use pills instead of multiselect

.gitignore

@@ -0,0 +1 @@
+venv

app.py

@@ -244,20 +244,47 @@ with tab1:
         # Filter data based on selected providers
         data = data[data["Model"].apply(lambda x: x.split('/')[0].lower()).isin(selected_providers)]
 
-    # Dodanie filtra widocznych kolumn poza expander
-    base_columns = ["Model", "Params", AVERAGE_COLUMN_NAME, IMPLICATURES_AVERAGE_COLUMN_NAME,
-                  SENTIMENT_COLUMN_NAME, UNDERSTANDING_COLUMN_NAME, PHRASEOLOGY_COLUMN_NAME, TRICKY_QUESTIONS_COLUMN_NAME]
-    default_columns = base_columns.copy()
-    selected_columns = st.multiselect("Visible columns", base_columns, default=default_columns)
+    
+    # Define all possible columns
+    all_columns = {
+        "Model": "Model",
+        "Params": "Params",
+        AVERAGE_COLUMN_NAME: "Average",
+        IMPLICATURES_AVERAGE_COLUMN_NAME: "Impl. Avg",
+        SENTIMENT_COLUMN_NAME: "Sentiment",
+        UNDERSTANDING_COLUMN_NAME: "Understanding",
+        PHRASEOLOGY_COLUMN_NAME: "Phraseology",
+        TRICKY_QUESTIONS_COLUMN_NAME: "Tricky Questions"
+    }
+    
+    # By default, all columns are selected
+    default_columns = list(all_columns.keys())
+    
+    # Use pills to select visible columns in multi-selection mode
+    selected_column_labels = st.pills(
+        label="Visible columns",
+        options=list(all_columns.values()),
+        default=list(all_columns.values()),  # Set all columns as default
+        selection_mode="multi",  # Enable multi-selection mode
+        key="visible_columns_pills"
+    )
+    
+    # Map selected labels back to column names
+    reverse_mapping = {v: k for k, v in all_columns.items()}
+    selected_columns = [reverse_mapping[label] for label in selected_column_labels]
+    
+    # If nothing is selected, show all columns
+    if not selected_columns:
+        selected_columns = default_columns
 
     # Display data
     styled_df_show = style_dataframe(data)
     styled_df_show = styler(styled_df_show)
 
-    # Dostosowanie column_config do wybranych kolumn
+    # Customize column_config based on selected columns
     column_config = {}
     
-    # Ustawiamy konfigurację dla wszystkich kolumn
+    # Set configuration for all columns
     if "Model" in styled_df_show.columns:
         column_config["Model"] = st.column_config.TextColumn("Model", help="Model name", width="large") if "Model" in selected_columns else None
     
@@ -271,7 +298,7 @@ with tab1:
         column_config[IMPLICATURES_AVERAGE_COLUMN_NAME] = st.column_config.NumberColumn(IMPLICATURES_AVERAGE_COLUMN_NAME) if IMPLICATURES_AVERAGE_COLUMN_NAME in selected_columns else None
     
     if RESULTS_COLUMN_NAME in styled_df_show.columns:
-        # Results pokazujemy tylko jeśli Average jest wybrane
+        # Show Results only if Average is selected
         column_config[RESULTS_COLUMN_NAME] = st.column_config.BarChartColumn(
             "Bar chart of results", help="Summary of the results of each task",
             y_min=0, y_max=5) if AVERAGE_COLUMN_NAME in selected_columns else None