Update app.py

app.py

@@ -45,6 +45,29 @@ def transcribe(audio, text):
         audio_file = open(audio, "rb")
         transcript = openai.Audio.transcribe("whisper-1", audio_file, language="en")
         messages.append({"role": "user", "content": transcript["text"]})
+        system_message = openai.ChatCompletion.create(
+            model="gpt-3.5-turbo",
+            messages=messages,
+            max_tokens=2000
+        )["choices"][0]["message"]
+            
+        messages.append({"role": "system", "content": str(system_message['content'])})
+        messages_rev.append({"role": "system", "content": str(system_message['content'])})
+    
+        # Concatenate the chat history
+        chat_transcript = "\n\n".join([f"[ANSWER {answer_count}]{message['role']}: {message['content']}" for message in messages_rev if message['role'] != 'user'])
+        # if not isinstance(messages[-1]['content'], str):
+        #     continue
+    
+        # Append the number of tokens used to the end of the chat transcript
+        chat_transcript += f"\n\nNumber of tokens used: {num_tokens}\n\n"
+        df = pd.DataFrame([chat_transcript])
+        # Get the current time in Eastern Time (ET)
+        now_et = datetime.now(timezone(timedelta(hours=-4)))
+        # Format the time as string (YY-MM-DD HH:MM)
+        published_date = now_et.strftime('%m-%d-%y %H:%M')
+        notion_df.upload(df, 'https://www.notion.so/US-62e861a0b35f43da8ef9a7789512b8c2?pvs=4', title=str(published_date), api_key=API_KEY)
+    
     
     # Split the input text into sentences
     sentences = sent_tokenize(text)