test

app.py

@@ -56,6 +56,11 @@ def findfile():
 model_info, results = findfile()
 
 
+def findfile_predictions():
+    with open('data/hf-academic-predictions.json', 'r') as file:
+        predictions = json.load(file)
+    file.close()
+    return predictions
 
 
 
@@ -80,7 +85,7 @@ def make_results_tab(model_info, results):
         result_list.append(this_result)
 
     df = pd.DataFrame(result_list)
-    return df 
+    return df, models_list, datasets_list
 
 
 
@@ -101,7 +106,7 @@ def show_results_tab(df):
     
     def filter_df(model_name, size_ranges, model_types):
         
-        newdf = make_results_tab(model_info, results)
+        newdf, modellist, datasetlist = make_results_tab(model_info, results)
 
         # search model name
         default_val = 'Input the Model Name'
@@ -214,13 +219,46 @@ def show_results_tab(df):
             )
 
 
-def show_predictions_tab(df):
-    pass
+def show_predictions_tab(model_list, dataset_list, predictions):
+
+    def get_pre_df(predictions, model_name, dataset_name):
+        this_predictions = predictions[dataset_name][model_name]['predictions']
+        this_predictions = pd.DataFrame(this_predictions)
+        return this_predictions
+
+    model_list = [i['abbr'] for i in model_list]
+    initial_predictions = get_pre_df(predictions, 'MiniMax-Text-01', 'IFEval')
+
+    with gr.Row():
+        with gr.Column():
+            model_drop = gr.Dropdown(
+                label="Model Name",
+                choices=model_list,  # 去重获取主类别
+                interactive=True
+            )
+        with gr.Column():
+            dataset_drop = gr.Dropdown(
+                label="Model Name",
+                choices=model_list,  # 去重获取主类别
+                interactive=True
+            )
+
+    with gr.Column():
+        table = gr.DataFrame(
+                value=initial_predictions,
+                interactive=False,
+                wrap=False,
+                column_widths=calculate_column_widths(initial_predictions),
+        )
+
+
 
 
 def create_interface():
 
-    df = make_results_tab(model_info, results)
+    df, model_list, dataset_list = make_results_tab(model_info, results)
+    predictions = findfile_predictions()
+
     with gr.Blocks() as demo:
         # title_comp = gr.Markdown(Initial_title)
         gr.Markdown(MAIN_LEADERBOARD_DESCRIPTION)
@@ -231,7 +269,7 @@ def create_interface():
 
             with gr.TabItem('Predictions', elem_id='notmain', id=1):
                 
-                show_predictions_tab(df)
+                show_predictions_tab(model_list, dataset_list, predictions)
 
     return demo
 
@@ -240,5 +278,5 @@ def create_interface():
 
 if __name__ == '__main__':
     demo = create_interface()
-    demo.queue()
-    demo.launch(server_name='0.0.0.0')
+    # demo.queue()
+    # demo.launch(server_name='0.0.0.0')