49 lines
1.2 KiB
Python
49 lines
1.2 KiB
Python
from ahserver.serverenv import ServerEnv
|
|
from appPublic.worker import awaitify
|
|
from appPublic.log import info, debug, warning, error, exception, critical
|
|
|
|
from ahserver.globalEnv import get_definition
|
|
import numpy as np
|
|
import base64
|
|
import whisper
|
|
|
|
# 编码
|
|
def base64_encode(text):
|
|
text_bytes = text.encode('utf-8')
|
|
encoded_bytes = base64.b64encode(text_bytes)
|
|
encoded_text = encoded_bytes.decode('utf-8')
|
|
return encoded_text
|
|
|
|
# 解码
|
|
def base64_decode(encoded_text):
|
|
encoded_bytes = encoded_text.encode('utf-8')
|
|
decoded_bytes = base64.b64decode(encoded_bytes)
|
|
decoded_text = decoded_bytes.decode('utf-8')
|
|
return decoded_text
|
|
|
|
class WhisperBase:
|
|
def __init__(self):
|
|
model_name = get_definition('whisper_model')
|
|
self.model = whisper.load_model(model_name)
|
|
|
|
def _stt(self, filepath):
|
|
e = Exception(f'{filepath=} WhisperBase can not use')
|
|
exception(f'{e=}')
|
|
raise e
|
|
|
|
|
|
class WhisperFile(WhisperBase):
|
|
def _stt(self, filepath):
|
|
return self.model.transcribe(filepath)
|
|
|
|
stt = awaitify(_stt)
|
|
|
|
class WhisperBase64(WhisperBase):
|
|
def _stt(self, audio_base64):
|
|
raw = base64_decode(audio_base64)
|
|
ndarr = np.frombuffer(raw, dtype=np.float32)
|
|
info(f'ndarr={ndarr}')
|
|
return self.model.transcribe(ndarr)
|
|
|
|
stt = awaitify(_stt)
|