erp_core/asr_and_tts.py

import os
# from dotenv import load_dotenv
import tempfile
import scipy.io.wavfile as wavfile
from openai import OpenAI
# from elevenlabs import ElevenLabs, VoiceSettings, play, stream

# Load API keys from .env file
# load_dotenv(override=True)
openai_api_key = os.getenv('OPENAI_API_KEY')
# elevenlabs_api_key = os.getenv('ELEVENLABS_API_KEY')

# Initialize clients
openai_client = OpenAI()
# elevenlabs_client = ElevenLabs(api_key=elevenlabs_api_key)

# Function to transcribe audio using OpenAI Whisper API
def transcribe(audio):
    if audio is None:
        return "No audio provided.", None
    
    # Audio is received as a tuple (sample_rate, audio_data)
    sample_rate, audio_data = audio
    
    # Save the audio data to a temporary file
    with tempfile.NamedTemporaryFile(suffix=".wav", delete=False) as temp_file:
        wavfile.write(temp_file.name, sample_rate, audio_data)
        temp_file_path = temp_file.name

    # Transcribe the audio file using OpenAI Whisper API
    with open(temp_file_path, "rb") as audio_file:
        transcription_response = openai_client.audio.transcriptions.create(
            model="whisper-1", 
            file=audio_file,
        )
    
    transcription_text = transcription_response.text
    return transcription_text

def tts(response_text):
    # Now, use ElevenLabs to convert the transcription text to speech
    # tts_response = elevenlabs_client.text_to_speech.convert(
    #     voice_id="CwhRBWXzGAHq8TQ4Fs17",
    #     optimize_streaming_latency="0",
    #     output_format="mp3_22050_32",
    #     text=response_text,
    #     voice_settings=VoiceSettings(
    #         stability=0.1,
    #         similarity_boost=0.3,
    #         style=0.2,
    #     ),
    # )
    
    # audio_file_path = "output_audio.mp3"
    # with open(audio_file_path, "wb") as audio_file:
    #     for chunk in tts_response:
    #         audio_file.write(chunk)
    
    # return audio_file_path

    tts_client = OpenAI()

    response = tts_client.audio.speech.create(
        model="tts-1",
        voice="onyx",
        input=response_text,
    )
    # file_path = "output.mp3"
    # if os.path.exists(file_path):
    # # Delete the file
    #     os.remove(file_path)
    response.stream_to_file("output.mp3")
    return "output.mp3"