Update app.py

app.py

@@ -220,217 +220,223 @@ def get_sequence_stats(sequence):
     
     return stats
 
-# Initialize model on startup
-print("Initializing model...")
-model_status = initialize_model()
+def create_interface():
+    """Create the Gradio interface"""
+    # Initialize model on startup
+    print("Initializing model...")
+    model_status = initialize_model()
 
-# Create custom CSS for better styling
-custom_css = """
-.gene-app {
-    font-family: 'Segoe UI', Tahoma, Geneva, Verdana, sans-serif;
-}
+    # Create custom CSS for better styling
+    custom_css = """
+    .gene-app {
+        font-family: 'Segoe UI', Tahoma, Geneva, Verdana, sans-serif;
+    }
 
-.status-ready {
-    background: linear-gradient(135deg, #d4edda 0%, #c3e6cb 100%);
-    border: 2px solid #28a745;
-    border-radius: 10px;
-    padding: 15px;
-    color: #155724;
-    font-weight: bold;
-    box-shadow: 0 2px 10px rgba(40, 167, 69, 0.2);
-}
+    .status-ready {
+        background: linear-gradient(135deg, #d4edda 0%, #c3e6cb 100%);
+        border: 2px solid #28a745;
+        border-radius: 10px;
+        padding: 15px;
+        color: #155724;
+        font-weight: bold;
+        box-shadow: 0 2px 10px rgba(40, 167, 69, 0.2);
+    }
 
-.status-error {
-    background: linear-gradient(135deg, #f8d7da 0%, #f5c6cb 100%);
-    border: 2px solid #dc3545;
-    border-radius: 10px;
-    padding: 15px;
-    color: #721c24;
-    font-weight: bold;
-    box-shadow: 0 2px 10px rgba(220, 53, 69, 0.2);
-}
+    .status-error {
+        background: linear-gradient(135deg, #f8d7da 0%, #f5c6cb 100%);
+        border: 2px solid #dc3545;
+        border-radius: 10px;
+        padding: 15px;
+        color: #721c24;
+        font-weight: bold;
+        box-shadow: 0 2px 10px rgba(220, 53, 69, 0.2);
+    }
 
-.main-title {
-    text-align: center;
-    background: linear-gradient(135deg, #2E8B57 0%, #20B2AA 100%);
-    -webkit-background-clip: text;
-    -webkit-text-fill-color: transparent;
-    background-clip: text;
-    font-size: 2.5rem;
-    font-weight: bold;
-    margin-bottom: 1rem;
-}
+    .main-title {
+        text-align: center;
+        background: linear-gradient(135deg, #2E8B57 0%, #20B2AA 100%);
+        -webkit-background-clip: text;
+        -webkit-text-fill-color: transparent;
+        background-clip: text;
+        font-size: 2.5rem;
+        font-weight: bold;
+        margin-bottom: 1rem;
+    }
 
-.instructions {
-    background: #f8f9fa;
-    border-radius: 10px;
-    padding: 20px;
-    border-left: 4px solid #2E8B57;
-    margin: 1rem 0;
-}
+    .instructions {
+        background: #f8f9fa;
+        border-radius: 10px;
+        padding: 20px;
+        border-left: 4px solid #2E8B57;
+        margin: 1rem 0;
+    }
 
-.sequence-stats {
-    font-size: 0.9rem;
-    color: #6c757d;
-    font-style: italic;
-    margin-top: 5px;
-}
-"""
+    .sequence-stats {
+        font-size: 0.9rem;
+        color: #6c757d;
+        font-style: italic;
+        margin-top: 5px;
+    }
+    """
 
-# Create the interface
-print("Creating Gradio interface...")
+    print("Creating Gradio interface...")
 
