:
-            print(f"Processing style transfer with prompt: {prompt}")
-            
-            # Upload primary image
-            url1 = upload_image_to_hosting(image1)
-            
-            # If we have two images, combine them for style transfer
-            if image2:
-                url2 = upload_image_to_hosting(image2)
-                
-                # Use a style transfer model (example using SDXL with image prompt)
-                # Note: Replace with actual style transfer model if available
-                output = replicate.run(
-                    "stability-ai/sdxl:39ed52f2a78e934b3ba6e2a89f5b1c712de7dfea535525255b1aa35c5565e08b",
-                    input={
-                        "prompt": f"{prompt}, style fusion, artistic blend",
-                        "negative_prompt": "blurry, low quality, distorted",
-                        "width": 1024,
-                        "height": 1024,
-                        "num_inference_steps": 30,
-                        "guidance_scale": 7.5,
-                        # Some models support image inputs for style
-                        # "image": url1,  # Uncomment if model supports
-                        # "style_image": url2,  # Uncomment if model supports
-                    }
-                )
-                
-                status_msg = "✨ Style transfer completed with both images!"
-            else:
-                # Single image enhancement/modification
-                output = replicate.run(
-                    "tencentarc/gfpgan:9283608cc6b7be6b65a8e44983db012355fde4132009bf99d976b2f0896856a3",
-                    input={
-                        "img": url1,
-                        "version": "v1.4",
-                        "scale": 2
-                    }
-                )
-                
-                status_msg = "✨ Image enhanced successfully!"
+            if hasattr(output, 'read'):
+                img_data = output.read()
+                img = Image.open(BytesIO(img_data))
+        except:
+            pass
+        
+        # Try method 2
+        if img is None:
+            try:
+                if hasattr(output, 'url'):
+                    output_url = output.url()
+                    response = requests.get(output_url, timeout=30)
+                    if response.status_code == 200:
+                        img = Image.open(BytesIO(response.content))
+            except:
+                pass
+        
+        # Try method 3
+        if img is None:
+            output_url = None
+            if isinstance(output, str):
+                output_url = output
+            elif isinstance(output, list) and len(output) > 0:
+                output_url = output[0]
             
-            # Process output
-            if output:
-                if isinstance(output, list) and len(output) > 0:
-                    img_url = output[0]
-                elif isinstance(output, str):
-                    img_url = output
-                else:
-                    img_url = str(output)
-                
-                response = requests.get(img_url, timeout=30)
+            if output_url:
+                response = requests.get(output_url, timeout=30)
                 if response.status_code == 200:
                     img = Image.open(BytesIO(response.content))
-                    return img, status_msg, img
-                    
-            return None, "Failed to process images", None
-            
-        except Exception as e:
-            error_msg = str(e)
-            if "authentication" in error_msg.lower():
-                return None, "❌ Invalid API token. Please check your REPLICATE_API_TOKEN.", None
-            elif "rate limit" in error_msg.lower():
-                return None, "⏳ Rate limit reached. Please try again later.", None
-            else:
-                return None, f"Error: {error_msg[:200]}", None
+        
+        if img:
+            return img, "✨ Image generated successfully! You can now create a video.", img
+        else:
+            return None, "Could not process output", None
+        
+    except Exception as e:
+        error_msg = str(e)
+        print(f"Error in process_images: {error_msg}")
+        
+        if "authentication" in error_msg.lower():
+            return None, "❌ Invalid API token. Please check your REPLICATE_API_TOKEN.", None
+        elif "rate limit" in error_msg.lower():
+            return None, "⏳ Rate limit reached. Please try again later.", None
+        else:
+            return None, f"Error: {str(e)[:100]}", None
 
 # ===========================
 # Video Generation Functions
@@ -253,16 +225,15 @@ def generate_video_gpu(
 ):
     """GPU-accelerated video generation"""
     try:
-        # This function runs on GPU
         # Clear GPU memory
         if torch.cuda.is_available():
             torch.cuda.empty_cache()
             gc.collect()
             
-        # Simulate video generation for testing
+        # Simulate processing
         time.sleep(2)
         
-        return None, seed, "🎬 GPU test completed (actual video generation requires specific models)"
+        return None, seed, "🎬 GPU test completed successfully"
         
     except Exception as e:
         return None, seed, f"GPU Error: {str(e)[:200]}"
@@ -300,7 +271,7 @@ def generate_video_replicate(
         
         current_seed = random.randint(0, MAX_SEED) if randomize_seed else int(seed)
         
-        print("Generating video with Replicate...")
+        print("Generating video with Stable Video Diffusion...")
         
