modified: main.py

main.py

@@ -345,24 +345,30 @@ def run(instruction, add_to_queue=None, send_chat_request_Azure = send_official_
 
 def gradio_interface(query, openai_key, openai_key_azure, api_base,engine):
     # Create a new thread to run the function.
-    if openai_key.startswith('sk') and openai_key_azure == '':
-        print('send_official_call')
-        thread = MyThread(target=run, args=(query, add_to_queue, send_official_call, openai_key))
-    elif openai_key =='' and len(openai_key_azure)>0:
-        print('send_chat_request_Azure')
-        thread = MyThread(target=run, args=(query, add_to_queue, send_chat_request_Azure, openai_key_azure, api_base, engine))
-    thread.start()
+    placeholder_dataframe = pd.DataFrame()
     placeholder_image = np.zeros((100, 100, 3), dtype=np.uint8)  # Create a placeholder image.
-    placeholder_dataframe =  pd.DataFrame()                      #
-
-    # Wait for the result of the calculate function and display the intermediate results simultaneously.
-    while thread.is_alive():
-        while not intermediate_results.empty():
-            yield intermediate_results.get(), placeholder_image,  'Running' , placeholder_dataframe         # Use the yield keyword to return intermediate results in real-time
-        time.sleep(0.1)                                          # Avoid excessive resource consumption.
-
-    finally_text, img, output, df = thread.get_result()
-    yield  finally_text, img, output, df
+    try:
+        if openai_key.startswith('sk') and openai_key_azure == '':
+            print('send_official_call')
+            thread = MyThread(target=run, args=(query, add_to_queue, send_official_call, openai_key))
+        elif openai_key =='' and len(openai_key_azure)>0:
+            print('send_chat_request_Azure')
+            thread = MyThread(target=run, args=(query, add_to_queue, send_chat_request_Azure, openai_key_azure, api_base, engine))
+        thread.start()
+
+                           #
+
+        # Wait for the result of the calculate function and display the intermediate results simultaneously.
+        while thread.is_alive():
+            while not intermediate_results.empty():
+                yield intermediate_results.get(), placeholder_image,  'Running' , placeholder_dataframe         # Use the yield keyword to return intermediate results in real-time
+            time.sleep(0.1)                                          # Avoid excessive resource consumption.
+
+        finally_text, img, output, df = thread.get_result()
+        yield  finally_text, img, output, df
+
+    except Exception as e:
+        yield str(e), placeholder_image, str(e), placeholder_dataframe
     # Return the final result.