-# Determine status message and styling
-if model_loaded:
-    status_html = '''
-    <div class="status-ready">
-        <strong>✅ Model Status:</strong> Ready for gene prediction!<br>
-        <small>🔬 Boundary-aware deep learning model loaded successfully</small>
-    </div>
-    '''
-else:
-    status_html = f'''
-    <div class="status-error">
-        <strong>❌ Model Status:</strong> Model initialization failed<br>
-        <small>📋 Details: {error_message}</small>
-    </div>
-    '''
+    # Determine status message and styling
+    if model_loaded:
+        status_html = '''
+        <div class="status-ready">
+            <strong>✅ Model Status:</strong> Ready for gene prediction!<br>
+            <small>🔬 Boundary-aware deep learning model loaded successfully</small>
+        </div>
+        '''
+    else:
+        status_html = f'''
+        <div class="status-error">
+            <strong>❌ Model Status:</strong> Model initialization failed<br>
+            <small>📋 Details: {error_message}</small>
+        </div>
+        '''
 
-# Example sequences
-examples = [
-    # Short example with clear gene
-    ["ATGAAACGCATTAGCACCACCATTACCACCACCATCACCATTACCACAGGTAACGGTGCGGGCTGACGCGTACAGGAAACACAGAAAAAAGCCCGCACCTGACAGTGCGGGCTTTTTTTTTCGACCAAAGGTAACGAGGTAACAACCATGCGAGTGTTGAAGTTCGGCGGTACATCAGTGGCAAATGCAGAACGTTTTCTGCGTAA"],
-    # Longer example
-    ["ATGAAACGCATTAGCACCACCATTACCACCACCATCACCATTACCACAGGTAACGGTGCGGGCTGACGCGTACAGGAAACACAGAAAAAAGCCCGCACCTGACAGTGCGGGCTTTTTTTTTCGACCAAAGGTAACGAGGTAACAACCATGCGAGTGTTGAAGTTCGGCGGTACATCAGTGGCAAATGCAGAACGTTTTCTGCGTGTTGCCGATATTCTGGAAAGCAATGCCAGGCAGGGGCAGGTGGCCACCGTCCTCTCTGCCCCCGCCAAAATCACCAACCACCTGGTGGCGATGATTGAAAAAACCATTAGCGGCCAGGATGCTTTACCCAATATCAGCGATGCCGAACGTATTTTTGCCGAACTTTTGACGGGACTCGCCGCCGCCCAGCCGGGGTTCCCGCTGGCGCAATTGAAAACTTTCGTCGATCAGGAATTTGCCCAATAG"],
-]
+    # Example sequences
+    examples = [
+        # Short example with clear gene
+        ["ATGAAACGCATTAGCACCACCATTACCACCACCATCACCATTACCACAGGTAACGGTGCGGGCTGACGCGTACAGGAAACACAGAAAAAAGCCCGCACCTGACAGTGCGGGCTTTTTTTTTCGACCAAAGGTAACGAGGTAACAACCATGCGAGTGTTGAAGTTCGGCGGTACATCAGTGGCAAATGCAGAACGTTTTCTGCGTAA"],
+        # Longer example
+        ["ATGAAACGCATTAGCACCACCATTACCACCACCATCACCATTACCACAGGTAACGGTGCGGGCTGACGCGTACAGGAAACACAGAAAAAAGCCCGCACCTGACAGTGCGGGCTTTTTTTTTCGACCAAAGGTAACGAGGTAACAACCATGCGAGTGTTGAAGTTCGGCGGTACATCAGTGGCAAATGCAGAACGTTTTCTGCGTGTTGCCGATATTCTGGAAAGCAATGCCAGGCAGGGGCAGGTGGCCACCGTCCTCTCTGCCCCCGCCAAAATCACCAACCACCTGGTGGCGATGATTGAAAAAACCATTAGCGGCCAGGATGCTTTACCCAATATCAGCGATGCCGAACGTATTTTTGCCGAACTTTTGACGGGACTCGCCGCCGCCCAGCCGGGGTTCCCGCTGGCGCAATTGAAAACTTTCGTCGATCAGGAATTTGCCCAATAG"],
+    ]
 
