@@ -1,13 +1,13 @@ | |||
# 简介 | |||
> 本项目是基于大模型的智能对话机器人,支持微信、企业微信、公众号、飞书、钉钉接入,可选择GPT3.5/GPT4.0/Claude/文心一言/讯飞星火/通义千问/Gemini/LinkAI,能处理文本、语音和图片,通过插件访问操作系统和互联网等外部资源,支持基于自有知识库定制企业AI应用。 | |||
> 本项目是基于大模型的智能对话机器人,支持微信、企业微信、公众号、飞书、钉钉接入,可选择GPT3.5/GPT4.0/Claude/文心一言/讯飞星火/通义千问/Gemini/LinkAI/ZhipuAI,能处理文本、语音和图片,通过插件访问操作系统和互联网等外部资源,支持基于自有知识库定制企业AI应用。 | |||
最新版本支持的功能如下: | |||
- [x] **多端部署:** 有多种部署方式可选择且功能完备,目前已支持个人微信、微信公众号和、企业微信、飞书、钉钉等部署方式 | |||
- [x] **基础对话:** 私聊及群聊的消息智能回复,支持多轮会话上下文记忆,支持 GPT-3.5, GPT-4, claude, Gemini, 文心一言, 讯飞星火, 通义千问 | |||
- [x] **基础对话:** 私聊及群聊的消息智能回复,支持多轮会话上下文记忆,支持 GPT-3.5, GPT-4, claude, Gemini, 文心一言, 讯飞星火, 通义千问,ChatGLM | |||
- [x] **语音能力:** 可识别语音消息,通过文字或语音回复,支持 azure, baidu, google, openai(whisper/tts) 等多种语音模型 | |||
- [x] **图像能力:** 支持图片生成、图片识别、图生图(如照片修复),可选择 Dall-E-3, stable diffusion, replicate, midjourney, vision模型 | |||
- [x] **图像能力:** 支持图片生成、图片识别、图生图(如照片修复),可选择 Dall-E-3, stable diffusion, replicate, midjourney, CogView-3, vision模型 | |||
- [x] **丰富插件:** 支持个性化插件扩展,已实现多角色切换、文字冒险、敏感词过滤、聊天记录总结、文档总结和对话、联网搜索等插件 | |||
- [x] **知识库:** 通过上传知识库文件自定义专属机器人,可作为数字分身、智能客服、私域助手使用,基于 [LinkAI](https://link-ai.tech) 实现 | |||
@@ -23,7 +23,6 @@ Demo made by [Visionn](https://www.wangpc.cc/) | |||
SaaS服务、私有化部署、稳定托管接入 等多种模式。 | |||
> | |||
> 目前已在私域运营、智能客服、企业效率助手等场景积累了丰富的 AI 解决方案, 在电商、文教、健康、新消费等各行业沉淀了 AI 落地的最佳实践,致力于打造助力中小企业拥抱 AI 的一站式平台。 | |||
企业服务和商用咨询可联系产品顾问: | |||
<img width="240" src="https://img-1317903499.cos.ap-guangzhou.myqcloud.com/docs/product-manager-qrcode.jpg"> | |||
@@ -3,6 +3,7 @@ | |||
import os | |||
import signal | |||
import sys | |||
import time | |||
from channel import channel_factory | |||
from common import const | |||
@@ -24,6 +25,21 @@ def sigterm_handler_wrap(_signo): | |||
signal.signal(_signo, func) | |||
def start_channel(channel_name: str): | |||
channel = channel_factory.create_channel(channel_name) | |||
if channel_name in ["wx", "wxy", "terminal", "wechatmp", "wechatmp_service", "wechatcom_app", "wework", | |||
const.FEISHU, const.DINGTALK]: | |||
PluginManager().load_plugins() | |||
if conf().get("use_linkai"): | |||
try: | |||
from common import linkai_client | |||
threading.Thread(target=linkai_client.start, args=(channel,)).start() | |||
except Exception as e: | |||
pass | |||
channel.startup() | |||
def run(): | |||
try: | |||
# load config | |||
@@ -41,22 +57,11 @@ def run(): | |||
if channel_name == "wxy": | |||
os.environ["WECHATY_LOG"] = "warn" | |||
# os.environ['WECHATY_PUPPET_SERVICE_ENDPOINT'] = '127.0.0.1:9001' | |||
channel = channel_factory.create_channel(channel_name) | |||
if channel_name in ["wx", "wxy", "terminal", "wechatmp", "wechatmp_service", "wechatcom_app", "wework", const.FEISHU,const.DINGTALK]: | |||
PluginManager().load_plugins() | |||
if conf().get("use_linkai"): | |||
try: | |||
from common import linkai_client | |||
threading.Thread(target=linkai_client.start, args=(channel, )).start() | |||
except Exception as e: | |||
pass | |||
# startup channel | |||
channel.startup() | |||
start_channel(channel_name) | |||
while True: | |||
time.sleep(1) | |||
except Exception as e: | |||
logger.error("App startup failed!") | |||
logger.exception(e) | |||
@@ -52,4 +52,9 @@ def create_bot(bot_type): | |||
