Removing Model Type Selection

src/app.py

@@ -22,8 +22,7 @@ from src.components.header import render_page_header
 from src.components.filters import (
     initialize_session_state, 
     render_metric_selection, 
-    render_task_selection, 
-    render_model_type_selection
+    render_task_selection
 )
 from src.components.leaderboard import render_leaderboard_table, render_empty_state
 from src.components.tasks import render_task_descriptions
@@ -100,17 +99,16 @@ def main():
         
         # Continue with other filters
         selected_tasks = render_task_selection(df)
-        selected_model_types = render_model_type_selection(df)
         
         # Render leaderboard if selections are valid
-        if selected_tasks and selected_model_types:
+        if selected_tasks:
             # Load the primary metric data first (always the first in selected_metrics)
             primary_metric = selected_metrics[0]
             primary_metric_data = load_metric_data(metrics_config[primary_metric]["file"])
             primary_df = process_data(primary_metric_data)
             
             # Filter and prepare data for primary metric
-            filtered_df = filter_and_prepare_data(primary_df, selected_tasks, selected_model_types)
+            filtered_df = filter_and_prepare_data(primary_df, selected_tasks, st.session_state.selected_model_types)
             
             # Format data for display
             display_df, metric_columns = format_display_dataframe(filtered_df, selected_tasks)
@@ -124,7 +122,7 @@ def main():
                 metric_df = process_data(metric_data)
                 
                 # Process and merge the additional metric data
-                metric_filtered_df = filter_and_prepare_data(metric_df, selected_tasks, selected_model_types)
+                metric_filtered_df = filter_and_prepare_data(metric_df, selected_tasks, st.session_state.selected_model_types)
                 metric_display_df, _ = format_display_dataframe(metric_filtered_df, selected_tasks)
                 
                 # Create a meaningful prefix for this metric

src/components/filters.py

@@ -18,16 +18,15 @@ def initialize_session_state(df):
         st.session_state.selected_metrics = [primary_metric]
     
     if 'selected_tasks' not in st.session_state:
-        # Select all tasks by default, excluding Model Type
+        # Select all tasks by default
         st.session_state.selected_tasks = [col for col in df.columns if col not in ['Model Type']]
     else:
         # Make sure selected_tasks only includes actual tasks from the dataframe
         valid_tasks = [col for col in df.columns if col not in ['Model Type']]
         st.session_state.selected_tasks = [task for task in st.session_state.selected_tasks if task in valid_tasks]
     
-    if 'selected_model_types' not in st.session_state:
-        # Ensure all model types are selected by default
-        st.session_state.selected_model_types = list(df['Model Type'].unique())
+    # Always select all model types
+    st.session_state.selected_model_types = list(df['Model Type'].unique())
 
 def render_metric_selection():
     """
@@ -126,45 +125,4 @@ def render_task_selection(df):
                             st.session_state.selected_tasks.append(task)
                         st.rerun()  # Force UI update
     
-    return st.session_state.selected_tasks
-
-def render_model_type_selection(df):
-    """
-    Render the model type selection component
-    
-    Args:
-        df (pandas.DataFrame): The DataFrame with model data
-        
-    Returns:
-        list: Selected model types
-    """
-    st.markdown("### Select Model Types")
-    
-    # Get unique model types
-    model_types = df['Model Type'].unique().tolist()
-    
-    # Determine number of columns - up to 4 columns max depending on number of model types
-    num_cols = min(len(model_types), 4)
-    
-    # Create columns
-    cols = st.columns(num_cols)
-    
-    # Add a button for each model type
-    for i, model_type in enumerate(model_types):
-        col_idx = i % num_cols  # Determine which column to place the button in
-        
-        with cols[col_idx]:
-            is_selected = model_type in st.session_state.selected_model_types
-            button_label = f"✓ {model_type}" if is_selected else model_type
-            button_type = "primary" if is_selected else "secondary"
-            
-            if st.button(button_label, key=f"model_type_{model_type}", type=button_type):
-                if is_selected:
-                    # Prevent deselecting all model types - ensure at least one remains selected
-                    if len(st.session_state.selected_model_types) > 1:
-                        st.session_state.selected_model_types.remove(model_type)
-                else:
-                    st.session_state.selected_model_types.append(model_type)
-                st.rerun()  # Force UI update
-    
-    return st.session_state.selected_model_types 
+    return st.session_state.selected_tasks 

src/components/leaderboard.py

@@ -240,6 +240,6 @@ def render_empty_state():
     """
     st.markdown("""
     <div class="warning-box">
-        <strong>No data to display.</strong> Please select at least one task and one model type to view the data.
+        <strong>No data to display.</strong> Please select at least one task to view the data.
     </div>
     """, unsafe_allow_html=True)