Update app.py

app.py

@@ -1,76 +1,123 @@
-import gradio as gr
-import json
-import os
-import pandas as pd
-import time
-
-# Configuration
-FOLDER_TO_WATCH = "model_results"  # Folder where JSON files are stored
-REFRESH_INTERVAL = 5  # Seconds between automatic refreshes
-COLUMNS_TO_DISPLAY = ["model_name", "accuracy", "precision", "recall", "f1_score", "timestamp"]
-
-# Create the folder if it doesn't exist
-os.makedirs(FOLDER_TO_WATCH, exist_ok=True)
-
-def load_data():
-    data = []
-    for filename in os.listdir(FOLDER_TO_WATCH):
-        if filename.endswith('.json'):
-            try:
-                with open(os.path.join(FOLDER_TO_WATCH, filename), 'r') as f:
-                    model_data = json.load(f)
-                    data.append(model_data)
-            except Exception as e:
-                print(f"Error loading {filename}: {e}")
-    
-    if data:
-        df = pd.DataFrame(data)
-        if not df.empty and 'accuracy' in df.columns:
-            df = df.sort_values(by='accuracy', ascending=False)
-        return df[COLUMNS_TO_DISPLAY] if all(col in df.columns for col in COLUMNS_TO_DISPLAY) else df
-    return pd.DataFrame(columns=COLUMNS_TO_DISPLAY)
-
-def update_leaderboard():
-    current_data = load_data()
-    return current_data, time.strftime("%Y-%m-%d %H:%M:%S")
-
-with gr.Blocks(title="Model Leaderboard") as demo:
-    gr.Markdown("# Model Performance Leaderboard")
-    gr.Markdown(f"Automatically updates from JSON files in `{FOLDER_TO_WATCH}` folder")
-    
-    with gr.Row():
-        refresh_btn = gr.Button("🔄 Refresh", variant="secondary")
-        last_update = gr.Textbox(label="Last Updated", interactive=False)
-    
-    leaderboard = gr.Dataframe(
-        headers=COLUMNS_TO_DISPLAY,
-        interactive=False,
-        wrap=True
-    )
-    
-    refresh_btn.click(
-        fn=update_leaderboard,
-        outputs=[leaderboard, last_update]
-    )
-    
-    # New way to implement auto-refresh
-    demo.load(
-        fn=lambda: update_leaderboard(),
-        outputs=[leaderboard, last_update]
-    )
-    
-    # Alternative auto-refresh method
-    def auto_refresh():
-        while True:
-            time.sleep(REFRESH_INTERVAL)
-            yield update_leaderboard()
-    
-    demo.queue()
-    leaderboard.change(
-        fn=auto_refresh,
-        outputs=[leaderboard, last_update],
-        show_progress=False
-    )
-
-if __name__ == "__main__":
-    demo.launch(share=True)
+import gradio as gr
+import json
+import os
+import pandas as pd
+import time
+
+# Configuration
+FOLDER_TO_WATCH = "model_results"  # Folder where JSON files are stored
+REFRESH_INTERVAL = 5  # Seconds between automatic refreshes
+COLUMNS_TO_DISPLAY = ["model_name", "accuracy", "precision", "recall", "f1_score", "timestamp"]
+
+# Create the folder if it doesn't exist
+os.makedirs(FOLDER_TO_WATCH, exist_ok=True)
+
+def load_data():
+    """Load all JSON files from the folder and return as DataFrame"""
+    data = []
+    for filename in os.listdir(FOLDER_TO_WATCH):
+        if filename.endswith('.json'):
+            try:
+                with open(os.path.join(FOLDER_TO_WATCH, filename), 'r') as f:
+                    model_data = json.load(f)
+                    data.append(model_data)
+            except Exception as e:
+                print(f"Error loading {filename}: {e}")
+    
+    if data:
+        return pd.DataFrame(data)
+    return pd.DataFrame(columns=COLUMNS_TO_DISPLAY)
+
+def update_leaderboard(sort_by="accuracy", sort_order="descending"):
+    """Update the leaderboard with current data and sorting"""
+    current_data = load_data()
+    
+    # Get available numeric columns for sorting
+    numeric_cols = [col for col in current_data.columns if pd.api.types.is_numeric_dtype(current_data[col])]
+    
+    # Default to accuracy if selected column isn't available
+    sort_by = sort_by if sort_by in numeric_cols else "accuracy"
+    
+    # Apply sorting
+    if not current_data.empty and sort_by in current_data.columns:
+        ascending = sort_order == "ascending"
+        current_data = current_data.sort_values(by=sort_by, ascending=ascending)
+    
+    # Select only the columns we want to display
+    display_cols = [col for col in COLUMNS_TO_DISPLAY if col in current_data.columns]
+    return current_data[display_cols], time.strftime("%Y-%m-%d %H:%M:%S"), gr.Dropdown(choices=numeric_cols)
+
+with gr.Blocks(title="Model Leaderboard") as demo:
+    gr.Markdown("# 🏆 Model Performance Leaderboard")
+    gr.Markdown(f"Automatically updates from JSON files in `{FOLDER_TO_WATCH}` folder")
+    
+    # Get initial data to populate sort options
+    initial_data = load_data()
+    numeric_cols = [col for col in initial_data.columns if pd.api.types.is_numeric_dtype(initial_data[col])]
+    
+    with gr.Row():
+        with gr.Column(scale=1):
+            sort_by = gr.Dropdown(
+                label="Sort by metric",
+                choices=numeric_cols,
+                value="accuracy"
+            )
+            sort_order = gr.Radio(
+                label="Sort order",
+                choices=["descending", "ascending"],
+                value="descending"
+            )
+            refresh_btn = gr.Button("🔄 Refresh", variant="secondary")
+        with gr.Column(scale=2):
+            last_update = gr.Textbox(label="Last Updated", interactive=False)
+    
+    leaderboard = gr.Dataframe(
+        headers=COLUMNS_TO_DISPLAY,
+        datatype=["str"] + ["number"]*(len(COLUMNS_TO_DISPLAY)-1),
+        interactive=False,
+        wrap=True
+    )
+    
+    # Input components for interactive controls
+    inputs = [sort_by, sort_order]
+    
+    # Manual refresh
+    refresh_btn.click(
+        fn=update_leaderboard,
+        inputs=inputs,
+        outputs=[leaderboard, last_update, sort_by]
+    )
+    
+    # Auto-refresh when sorting changes
+    sort_by.change(
+        fn=update_leaderboard,
+        inputs=inputs,
+        outputs=[leaderboard, last_update, sort_by]
+    )
+    sort_order.change(
+        fn=update_leaderboard,
+        inputs=inputs,
+        outputs=[leaderboard, last_update, sort_by]
+    )
+    
+    # Initial load and periodic refresh
+    def auto_refresh(sort_by, sort_order):
+        while True:
+            time.sleep(REFRESH_INTERVAL)
+            df, timestamp, _ = update_leaderboard(sort_by, sort_order)
+            yield df, timestamp, gr.Dropdown(choices=numeric_cols)
+    
+    demo.queue()
+    demo.load(
+        fn=lambda: update_leaderboard("accuracy", "descending"),
+        outputs=[leaderboard, last_update, sort_by]
+    )
+    leaderboard.change(
+        fn=auto_refresh,
+        inputs=inputs,
+        outputs=[leaderboard, last_update, sort_by],
+        show_progress=False
+    )
+
+if __name__ == "__main__":
+    demo.launch()