Create app.py

app.py

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+import gradio as gr
+import replicate
+import os
+from PIL import Image
+import requests
+from io import BytesIO
+import time
+
+# Set up Replicate API key from environment variable
+os.environ['REPLICATE_API_TOKEN'] = os.getenv('REPLICATE_API_TOKEN')
+
+def process_images(prompt, image1, image2=None):
+    """
+    Process uploaded images with Replicate API
+    """
+    if not image1:
+        return None, "Please upload at least one image"
+    
+    # Check if API token is set
+    if not os.getenv('REPLICATE_API_TOKEN'):
+        return None, "⚠️ Please set REPLICATE_API_TOKEN environment variable"
+    
+    try:
+        # Prepare input images list
+        image_inputs = []
+        
+        # Convert PIL images to temporary files or use file paths
+        # Note: In production, you'd upload these to a cloud service
+        # For this example, we'll assume the images are accessible via URLs
+        # You may need to upload them to a service like Cloudinary or S3 first
+        
+        # This is a placeholder - in real implementation, you'd need to:
+        # 1. Save images temporarily
+        # 2. Upload to a cloud service
+        # 3. Get the URLs
+        
+        status_message = "🎨 Processing your images..."
+        
+        # Prepare input for Replicate
+        input_data = {
+            "prompt": prompt,
+            "image_input": image_inputs  # This should contain actual URLs
+        }
+        
+        # Run the model
+        output = replicate.run(
+            "google/nano-banana",  # Replace with actual model
+            input=input_data
+        )
+        
+        # Get the output URL
+        if hasattr(output, 'url'):
+            output_url = output.url()
+        else:
+            output_url = str(output)
+        
+        # Download and return the generated image
+        response = requests.get(output_url)
+        img = Image.open(BytesIO(response.content))
+        
+        return img, "✅ Image generated successfully!"
+        
+    except Exception as e:
+        return None, f"❌ Error: {str(e)}"
+
+# Create Gradio interface with gradient theme
+css = """
+.gradio-container {
+    background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
+    font-family: 'Inter', sans-serif;
+}
+.gr-button {
+    background: linear-gradient(135deg, #f093fb 0%, #f5576c 100%);
+    border: none;
+    color: white;
+    font-weight: bold;
+    transition: transform 0.2s;
+}
+.gr-button:hover {
+    transform: scale(1.05);
+    box-shadow: 0 10px 20px rgba(0,0,0,0.2);
+}
+.gr-input {
+    border-radius: 10px;
+    border: 2px solid rgba(255,255,255,0.3);
+    background: rgba(255,255,255,0.9);
+}
+.header-text {
+    background: linear-gradient(135deg, #f093fb 0%, #f5576c 100%);
+    -webkit-background-clip: text;
+    -webkit-text-fill-color: transparent;
+    background-clip: text;
+    font-size: 2.5em;
+    font-weight: bold;
+    text-align: center;
+    margin-bottom: 20px;
+}
+.description-text {
+    color: white;
+    text-align: center;
+    font-size: 1.1em;
+    margin-bottom: 30px;
+    text-shadow: 2px 2px 4px rgba(0,0,0,0.2);
+}
+"""
+
+# Build the Gradio interface
+with gr.Blocks(css=css, theme=gr.themes.Soft()) as demo:
+    gr.HTML("""
+        <div class="header-text">🎨 AI Image Style Transfer Studio</div>
+        <div class="description-text">
+            Upload 1-2 images and describe how you want them styled.
+            The AI will create a beautiful transformation!
+        </div>
+    """)
+    
+    with gr.Row():
+        with gr.Column(scale=1):
+            gr.Markdown("### 📤 Input Section")
+            
+            prompt = gr.Textbox(
+                label="✏️ Style Prompt",
+                placeholder="Describe how you want to style your images...",
+                lines=3,
+                value="Make the sheets in the style of the logo. Make the scene natural."
+            )
+            
+            with gr.Row():
+                image1 = gr.Image(
+                    label="Image 1 (Required)",
+                    type="pil",
+                    height=200
+                )
+                image2 = gr.Image(
+                    label="Image 2 (Optional)",
+                    type="pil",
+                    height=200
+                )
+            
+            generate_btn = gr.Button(
+                "🚀 Generate Styled Image",
+                variant="primary",
+                size="lg"
+            )
+            
+            gr.Markdown("""
+            #### 💡 Tips:
+            - Upload high-quality images for best results
+            - Be specific in your style description
+            - Experiment with different prompts!
+            """)
+        
+        with gr.Column(scale=1):
+            gr.Markdown("### 🎯 Output Section")
+            
+            output_image = gr.Image(
+                label="Generated Image",
+                type="pil",
+                height=400
+            )
+            
+            status = gr.Textbox(
+                label="Status",
+                interactive=False,
+                lines=2
+            )
+    
+    # Examples section
+    with gr.Row():
+        gr.Examples(
+            examples=[
+                ["Transform into watercolor painting style", None, None],
+                ["Make it look like a vintage photograph", None, None],
+                ["Apply cyberpunk neon style", None, None],
+                ["Convert to minimalist line art", None, None],
+            ],
+            inputs=[prompt, image1, image2],
+            label="Example Prompts"
+        )
+    
+    # Event handlers
+    generate_btn.click(
+        fn=process_images,
+        inputs=[prompt, image1, image2],
+        outputsocaloutput_image, status],
+        api_name="generate"
+    )
+    
+    # Additional information
+    gr.Markdown("""
+    ---
+    ### ⚙️ Setup Instructions:
+    
+    1. **Set Environment Variable:**
+       ```bash
+       export REPLICATE_API_TOKEN="your_api_token_here"
+       ```
+    
+    2. **Install Required Packages:**
+       ```bash
+       pip install gradio replicate pillow requests
+       ```
+    
+    3. **Note:** For production use, you'll need to:
+       - Implement proper image upload to cloud storage (S3, Cloudinary, etc.)
+       - Replace the model name with the actual Replicate model you want to use
+       - Add proper error handling and rate limiting
+    
+    ### 🔒 Security:
+    - API keys are managed through environment variables
+    - Never commit API keys to version control
+    - Consider implementing user authentication for production
+    """)
+
+# Launch the app
+if __name__ == "__main__":
+    demo.launch(
+        share=True,
+        server_name="0.0.0.0",
+        server_port=7860,
+        show_error=True
+    )