from bot.gemini.google_gemini_bot import GoogleGeminiBot | |||
return GoogleGeminiBot() | |||
elif bot_type == const.ZHIPU_AI: | |||
from bot.zhipuai.zhipuai_bot import ZHIPUAIBot | |||
return ZHIPUAIBot() | |||
raise RuntimeError |
@@ -44,6 +44,7 @@ class GoogleGeminiBot(Bot): | |||
except Exception as e: | |||
logger.error("[Gemini] fetch reply error, may contain unsafe content") | |||
logger.error(e) | |||
return Reply(ReplyType.ERROR, "invoke [Gemini] api failed!") | |||
def _convert_to_gemini_messages(self, messages: list): | |||
res = [] | |||
@@ -63,6 +64,8 @@ class GoogleGeminiBot(Bot): | |||
def _filter_messages(self, messages: list): | |||
res = [] | |||
turn = "user" | |||
if not messages: | |||
return res | |||
for i in range(len(messages) - 1, -1, -1): | |||
message = messages[i] | |||
if message.get("role") != turn: | |||
@@ -92,7 +92,8 @@ class LinkAIBot(Bot): | |||
"frequency_penalty": conf().get("frequency_penalty", 0.0), # [-2,2]之间,该值越大则更倾向于产生不同的内容 | |||
"presence_penalty": conf().get("presence_penalty", 0.0), # [-2,2]之间,该值越大则更倾向于产生不同的内容 | |||
"session_id": session_id, | |||
"channel_type": conf().get("channel_type") | |||
"sender_id": session_id, | |||
"channel_type": conf().get("channel_type", "wx") | |||
} | |||
try: | |||
from linkai import LinkAIClient | |||
@@ -400,7 +401,7 @@ class LinkAIBot(Bot): | |||
i += 1 | |||
if url.endswith(".mp4"): | |||
reply_type = ReplyType.VIDEO_URL | |||
elif url.endswith(".pdf") or url.endswith(".doc") or url.endswith(".docx"): | |||
elif url.endswith(".pdf") or url.endswith(".doc") or url.endswith(".docx") or url.endswith(".csv"): | |||
reply_type = ReplyType.FILE | |||
url = _download_file(url) | |||
if not url: | |||
@@ -46,8 +46,9 @@ class XunFeiBot(Bot): | |||
self.domain = "generalv3" | |||
# 默认使用v2.0版本: "ws://spark-api.xf-yun.com/v2.1/chat" | |||
# v1.5版本为: "ws://spark-api.xf-yun.com/v1.1/chat" | |||
# v3.5版本为: "ws://spark-api.xf-yun.com/v3.5/chat" | |||
self.spark_url = "ws://spark-api.xf-yun.com/v3.5/chat" | |||
# v3.0版本为: "ws://spark-api.xf-yun.com/v3.1/chat" | |||
# v3.5版本为: "wss://spark-api.xf-yun.com/v3.5/chat" | |||
self.spark_url = "wss://spark-api.xf-yun.com/v3.5/chat" | |||
self.host = urlparse(self.spark_url).netloc | |||
self.path = urlparse(self.spark_url).path | |||
# 和wenxin使用相同的session机制 | |||
@@ -0,0 +1,29 @@ | |||
from common.log import logger | |||
from config import conf | |||
# ZhipuAI提供的画图接口 | |||
class ZhipuAIImage(object): | |||
def __init__(self): | |||
from zhipuai import ZhipuAI | |||
self.client = ZhipuAI(api_key=conf().get("zhipu_ai_api_key")) | |||
def create_img(self, query, retry_count=0, api_key=None, api_base=None): | |||
try: | |||
if conf().get("rate_limit_dalle"): | |||
return False, "请求太快了,请休息一下再问我吧" | |||
logger.info("[ZHIPU_AI] image_query={}".format(query)) | |||
response = self.client.images.generations( | |||
prompt=query, | |||
n=1, # 每次生成图片的数量 | |||
model=conf().get("text_to_image") or "cogview-3", | |||
size=conf().get("image_create_size", "1024x1024"), # 图片大小,可选有 256x256, 512x512, 1024x1024 | |||
quality="standard", | |||
) | |||
image_url = response.data[0].url | |||
logger.info("[ZHIPU_AI] image_url={}".format(image_url)) | |||
return True, image_url | |||
except Exception as e: | |||
