update app.py

app.py

@@ -35,6 +35,14 @@ def upload_file(files):
     return file_paths
 
 
+def create_df(input_file):
+    bytes_data = input_file.value
+    json_string = bytes_data.decode('utf-8')
+    data = json.loads(json_string)
+    df = pd.DataFrame(data)
+
+    return df
+
 # Accuracy Report
 def report_acc(df, groupd='category', metric_type="dual"):
     assert 'split' in df
@@ -90,7 +98,7 @@ def eval_result_dual(data_main, metric_type="dual"):
 
 
 def calculate_score(input_file):
-    dual_df = pd.DataFrame(input_file)
+    dual_df = create_df(input_file)
     overall_dual, leaf_dual = eval_result_dual(dual_df)
     overall_standard, leaf_standard = eval_result_dual(dual_df, metric_type="standard")
     overall_upd, leaf_upd = eval_result_dual(dual_df, metric_type="upd")
@@ -100,7 +108,7 @@ def calculate_score(input_file):
 
 # add the new data into the queue
 def add_queue(base_df, input_file, model_name):
-    dual_df = pd.DataFrame(input_file)
+    dual_df = create_df(input_file)
     base_df[f"{model_name}_prediction_standard"] = dual_df["prediction_standard"]
     base_df[f"{model_name}_hit_standard"] = dual_df["hit_standard"]
     base_df[f"{model_name}_prediction_upd"] = dual_df["prediction_upd"]
@@ -112,7 +120,7 @@ def add_queue(base_df, input_file, model_name):
 # check whether the input file is correct or not
 def validity_check(input_file, UPD_type, question_type):
 
-    input_df = pd.DataFrame(input_file)
+    input_df = create_df(input_file)
 
     # check for the correct data size
     data_num_dict = {"AAD": 820, "IASD": 919, "IVQD": 356}