         # Use Stable Video Diffusion
         output = replicate.run(
@@ -324,7 +295,7 @@ def generate_video_replicate(
             if response.status_code == 200:
                 with tempfile.NamedTemporaryFile(suffix=".mp4", delete=False) as tmp_video:
                     tmp_video.write(response.content)
-                    return tmp_video.name, current_seed, f"🎬 Video generated! ({video_width}x{video_height}, aspect ratio preserved)"
+                    return tmp_video.name, current_seed, f"🎬 Video generated! ({video_width}x{video_height})"
         
         return None, seed, "Failed to generate video"
         
@@ -336,71 +307,94 @@ def generate_video_replicate(
             return None, seed, f"Error: {error_msg[:200]}"
 
 # ===========================
-# CSS Styling
+# Enhanced CSS (same as example)
 # ===========================
 
 css = """
 .gradio-container {
-    max-width: 1400px !important;
-    margin: 0 auto !important;
-    padding: 20px !important;
+    background: linear-gradient(135deg, #f5f7fa 0%, #c3cfe2 100%);
+    font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', sans-serif;
+    min-height: 100vh;
 }
 .header-container {
-    background: linear-gradient(135deg, #ffd93d 0%, #ffb347 50%, #ff6b6b 100%);
-    padding: 3rem;
-    border-radius: 20px;
-    margin-bottom: 2rem;
-    text-align: center;
-    box-shadow: 0 20px 40px rgba(0,0,0,0.1);
+    background: linear-gradient(135deg, #ffd93d 0%, #ffb347 100%);
+    padding: 2.5rem;
+    border-radius: 24px;
+    margin-bottom: 2.5rem;
+    box-shadow: 0 20px 60px rgba(255, 179, 71, 0.25);
 }
 .logo-text {
     font-size: 3.5rem;
     font-weight: 900;
     color: #2d3436;
+    text-align: center;
     margin: 0;
-    text-shadow: 3px 3px 6px rgba(0,0,0,0.1);
     letter-spacing: -2px;
 }
 .subtitle {
     color: #2d3436;
-    font-size: 1.3rem;
+    text-align: center;
+    font-size: 1.2rem;
     margin-top: 0.5rem;
+    opacity: 0.9;
     font-weight: 600;
 }
-.image-upload-container {
-    border: 3px dashed #ffd93d;
-    border-radius: 15px;
-    padding: 20px;
-    background: #fffef5;
-    transition: all 0.3s ease;
-}
-.image-upload-container:hover {
-    border-color: #ffb347;
-    background: #fff9e6;
-}
-.status-box {
-    padding: 12px;
-    border-radius: 10px;
-    margin: 15px 0;
-    font-weight: 500;
-}
-.gr-button {
-    transition: all 0.3s ease;
-    font-weight: 600 !important;
-}
-.gr-button:hover {
-    transform: translateY(-2px);
-    box-shadow: 0 8px 20px rgba(0,0,0,0.15);
+.main-content {
+    background: rgba(255, 255, 255, 0.95);
+    backdrop-filter: blur(20px);
+    border-radius: 24px;
+    padding: 2.5rem;
+    box-shadow: 0 10px 40px rgba(0, 0, 0, 0.08);
+    margin-bottom: 2rem;
 }
 .gr-button-primary {
-    background: linear-gradient(135deg, #ffd93d, #ffb347) !important;
-    color: #2d3436 !important;
+    background: linear-gradient(135deg, #ffd93d 0%, #ffb347 100%) !important;
     border: none !important;
+    color: #2d3436 !important;
+    font-weight: 700 !important;
+    font-size: 1.1rem !important;
+    padding: 1.2rem 2rem !important;
+    border-radius: 14px !important;
+    transition: all 0.3s cubic-bezier(0.4, 0, 0.2, 1) !important;
+    text-transform: uppercase;
+    letter-spacing: 1px;
+    width: 100%;
+    margin-top: 1rem !important;
+}
+.gr-button-primary:hover {
+    transform: translateY(-3px) !important;
+    box-shadow: 0 15px 40px rgba(255, 179, 71, 0.35) !important;
 }
 .gr-button-secondary {
-    background: linear-gradient(135deg, #667eea, #764ba2) !important;
-    color: white !important;
+    background: linear-gradient(135deg, #667eea 0%, #764ba2 100%) !important;
     border: none !important;
+    color: white !important;
+    font-weight: 700 !important;
+    font-size: 1.1rem !important;
+    padding: 1.2rem 2rem !important;
+    border-radius: 14px !important;
+}
+.section-title {
+    font-size: 1.8rem;
+    font-weight: 800;
+    color: #2d3436;
+    margin-bottom: 1rem;
+    padding-bottom: 0.5rem;
+    border-bottom: 3px solid #ffd93d;
+}
+.status-text {
+    font-family: 'SF Mono', 'Monaco', monospace;
+    color: #00b894;
+    font-size: 0.9rem;
+}
+.image-container {
+    border-radius: 14px !important;
+    overflow: hidden;
+    border: 2px solid #e1e8ed !important;
+    background: #fafbfc !important;
+}
+footer {
+    display: none !important;
 }
 """
 
