Update app.py

app.py

@@ -26,8 +26,8 @@ import urllib.request
 import sqlite3
 import pandas as pd
 import pandasql as ps
-import pyaudio
-import wave
+import sounddevice as sd
+import soundfile as sf
 
 
 def clean(value):
@@ -253,43 +253,46 @@ def g_sheet_log(myinput, output):
   ).execute()
 
 openai.api_key = st.secrets["OPENAI_KEY"]
-RATE = 44100
-CHANNELS = 1
-FORMAT = pyaudio.paInt16
-CHUNK = 1024
-RECORD_SECONDS = 5
+duration = 5
+fs = 44100
+channels = 1
+filename = "output.wav"
 
 def record_audio():
-    p = pyaudio.PyAudio()
-
-    # Open the microphone stream
-    stream = p.open(format=FORMAT,
-                    channels=CHANNELS,
-                    rate=RATE,
-                    input=True,
-                    frames_per_buffer=CHUNK)
-
-    # Record the audio
-    frames = []
-    for i in range(0, int(RATE / CHUNK * RECORD_SECONDS)):
-        data = stream.read(CHUNK)
-        frames.append(data)
-
-    # Close the microphone stream
-    stream.stop_stream()
-    stream.close()
-    p.terminate()
-
-    # Save the recorded audio to a WAV file
-    wf = wave.open("output.mp3", "wb")
-    wf.setnchannels(CHANNELS)
-    wf.setsampwidth(p.get_sample_size(FORMAT))
-    wf.setframerate(RATE)
-    wf.writeframes(b"".join(frames))
-    wf.close()
-
-    # Return the path to the recorded audio file
-    return "output.mp3"
+    myrecording = sd.rec(int(duration * fs), samplerate=fs, channels=channels)
+    sd.wait()
+    sf.write(filename, myrecording, fs)
+    return filename
+    # p = pyaudio.PyAudio()
+
+    # # Open the microphone stream
+    # stream = p.open(format=FORMAT,
+    #                 channels=CHANNELS,
+    #                 rate=RATE,
+    #                 input=True,
+    #                 frames_per_buffer=CHUNK)
+
+    # # Record the audio
+    # frames = []
+    # for i in range(0, int(RATE / CHUNK * RECORD_SECONDS)):
+    #     data = stream.read(CHUNK)
+    #     frames.append(data)
+
+    # # Close the microphone stream
+    # stream.stop_stream()
+    # stream.close()
+    # p.terminate()
+
+    # # Save the recorded audio to a WAV file
+    # wf = wave.open("output.mp3", "wb")
+    # wf.setnchannels(CHANNELS)
+    # wf.setsampwidth(p.get_sample_size(FORMAT))
+    # wf.setframerate(RATE)
+    # wf.writeframes(b"".join(frames))
+    # wf.close()
+
+    # # Return the path to the recorded audio file
+    # return "output.mp3"
 
 
 def openai_response(PROMPT):
@@ -625,6 +628,7 @@ elif Usage == 'Random Questions':
                 transcription = openai.Audio.transcribe("whisper-1", file)
                 result = transcription["text"]
                 st.write(f"Fetched from audio - {result}")
+                
                 question = result
                 response = openai.Completion.create(
                 model="text-davinci-003",