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[voice] add support for whisper-1 model

master
wanggang 1 年之前
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共有 4 個檔案被更改,包括 13 行新增7 行删除
  1. +3
    -0
      README.md
  2. +4
    -3
      channel/wechat/wechat_channel.py
  3. +1
    -1
      voice/google/google_voice.py
  4. +5
    -3
      voice/openai/openai_voice.py

+ 3
- 0
README.md 查看文件

@@ -72,6 +72,9 @@ cd chatgpt-on-wechat/
pip3 install itchat-uos==1.5.0.dev0
pip3 install --upgrade openai

默认使用openai的whisper-1模型
如果使用百度的语音识别,需要安装百度的pythonSDK
pip3 install baidu-aip
如果使用google的语音识别,需要安装speech_recognition和依赖的ffmpeg和espeak
pip3 install SpeechRecognition
--在MacOS中安装ffmpeg,brew install ffmpeg espeak


+ 4
- 3
channel/wechat/wechat_channel.py 查看文件

@@ -5,6 +5,7 @@ wechat channel
"""

import os
import pathlib
import itchat
import json
from itchat.content import *
@@ -37,11 +38,11 @@ def handler_single_voice(msg):


class WechatChannel(Channel):
tmpFilePath = './tmp/'
tmpFilePath = pathlib.Path('./tmp/')

def __init__(self):
isExists = os.path.exists(self.tmpFilePath)
if not isExists:
pathExists = os.path.exists(self.tmpFilePath)
if not pathExists and conf().get('speech_recognition') == True:
os.makedirs(self.tmpFilePath)

def startup(self):


+ 1
- 1
voice/google/google_voice.py 查看文件

@@ -3,6 +3,7 @@
google voice service
"""

import pathlib
import subprocess
import time
import speech_recognition
@@ -12,7 +13,6 @@ from voice.voice import Voice


class GoogleVoice(Voice):
tmpFilePath = './tmp/'
recognizer = speech_recognition.Recognizer()
engine = pyttsx3.init()



+ 5
- 3
voice/openai/openai_voice.py 查看文件

@@ -4,19 +4,21 @@ google voice service
"""
import json
import openai
from config import conf
from common.log import logger
from voice.voice import Voice


class OpenaiVoice(Voice):
def __init__(self):
pass
openai.api_key = conf().get('open_ai_api_key')

def voiceToText(self, voice_file):
logger.debug(
'[Openai] voice file name={}'.format(voice_file))
file = open(voice_file, "rb")
reply = openai.Audio.transcribe("whisper-1", file)
json_dict = json.loads(reply)
text = json_dict['text']
text = reply["text"]
logger.info(
'[Openai] voiceToText text={} voice file name={}'.format(text, voice_file))
return text


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