Remove backend library info

app.py

@@ -95,7 +95,6 @@ def filter_models(
     num_few_shots_query: list,
     version_query: list,
     vllm_query: list,
-    # backend_query: list,
 ) -> pd.DataFrame:
     print(f"Initial df shape: {df.shape}")
     print(f"Initial df content:\n{df}")
@@ -137,10 +136,6 @@ def filter_models(
     filtered_df = filtered_df[filtered_df["vllm version"].isin(vllm_query)]
     print(f"After vllm version filter: {filtered_df.shape}")
 
-    # Backend フィルタリング
-    # filtered_df = filtered_df[filtered_df["Backend Library"].isin(backend_query)]
-    # print(f"After backend filter: {filtered_df.shape}")
-
     print("Filtered dataframe head:")
     print(filtered_df.head())
     return filtered_df
@@ -191,7 +186,6 @@ def update_table(
     num_few_shots_query: list,
     version_query: list,
     vllm_query: list,
-    # backend_query: list,
     query: str,
     *columns,
 ):
@@ -209,7 +203,6 @@ def update_table(
         num_few_shots_query,
         version_query,
         vllm_query,
-        #    backend_query,
     )
     print(f"filtered_df shape after filter_models: {filtered_df.shape}")
 
@@ -242,7 +235,6 @@ leaderboard_df = filter_models(
     [i.value.name for i in NumFewShots],
     [i.value.name for i in Version],
     [i.value.name for i in VllmVersion],
-    #    [i.value.name for i in Backend],
 )
 # DataFrameの初期化部分のみを修正
 INITIAL_COLUMNS = ["T"] + [
@@ -469,13 +461,6 @@ with gr.Blocks() as demo_leaderboard:
                 elem_id="filter-columns-vllm",
             )
 
-            # filter_columns_backend = gr.CheckboxGroup(
-            #    label="Backend Library",
-            #    choices=[i.value.name for i in Backend],
-            #    value=[i.value.name for i in Backend],
-            #    elem_id="filter-columns-backend",
-            # )
-
     leaderboard_table = gr.Dataframe(
         value=leaderboard_df,
         headers=INITIAL_COLUMNS,
@@ -516,7 +501,6 @@ with gr.Blocks() as demo_leaderboard:
             filter_columns_num_few_shots.change,
             filter_columns_version.change,
             filter_columns_vllm.change,
-            # filter_columns_backend.change,
             search_bar.submit,
         ]
         + [shown_columns.change for shown_columns in shown_columns_dict.values()],
@@ -529,7 +513,6 @@ with gr.Blocks() as demo_leaderboard:
             filter_columns_num_few_shots,
             filter_columns_version,
             filter_columns_vllm,
-            # filter_columns_backend,
             search_bar,
         ]
         + [shown_columns for shown_columns in shown_columns_dict.values()],

src/display/utils.py

@@ -61,7 +61,6 @@ auto_eval_column_dict.append(
     ["llm_jp_eval_version", ColumnContent, ColumnContent("llm-jp-eval version", "str", False)]
 )
 auto_eval_column_dict.append(["vllm_version", ColumnContent, ColumnContent("vllm version", "str", False)])
-auto_eval_column_dict.append(["backend", ColumnContent, ColumnContent("Backend Library", "str", False, dummy=True)])
 auto_eval_column_dict.append(["dummy", ColumnContent, ColumnContent("model_name_for_query", "str", False, dummy=True)])
 auto_eval_column_dict.append(["row_id", ColumnContent, ColumnContent("ID", "number", False, dummy=True)])
 
@@ -160,17 +159,6 @@ class Version(Enum):
             return Version.Unknown
 
 
-class Backend(Enum):
-    vllm = ModelDetails("vllm")
-    Unknown = ModelDetails("?")
-
-    def from_str(backend):
-        if backend == "vllm":
-            return Backend.vllm
-        else:
-            return Backend.Unknown
-
-
 class VllmVersion(Enum):
     current = ModelDetails("v0.6.3.post1")
     Unknown = ModelDetails("?")

src/populate.py

@@ -15,7 +15,6 @@ def get_leaderboard_df(contents_repo: str, cols: list, benchmark_cols: list) ->
     df = datasets.load_dataset(contents_repo, split="train").to_pandas()
     df["Model"] = df["model"].map(make_clickable_model)
     df["T"] = df["model_type"].map(lambda x: x.split(":")[0].strip())
-    df["Backend Library"] = "vllm"
     df = df.rename(columns={task.value.metric: task.value.col_name for task in Tasks})
     df = df.rename(
         columns={