Update app.py

app.py

@@ -1,6 +1,8 @@
 import os
 import openai
 import gradio as gr
+import time
+from ftr import warn
 
 # Set up password
 username = os.getenv('username')
@@ -26,20 +28,24 @@ def chat_with_assistant(message, history):
         role="user",
         content=message
     )
-
-    # Run the assistant with streaming
-    response = client.chat.completions.create(
-        model='gpt-4o-mini',
-        messages=[{'role': 'user', 'content': message}],
-        stream=True
+    
+    # Run the assistant
+    run = client.beta.threads.runs.create(
+        thread_id=thread.id,
+        assistant_id=assistant_id
     )
     
-    # Handle the streaming response
-    response_text = ""
-    for chunk in response:
-        if hasattr(chunk.choices[0].delta, 'content'):
-            response_text += chunk.choices[0].delta.content
-            yield response_text
+    # Wait for the assistant's response
+    while True:
+        run_status = client.beta.threads.runs.retrieve(thread_id=thread.id, run_id=run.id)
+        if run_status.status == 'completed':
+            # Retrieve the assistant's response
+            messages = client.beta.threads.messages.list(thread_id=thread.id)
+            assistant_response = messages.data[0].content[0].text.value
+            break
+        time.sleep(1)
+    
+    return assistant_response
 
 # Custom CSS for chat bubbles and colors
 custom_css = """
@@ -49,7 +55,7 @@ custom_css = """
 
 # Create the Gradio interface
 with gr.Blocks(css=custom_css) as demo:
-    gr.HTML(f"""<img src = "https://i.postimg.cc/L6mbcC7F/DASH.png" width="150" height="112">""")
+    gr.HTML(f"""<img src="https://i.postimg.cc/L6mbcC7F/DASH.png" width="150" height="112">""")
     gr.Markdown("# **Learning Scales Assistant**🐬")
     chatbot = gr.Chatbot(
         [],
@@ -67,14 +73,14 @@ with gr.Blocks(css=custom_css) as demo:
 
     def bot(history):
         user_message = history[-1][0]
-        bot_message = ""
-        for response_text in chat_with_assistant(user_message, history):
-            history[-1][1] = response_text
-            chatbot.update(history)
+        bot_message = chat_with_assistant(user_message, history)
+        history[-1][1] = bot_message
         return history
 
     msg.submit(user, [msg, chatbot], [msg, chatbot], queue=False).then(
         bot, chatbot, chatbot
     )
+    gr.Markdown(warn)
 
 demo.launch(auth=(username, password))
+