Update app.py

app.py

@@ -158,6 +158,22 @@ class TimeoutException(Exception):
 def alarm_handler(signum, frame):
     raise TimeoutException("Timed out!")
 
+# Define the function that will be called when the user submits its feedback (to be called in Gradio)
+def save_feedback(user_input:str, context_for_query: str, prediction:str) -> None:
+    """
+    Append input/outputs and user feedback to a JSON Lines file using a thread lock to avoid concurrent writes from different users.
+    """
+    with scheduler.lock:
+        with log_file.open("a") as f:
+            f.write(json.dumps({"user_input": user_input,"retrieved_context": context_for_query,"model_response": prediction}))
+            f.write("\n")
+
+# json_data = {
+ #               "user_input": user_input,
+  #              "retrieved_context": context_for_query,
+   #             "model_response": prediction
+    #            }
+
 
 # Initialize conversation history
 conversation_history = []
@@ -225,22 +241,6 @@ def predict(user_input, timeout_seconds=1800): # 30 minutes = 1800 seconds
     # While the prediction is made, log boh the inputs and outputs to a local log file
     # while writing to the log file, ensure that the commit scheduler is locked to avoid parallel
     # access
-    
-    json_data = {
-                "user_input": user_input,
-                "retrieved_context": context_for_query,
-                "model_response": prediction
-                }
-    
-        with scheduler.lock:
-            with log_file.open("a") as f:
-                try:
-                    #json.dump(json_data, f)
-                    f.write(json.dumps(json_data))
-                    f.write("\n")
-                except TypeError as e:
-                    logger.error(f"Failed to serialize JSON: {str(e)}")
-                    raise
 
     return prediction
 
@@ -256,5 +256,7 @@ demo = gr.Interface(
     concurrency_limit=16
 )
 
+save_feedback()
+
 demo.queue()
 demo.launch(share=True)