n-shot filter

app.py

@@ -73,11 +73,12 @@ def update_table(
     type_query: list,
     precision_query: str,
     size_query: list,
+    nshot_query: list,
     show_deleted: bool,
     query: str,
 ):
     print('1', len(hidden_df))
-    filtered_df = filter_models(hidden_df, type_query, size_query, precision_query, show_deleted)
+    filtered_df = filter_models(hidden_df, type_query, size_query, nshot_query, precision_query, show_deleted)
     print('2', len(filtered_df))
     filtered_df = filter_queries(query, filtered_df)
     print('3', len(filtered_df))
@@ -122,7 +123,7 @@ def filter_queries(query: str, filtered_df: pd.DataFrame) -> pd.DataFrame:
 
 
 def filter_models(
-    df: pd.DataFrame, type_query: list, size_query: list, precision_query: list, show_deleted: bool
+    df: pd.DataFrame, type_query: list, size_query: list, nshot_query: list, precision_query: list, show_deleted: bool
 ) -> pd.DataFrame:
     # Show all models
     if show_deleted:
@@ -133,6 +134,9 @@ def filter_models(
     type_emoji = [t[0] for t in type_query]
     filtered_df = filtered_df.loc[df[AutoEvalColumn.model_type_symbol.name].isin(type_emoji)]
     filtered_df = filtered_df.loc[df[AutoEvalColumn.precision.name].isin(precision_query + ["None"])]
+    print(df[AutoEvalColumn.n_shot.name])
+    print(nshot_query)
+    filtered_df = filtered_df.loc[df[AutoEvalColumn.n_shot.name].isin(nshot_query + ["None"])]
 
     numeric_interval = pd.IntervalIndex(sorted([NUMERIC_INTERVALS[s] for s in size_query]))
     params_column = pd.to_numeric(df[AutoEvalColumn.params.name], errors="coerce")