logger.exception(e) | |||
return False, "画图出现问题,请休息一下再问我吧" |
@@ -0,0 +1,51 @@ | |||
from bot.session_manager import Session | |||
from common.log import logger | |||
class ZhipuAISession(Session): | |||
def __init__(self, session_id, system_prompt=None, model="glm-4"): | |||
super().__init__(session_id, system_prompt) | |||
self.model = model | |||
self.reset() | |||
def discard_exceeding(self, max_tokens, cur_tokens=None): | |||
precise = True | |||
try: | |||
cur_tokens = self.calc_tokens() | |||
except Exception as e: | |||
precise = False | |||
if cur_tokens is None: | |||
raise e | |||
logger.debug("Exception when counting tokens precisely for query: {}".format(e)) | |||
while cur_tokens > max_tokens: | |||
if len(self.messages) > 2: | |||
self.messages.pop(1) | |||
elif len(self.messages) == 2 and self.messages[1]["role"] == "assistant": | |||
self.messages.pop(1) | |||
if precise: | |||
cur_tokens = self.calc_tokens() | |||
else: | |||
cur_tokens = cur_tokens - max_tokens | |||
break | |||
elif len(self.messages) == 2 and self.messages[1]["role"] == "user": | |||
logger.warn("user message exceed max_tokens. total_tokens={}".format(cur_tokens)) | |||
break | |||
else: | |||
logger.debug("max_tokens={}, total_tokens={}, len(messages)={}".format(max_tokens, cur_tokens, | |||
len(self.messages))) | |||
break | |||
if precise: | |||
cur_tokens = self.calc_tokens() | |||
else: | |||
cur_tokens = cur_tokens - max_tokens | |||
return cur_tokens | |||
def calc_tokens(self): | |||
return num_tokens_from_messages(self.messages, self.model) | |||
def num_tokens_from_messages(messages, model): | |||
tokens = 0 | |||
for msg in messages: | |||
tokens += len(msg["content"]) | |||
return tokens |
@@ -0,0 +1,149 @@ | |||
# encoding:utf-8 | |||
import time | |||
import openai | |||
import openai.error | |||
from bot.bot import Bot | |||
from bot.zhipuai.zhipu_ai_session import ZhipuAISession | |||
from bot.zhipuai.zhipu_ai_image import ZhipuAIImage | |||
from bot.session_manager import SessionManager | |||
from bridge.context import ContextType | |||
from bridge.reply import Reply, ReplyType | |||
from common.log import logger | |||
from config import conf, load_config | |||
from zhipuai import ZhipuAI | |||
# ZhipuAI对话模型API | |||
class ZHIPUAIBot(Bot, ZhipuAIImage): | |||
def __init__(self): | |||
super().__init__() | |||
self.sessions = SessionManager(ZhipuAISession, model=conf().get("model") or "ZHIPU_AI") | |||
self.args = { | |||
"model": conf().get("model") or "glm-4", # 对话模型的名称 | |||
"temperature": conf().get("temperature", 0.9), # 值在(0,1)之间(智谱AI 的温度不能取 0 或者 1) | |||
"top_p": conf().get("top_p", 0.7), # 值在(0,1)之间(智谱AI 的 top_p 不能取 0 或者 1) | |||
} | |||
self.client = ZhipuAI(api_key=conf().get("zhipu_ai_api_key")) | |||
def reply(self, query, context=None): | |||
# acquire reply content | |||
if context.type == ContextType.TEXT: | |||
logger.info("[ZHIPU_AI] query={}".format(query)) | |||
session_id = context["session_id"] | |||
reply = None | |||
clear_memory_commands = conf().get("clear_memory_commands", ["#清除记忆"]) | |||
if query in clear_memory_commands: | |||
self.sessions.clear_session(session_id) | |||
reply = Reply(ReplyType.INFO, "记忆已清除") | |||
elif query == "#清除所有": | |||
