Update app.py

app.py

@@ -16,7 +16,9 @@ tokenizer = GPT2Tokenizer.from_pretrained('gpt2-medium')
 model = openai.api_key = os.environ["OAPI_KEY"]
 
 # Define the initial message and messages list
-initial_message = {"role": "system", "content": 'You are a USMLE Tutor. Respond with ALWAYS layered "bullet points" (listing rather than sentences) to all input with a fun mneumonics to memorize that list. But you can answer up to 1200 words if the user requests longer response.'}
+initial_message = {"role": "system", "content": 'You are a USMLE Tutor. Respond with ALWAYS layered "bullet points" (listing rather than sentences) \
+                   to all input with a fun mneumonics to memorize that list. But you can answer up to 1200 words if the user requests longer response. \
+                    You are going to keep answer and also challenge the student to learn renal phsysiology.'}
 messages = [initial_message]
 
 # Define the answer counter
@@ -118,7 +120,7 @@ def transcribe(audio, text):
     notion_df.upload(df, 'https://www.notion.so/YENA-be569d0a40c940e7b6e0679318215790?pvs=4', title=str(published_date), api_key=API_KEY)
 
     # Return the chat transcript
-    return system_message
+    return system_message['content']
     
 # Define the input and output components for Gradio
 audio_input = Audio(source="microphone", type="filepath", label="Record your message")
@@ -132,7 +134,7 @@ iface = gr.Interface(
     inputs=[audio_input, text_input],
     outputs=[output_text],
     title="Your Excellence Never Abates (YENA)",
-    description="Talk to the AI Tutor YENA",
+    description="Talk to the AI Renal Tutor YENA",
     theme="compact",
     layout="vertical",
     allow_flagging=False