mirror of
https://github.com/zhayujie/chatgpt-on-wechat.git
synced 2026-03-20 05:51:55 +08:00
@@ -110,6 +110,7 @@ pip3 install --upgrade tiktoken
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"image_create_prefix": ["画", "看", "找"], # 开启图片回复的前缀
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"conversation_max_tokens": 1000, # 支持上下文记忆的最多字符数
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"speech_recognition": false, # 是否开启语音识别
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"group_speech_recognition": false, # 是否开启群组语音识别 (目前仅支持wechaty)
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"use_azure_chatgpt": false, # 是否使用Azure ChatGPT service代替openai ChatGPT service. 当设置为true时需要设置 open_ai_api_base,如 https://xxx.openai.azure.com/
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"character_desc": "你是ChatGPT, 一个由OpenAI训练的大型语言模型, 你旨在回答并解决人们的任何问题,并且可以使用多种语言与人交流。", # 人格描述,
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}
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@@ -130,8 +131,9 @@ pip3 install --upgrade tiktoken
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**3.语音识别**
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+ 添加 `"speech_recognition": true` 将开启语音识别,默认使用openai的whisper模型识别为文字,同时以文字回复,目前只支持私聊 (注意由于语音消息无法匹配前缀,一旦开启将对所有语音自动回复);
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+ 添加 `"voice_reply_voice": true` 将开启语音回复语音,但是需要配置对应语音合成平台的key,由于itchat协议的限制,只能发送语音mp3文件,若使用wechaty则回复的是微信语音。
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+ 添加 `"speech_recognition": true` 将开启语音识别,默认使用openai的whisper模型识别为文字,同时以文字回复,该参数仅支持私聊 (注意由于语音消息无法匹配前缀,一旦开启将对所有语音自动回复);
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+ 添加 `"group_speech_recognition": true` 将开启群组语音识别,默认使用openai的whisper模型识别为文字,同时以文字回复,参数仅支持群聊 (可以匹配group_chat_prefix和group_chat_keyword,目前仅支持wechaty方案);
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+ 添加 `"voice_reply_voice": true` 将开启语音回复语音(同时作用于私聊和群聊),但是需要配置对应语音合成平台的key,由于itchat协议的限制,只能发送语音mp3文件,若使用wechaty则回复的是微信语音。
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**4.其他配置**
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@@ -164,6 +164,67 @@ class WechatyChannel(Channel):
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await self._do_send_group_img(content, room_id)
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else:
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await self._do_send_group(content, room_id, room_name, from_user_id, from_user_name)
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elif room and msg.type() == MessageType.MESSAGE_TYPE_AUDIO:
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# 群组&语音消息
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room_id = room.room_id
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room_name = await room.topic()
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from_user_id = from_contact.contact_id
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from_user_name = from_contact.name
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is_at = await msg.mention_self()
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config = conf()
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# 是否开启语音识别、群消息响应功能、群名白名单符合等条件
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if config.get('group_speech_recognition') and (
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'ALL_GROUP' in config.get('group_name_white_list') or room_name in config.get(
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'group_name_white_list') or self.check_contain(room_name, config.get(
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'group_name_keyword_white_list'))):
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# 下载语音文件
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voice_file = await msg.to_file_box()
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silk_file = TmpDir().path() + voice_file.name
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await voice_file.to_file(silk_file)
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logger.info("[WX]receive voice file: " + silk_file)
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# 将文件转成wav格式音频
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wav_file = silk_file.replace(".slk", ".wav")
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with open(silk_file, 'rb') as f:
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silk_data = f.read()
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pcm_data = pysilk.decode(silk_data)
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with wave.open(wav_file, 'wb') as wav_data:
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wav_data.setnchannels(1)
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wav_data.setsampwidth(2)
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wav_data.setframerate(24000)
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wav_data.writeframes(pcm_data)
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if os.path.exists(wav_file):
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converter_state = "true" # 转换wav成功
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else:
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converter_state = "false" # 转换wav失败
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logger.info("[WX]receive voice converter: " + converter_state)
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# 语音识别为文本
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query = super().build_voice_to_text(wav_file).content
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# 校验关键字
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match_prefix = self.check_prefix(query, config.get('group_chat_prefix')) \
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or self.check_contain(query, config.get('group_chat_keyword'))
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# Wechaty判断is_at为True,返回的内容是过滤掉@之后的内容;而is_at为False,则会返回完整的内容
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if match_prefix is not None:
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# 故判断如果匹配到自定义前缀,则返回过滤掉前缀+空格后的内容,用于实现类似自定义+前缀触发生成AI图片的功能
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prefixes = config.get('group_chat_prefix')
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for prefix in prefixes:
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if query.startswith(prefix):
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query = query.replace(prefix, '', 1).strip()
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break
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# 返回消息
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img_match_prefix = self.check_prefix(query, conf().get('image_create_prefix'))
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if img_match_prefix:
