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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:
# Convert audio (from audiorecorder) to AudioSegment
audio_segment = AudioSegment.from_file(io.BytesIO(audio), format="wav")
prompt = inference(audio_segment)
# 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})
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