diff --git a/flask_predict_no_batch_t5.py b/flask_predict_no_batch_t5.py
index 1ad5ea9..add4459 100644
--- a/flask_predict_no_batch_t5.py
+++ b/flask_predict_no_batch_t5.py
@@ -74,7 +74,7 @@ def chulichangju_1(text, snetence_id, chulipangban_return_list, short_num):
     return chulipangban_return_list
 
 
-def chulipangban_test_1(text, snetence_id):
+def chulipangban_test_1(snetence_id, text):
     # 引号处理
 
     dialogs_text, dialogs_index, other_index = get_dialogs_index(text)
@@ -120,11 +120,11 @@ def paragraph_test_(text:list, text_new:list):
     # text_new_str = "".join(text_new)
     return text_new
 
-def paragraph_test(text:list):
+def paragraph_test(texts:dict):
 
     text_new = []
-    for i in range(len(text)):
-        text_list = chulipangban_test_1(text[i], i)
+    for i, text in texts.items():
+        text_list = chulipangban_test_1(i, text)
         text_new.extend(text_list)
 
     # text_new_str = "".join(text_new)
@@ -186,25 +186,26 @@ def one_predict(data_text):
 def predict_data_post_processing(text_list):
     text_list_sentence = []
     # text_list_sentence.append([text_list[0][0], text_list[0][1]])
+
     for i in range(len(text_list)):
         if text_list[i][2] != 0:
             text_list_sentence[-1][0] += text_list[i][0]
         else:
             text_list_sentence.append([text_list[i][0], text_list[i][1]])
 
-    return_list = []
+    return_list = {}
     sentence_one = []
-    sentence_id = 0
+    sentence_id = "0"
     for i in text_list_sentence:
         if i[1] == sentence_id:
             sentence_one.append(i[0])
         else:
+            return_list[sentence_id] = "。".join(sentence_one)
             sentence_id = i[1]
-            return_list.append("。".join(sentence_one))
             sentence_one = []
             sentence_one.append(i[0])
     if sentence_one != []:
-        return_list.append("。".join(sentence_one))
+        return_list[sentence_id] = "。".join(sentence_one)
     return return_list
 
 
@@ -217,7 +218,7 @@ def predict_data_post_processing(text_list):
 #     # return_list = predict_data_post_processing(text_list)
 #     # return return_list
 
-def main(text: list):
+def main(text: dict):
     text_list = paragraph_test(text)
     text_list_new = []
     for i in text_list:
@@ -235,7 +236,7 @@ def sentence():
     # question = question.strip('。、！？?')
 
 
-    if isinstance(texts, list):
+    if isinstance(texts, dict):
         texts_list = []
         y_pred_label_list = []
         position_list = []