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query = query.split(img_match_prefix, 1)[1].strip()
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await self._do_send_group_img(query, room_id)
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elif config.get('voice_reply_voice'):
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await self._do_send_group_voice(query, room_id, room_name, from_user_id, from_user_name)
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else:
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await self._do_send_group(query, room_id, room_name, from_user_id, from_user_name)
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else:
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logger.info("[WX]receive voice check prefix: " + 'False')
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# 清除缓存文件
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os.remove(wav_file)
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os.remove(silk_file)
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async def send(self, message: Union[str, Message, FileBox, Contact, UrlLink, MiniProgram], receiver):
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logger.info('[WX] sendMsg={}, receiver={}'.format(message, receiver))
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@@ -189,7 +250,6 @@ class WechatyChannel(Channel):
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except Exception as e:
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logger.exception(e)
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async def _do_send_voice(self, query, reply_user_id):
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try:
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if not query:
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@@ -261,6 +321,42 @@ class WechatyChannel(Channel):
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reply_text = '@' + group_user_name + ' ' + reply_text.strip()
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await self.send_group(conf().get("group_chat_reply_prefix", "") + reply_text, group_id)
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async def _do_send_group_voice(self, query, group_id, group_name, group_user_id, group_user_name):
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if not query:
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return
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context = Context(ContextType.TEXT, query)
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group_chat_in_one_session = conf().get('group_chat_in_one_session', [])
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if ('ALL_GROUP' in group_chat_in_one_session or \
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group_name in group_chat_in_one_session or \
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self.check_contain(group_name, group_chat_in_one_session)):
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context['session_id'] = str(group_id)
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else:
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context['session_id'] = str(group_id) + '-' + str(group_user_id)
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reply_text = super().build_reply_content(query, context).content
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if reply_text:
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reply_text = '@' + group_user_name + ' ' + reply_text.strip()
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# 转换 mp3 文件为 silk 格式
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mp3_file = super().build_text_to_voice(reply_text).content
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silk_file = mp3_file.replace(".mp3", ".silk")
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# Load the MP3 file
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audio = AudioSegment.from_file(mp3_file, format="mp3")
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# Convert to WAV format
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audio = audio.set_frame_rate(24000).set_channels(1)
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wav_data = audio.raw_data
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sample_width = audio.sample_width
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# Encode to SILK format
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silk_data = pysilk.encode(wav_data, 24000)
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# Save the silk file
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with open(silk_file, "wb") as f:
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f.write(silk_data)
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# 发送语音
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t = int(time.time())
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file_box = FileBox.from_file(silk_file, name=str(t) + '.silk')
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await self.send_group(file_box, group_id)
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# 清除缓存文件
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os.remove(mp3_file)
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os.remove(silk_file)
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async def _do_send_group_img(self, query, reply_room_id):
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try:
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if not query:
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@@ -10,6 +10,7 @@
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"group_chat_in_one_session": ["ChatGPT测试群"],
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"image_create_prefix": ["画", "看", "找"],
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"speech_recognition": false,
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"group_speech_recognition": false,
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"voice_reply_voice": false,
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"conversation_max_tokens": 1000,
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"expires_in_seconds": 3600,
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@@ -43,6 +43,7 @@ available_setting ={
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#语音设置
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"speech_recognition": False, # 是否开启语音识别
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"group_speech_recognition": False, # 是否开启群组语音识别
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"voice_reply_voice": False, # 是否使用语音回复语音,需要设置对应语音合成引擎的api key
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"voice_to_text": "openai", # 语音识别引擎,支持openai和google
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"text_to_voice": "baidu", # 语音合成引擎,支持baidu和google
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