Add training pair upload and preview functionality to Custom Training tab

app.py

@@ -180,8 +180,78 @@ with gr.Blocks(title="🏛️ Architecture AI Enhancer") as demo:
             
             ## ⚠️ Important Note
             
-            **Training is not available on this HF Space** due to computational requirements. However, you can train locally and deploy your custom model!
+            **Training execution is not available on this HF Space** due to computational requirements. However, you can:
+            1. Upload and preview your training pairs below
+            2. Download the guide to train locally
+            3. Deploy your custom model
+            """)
+            
+            gr.Markdown("---")
+            
+            # Training pair upload section
+            gr.Markdown("""
+            ## 📸 Preview Training Pairs
+            
+            Upload example pairs to visualize what you'll train with:
+            """)
+            
+            with gr.Row():
+                with gr.Column():
+                    gr.Markdown("### Input Image (Before)")
+                    training_input = gr.Image(label="Input Render", type="pil")
+                
+                with gr.Column():
+                    gr.Markdown("### Target Image (After)")
+                    training_target = gr.Image(label="Target Enhanced", type="pil")
+            
+            with gr.Row():
+                preview_btn = gr.Button("👁️ Preview Training Pair", variant="secondary")
+                clear_btn = gr.Button("🗑️ Clear", variant="secondary")
+            
+            training_preview = gr.Gallery(
+                label="Training Pair Preview",
+                columns=2,
+                rows=1,
+                height="auto"
+            )
+            
+            def preview_training_pair(input_img, target_img):
+                """Preview training pair side by side"""
+                if input_img is None or target_img is None:
+                    return []
+                return [input_img, target_img]
             
+            def clear_training():
+                """Clear training inputs"""
+                return None, None, []
+            
+            preview_btn.click(
+                fn=preview_training_pair,
+                inputs=[training_input, training_target],
+                outputs=training_preview
+            )
+            
+            clear_btn.click(
+                fn=clear_training,
+                inputs=[],
+                outputs=[training_input, training_target, training_preview]
+            )
+            
+            gr.Markdown("""
+            ---
+            
+            ## 💡 Tips for Good Training Pairs
+            
+            - **Consistency**: Use similar compositions between input and target
+            - **Quality**: High-resolution images (512x512 minimum)
+            - **Variety**: Include different views and lighting conditions
+            - **Alignment**: Input and target should show the same scene
+            - **Target Quality**: Ensure targets represent your desired style accurately
+            
+            ---
+            """)
+            
+            gr.Markdown("""
             ## 🚀 What is LoRA Training?
             
             LoRA (Low-Rank Adaptation) allows you to fine-tune the AI with just 10-50 image pairs to learn: