update

app.py

@@ -2,15 +2,6 @@ import gradio as gr
 import pandas as pd
 from functools import reduce
 
-import pandas as pd
-import gradio as gr
-from collections import defaultdict
-import os
-from yaml import safe_load
-
-from collections import defaultdict
-import os
-
 CONFIG = safe_load(open("config.yaml"))
 
 data = defaultdict(dict)
@@ -19,12 +10,12 @@ data = defaultdict(dict)
 for settings in CONFIG['settings']:
     for type in CONFIG['types']:
         # 根据配置文件中的路径读取数据
-        data[settings][type] = pd.read_excel('data/'+CONFIG["settings_mapping"][settings] + f"-{type}.xlsx")
+        data[settings][type] = pd.read_excel('data/' + CONFIG["settings_mapping"][settings] + f"-{type}.xlsx")
         
-# 添加平均分列
+# 添加平均分列并四舍五入到小数点后两位
 for settings in CONFIG['settings']:
     for type in CONFIG['types']:
-        data[settings][type]["Average"] = data[settings][type].iloc[:,1:].mean(axis=1)
+        data[settings][type]["Average"] = data[settings][type].iloc[:,1:].mean(axis=1).round(2)
 # 添加rank列
 for settings in CONFIG['settings']:
     for type in CONFIG['types']:
@@ -36,6 +27,11 @@ for settings in CONFIG['settings']:
         cols = cols[-1:] + cols[:-1]
         data[settings][type] = data[settings][type][cols]
 
+# 四舍五入整个DataFrame到小数点后两位
+for settings in CONFIG['settings']:
+    for type in CONFIG['types']:
+        data[settings][type] = data[settings][type].round(2)
+
 css = """
 table > thead {
     white-space: normal;
@@ -59,7 +55,6 @@ table > tbody > tr > td:nth-child(2) {
     width: auto;
 }
 
-
 /* 紧凑显示其他列 */
 table > tbody > tr > td:not(:nth-child(2)) {
     white-space: normal;
@@ -67,15 +62,6 @@ table > tbody > tr > td:not(:nth-child(2)) {
 }
 """
 
-"""
-Each inner tab can have the following keys:
-- language: The language of the leaderboard
-- language_long: [optional] The long form of the language
-- description: The description of the leaderboard
-- credits: [optional] The credits for the leaderboard
-- desc: [optional] The description of the leaderboard
-- data: The data for the leaderboard
-"""
 # 定义模型类型和大小（占位符）
 MODEL_TYPES = [
     "Open",
@@ -95,7 +81,7 @@ NUMERIC_INTERVALS = {
     ">1B": pd.Interval(1000, 1_000_000, closed="right"),
 }
 
-#定义
+# 定义过滤函数
 def filter_data(search_query, model_types, model_sizes):
     output_df = df.copy()
     
@@ -117,52 +103,62 @@ def filter_data(search_query, model_types, model_sizes):
         # Placeholder logic for model size filtering
         pass
     
-    return output_df
+    return output_df.round(2)
+
+# 创建示例 DataFrame (假设 df 是一个示例 DataFrame)
+df = pd.DataFrame({
+    'Model': ['ModelA', 'ModelB'],
+    'Metric1': [0.123456, 0.789123],
+    'Metric2': [0.654321, 0.321654],
+    'Average': [0.0, 0.0],
+    'Rank': [0, 0]
+})
+
+# 计算 Average 和 Rank 并四舍五入
+df['Average'] = df.iloc[:, 1:-1].mean(axis=1).round(2)
+df['Rank'] = df['Average'].rank(ascending=False, method='min').astype(int)
+cols = df.columns.tolist()
+cols = cols[-1:] + cols[:-1]
+df = df[cols]
 
 # Create the Gradio interface
 with gr.Blocks(css=css) as demo:
-    gr.Markdown("# Model Leaderboard")
-    
-    with gr.Row():
-        search_box = gr.Textbox(
-            label="Search Models (separate by ';')",
-            placeholder=" 🔍 Search for a model and press enter..."
-        )
-        model_type_checkbox_group = gr.CheckboxGroup(
-            label="Model types",
-            choices=MODEL_TYPES, 
-            value=MODEL_TYPES,
-            interactive=True,
-            elem_classes=["filter-checkbox-group"],
-            scale=3
-        )
-        model_size_checkbox_group = gr.CheckboxGroup(
-            label="Model sizes (in number of parameters)",
-            choices=list(NUMERIC_INTERVALS.keys()),
-            value=list(NUMERIC_INTERVALS.keys()),
-            interactive=True,
-            elem_classes=["filter-checkbox-group"],
-            scale=2,
-        )
-    submit_button = gr.Button("Filter Data")
-    
-    with gr.Tabs() as result_table:
-        for settings in CONFIG['settings']:
-            with gr.Tab(label=settings):
-                for type in CONFIG['types']:
-                    with gr.Tab(label=type):
-                        # gr.Dataframe(data[settings][type], headers=data[settings][type].columns.tolist(), datatype=["str"] + ["number"] * (len(data[settings][type].columns) - 1))
-                        gr.DataFrame(data[settings][type], type="pandas")
-            
-            
-    # result_table = gr.Dataframe(headers=df.columns.tolist(), datatype=["str"] + ["number"] * (len(df.columns) - 1))
-    
-    # Initially display the entire DataFrame
-    # vis = gr.DataFrame(df)
-    
-    # submit_button.click(fn=filter_data, inputs=[search_box, model_type_checkbox_group, model_size_checkbox_group], outputs=result_table)
-    
-    # Display the initial DataFrame
+    with gr.Box(className="container"):
+        gr.Markdown("# Model Leaderboard")
+        
+        with gr.Row():
+            search_box = gr.Textbox(
+                label="Search Models (separate by ';')",
+                placeholder="🔍 Search for a model and press enter...",
+                scale=3
+            )
+            model_type_checkbox_group = gr.CheckboxGroup(
+                label="Model types",
+                choices=MODEL_TYPES, 
+                value=MODEL_TYPES,
+                interactive=True,
+                elem_classes=["filter-checkbox-group"],
+                scale=3
+            )
+            model_size_checkbox_group = gr.CheckboxGroup(
+                label="Model sizes (in number of parameters)",
+                choices=list(NUMERIC_INTERVALS.keys()),
+                value=list(NUMERIC_INTERVALS.keys()),
+                interactive=True,
+                elem_classes=["filter-checkbox-group"],
+                scale=2,
+            )
+        submit_button = gr.Button("Filter Data")
+        
+        with gr.Tabs() as result_table:
+            for settings in CONFIG['settings']:
+                with gr.Tab(label=settings):
+                    for type in CONFIG['types']:
+                        with gr.Box(className="container"):
+                            gr.Markdown(f"### {type} Leaderboard")
+                            gr.DataFrame(data[settings][type], type="pandas")
+                
+
 
 demo.launch()
 

requirements.txt

@@ -13,4 +13,5 @@ python-dateutil
 tqdm
 transformers
 tokenizers>=0.15.0
-sentencepiece
+sentencepiece
+openpyxl