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obi-chatgpt-voice.py
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obi-chatgpt-voice.py
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import pyaudio, wave, datetime, whisper, openai, time
import ffmpeg
import pvporcupine
import struct
import math
from pydub import AudioSegment
from pydub.playback import play
import simpleaudio as sa
import threading
openai.api_key = #OPENAI_API_KEY
porcupine = pvporcupine.create(
access_key= #PORCUPINE_ACCESS_KEY,
keyword_paths=['Hey-Obi_en_mac_v2_2_0.ppn'],
sensitivities = [0.5]
)
participantid = input("Enter the participant's ID: ")
ct = datetime.datetime.now()
LOG_FILE_PATH = f"obi-logs/{participantid}_{ct}.txt"
TEMPERATURE = 0.1
pa = pyaudio.PyAudio()
channels = 1
sample_format = pyaudio.paInt16
fs = porcupine.sample_rate
mic_num = 0
audio_stream = pa.open(
rate=fs,
channels=channels,
format=sample_format,
input=True,
frames_per_buffer=porcupine.frame_length,
input_device_index=mic_num)
def sound_play_threading(sound):
wave_obj = sa.WaveObject.from_wave_file(sound)
play_obj = wave_obj.play()
def get_chatgpt_code(messages):
begintime = time.time()
completion = openai.ChatCompletion.create(
model="gpt-3.5-turbo-0613",
temperature=TEMPERATURE,
messages=messages
)
elapsedtime = time.time() - begintime
output = completion.choices[0].message.content
messages.append({"role": "assistant", "content": output})
with open(LOG_FILE_PATH, 'a') as f:
f.write(f'ChatGPT Response Time: {elapsedtime}\nChatGPT: {output}\n\n\n')
print("ChatGPT Response Time: " + str(elapsedtime))
print("ChatGPT: " + output)
mod_output = output.replace("import obirobot", "")
if '```' in mod_output:
mod_output = mod_output.split('```')[1]
mod_output = mod_output.replace("python", "")
with open('obi-code.txt', 'a') as f:
f.write(mod_output)
print()
def process_frames(frames):
ct = datetime.datetime.now()
RECORDING_FILE_PATH = f"voice-recordings/{ct}.wav"
print('Finished recording.')
sound_file = "sounds_wav/processing.wav"
sound_play_threading(sound_file)
#play(sound)
transcription_begintime = time.time()
# Save the recorded data as a WAV file
wf = wave.open(RECORDING_FILE_PATH, 'wb')
wf.setnchannels(channels)
wf.setsampwidth(pa.get_sample_size(sample_format))
wf.setframerate(fs)
wf.writeframes(b''.join(frames))
wf.close()
model = whisper.load_model("base.en")
result = model.transcribe(RECORDING_FILE_PATH, fp16=False)["text"]
transcription_elapsedtime = time.time() - transcription_begintime
print("Transcription Time: " + str(transcription_elapsedtime))
print("You: " + result)
print()
return result
with open('obi-prompt.txt', 'r') as f:
file_contents = f.read()
with open(LOG_FILE_PATH, 'w') as f:
f.write(f'System: {file_contents} \n\nTemp: {TEMPERATURE} \n\n\n')
messages = [{"role": "system", "content": file_contents}]
recording = False
SHORT_NORMALIZE = (1.0/32768.0)
swidth = 2
def rms(frame):
count = len(frame)/swidth
format = "%dh"%(count)
# short is 16 bit int
shorts = struct.unpack( format, frame )
sum_squares = 0.0
for sample in shorts:
n = sample * SHORT_NORMALIZE
sum_squares += n*n
# compute the rms
rms = math.pow(sum_squares/count,0.5)
return rms * 1000
if __name__ == "__main__":
audio_stream.start_stream()
mic_silence_value = 4 #TODO: change
print()
print("Current set mic silence value:", mic_silence_value)
current_mic_value = round(rms(audio_stream.read(1024)),2)
print("Current silence value (assuming no one talking):", current_mic_value)
print()
print()
print("READY")
try:
while True:
data = audio_stream.read(porcupine.frame_length)
pcm = struct.unpack_from("h" * porcupine.frame_length, data)
keyword_index = porcupine.process(pcm)
if keyword_index == 0:
sound_file = "sounds_wav/heyobi-beep.wav"
sound_play_threading(sound_file)
data = audio_stream.read(1024)
threshold = mic_silence_value*2
print()
print('detected obi')
print("Silence Threshold:", threshold)
print()
frames = []
timeout_started = False
timeout_start_time = time.time()
threshold_timeout = 1.5 #second
passed_initial_threshold = 0 #0 is false, 1 is true
passed_initial_threshold_start_time = 0
passed_initial_threshold_timeout = 0.2
passed_initial_threshold_started = False
while True:
last_data = data
data = audio_stream.read(1024)
print("Noise Level:", round(rms(data),2), threshold)
if rms(data) > threshold and passed_initial_threshold == 0 and passed_initial_threshold_started == False:
passed_initial_threshold_start_time = time.time()
#passed_initial_threshold = 1
frames.append(last_data)
frames.append(data)
print("passed initial threshold")
passed_initial_threshold_started = True
elif passed_initial_threshold_started == True:
if rms(data) < threshold:
frames = []
passed_initial_threshold = 0
passed_initial_threshold_started = False
elif time.time()-passed_initial_threshold_start_time < passed_initial_threshold_timeout:
frames.append(data)
print(time.time()-passed_initial_threshold_start_time)
else:
passed_initial_threshold = 1
frames.append(data)
print("passed initial threshold")
passed_initial_threshold_started = False
elif passed_initial_threshold == 1:
if timeout_started == True and time.time()-timeout_start_time > threshold_timeout:
frames.append(data)
print("ended")
break
elif rms(data) < threshold and timeout_started == False:
timeout_start_time = time.time()
print("started")
timeout_started = True
frames.append(data)
elif rms(data) < threshold and timeout_started == True:
frames.append(data)
print("Time Elapsed since Silence started:", time.time()-timeout_start_time)
else:
frames.append(data)
timeout_start_time = time.time()
timeout_started = False
else:
print("Waiting for person to speak")
audio_stream.stop_stream()
#audio_stream.close()
chatgpt_input = process_frames(frames)
with open(LOG_FILE_PATH, 'a') as f:
f.write(f'User: {chatgpt_input}\n\n\n')
messages.append({"role": "user", "content": chatgpt_input})
get_chatgpt_code(messages)
audio_stream.start_stream()
except KeyboardInterrupt:
with open('obi-code.txt', 'w') as f:
f.write('SYSTEM_TERMINATE()')
pass
pa.terminate()