self.sessions.clear_all_session() | |||
reply = Reply(ReplyType.INFO, "所有人记忆已清除") | |||
elif query == "#更新配置": | |||
load_config() | |||
reply = Reply(ReplyType.INFO, "配置已更新") | |||
if reply: | |||
return reply | |||
session = self.sessions.session_query(query, session_id) | |||
logger.debug("[ZHIPU_AI] session query={}".format(session.messages)) | |||
api_key = context.get("openai_api_key") or openai.api_key | |||
model = context.get("gpt_model") | |||
new_args = None | |||
if model: | |||
new_args = self.args.copy() | |||
new_args["model"] = model | |||
# if context.get('stream'): | |||
# # reply in stream | |||
# return self.reply_text_stream(query, new_query, session_id) | |||
reply_content = self.reply_text(session, api_key, args=new_args) | |||
logger.debug( | |||
"[ZHIPU_AI] new_query={}, session_id={}, reply_cont={}, completion_tokens={}".format( | |||
session.messages, | |||
session_id, | |||
reply_content["content"], | |||
reply_content["completion_tokens"], | |||
) | |||
) | |||
if reply_content["completion_tokens"] == 0 and len(reply_content["content"]) > 0: | |||
reply = Reply(ReplyType.ERROR, reply_content["content"]) | |||
elif reply_content["completion_tokens"] > 0: | |||
self.sessions.session_reply(reply_content["content"], session_id, reply_content["total_tokens"]) | |||
reply = Reply(ReplyType.TEXT, reply_content["content"]) | |||
else: | |||
reply = Reply(ReplyType.ERROR, reply_content["content"]) | |||
logger.debug("[ZHIPU_AI] reply {} used 0 tokens.".format(reply_content)) | |||
return reply | |||
elif context.type == ContextType.IMAGE_CREATE: | |||
ok, retstring = self.create_img(query, 0) | |||
reply = None | |||
if ok: | |||
reply = Reply(ReplyType.IMAGE_URL, retstring) | |||
else: | |||
reply = Reply(ReplyType.ERROR, retstring) | |||
return reply | |||
else: | |||
reply = Reply(ReplyType.ERROR, "Bot不支持处理{}类型的消息".format(context.type)) | |||
return reply | |||
def reply_text(self, session: ZhipuAISession, api_key=None, args=None, retry_count=0) -> dict: | |||
""" | |||
call openai's ChatCompletion to get the answer | |||
:param session: a conversation session | |||
:param session_id: session id | |||
:param retry_count: retry count | |||
:return: {} | |||
""" | |||
try: | |||
# if conf().get("rate_limit_chatgpt") and not self.tb4chatgpt.get_token(): | |||
# raise openai.error.RateLimitError("RateLimitError: rate limit exceeded") | |||
# if api_key == None, the default openai.api_key will be used | |||
if args is None: | |||
args = self.args | |||
# response = openai.ChatCompletion.create(api_key=api_key, messages=session.messages, **args) | |||
response = self.client.chat.completions.create(messages=session.messages, **args) | |||
# logger.debug("[ZHIPU_AI] response={}".format(response)) | |||
# logger.info("[ZHIPU_AI] reply={}, total_tokens={}".format(response.choices[0]['message']['content'], response["usage"]["total_tokens"])) | |||
return { | |||
"total_tokens": response.usage.total_tokens, | |||
"completion_tokens": response.usage.completion_tokens, | |||
"content": response.choices[0].message.content, | |||
} | |||
except Exception as e: | |||
need_retry = retry_count < 2 | |||
result = {"completion_tokens": 0, "content": "我现在有点累了,等会再来吧"} | |||
