Update app.py

app.py

@@ -18,6 +18,7 @@ model = openai.api_key = os.environ["OPENAI_API_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.'}
 messages = [initial_message]
+messages_rev = [initial_message]
 
 # Define the answer counter
 answer_count = 0
@@ -29,6 +30,9 @@ def transcribe(audio, text):
     global messages
     global answer_count
 
+    transcript = {'text': ''} 
+    input_text = []
+    
     # Transcribe the audio if provided
     if audio is not None:
         audio_file = open(audio, "rb")
@@ -58,10 +62,11 @@ def transcribe(audio, text):
                 break
         # Decode the input tokens into text
         input_text = tokenizer.decode(input_tokens)
-    
         # Add the input text to the messages list
         # messages.append({"role": "user", "content": input_text})
 
+    # Add the input text to the messages list
+    messages.append({"role": "user", "content": transcript["text"]+input_text})
 
     # Check if the accumulated tokens have exceeded 2096
     num_tokens = sum(len(tokenizer.encode(message["content"])) for message in messages)
@@ -102,13 +107,12 @@ def transcribe(audio, text):
     # messages.append(system_message)
 
     # Add the system message to the beginning of the messages list
-    messages.insert(0, system_message)
+    messages_rev.insert(0, system_message)
     # Add the input text to the messages list
-    messages.insert(0, {"role": "user", "content": input_text + transcript["text"]})
-
+    messages_rev.insert(0, {"role": "user", "content": input_text + transcript["text"]})
     
     # Concatenate the chat history
-    chat_transcript = "\n\n".join([f"[ANSWER {answer_count}]{message['role']}: {message['content']}" for message in messages if message['role'] != 'system'])
+    chat_transcript = "\n\n".join([f"[ANSWER {answer_count}]{message['role']}: {message['content']}" for message in messages_rev if message['role'] != 'system'])
     
     # 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"