fix bugs

requirements.txt

@@ -1,5 +1,5 @@
-gradio==4.44.1
-pandas
+gradio>=5.31.0
+pandas>=1.5
 numpy
 plotly
 pathlib 

tabs/leaderboard_tab.py

@@ -1,3 +1,4 @@
+from __future__ import annotations
 import gradio as gr
 import pandas as pd
 from pathlib import Path
@@ -7,9 +8,9 @@ from typing import Union
 BASE_DIR = Path(__file__).resolve().parent.parent
 DATA_PATH = BASE_DIR / "data" / "leaderboard.csv"
 
-# 用于高亮显示的常量
-HIGHLIGHT_COLOR = "#E6D8FF"  
+# 用于标注的常量
 CATEGORY_TO_HIGHLIGHT = "Deep Research Agent"
+HIGHLIGHT_EMOJI = "🚀"
 
 # 列名重命名映射
 COLUMN_RENAME_MAP = {
@@ -59,7 +60,7 @@ def load_leaderboard() -> pd.DataFrame:
         for category, models in MODEL_CATEGORIES.items():
             if model_name in models:
                 return category
-        return "Others"  # 为不在预定义类别中的模型提供默认类别
+        return "Others"
     
     df['category'] = df['model'].apply(get_category)
     return df
@@ -77,32 +78,15 @@ def make_ranked(df: pd.DataFrame) -> pd.DataFrame:
         if col in ranked.columns:
             ranked[col] = ranked[col].round(2)
     
-    return ranked
-
-def apply_styling(df: pd.DataFrame) -> pd.io.formats.style.Styler:
-    """
-    应用样式到 DataFrame，高亮显示 Deep Research Agent 类别的行
-    """
-    def highlight_row(row):
-        if row['category'] == CATEGORY_TO_HIGHLIGHT:
-            return [f'background-color: {HIGHLIGHT_COLOR}'] * len(row)
-        else:
-            return [''] * len(row)
-    
-    # 创建 styler 对象
-    styler = df.style.apply(highlight_row, axis=1)
-    
-    # 格式化数值列显示
-    numeric_columns = ['overall', 'comp.', 'insight', 'inst.', 'read.', 'c.acc.', 'eff.c.']
-    format_dict = {}
-    for col in numeric_columns:
-        if col in df.columns:
-            format_dict[col] = '{:.2f}'
+    # 为 Deep Research Agent 添加 HTML 格式（加粗 + 颜色）
+    ranked['model'] = ranked.apply(
+        lambda row: f'<span style="color: #823AFF;">{HIGHLIGHT_EMOJI} {row["model"]}</span>' 
+                    if row['category'] == CATEGORY_TO_HIGHLIGHT 
+                    else row['model'],
+        axis=1
+    )
     
-    if format_dict:
-        styler = styler.format(format_dict)
-    
-    return styler
+    return ranked
 
 def filter_data(search_text: str, selected_categories: list):
     df = load_leaderboard()
@@ -114,37 +98,47 @@ def filter_data(search_text: str, selected_categories: list):
         df = df[df['category'].isin(selected_categories)]
     
     ranked_df = make_ranked(df)
-    return apply_styling(ranked_df)
+    return ranked_df
 
 def create_leaderboard_tab():
     with gr.Tab("🏆Leaderboard"):
         with gr.Row():
-            search_box = gr.Textbox(
-                label="Model Search", 
-                placeholder="Entering model name to search...",
-                value=""
-            )
-            category_checkboxes = gr.CheckboxGroup(
-                label="Model Categories",
-                choices=list(MODEL_CATEGORIES.keys()),
-                value=list(MODEL_CATEGORIES.keys())
-            )
+            with gr.Column(scale=1):
+                search_box = gr.Textbox(
+                    label="Model Search", 
+                    placeholder="Entering model name to search...",
+                    value=""
+                )
+            with gr.Column(scale=2):
+                category_checkboxes = gr.CheckboxGroup(
+                    label="Model Categories",
+                    choices=list(MODEL_CATEGORIES.keys()),
+                    value=list(MODEL_CATEGORIES.keys())
+                )
         
-        # 初始化数据并应用样式
+        # 初始化数据（不使用样式）
         initial_df = make_ranked(load_leaderboard())
-        styled_initial_df = apply_styling(initial_df)
         
-        # 创建 Dataframe 组件，使用 interactive=False 以支持样式
+        # 获取列数据类型，将 model 列设置为 html
+        column_count = len(initial_df.columns)
+        datatypes = ["str"] * column_count
+        model_col_index = initial_df.columns.get_loc('model')
+        datatypes[model_col_index] = "html"
+        
+        # 创建 Dataframe 组件
         table = gr.Dataframe(
-            value=styled_initial_df,
-            interactive=False,  # 关键：必须为 False 才能显示样式
-            wrap=False,
-            show_search="search"  # 添加搜索框功能
+            value=initial_df,
+            datatype=datatypes,  # 设置数据类型，model 列为 html
+            wrap=False,  # 防止文本换行
+            line_breaks=False,  # 单元格内不换行
+            max_height=600,  # 设置表格最大高度
+            show_label=False,  # 不显示标签
+            elem_id="leaderboard_table"  # 添加元素ID
         )
 
         def update_display(search_text, selected_categories):
-            styled_df = filter_data(search_text, selected_categories)
-            return styled_df
+            df = filter_data(search_text, selected_categories)
+            return df
 
         # 绑定搜索框和复选框的变化事件
         search_box.change(
@@ -158,19 +152,20 @@ def create_leaderboard_tab():
             outputs=table
         )
         
-        # 在底部添加列名说明
-        gr.Markdown(f"""
-        ### Column Abbreviations
-        The leaderboard uses abbreviated column names for compact display:
-        - **overall** - Overall Score
-        - **comp.** - Comprehensiveness
-        - **insight** - Insight quality
-        - **inst.** - Instruction Following
-        - **read.** - Readability
-        - **c.acc.** - Citation Accuracy
-        - **eff.c.** - Effective Citations
-        
-        Rows highlighted in purple indicate **{CATEGORY_TO_HIGHLIGHT}** models.
-        """)
+        # 在底部添加说明
+        with gr.Row():
+            gr.Markdown(f"""
+            ### 📊 Column Descriptions
+            - **Rank**: Model ranking based on overall score
+            - **model**: Model name (<span style="color: #823AFF;">{HIGHLIGHT_EMOJI} = {CATEGORY_TO_HIGHLIGHT}</span>)
+            - **overall**: Overall Score (weighted average of all metrics)
+            - **comp.**: Comprehensiveness - How thorough and complete the research is
+            - **insight**: Insight Quality - Depth and value of analysis
+            - **inst.**: Instruction Following - Adherence to user instructions
+            - **read.**: Readability - Clarity and organization of content
+            - **c.acc.**: Citation Accuracy - Correctness of references
+            - **eff.c.**: Effective Citations - Relevance and quality of sources
+            - **category**: Model category
+            """)
         
     return search_box