-# Create the interface with custom theme
-with gr.Blocks(
-    title="🧬 Gene Prediction Tool", 
-    theme=gr.themes.Soft(primary_hue="emerald", secondary_hue="teal"),
-    css=custom_css,
-    head="<meta name='viewport' content='width=device-width, initial-scale=1.0'>"
-) as demo:
-    
-    gr.HTML('<h1 class="main-title">🧬 Advanced Gene Prediction Tool</h1>')
-    gr.HTML('<p style="text-align: center; font-size: 1.1rem; color: #6c757d; margin-bottom: 2rem;">AI-powered boundary-aware gene detection system</p>')
-    
-    gr.HTML(status_html)
-    
-    with gr.Row():
-        gr.HTML('''
-        <div class="instructions">
-            <h3>🔬 How to Use:</h3>
-            <ol>
-                <li><strong>Enter DNA sequence:</strong> Paste your sequence using A, T, C, G, N characters</li>
-                <li><strong>Click Analyze:</strong> The AI model will predict gene regions</li>
-                <li><strong>Review results:</strong> View detected genes with positions, codons, and confidence</li>
-            </ol>
+    # Create the interface with custom theme
+    with gr.Blocks(
+        title="🧬 Gene Prediction Tool", 
+        theme=gr.themes.Soft(primary_hue="emerald", secondary_hue="teal"),
+        css=custom_css
+    ) as interface:
+        
+        gr.HTML('<h1 class="main-title">🧬 Advanced Gene Prediction Tool</h1>')
+        gr.HTML('<p style="text-align: center; font-size: 1.1rem; color: #6c757d; margin-bottom: 2rem;">AI-powered boundary-aware gene detection system</p>')
+        
+        gr.HTML(status_html)
+        
+        with gr.Row():
+            gr.HTML('''
+            <div class="instructions">
+                <h3>🔬 How to Use:</h3>
+                <ol>
+                    <li><strong>Enter DNA sequence:</strong> Paste your sequence using A, T, C, G, N characters</li>
+                    <li><strong>Click Analyze:</strong> The AI model will predict gene regions</li>
+                    <li><strong>Review results:</strong> View detected genes with positions, codons, and confidence</li>
+                </ol>
+                
+                <h4>📏 Requirements:</h4>
+                <ul>
+                    <li>Characters: Only A, T, C, G, N allowed</li>
+                    <li>Length: 3 - 10,000 nucleotides</li>
+                    <li>Format: Raw sequence (FASTA headers will be ignored)</li>
+                </ul>
+            </div>
+            ''')
+        
+        with gr.Row():
+            with gr.Column(scale=1):
+                sequence_input = gr.Textbox(
+                    label="🧬 DNA Sequence Input",
+                    placeholder="Enter or paste your DNA sequence here...\nExample: ATGAAACGCATTAGCACC...",
+                    lines=10,
+                    max_lines=20,
+                    show_copy_button=True,
+                    container=True
+                )
+                
+                # Real-time sequence stats
+                sequence_stats = gr.HTML(value="", elem_classes=["sequence-stats"])
+                
+                with gr.Row():
+                    submit_btn = gr.Button("🔬 Analyze Sequence", variant="primary", size="lg", scale=2)
+                    clear_btn = gr.Button("🗑️ Clear", variant="secondary", size="lg", scale=1)
+                
+                # Example buttons
+                gr.Markdown("### 📝 Quick Examples:")
+                with gr.Row():
+                    example1_btn = gr.Button("Short Gene", variant="secondary", size="sm")
+                    example2_btn = gr.Button("Longer Sequence", variant="secondary", size="sm")
             
-            <h4>📏 Requirements:</h4>
-            <ul>
-                <li>Characters: Only A, T, C, G, N allowed</li>
-                <li>Length: 3 - 10,000 nucleotides</li>
-                <li>Format: Raw sequence (FASTA headers will be ignored)</li>
-            </ul>
+            with gr.Column(scale=2):
+                output = gr.Textbox(
+                    label="🔬 Analysis Results",
+                    lines=25,
+                    max_lines=35,
+                    show_copy_button=True,
+                    container=True,
+                    placeholder="Results will appear here after analysis..."
+                )
+        
+        # Footer
+        gr.HTML('''
+        <div style="text-align: center; margin-top: 2rem; padding: 1rem; border-top: 1px solid #dee2e6; color: #6c757d;">
+            <small>🧬 Powered by boundary-aware deep learning | Built with PyTorch & Gradio</small>
         </div>
         ''')
+        
+        # Event handlers
+        def update_stats(sequence):
+            return get_sequence_stats(sequence)
+        
+        # Real-time sequence stats update
+        sequence_input.change(
+            fn=update_stats,
+            inputs=sequence_input,
+            outputs=sequence_stats
+        )
+        
+        # Main prediction
+        submit_btn.click(
+            fn=predict_genes,
+            inputs=sequence_input,
+            outputs=output
+        )
+        
+        # Clear functionality
+        clear_btn.click(
+            fn=lambda: ("", "", ""),
+            outputs=[sequence_input, output, sequence_stats]
+        )
+        
+        # Example buttons
+        example1_btn.click(
+            fn=lambda: examples[0][0],
+            outputs=sequence_input
+        )
+        
+        example2_btn.click(
+            fn=lambda: examples[1][0],
+            outputs=sequence_input
+        )
+        
+        # Allow Enter key to submit
+        sequence_input.submit(
+            fn=predict_genes,
+            inputs=sequence_input,
+            outputs=output
+        )
     