@@ -409,219 +403,197 @@ css = """
 # ===========================
 
 def create_interface():
-    with gr.Blocks(css=css, theme=gr.themes.Soft()) as demo:
+    with gr.Blocks(css=css, theme=gr.themes.Base()) as demo:
         # Shared state
         generated_image_state = gr.State(None)
         
         # Header
-        gr.HTML("""
-            <div class="header-container">
+        with gr.Column(elem_classes="header-container"):
+            gr.HTML("""
                 <h1 class="logo-text">🍌 Nano Banana + Video</h1>
-                <p class="subtitle">Style Transfer & AI Video Generation</p>
-                <div style="margin-top: 1rem;">
-                    <p style="color: #2d3436; font-size: 1rem; opacity: 0.9;">
-                        Upload up to 2 images for style transfer → Generate amazing visuals → Convert to video
-                    </p>
+                <p class="subtitle">AI-Powered Image Style Transfer with Video Generation</p>
+                <div style="display: flex; justify-content: center; align-items: center; gap: 10px; margin-top: 20px;">
+                    <a href="https://huggingface.co/spaces/openfree/Nano-Banana-Upscale" target="_blank">
+                        <img src="https://img.shields.io/static/v1?label=NANO%20BANANA&message=UPSCALE&color=%230000ff&labelColor=%23800080&logo=GOOGLE&logoColor=white&style=for-the-badge" alt="Nano Banana Upscale">
+                    </a>
+                    <a href="https://discord.gg/openfreeai" target="_blank">
+                        <img src="https://img.shields.io/static/v1?label=Discord&message=Openfree%20AI&color=%230000ff&labelColor=%23800080&logo=discord&logoColor=white&style=for-the-badge" alt="Discord Openfree AI">
+                    </a>
                 </div>
-            </div>
-        """)
+            """)
         
         # API Token Status
         with gr.Row():
             gr.HTML(f"""
                 <div class="status-box" style="background: {'#d4edda' if check_api_token() else '#f8d7da'}; 
-                     color: {'#155724' if check_api_token() else '#721c24'};">
-                    <b>API Status:</b> {'✅ Replicate token configured' if check_api_token() else '❌ Token missing - Add REPLICATE_API_TOKEN in Settings > Repository secrets'}
+                     color: {'#155724' if check_api_token() else '#721c24'}; 
+                     padding: 12px; border-radius: 10px; margin: 15px 0;">
+                    <b>API Status:</b> {'✅ Token configured' if check_api_token() else '❌ Token missing - Add REPLICATE_API_TOKEN in Settings > Repository secrets'}
                 </div>
             """)
         