if isinstance(e, openai.error.RateLimitError): | |||
logger.warn("[ZHIPU_AI] RateLimitError: {}".format(e)) | |||
result["content"] = "提问太快啦,请休息一下再问我吧" | |||
if need_retry: | |||
time.sleep(20) | |||
elif isinstance(e, openai.error.Timeout): | |||
logger.warn("[ZHIPU_AI] Timeout: {}".format(e)) | |||
result["content"] = "我没有收到你的消息" | |||
if need_retry: | |||
time.sleep(5) | |||
elif isinstance(e, openai.error.APIError): | |||
logger.warn("[ZHIPU_AI] Bad Gateway: {}".format(e)) | |||
result["content"] = "请再问我一次" | |||
if need_retry: | |||
time.sleep(10) | |||
elif isinstance(e, openai.error.APIConnectionError): | |||
logger.warn("[ZHIPU_AI] APIConnectionError: {}".format(e)) | |||
result["content"] = "我连接不到你的网络" | |||
if need_retry: | |||
time.sleep(5) | |||
else: | |||
logger.exception("[ZHIPU_AI] Exception: {}".format(e), e) | |||
need_retry = False | |||
self.sessions.clear_session(session.session_id) | |||
if need_retry: | |||
logger.warn("[ZHIPU_AI] 第{}次重试".format(retry_count + 1)) | |||
return self.reply_text(session, api_key, args, retry_count + 1) | |||
else: | |||
return result |
@@ -31,6 +31,8 @@ class Bridge(object): | |||
self.btype["chat"] = const.QWEN | |||
if model_type in [const.GEMINI]: | |||
self.btype["chat"] = const.GEMINI | |||
if model_type in [const.ZHIPU_AI]: | |||
self.btype["chat"] = const.ZHIPU_AI | |||
if conf().get("use_linkai") and conf().get("linkai_api_key"): | |||
self.btype["chat"] = const.LINKAI | |||
@@ -11,7 +11,7 @@ class ReplyType(Enum): | |||
VIDEO_URL = 5 # 视频URL | |||
FILE = 6 # 文件 | |||
CARD = 7 # 微信名片,仅支持ntchat | |||
InviteRoom = 8 # 邀请好友进群 | |||
INVITE_ROOM = 8 # 邀请好友进群 | |||
INFO = 9 | |||
ERROR = 10 | |||
TEXT_ = 11 # 强制文本 | |||
@@ -4,6 +4,7 @@ import threading | |||
import time | |||
from asyncio import CancelledError | |||
from concurrent.futures import Future, ThreadPoolExecutor | |||
from concurrent import futures | |||
from bridge.context import * | |||
from bridge.reply import * | |||
@@ -17,6 +18,8 @@ try: | |||
except Exception as e: | |||
pass | |||
handler_pool = ThreadPoolExecutor(max_workers=8) # 处理消息的线程池 | |||
# 抽象类, 它包含了与消息通道无关的通用处理逻辑 | |||
class ChatChannel(Channel): | |||
@@ -25,7 +28,6 @@ class ChatChannel(Channel): | |||
futures = {} # 记录每个session_id提交到线程池的future对象, 用于重置会话时把没执行的future取消掉,正在执行的不会被取消 | |||
sessions = {} # 用于控制并发,每个session_id同时只能有一个context在处理 | |||
lock = threading.Lock() # 用于控制对sessions的访问 | |||
handler_pool = ThreadPoolExecutor(max_workers=8) # 处理消息的线程池 | |||
def __init__(self): | |||
_thread = threading.Thread(target=self.consume) | |||
@@ -168,11 +170,13 @@ class ChatChannel(Channel): | |||
reply = self._generate_reply(context) | |||
logger.debug("[WX] ready to decorate reply: {}".format(reply)) | |||
# reply的包装步骤 | |||
reply = self._decorate_reply(context, reply) | |||
if reply and reply.content: | |||
reply = self._decorate_reply(context, reply) | |||
# reply的发送步骤 | |||
self._send_reply(context, reply) | |||
# reply的发送步骤 | |||
self._send_reply(context, reply) | |||
def _generate_reply(self, context: Context, reply: Reply = Reply()) -> Reply: | |||
e_context = PluginManager().emit_event( | |||
@@ -339,7 +343,7 @@ class ChatChannel(Channel): | |||
if not context_queue.empty(): | |||
