import streamlit as st import openai from text_speech_utils import * # Import the new functions from text_speech_utils.py # Define filenames for audio and conversation output input_audio_filename = 'input.wav' output_audio_filename = 'chatgpt_response.wav' output_conversation_filename = 'ChatGPT_conversation.txt' # Initialize app if 'messages' not in st.session_state: st.session_state['messages'] = [{"role": "system", "content": "You are a helpful assistant."}] # Allow user to input OpenAI API Key via Streamlit text input openai.api_key = st.text_input("Enter your OpenAI API Key", type="password") # Display a warning if API key is not provided if not openai.api_key: st.warning("Please enter your OpenAI API key to proceed.") # UI components st.title("My awesome personal assistant") sec = st.slider("Select number of seconds of recording", min_value=2, max_value=8, value=5) # Record audio + transcribe with Whisper + get GPT-3 response if st.button('Record audio'): if openai.api_key: # Proceed only if API key is provided st.write("Recording...") record_audio(input_audio_filename, sec) transcription = transcribe_audio(input_audio_filename) st.write(f"Me: {transcription['text']}") st.session_state['messages'].append({"role": "user", "content": transcription['text']}) bot = openai.ChatCompletion.create(model="gpt-3.5-turbo", messages=st.session_state['messages']) response = bot.choices[0].message.content st.write(f"GPT: {response}") save_text_as_audio(response, output_audio_filename) play_audio(output_audio_filename) st.session_state['messages'].append({"role": "assistant", "content": response}) else: st.error("API key is required to interact with GPT.") # Function to generate conversation as plain text def generate_conversation_text(messages): conversation_text = "" for message in messages: if message["role"] == "user": conversation_text += f"Me: {message['content']}\n" elif message["role"] == "assistant": conversation_text += f"GPT: {message['content']}\n" elif message["role"] == "system": conversation_text += f"System: {message['content']}\n" return conversation_text # Download conversation button st.download_button( label="Download conversation", data=generate_conversation_text(st.session_state['messages']).encode('utf-8'), file_name=output_conversation_filename, mime="text/plain" )