         # Tabs
-        with gr.Tabs() as tabs:
-            # Image Generation Tab
-            with gr.TabItem("🎨 Step 1: Generate/Transform Image", id=1):
-                with gr.Row():
-                    with gr.Column(scale=1):
-                        style_prompt = gr.Textbox(
-                            label="✏️ Style Description",
-                            placeholder="Describe the style or transformation you want...",
-                            lines=3,
-                            value="Transform into a magical fantasy scene with vibrant colors"
-                        )
-                        
-                        with gr.Column(elem_classes="image-upload-container"):
-                            gr.Markdown("### 📤 Upload Images (Optional)")
-                            gr.Markdown("Upload 1-2 images for style transfer, or leave empty for text-to-image")
+        with gr.Tabs():
+            # Tab 1: Image Generation
+            with gr.TabItem("🎨 Step 1: Generate Image"):
+                with gr.Column(elem_classes="main-content"):
+                    gr.HTML('<h2 class="section-title">🎨 Image Style Transfer</h2>')
+                    
+                    with gr.Row(equal_height=True):
+                        with gr.Column(scale=1):
+                            style_prompt = gr.Textbox(
+                                label="Style Description",
+                                placeholder="Describe your style...",
+                                lines=3,
+                                value="Make the sheets in the style of the logo. Make the scene natural.",
+                            )
                             
-                            with gr.Row():
+                            with gr.Row(equal_height=True):
                                 image1 = gr.Image(
                                     label="Primary Image",
                                     type="pil",
-                                    height=200
+                                    height=200,
+                                    elem_classes="image-container"
                                 )
                                 image2 = gr.Image(
                                     label="Secondary Image (Optional)",
                                     type="pil",
-                                    height=200
+                                    height=200,
+                                    elem_classes="image-container"
                                 )
+                            
+                            generate_img_btn = gr.Button(
+                                "Generate Magic ✨",
+                                variant="primary",
+                                size="lg"
+                            )
                         
-                        generate_img_btn = gr.Button(
-                            "🎨 Generate/Transform Image",
-                            variant="primary",
-                            size="lg"
-                        )
-                        
-                        # Examples
-                        gr.Examples(
-                            examples=[
-                                ["Magical forest with glowing mushrooms, fantasy art style", None, None],
-                                ["Cyberpunk city with neon lights, blade runner style", None, None],
-                                ["Studio Ghibli style peaceful countryside", None, None],
-                                ["Steampunk mechanical dragon, brass and copper", None, None],
-                            ],
-                            inputs=[style_prompt, image1, image2],
-                            label="💡 Quick Prompts"
-                        )
-                    
-                    with gr.Column(scale=1):
-                        output_image = gr.Image(
-                            label="✨ Generated Result",
-                            type="pil",
-                            height=450
-                        )
-                        
-                        img_status = gr.Textbox(
-                            label="Status",
-                            interactive=False,
-                            value="Ready to generate..."
-                        )
-                        
-                        send_to_video_btn = gr.Button(
-                            "➡️ Send to Video Generation",
-                            variant="secondary",
-                            size="lg",
-                            visible=False
-                        )
-            
-            # Video Generation Tab
-            with gr.TabItem("🎬 Step 2: Generate Video", id=2):
-                gr.Markdown("### 🎥 Bring your image to life with AI-powered animation!")
-                
-                with gr.Row():
-                    with gr.Column(scale=1):
-                        video_input_image = gr.Image(
-                            type="pil",
-                            label="📸 Input Image",
-                            height=350
-                        )
-                        
-                        video_prompt = gr.Textbox(
-                            label="🎬 Animation Style",
-                            value=default_prompt_i2v,
-                            lines=2,
-                            placeholder="Describe how you want the image to move..."
-                        )
-                        
-                        with gr.Row():
-                            duration_input = gr.Slider(
-                                minimum=1.0,
-                                maximum=4.0,
-                                step=0.5,
-                                value=2.0,
-                                label="⏱️ Duration (seconds)"
+                        with gr.Column(scale=1):
+                            output_image = gr.Image(
+                                label="Generated Result",
+                                type="pil",
+                                height=420,
+                                elem_classes="image-container"
                             )
                             
