Update app.py

app.py

@@ -1,12 +1,14 @@
-
 __all__ = ['block', 'make_clickable_model', 'make_clickable_user', 'get_submissions']
-
+import os
 import gradio as gr
 import pandas as pd
 import json
 import tempfile
 
 from constants import *
+from huggingface_hub import Repository
+
+HF_TOKEN = os.environ.get("HF_TOKEN")
 
 global data_component, filter_component
 
@@ -29,6 +31,8 @@ def add_new_eval(
         return "Error! Empty file!"
 
     upload_data=json.loads(input_file)
+    submission_repo = Repository(local_dir=SUBMISSION_NAME, clone_from=SUBMISSION_URL, use_auth_token=HF_TOKEN, repo_type="dataset")
+    submission_repo.git_pull()
     csv_data = pd.read_csv(CSV_DIR)
 
     if LLM_type == 'Other':
@@ -66,10 +70,12 @@ def add_new_eval(
             new_data.append(0)
     csv_data.loc[col] = new_data
     csv_data = csv_data.to_csv(CSV_DIR, index=False)
+    submission_repo.push_to_hub()
     return 0
 
 def get_baseline_df():
-    # pdb.set_trace()
+    submission_repo = Repository(local_dir=SUBMISSION_NAME, clone_from=SUBMISSION_URL, use_auth_token=HF_TOKEN, repo_type="dataset")
+    submission_repo.git_pull()
     df = pd.read_csv(CSV_DIR)
     df = df.sort_values(by="Avg", ascending=False)
     present_columns = MODEL_INFO + checkbox_group.value
@@ -77,6 +83,8 @@ def get_baseline_df():
     return df
 
 def get_all_df():
+    submission_repo = Repository(local_dir=SUBMISSION_NAME, clone_from=SUBMISSION_URL, use_auth_token=HF_TOKEN, repo_type="dataset")
+    submission_repo.git_pull()
     df = pd.read_csv(CSV_DIR)
     df = df.sort_values(by="Avg", ascending=False)
     return df
@@ -111,9 +119,6 @@ with block:
                 interactive=True,
             )
 
-
-
-            # 创建数据帧组件
             data_component = gr.components.Dataframe(
                 value=get_baseline_df, 
                 headers=COLUMN_NAMES,
@@ -129,6 +134,7 @@ with block:
                 # columns:
                 selected_columns = [item for item in TASK_INFO if item in selected_columns]
                 present_columns = MODEL_INFO + selected_columns
+                print("selected_columns",'|'.join(selected_columns))
                 updated_data = updated_data[present_columns]
                 updated_data = updated_data.sort_values(by=selected_columns[0], ascending=False)
                 updated_headers = present_columns
@@ -226,7 +232,6 @@ with block:
 
     def refresh_data():
         value1 = get_baseline_df()
-
         return value1
 
     with gr.Row():