File size: 2,691 Bytes
42f5a8f | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 | import os
import pyaudio
import streamlit as st
from langchain.memory import ConversationBufferMemory
from utils import record_audio_chunk, transcribe_audio, get_response_llm, play_text_to_speech, load_whisper
from groq import Groq
model = load_whisper()
chunk_file = os.path.dirname(__file__) + "/temp_audio_chunk.wav"
groq_api_key = os.getenv("GROQ_API_KEY")
client = Groq(api_key = groq_api_key)
def main():
groq_api_key = os.getenv("GROQ_API_KEY")
client = Groq(api_key = groq_api_key)
chunk_file = os.path.dirname(__file__) + "/temp_audio_chunk.wav"
st.markdown('<h1 style="color: darkblue;">AI Voice Assistant️</h1>', unsafe_allow_html=True)
memory = ConversationBufferMemory(memory_key="chat_history")
if st.button("Start Recording"):
while True:
# Audio Stream Initialization
audio = pyaudio.PyAudio()
stream = audio.open(format=pyaudio.paInt16, channels=1, rate=16000, input=True, frames_per_buffer=1024)
# Record and save audio chunk
record_audio_chunk(audio, stream)
text = 'hi'
with open(chunk_file, "rb") as file:
transcription = client.audio.transcriptions.create(
file=(chunk_file, file.read()),
model="whisper-large-v3",
prompt="Specify context or spelling", # Optional
response_format="json", # Optional
language="en", # Optional
temperature=0.0 # Optional
)
text = transcription.text
if text is not None:
with st.chat_message("Customer"):
st.write("Customer 👤"+text)
# st.markdown(
# f'<div style="background-color: #f0f0f0; padding: 10px; border-radius: 5px;">Customer 👤: {text}</div>',
# unsafe_allow_html=True)
os.remove(chunk_file)
response_llm = get_response_llm(user_question=text, memory=memory)
with st.chat_message("AI"):
st.write("AI Assistant 🤖"+response_llm)
# st.markdown(
# f'<div style="background-color: #f0f0f0; padding: 10px; border-radius: 5px;">AI Assistant 🤖: {response_llm}</div>',
# unsafe_allow_html=True)
play_text_to_speech(text=response_llm)
else:
stream.stop_stream()
stream.close()
audio.terminate()
break # Exit the while loop
print("End Conversation")
if __name__ == "__main__":
main() |