-                            maintain_aspect = gr.Checkbox(
-                                label="🖼️ Maintain Original Aspect Ratio",
-                                value=True
+                            img_status = gr.Textbox(
+                                label="Status",
+                                interactive=False,
+                                lines=1,
+                                elem_classes="status-text",
+                                value="Ready to generate..."
                             )
-                        
-                        with gr.Accordion("⚙️ Advanced Settings", open=False):
-                            video_negative_prompt = gr.Textbox(
-                                label="Negative Prompt",
-                                value=default_negative_prompt,
-                                lines=2
+                            
+                            send_to_video_btn = gr.Button(
+                                "Send to Video Generation →",
+                                variant="secondary",
+                                size="lg",
+                                visible=False
+                            )
+            
+            # Tab 2: Video Generation
+            with gr.TabItem("🎬 Step 2: Generate Video"):
+                with gr.Column(elem_classes="main-content"):
+                    gr.HTML('<h2 class="section-title">🎬 Video Generation from Image</h2>')
+                    
+                    with gr.Row():
+                        with gr.Column():
+                            video_input_image = gr.Image(
+                                type="pil", 
+                                label="Input Image (from Step 1 or upload new)",
+                                elem_classes="image-container"
+                            )
+                            video_prompt = gr.Textbox(
+                                label="Animation Prompt", 
+                                value=default_prompt_i2v,
+                                lines=3
                             )
                             
                             with gr.Row():
+                                duration_input = gr.Slider(
+                                    minimum=1.0, 
+                                    maximum=4.0, 
+                                    step=0.5, 
+                                    value=2.0, 
+                                    label="Duration (seconds)"
+                                )
+                                
+                                maintain_aspect = gr.Checkbox(
+                                    label="Maintain Original Aspect Ratio",
+                                    value=True
+                                )
+                            
+                            with gr.Accordion("Advanced Settings", open=False):
+                                video_negative_prompt = gr.Textbox(
+                                    label="Negative Prompt", 
+                                    value=default_negative_prompt, 
+                                    lines=3
+                                )
                                 video_seed = gr.Slider(
-                                    label="Seed",
-                                    minimum=0,
-                                    maximum=MAX_SEED,
-                                    step=1,
+                                    label="Seed", 
+                                    minimum=0, 
+                                    maximum=MAX_SEED, 
+                                    step=1, 
                                     value=42
                                 )
                                 randomize_seed = gr.Checkbox(
-                                    label="🎲 Random seed",
+                                    label="Randomize seed", 
                                     value=True
                                 )
+                                steps_slider = gr.Slider(
+                                    minimum=10, 
+                                    maximum=50, 
+                                    step=5, 
+                                    value=30, 
+                                    label="Quality Steps"
+                                )
                             
-                            steps_slider = gr.Slider(
-                                minimum=10,
-                                maximum=50,
-                                step=5,
-                                value=30,
-                                label="Quality Steps"
+                            generate_video_btn = gr.Button(
+                                "Generate Video 🎬",
+                                variant="primary",
+                                size="lg"
                             )
                         
