interviewer / api /audio.py
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Huge refactoring
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import io
import wave
import requests
from openai import OpenAI
def numpy_audio_to_bytes(audio_data):
sample_rate = 44100
num_channels = 1
sampwidth = 2
buffer = io.BytesIO()
with wave.open(buffer, "wb") as wf:
wf.setnchannels(num_channels)
wf.setsampwidth(sampwidth)
wf.setframerate(sample_rate)
wf.writeframes(audio_data.tobytes())
return buffer.getvalue()
class STTManager:
def __init__(self, config):
self.config = config
def speech_to_text(self, audio, convert_to_bytes=True):
if convert_to_bytes:
audio = numpy_audio_to_bytes(audio[1])
if self.config.stt.type == "OPENAI_API":
data = ("temp.wav", audio, "audio/wav")
client = OpenAI(base_url=self.config.stt.url, api_key=self.config.stt.key)
transcription = client.audio.transcriptions.create(model=self.config.stt.name, file=data, response_format="text")
elif self.config.stt.type == "HF_API":
headers = {"Authorization": "Bearer " + self.config.stt.key}
transcription = requests.post(self.config.stt.url, headers=headers, data=audio)
transcription = transcription.json()["text"]
return transcription
class TTSManager:
def __init__(self, config):
self.config = config
def text_to_speech(self, text):
if self.config.tts.type == "OPENAI_API":
client = OpenAI(base_url=self.config.tts.url, api_key=self.config.tts.key)
response = client.audio.speech.create(model=self.config.tts.name, voice="alloy", response_format="opus", input=text)
elif self.config.tts.type == "HF_API":
headers = {"Authorization": "Bearer " + self.config.tts.key}
response = requests.post(self.config.tts.url, headers=headers)
return response.content
def read_last_message(self, chat_display):
if chat_display:
last_message = chat_display[-1][1] # Assuming the message is stored at index 1 of the last tuple/list in chat_display
if last_message is not None:
return self.text_to_speech(last_message)
return None