Update app.py

app.py

@@ -107,7 +107,6 @@ def transcribe(audio, text):
     )["choices"][0]["message"]
 
 
-
     # Add the system message to the messages list
     messages.append({"role": "system", "content": system_message})
 
@@ -119,35 +118,18 @@ def transcribe(audio, text):
     
     # Append the number of tokens used to the end of the chat transcript
     num_tokens = num_tokens_from_messages(messages)
-    chat_transcript += f"Number of tokens used: {num_tokens}\n\n"
     
     # Get the current time in Eastern Time (ET)
     now_et = datetime.now(timezone(timedelta(hours=-5)))
     # Format the time as string (YY-MM-DD HH:MM)
     published_date = now_et.strftime('%m-%d-%y %H:%M')
+    chat_transcript_copy = chat_transcript
+    chat_transcript_copy += f"Number of tokens used: {num_tokens}\n\n"
     
     # Upload the chat transcript to Notion
-    df = pd.DataFrame([chat_transcript])
+    df = pd.DataFrame([chat_transcript_copy])
     notion_df.upload(df, 'https://www.notion.so/personal-5e3978680ca848bda844452129955138?pvs=4', title=str(published_date), api_key=API_KEY)
     
-    # Reset the messages list and answer counter if the token limit is exceeded
-    if num_tokens > 2096:
-        messages = [initial_message]
-        answer_count = 0
-    else:
-        # Increment the answer counter
-        answer_count += 1
-    
-    # Generate the system message using the OpenAI API
-    system_message = openai.Completion.create(
-        engine="text-davinci-002",
-        prompt=[{"text": f"{message['role']}: {message['content']}\n\n"} for message in messages],
-        temperature=0.7,
-        max_tokens=2000,
-        n=1,
-        stop=None,
-    )[0]["text"]
-    
     # Add the system message to the messages list
     messages.append({"role": "system", "content": system_message})