debug

app.py

@@ -51,7 +51,7 @@ import pandas as pd
 from typing import List, Dict, Union, Optional, Any
 from dataclasses import fields
 
-class SmartSelectColumns(SelectColumns):
+# class SmartSelectColumns(SelectColumns):
     """
     Enhanced SelectColumns component with basic filtering functionality.
     """
@@ -128,7 +128,67 @@ class SmartSelectColumns(SelectColumns):
             
         return super().update(value)
 
+class SmartSelectColumns(SelectColumns):
+    """
+    Enhanced SelectColumns component with minimal modifications from original.
+    """
+    def __init__(
+        self,
+        benchmark_keywords: Optional[List[str]] = None,
+        model_keywords: Optional[List[str]] = None,
+        initial_selected: Optional[List[str]] = None,
+        label: str = "Select Results:",
+        **kwargs
+    ):
+        """
+        Initialize SmartSelectColumns.
+        """
+        super().__init__(label=label, **kwargs)
+        self.benchmark_keywords = benchmark_keywords or []
+        self.model_keywords = model_keywords or []
+        self.initial_selected = initial_selected or []
+
+    def get_filtered_groups(self, columns: List[str]) -> Dict[str, List[str]]:
+        """Get column groups based on keywords."""
+        filtered_groups = {}
+        
+        # Add benchmark groups
+        for benchmark in self.benchmark_keywords:
+            matching_cols = [
+                col for col in columns 
+                if benchmark in col.lower()
+            ]
+            if matching_cols:
+                filtered_groups[f"Benchmark group for {benchmark}"] = matching_cols
+        
+        # Add model groups
+        for model in self.model_keywords:
+            matching_cols = [
+                col for col in columns 
+                if model in col.lower()
+            ]
+            if matching_cols:
+                filtered_groups[f"Model group for {model}"] = matching_cols
+        
+        return filtered_groups
 
+    def update(
+        self, 
+        value: Union[pd.DataFrame, Dict[str, List[str]], Any]
+    ) -> Dict:
+        """Update component, staying close to original SelectColumns behavior."""
+        if isinstance(value, pd.DataFrame):
+            columns = list(value.columns)
+            filtered_cols = self.get_filtered_groups(columns)
+            
+            return {
+                "choices": columns,
+                "value": self.initial_selected or columns,
+                "filtered_cols": filtered_cols,
+                "__type__": "update"
+            }
+            
+        return super().update(value)
 
 
 
@@ -409,14 +469,15 @@ def init_leaderboard_mib_subgraph(dataframe, track):
     benchmark_keywords = ["ioi", "mcqa", "arithmetic", "arc"]
     model_keywords = ["qwen2_5", "gpt2", "gemma2", "llama3"]
 
-    # Create SmartSelectColumns with minimal configuration
+    # Create SmartSelectColumns instance
     smart_columns = SmartSelectColumns(
         benchmark_keywords=benchmark_keywords,
         model_keywords=model_keywords,
-        initial_selected=["Method", "Average"]
+        initial_selected=["Method", "Average"],
+        label="Select Results:"  # Match original label
     )
 
-    # Create and return the leaderboard
+    # Create Leaderboard
     print("\nCreating leaderboard...")
     leaderboard = Leaderboard(
         value=dataframe,
@@ -427,6 +488,7 @@ def init_leaderboard_mib_subgraph(dataframe, track):
         interactive=False
     )
     print("Leaderboard created successfully")
+    print("Leaderboard is", leaderboard)
     return leaderboard