-    with gr.Row():
-        with gr.Column(scale=1):
-            sequence_input = gr.Textbox(
-                label="🧬 DNA Sequence Input",
-                placeholder="Enter or paste your DNA sequence here...\nExample: ATGAAACGCATTAGCACC...",
-                lines=10,
-                max_lines=20,
-                show_copy_button=True,
-                container=True
-            )
-            
-            # Real-time sequence stats
-            sequence_stats = gr.HTML(value="", elem_classes=["sequence-stats"])
-            
-            with gr.Row():
-                submit_btn = gr.Button("🔬 Analyze Sequence", variant="primary", size="lg", scale=2)
-                clear_btn = gr.Button("🗑️ Clear", variant="secondary", size="lg", scale=1)
-            
-            # Example buttons
-            gr.Markdown("### 📝 Quick Examples:")
-            with gr.Row():
-                example1_btn = gr.Button("Short Gene", variant="secondary", size="sm")
-                example2_btn = gr.Button("Longer Sequence", variant="secondary", size="sm")
-        
-        with gr.Column(scale=2):
-            output = gr.Textbox(
-                label="🔬 Analysis Results",
-                lines=25,
-                max_lines=35,
-                show_copy_button=True,
-                container=True,
-                placeholder="Results will appear here after analysis..."
-            )
-    
-    # Footer
-    gr.HTML('''
-    <div style="text-align: center; margin-top: 2rem; padding: 1rem; border-top: 1px solid #dee2e6; color: #6c757d;">
-        <small>🧬 Powered by boundary-aware deep learning | Built with PyTorch & Gradio</small>
-    </div>
-    ''')
-    
-    # Event handlers
-    def update_stats(sequence):
-        return get_sequence_stats(sequence)
-    
-    # Real-time sequence stats update
-    sequence_input.change(
-        fn=update_stats,
-        inputs=sequence_input,
-        outputs=sequence_stats
-    )
-    
-    # Main prediction
-    submit_btn.click(
-        fn=predict_genes,
-        inputs=sequence_input,
-        outputs=output
-    )
-    
-    # Clear functionality
-    clear_btn.click(
-        fn=lambda: ("", "", ""),
-        outputs=[sequence_input, output, sequence_stats]
-    )
-    
-    # Example buttons
-    example1_btn.click(
-        fn=lambda: examples[0][0],
-        outputs=sequence_input
-    )
-    
-    example2_btn.click(
-        fn=lambda: examples[1][0],
-        outputs=sequence_input
-    )
-    
-    # Allow Enter key to submit
-    sequence_input.submit(
-        fn=predict_genes,
-        inputs=sequence_input,
-        outputs=output
-    )
+    return interface
 
-# Launch configuration
+# Create and launch the interface
 if __name__ == "__main__":
     print("🚀 Launching Gene Prediction App...")
+    
+    # Create the interface
+    demo = create_interface()
+    
     print(f"Model loaded: {model_loaded}")
     print(f"Open your browser to see the interface")
     
+    # Launch with Hugging Face Spaces compatible settings
     demo.launch(
         server_name="0.0.0.0",
         server_port=7860,
+        share=False,
+        debug=False,
         show_error=True,
-        show_api=False,
-        share=False,  # Set to True if you want a public link
-        inbrowser=True,  # Automatically open browser
-        prevent_thread_lock=False
+        quiet=False
     )