context = context_queue.get() | |||
logger.debug("[WX] consume context: {}".format(context)) | |||
future: Future = self.handler_pool.submit(self._handle, context) | |||
future: Future = handler_pool.submit(self._handle, context) | |||
future.add_done_callback(self._thread_pool_callback(session_id, context=context)) | |||
if session_id not in self.futures: | |||
self.futures[session_id] = [] | |||
@@ -15,6 +15,7 @@ import requests | |||
from bridge.context import * | |||
from bridge.reply import * | |||
from channel.chat_channel import ChatChannel | |||
from channel import chat_channel | |||
from channel.wechat.wechat_message import * | |||
from common.expired_dict import ExpiredDict | |||
from common.log import logger | |||
@@ -112,30 +113,39 @@ class WechatChannel(ChatChannel): | |||
self.auto_login_times = 0 | |||
def startup(self): | |||
itchat.instance.receivingRetryCount = 600 # 修改断线超时时间 | |||
# login by scan QRCode | |||
hotReload = conf().get("hot_reload", False) | |||
status_path = os.path.join(get_appdata_dir(), "itchat.pkl") | |||
itchat.auto_login( | |||
enableCmdQR=2, | |||
hotReload=hotReload, | |||
statusStorageDir=status_path, | |||
qrCallback=qrCallback, | |||
exitCallback=self.exitCallback, | |||
loginCallback=self.loginCallback | |||
) | |||
self.user_id = itchat.instance.storageClass.userName | |||
self.name = itchat.instance.storageClass.nickName | |||
logger.info("Wechat login success, user_id: {}, nickname: {}".format(self.user_id, self.name)) | |||
# start message listener | |||
itchat.run() | |||
try: | |||
itchat.instance.receivingRetryCount = 600 # 修改断线超时时间 | |||
# login by scan QRCode | |||
hotReload = conf().get("hot_reload", False) | |||
status_path = os.path.join(get_appdata_dir(), "itchat.pkl") | |||
itchat.auto_login( | |||
enableCmdQR=2, | |||
hotReload=hotReload, | |||
statusStorageDir=status_path, | |||
qrCallback=qrCallback, | |||
exitCallback=self.exitCallback, | |||
loginCallback=self.loginCallback | |||
) | |||
self.user_id = itchat.instance.storageClass.userName | |||
self.name = itchat.instance.storageClass.nickName | |||
logger.info("Wechat login success, user_id: {}, nickname: {}".format(self.user_id, self.name)) | |||
# start message listener | |||
itchat.run() | |||
except Exception as e: | |||
logger.error(e) | |||
def exitCallback(self): | |||
_send_logout() | |||
time.sleep(3) | |||
self.auto_login_times += 1 | |||
if self.auto_login_times < 100: | |||
self.startup() | |||
try: | |||
from common.linkai_client import chat_client | |||
if chat_client.client_id and conf().get("use_linkai"): | |||
_send_logout() | |||
time.sleep(2) | |||
self.auto_login_times += 1 | |||
if self.auto_login_times < 100: | |||
chat_channel.handler_pool._shutdown = False | |||
self.startup() | |||
except Exception as e: | |||
pass | |||
def loginCallback(self): | |||
logger.debug("Login success") | |||
@@ -223,7 +233,6 @@ class WechatChannel(ChatChannel): | |||
logger.info("[WX] sendImage url={}, receiver={}".format(img_url, receiver)) | |||
elif reply.type == ReplyType.IMAGE: # 从文件读取图片 | |||
image_storage = reply.content | |||
image_storage.seek(0) | |||
itchat.send_image(image_storage, toUserName=receiver) | |||
