Fifth commit

app.py

@@ -248,60 +248,62 @@ def train_model(
 
 # Create Gradio interface
 def create_interface():
-    # Configure Gradio to handle larger file uploads
-    gr.Config(upload_size_limit=100)
-        
-        with gr.Row():
-            with gr.Column():
-                file_input = gr.File(
-                    label="Upload Training Data (CSV)",
-                    type="binary",
-                    file_types=[".csv"]
-                )
-                
-                learning_rate = gr.Slider(
-                    minimum=1e-5,
-                    maximum=1e-3,
-                    value=2e-4,
-                    label="Learning Rate"
-                )
-                
-                num_epochs = gr.Slider(
-                    minimum=1,
-                    maximum=10,
-                    value=3,
-                    step=1,
-                    label="Number of Epochs"
-                )
-                
-                batch_size = gr.Slider(
-                    minimum=1,
-                    maximum=8,
-                    value=4,
-                    step=1,
-                    label="Batch Size"
-                )
-                
-                train_button = gr.Button("Start Training")
-                
-            with gr.Column():
-                output = gr.Textbox(label="Training Status")
-                
-        train_button.click(
-            fn=train_model,
-            inputs=[file_input, learning_rate, num_epochs, batch_size],
-            outputs=output
-        )
-        
-        gr.Markdown("""
-        ## Instructions
-        1. Upload your training data in CSV format with columns:
-           - chunk_id (questions)
-           - text (answers)
-        2. Adjust training parameters if needed
-        3. Click 'Start Training'
-        4. Wait for training to complete
-        """)
+    demo = gr.Interface(
+        # Configure Gradio to handle larger file uploads
+        upload_size_limit=100
+    )
+    
+    with gr.Row():
+        with gr.Column():
+            file_input = gr.File(
+                label="Upload Training Data (CSV)",
+                type="binary",
+                file_types=[".csv"]
+            )
+            
+            learning_rate = gr.Slider(
+                minimum=1e-5,
+                maximum=1e-3,
+                value=2e-4,
+                label="Learning Rate"
+            )
+            
+            num_epochs = gr.Slider(
+                minimum=1,
+                maximum=10,
+                value=3,
+                step=1,
+                label="Number of Epochs"
+            )
+            
+            batch_size = gr.Slider(
+                minimum=1,
+                maximum=8,
+                value=4,
+                step=1,
+                label="Batch Size"
+            )
+            
+            train_button = gr.Button("Start Training")
+            
+        with gr.Column():
+            output = gr.Textbox(label="Training Status")
+            
+    train_button.click(
+        fn=train_model,
+        inputs=[file_input, learning_rate, num_epochs, batch_size],
+        outputs=output
+    )
+    
+    gr.Markdown("""
+    ## Instructions
+    1. Upload your training data in CSV format with columns:
+       - chunk_id (questions)
+       - text (answers)
+    2. Adjust training parameters if needed
+    3. Click 'Start Training'
+    4. Wait for training to complete
+    """)
     
     return demo