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| import streamlit as st | |
| from tempfile import NamedTemporaryFile | |
| from audiorecorder import audiorecorder | |
| from whispercpp import Whisper | |
| from pydub import AudioSegment | |
| import io | |
| # Initialize whisper.cpp | |
| w = Whisper('tiny') | |
| def inference(audio_segment): | |
| # Convert AudioSegment to WAV format in memory | |
| with NamedTemporaryFile(suffix=".wav", delete=False) as temp: | |
| # Export AudioSegment to raw bytes in WAV format | |
| audio_segment.export(temp.name, format="wav") | |
| temp.close() # Ensure the file is written and closed before passing it to Whisper | |
| result = w.transcribe(temp.name) | |
| text = w.extract_text(result) | |
| return text[0] | |
| # Streamlit UI setup | |
| with st.sidebar: | |
| audio = audiorecorder("Click to send voice message", "Recording... Click when you're done", key="recorder") | |
| st.title("Echo Bot with Whisper") | |
| # Initialize chat history | |
| if "messages" not in st.session_state: | |
| st.session_state.messages = [] | |
| # Display chat messages from history on app rerun | |
| for message in st.session_state.messages: | |
| with st.chat_message(message["role"]): | |
| st.markdown(message["content"]) | |
| # React to user input | |
| if (prompt := st.chat_input("Your message")) or len(audio): | |
| # If it's coming from the audio recorder transcribe the message with whisper.cpp | |
| if len(audio) > 0: | |
| # Debugging: Check the type of the audio object | |
| st.write(f"Audio Type: {type(audio)}") | |
| # Handle the case where audio is in a byte format | |
| if isinstance(audio, bytes): | |
| try: | |
| # Convert the raw byte data to an AudioSegment instance | |
| audio_segment = AudioSegment.from_file(io.BytesIO(audio), format="wav") | |
| prompt = inference(audio_segment) | |
| except Exception as e: | |
| st.error(f"Error processing audio: {e}") | |
| prompt = "Sorry, there was an error processing your audio." | |
| # Handle the case where audio is an AudioSegment object | |
| elif isinstance(audio, AudioSegment): | |
| # Process it directly since it's already an AudioSegment | |
| prompt = inference(audio) | |
| else: | |
| st.error("The audio data is not in the expected format.") | |
| prompt = "Sorry, the audio format is not correct." | |
| # Display user message in chat message container | |
| st.chat_message("user").markdown(prompt) | |
| # Add user message to chat history | |
| st.session_state.messages.append({"role": "user", "content": prompt}) | |
| response = f"Echo: {prompt}" | |
| # Display assistant response in chat message container | |
| with st.chat_message("assistant"): | |
| st.markdown(response) | |
| # Add assistant response to chat history | |
| st.session_state.messages.append({"role": "assistant", "content": response}) | |