Clean up

app.py

@@ -99,46 +99,41 @@ def filter_models(
     print(f"Initial df shape: {df.shape}")
     print(f"Initial df content:\n{df}")
 
-    filtered_df = df
-
     # Model Type フィルタリング
-    type_column = "T" if "T" in df.columns else "Type_"
     type_emoji = [t.split()[0] for t in type_query]
-    filtered_df = df[df[type_column].isin(type_emoji)]
-    print(f"After type filter: {filtered_df.shape}")
+    df = df[df["T"].isin(type_emoji)]
+    print(f"After type filter: {df.shape}")
 
     # Precision フィルタリング
-    filtered_df = filtered_df[filtered_df["Precision"].isin(precision_query)]
-    print(f"After precision filter: {filtered_df.shape}")
+    df = df[df["Precision"].isin(precision_query)]
+    print(f"After precision filter: {df.shape}")
 
     # Model Size フィルタリング
-    size_mask = filtered_df["#Params (B)"].apply(
-        lambda x: any(x in NUMERIC_INTERVALS[s] for s in size_query if s != "Unknown")
-    )
+    size_mask = df["#Params (B)"].apply(lambda x: any(x in NUMERIC_INTERVALS[s] for s in size_query if s != "Unknown"))
     if "Unknown" in size_query:
-        size_mask |= filtered_df["#Params (B)"].isna() | (filtered_df["#Params (B)"] == 0)
-    filtered_df = filtered_df[size_mask]
-    print(f"After size filter: {filtered_df.shape}")
+        size_mask |= df["#Params (B)"].isna() | (df["#Params (B)"] == 0)
+    df = df[size_mask]
+    print(f"After size filter: {df.shape}")
 
     # Add Special Tokens フィルタリング
-    filtered_df = filtered_df[filtered_df["Add Special Tokens"].isin(add_special_tokens_query)]
-    print(f"After add_special_tokens filter: {filtered_df.shape}")
+    df = df[df["Add Special Tokens"].isin(add_special_tokens_query)]
+    print(f"After add_special_tokens filter: {df.shape}")
 
     # Num Few Shots フィルタリング
-    filtered_df = filtered_df[filtered_df["Few-shot"].astype(str).isin(num_few_shots_query)]
-    print(f"After num_few_shots filter: {filtered_df.shape}")
+    df = df[df["Few-shot"].astype(str).isin(num_few_shots_query)]
+    print(f"After num_few_shots filter: {df.shape}")
 
     # Version フィルタリング
-    filtered_df = filtered_df[filtered_df["llm-jp-eval version"].isin(version_query)]
-    print(f"After version filter: {filtered_df.shape}")
+    df = df[df["llm-jp-eval version"].isin(version_query)]
+    print(f"After version filter: {df.shape}")
 
     # Vllm Version フィルタリング
-    filtered_df = filtered_df[filtered_df["vllm version"].isin(vllm_query)]
-    print(f"After vllm version filter: {filtered_df.shape}")
+    df = df[df["vllm version"].isin(vllm_query)]
+    print(f"After vllm version filter: {df.shape}")
 
     print("Filtered dataframe head:")
-    print(filtered_df.head())
-    return filtered_df
+    print(df.head())
+    return df
 
 
 def search_model_by_name(df: pd.DataFrame, model_name: str) -> pd.DataFrame: