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| import base64 | |
| import os | |
| import openai | |
| import streamlit as st | |
| from audio_recorder_streamlit import audio_recorder | |
| from utils.helper import * | |
| # API KEY | |
| st.set_page_config(layout="wide") | |
| api_key = os.environ["OPENAI_API_KEY"] | |
| # Initialize the ChatBot with the OpenAI API key and a protocol. | |
| assistant = ChatBot( | |
| api_key=api_key, | |
| protocol=""" | |
| You are a helpful assistant. | |
| """, | |
| ) | |
| # Set the title of the Streamlit app | |
| st.title("Voice Command Here") | |
| # Initialize session state for conversation history | |
| if "history" not in st.session_state: | |
| st.session_state.history = [] | |
| # Create two columns | |
| col1, col2 = st.columns(2) | |
| # Column 1: Audio control and playback | |
| with col1: | |
| # Set the initial status to "recording" | |
| status = "recording" | |
| # Record audio from the user | |
| audio_bytes = audio_recorder( | |
| text="Click here to record!", | |
| recording_color="#e8b62c", | |
| neutral_color="#6aa36f", | |
| icon_name="user", | |
| icon_size="6x", | |
| ) | |
| with st.expander("Expand/collapse to listen to your own audio:"): | |
| if audio_bytes: | |
| # If audio is recorded, play the audio in the app | |
| st.audio(audio_bytes, format="audio/wav") | |
| # Define the filename for the recorded audio | |
| some_string = generate_random_string() | |
| audio_file = f"audio_{some_string}.wav" | |
| # Save the recorded audio to a file | |
| status = "" | |
| with open(audio_file, "wb") as f: | |
| try: | |
| f.write(audio_bytes) | |
| status = "Recording saved successfully." | |
| st.success("Success.") # Notify the user that the audio has been saved | |
| except: | |
| st.warning( | |
| "Please record audio." | |
| ) # Warn the user if the audio could not be saved | |
| if len(status) > 1: | |
| # If the audio file has been saved successfully | |
| # Open the saved audio file for reading | |
| audio_file = open(audio_file, "rb") | |
| # Transcribe the audio using OpenAI's Whisper model | |
| transcript = assistant.client.audio.transcriptions.create( | |
| model="whisper-1", file=audio_file | |
| ) | |
| # Extract the transcribed text | |
| prompt = transcript.text | |
| # Add user input to session state history | |
| st.session_state.history.append(f"🤔 User: {prompt}") | |
| # Generate a response from the assistant using the transcribed text | |
| response = assistant.generate_response(prompt) | |
| # Add assistant response to session state history | |
| st.session_state.history.append(f"🤖 Bot: {response}") | |
| try: | |
| # Clear existing audio elements | |
| st.empty() | |
| # Convert the assistant's response to speech using OpenAI's TTS model | |
| response_voice = assistant.client.audio.speech.create( | |
| model="tts-1", voice="alloy", input=response | |
| ) | |
| # Define the filename for the generated speech | |
| some_string_out = generate_random_string() | |
| speech_file_path = f"output_{some_string_out}.mp3" | |
| # Save the generated speech to a file | |
| response_voice.write_to_file(speech_file_path) | |
| # Play the generated speech in the app | |
| autoplay_audio(speech_file_path) | |
| st.success( | |
| "Autoplay attempted." | |
| ) # Notify the user that autoplay was attempted | |
| except: | |
| st.error( | |
| "No response file found." | |
| ) # Display an error if the response file could not be found | |
| # Column 2: Display conversation history | |
| with col2: | |
| st.header("Conversation History") | |
| for entry in st.session_state.history: | |
| st.markdown(entry) | |