Update app.py

app.py

@@ -7,6 +7,7 @@ import re
 import secrets
 from pathlib import Path
 from pydub import AudioSegment
+import ast
 
 torch.manual_seed(420)
 tokenizer = AutoTokenizer.from_pretrained("Qwen/Qwen-Audio-Chat", trust_remote_code=True)
@@ -49,6 +50,9 @@ def predict(_chatbot, task_history, user_input):
     print("Type of task_history:", type(task_history))
     if task_history is None or not isinstance(task_history, list):
         task_history = [] 
+    else 
+        task_history = parse_task_history(task_history)
+
     print("Predict - Start: task_history =", task_history)
     if not isinstance(task_history, list) or not all(isinstance(item, tuple) and len(item) == 2 for item in task_history):
         print("Error: task_history should be a list of tuples of length 2.")
@@ -109,7 +113,17 @@ def predict(_chatbot, task_history, user_input):
     print("Predict - End: task_history =", task_history)
     return _chatbot[-1][1], _chatbot
 
-
+def parse_task_history(task_history_str):
+    try:
+        parsed_task_history = ast.literal_eval(task_history_str)
+        if isinstance(parsed_task_history, list) and all(isinstance(item, tuple) and len(item) == 2 for item in parsed_task_history):
+            return parsed_task_history
+        else:
+            raise ValueError("Parsed task history is not a list of tuples")
+    except Exception as e:
+        print(f"Error parsing task history: {e}")
+        return [] 
+        
 def regenerate(_chatbot, task_history):
     if task_history is None or not isinstance(task_history, list):
         task_history = []