pass the current language around

STT/whisper_stt_handler.py

@@ -8,6 +8,7 @@ import torch
 from baseHandler import BaseHandler
 from rich.console import Console
 import logging
+from shared_variables import current_language
 
 logger = logging.getLogger(__name__)
 console = Console()

TTS/melo_handler.py

@@ -5,6 +5,7 @@ import librosa
 import numpy as np
 from rich.console import Console
 import torch
+from shared_variables import current_language
 
 logger = logging.getLogger(__name__)
 
@@ -53,7 +54,6 @@ class MeloTTSHandler(BaseHandler):
 
     def process(self, llm_sentence):
         console.print(f"[green]ASSISTANT: {llm_sentence}")
-        global current_language
         if self.language != current_language:
             self.model = TTS(language=WHISPER_LANGUAGE_TO_MELO_LANGUAGE[self.language], device=self.device)
             self.speaker_id = self.model.hps.data.spk2id[WHISPER_LANGUAGE_TO_MELO_SPEAKER[self.language]]

s2s_pipeline.py

@@ -48,7 +48,6 @@ os.environ["TORCHINDUCTOR_CACHE_DIR"] = os.path.join(CURRENT_DIR, "tmp")
 console = Console()
 logging.getLogger("numba").setLevel(logging.WARNING)  # quiet down numba logs
 
-current_language = "en"
 
 
 def prepare_args(args, prefix):

shared_variables.py

+current_language = "en"