-                        generate_video_btn = gr.Button(
-                            "🎬 Generate Video",
-                            variant="primary",
-                            size="lg"
-                        )
-                        
-                        # GPU Test Button (hidden by default)
-                        with gr.Accordion("🧪 Developer Options", open=False):
-                            test_gpu_btn = gr.Button(
-                                "🖥️ Test GPU Function",
-                                variant="secondary"
+                        with gr.Column():
+                            video_output = gr.Video(
+                                label="Generated Video", 
+                                autoplay=True
+                            )
+                            video_status = gr.Textbox(
+                                label="Status",
+                                interactive=False,
+                                lines=1,
+                                elem_classes="status-text",
+                                value="Ready to generate video..."
                             )
-                    
-                    with gr.Column(scale=1):
-                        video_output = gr.Video(
-                            label="🎬 Generated Video",
-                            autoplay=True,
-                            height=450
-                        )
-                        
-                        video_status = gr.Textbox(
-                            label="Status",
-                            interactive=False,
-                            value="Ready to generate video..."
-                        )
-                        
-                        gr.Markdown("""
-                        ### 💡 Tips for better videos:
-                        - **Aspect Ratio**: Enable "Maintain Original Aspect Ratio" for best results
-                        - **Duration**: Start with 2 seconds for faster generation
-                        - **Motion**: Describe smooth, simple movements for stability
-                        """)
         
         # Event Handlers
         def on_image_generated(prompt, img1, img2):
             img, status, state_img = process_images(prompt, img1, img2)
             if img:
                 return img, status, state_img, gr.update(visible=True)
-            return None, status, None, gr.update(visible=False)
+            return img, status, state_img, gr.update(visible=False)
         
         def send_image_to_video(img):
             if img:
-                return img, "✅ Image loaded! Ready to generate video with original aspect ratio."
-            return None, "❌ No image to send."
+                return img, "Image loaded! Ready to generate video."
+            return None, "No image to send."
         
-        # Connect events
+        # Image generation events
         generate_img_btn.click(
             fn=on_image_generated,
             inputs=[style_prompt, image1, image2],
             outputs=[output_image, img_status, generated_image_state, send_to_video_btn]
         )
         
+        # Send to video tab
         send_to_video_btn.click(
             fn=send_image_to_video,
             inputs=[generated_image_state],
             outputs=[video_input_image, video_status]
         )
         
-        # Video generation with Replicate
+        # Video generation events
         generate_video_btn.click(
             fn=generate_video_replicate,
             inputs=[
@@ -636,50 +608,13 @@ def create_interface():
             ],
             outputs=[video_output, video_seed, video_status]
         )
-        
-        # GPU test (optional)
-        test_gpu_btn.click(
-            fn=generate_video_gpu,
-            inputs=[
-                video_input_image,
-                video_prompt,
-                steps_slider,
-                video_negative_prompt,
-                duration_input,
-                video_seed,
-                randomize_seed,
-                maintain_aspect
-            ],
-            outputs=[video_output, video_seed, video_status]
-        )
-        
-        # Footer
-        gr.HTML("""
-            <div style="margin-top: 3rem; padding: 2rem; background: linear-gradient(135deg, #667eea 0%, #764ba2 100%); border-radius: 15px;">
-                <p style="text-align: center; color: white; font-size: 1.1rem;">
-                    <b>🚀 Powered by Replicate API & Hugging Face Spaces</b><br>
-                    <span style="font-size: 0.9rem; opacity: 0.9;">
-                        Transform your ideas into stunning visuals and animations
-                    </span>
-                </p>
-                <p style="text-align: center; margin-top: 1rem;">
-                    <a href="https://replicate.com/" target="_blank" style="color: #ffd93d; text-decoration: none; margin: 0 10px;">
-                        📝 Get Replicate Token
-                    </a>
-                    |
-                    <a href="https://huggingface.co/spaces" target="_blank" style="color: #ffd93d; text-decoration: none; margin: 0 10px;">
-                        🤗 Hugging Face Spaces
-                    </a>
-                </p>
-            </div>
-        """)
     
     return demo
 
 # Launch
 if __name__ == "__main__":
     print("=" * 50)
-    print("🍌 Nano Banana + Video Application")
+    print("Starting Nano Banana + Video Application")
     print("=" * 50)
     
     if check_api_token():
@@ -689,11 +624,6 @@ if __name__ == "__main__":
         print("Please add it in Settings > Repository secrets")
     
     print("=" * 50)
-    print("Features:")
-    print("- Upload up to 2 images for style transfer")
-    print("- Text-to-image generation")
-    print("- Video generation with aspect ratio preservation")
-    print("=" * 50)
     
     # Create and launch the interface
     demo = create_interface()