add depricated

app.py

@@ -16,10 +16,24 @@ leader_component_values = [None] * 5
 
 promo_banner = """
 <div style="background-color: #ffcc00; color: black; padding: 10px; text-align: center; font-weight: bold; font-size: 18px; border: 2px solid #000;">
-    llmarena.ru - USE THE LATEST VERSIONS OF THE BEST CHATBOTS IN RUSSIAN FOR FREE
+    USE THE LATEST VERSIONS OF THE BEST CHATBOTS IN RUSSIAN FOR FREE
 </div>
 """
 
+deprecated_model_name = [
+    "GigaChat 3.1.25.3",
+    "GigaChat-Pro 2.2.25.3",
+    "saiga_llama3_8b_v6",
+    "saiga_phi3_medium",
+    "GigaChat-Plus 3.1.25.3",
+    "GigaChat-Pro 4.0.26.8",
+    "GigaChat 4.0.26.8",
+    "xAI: Grok 2",
+    "GigaChat-Pro 4.0.26.15",
+    "GigaChat 4.0.26.15",
+    "YandexGPT Experimental", "yandex-gpt-arena"
+]
+
 def make_default_md_1():
     leaderboard_md = f"""
 # 🏆 LLM Arena in Russian: Leaderboard
@@ -136,14 +150,15 @@ def recompute_final_ranking(arena_df):
     return list(ranking.values())
 
 
-def get_arena_table(arena_df, model_table_df, arena_subset_df=None):
+def get_arena_table(arena_df, model_table_df, arena_subset_df=None, hidden_models=None):
     arena_df = arena_df.sort_values(
         by=["final_ranking", "rating"], ascending=[True, False]
     )
+
+    if hidden_models:
+        arena_df = arena_df[~arena_df.index.isin(hidden_models)].copy()  # Filter deprecated models
+
     arena_df["final_ranking"] = recompute_final_ranking(arena_df)
-    arena_df = arena_df.sort_values(
-        by=["final_ranking", "rating"], ascending=[True, False]
-    )
 
     # sort by rating
     if arena_subset_df is not None:
@@ -319,6 +334,13 @@ def build_leaderboard_tab(
                             value=selected_category,     # Default to selected_category
                             label="Category",
                         )
+                    with gr.Column(scale=2): # New CheckboxGroup for deprecated models
+                         category_checkbox = gr.CheckboxGroup(
+                             ["Show Deprecated Models"],
+                             label="Filter",
+                             info="",
+                         )
+
                     default_category_details = make_category_arena_leaderboard_md(
                         arena_df, arena_df, name=selected_category
                     )
@@ -458,7 +480,7 @@ def build_leaderboard_tab(
             highlight_rank_max, subset=["Delta"]
         )
 
-    def update_leaderboard_and_plots(category):
+    def update_leaderboard_and_plots(category, filters):
         _, arena_dfs, category_elo_results, _ , model_table_df = read_elo_file(elo_results_file, leaderboard_table_file)
 
         arena_subset_df = arena_dfs[category]
@@ -471,6 +493,7 @@ def build_leaderboard_tab(
             arena_df,
             model_table_df,
             arena_subset_df=arena_subset_df if category != "Overall" else None,
+            hidden_models=None if "Show Deprecated Models" in filters else deprecated_model_name # Pass filter value
         )
         if category != "Overall":
             arena_values = update_leaderboard_df(arena_values)
@@ -546,7 +569,20 @@ def build_leaderboard_tab(
     if leaderboard_table_file:
         category_dropdown.change(
             fn=update_leaderboard_and_plots,
-            inputs=[category_dropdown],
+            inputs=[category_dropdown, category_checkbox], # Pass checkbox value
+            outputs=[
+                elo_display_df,
+                plot_1,
+                plot_2,
+                plot_3,
+                plot_4,
+                more_stats_md,
+                category_deets,
+            ],
+        )
+        category_checkbox.change( # Add a separate change handler for the checkbox
+            fn=update_leaderboard_and_plots,
+            inputs=[category_dropdown, category_checkbox],
             outputs=[
                 elo_display_df,
                 plot_1,
@@ -719,4 +755,4 @@ if __name__ == "__main__":
     leaderboard_table_file = leaderboard_table_files[-1]
 
     demo = build_demo(elo_result_file, leaderboard_table_file)
-    demo.launch(show_api=False)
+    demo.launch(show_api=False)