Update app.py

app.py

@@ -1,23 +1,14 @@
-import streamlit as st
-from responser import responsr
-from gtts import gTTS
-from io import BytesIO
-
 import streamlit as st
 from responser import responsr
 from gtts import gTTS
 from io import BytesIO
 import whisper
-import pyaudio
+import sounddevice as sd
 import numpy as np
-import time
 
 # Load Whisper model
 whisper_model = whisper.load_model("base")
 
-# Initialize PyAudio
-p = pyaudio.PyAudio()
-
 # Function to convert text to speech and return audio file
 def text_to_speech(text):
     tts = gTTS(text)
@@ -28,15 +19,11 @@ def text_to_speech(text):
 
 # Function to record audio from the microphone
 def record_audio(duration=5, fs=16000):
-    stream = p.open(format=pyaudio.paInt16, channels=1, rate=fs, input=True, frames_per_buffer=1024)
-    frames = []
-    for _ in range(int(fs / 1024 * duration)):
-        data = stream.read(1024)
-        frames.append(data)
-    stream.stop_stream()
-    stream.close()
-    audio_data = b''.join(frames)
-    return np.frombuffer(audio_data, dtype=np.int16)
+    st.write("Recording...")
+    audio_data = sd.rec(int(duration * fs), samplerate=fs, channels=1, dtype='int16')
+    sd.wait()  # Wait until recording is finished
+    st.write("Recording complete.")
+    return audio_data.flatten()
 
 # Function to recognize speech using Whisper
 def recognize_speech(audio_data):
@@ -69,7 +56,6 @@ def main():
 
     # Button to record audio input
     if st.button('Record Audio'):
-        st.write("Recording...")
         audio_data = record_audio(duration=5)  # Adjust duration as needed
         st.write("Processing...")
         user_input = recognize_speech(audio_data)
@@ -107,6 +93,3 @@ def main():
 
 if __name__ == "__main__":
     main()
-
-
-