logger.info("[WX] sendImage, receiver={}".format(receiver)) | |||
elif reply.type == ReplyType.FILE: # 新增文件回复类型 | |||
@@ -259,7 +268,6 @@ def _send_login_success(): | |||
def _send_logout(): | |||
try: | |||
from common.linkai_client import chat_client | |||
time.sleep(2) | |||
if chat_client.client_id: | |||
chat_client.send_logout() | |||
except Exception as e: | |||
@@ -268,7 +276,6 @@ def _send_logout(): | |||
def _send_qr_code(qrcode_list: list): | |||
try: | |||
from common.linkai_client import chat_client | |||
time.sleep(2) | |||
if chat_client.client_id: | |||
chat_client.send_qrcode(qrcode_list) | |||
except Exception as e: | |||
@@ -8,6 +8,8 @@ LINKAI = "linkai" | |||
CLAUDEAI = "claude" | |||
QWEN = "qwen" | |||
GEMINI = "gemini" | |||
ZHIPU_AI = "glm-4" | |||
# model | |||
GPT35 = "gpt-3.5-turbo" | |||
@@ -19,7 +21,7 @@ TTS_1 = "tts-1" | |||
TTS_1_HD = "tts-1-hd" | |||
MODEL_LIST = ["gpt-3.5-turbo", "gpt-3.5-turbo-16k", "gpt-4", "wenxin", "wenxin-4", "xunfei", "claude", "gpt-4-turbo", | |||
"gpt-4-turbo-preview", "gpt-4-1106-preview", GPT4_TURBO_PREVIEW, QWEN, GEMINI] | |||
"gpt-4-turbo-preview", "gpt-4-1106-preview", GPT4_TURBO_PREVIEW, QWEN, GEMINI, ZHIPU_AI] | |||
# channel | |||
FEISHU = "feishu" | |||
@@ -2,7 +2,9 @@ from bridge.context import Context, ContextType | |||
from bridge.reply import Reply, ReplyType | |||
from common.log import logger | |||
from linkai import LinkAIClient, PushMsg | |||
from config import conf | |||
from config import conf, pconf, plugin_config | |||
from plugins import PluginManager | |||
chat_client: LinkAIClient | |||
@@ -22,6 +24,29 @@ class ChatClient(LinkAIClient): | |||
context["isgroup"] = push_msg.is_group | |||
self.channel.send(Reply(ReplyType.TEXT, content=msg_content), context) | |||
def on_config(self, config: dict): | |||
if not self.client_id: | |||
return | |||
logger.info(f"从控制台加载配置: {config}") | |||
local_config = conf() | |||
for key in local_config.keys(): | |||
if config.get(key) is not None: | |||
local_config[key] = config.get(key) | |||
if config.get("reply_voice_mode"): | |||
if config.get("reply_voice_mode") == "voice_reply_voice": | |||
local_config["voice_reply_voice"] = True | |||
elif config.get("reply_voice_mode") == "always_reply_voice": | |||
local_config["always_reply_voice"] = True | |||
# if config.get("admin_password") and plugin_config["Godcmd"]: | |||
# plugin_config["Godcmd"]["password"] = config.get("admin_password") | |||
# PluginManager().instances["Godcmd"].reload() | |||
# if config.get("group_app_map") and pconf("linkai"): | |||
# local_group_map = {} | |||
# for mapping in config.get("group_app_map"): | |||
# local_group_map[mapping.get("group_name")] = mapping.get("app_code") | |||
# pconf("linkai")["group_app_map"] = local_group_map | |||
# PluginManager().instances["linkai"].reload() | |||
def start(channel): | |||
global chat_client | |||
@@ -83,7 +83,7 @@ available_setting = { | |||
"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 | |||
"always_reply_voice": False, # 是否一直使用语音回复 | |||
"voice_to_text": "openai", # 语音识别引擎,支持openai,baidu,google,azure | |||
"text_to_voice": "openai", # 语音合成引擎,支持openai,baidu,google,pytts(offline),azure,elevenlabs | |||
"text_to_voice": "openai", # 语音合成引擎,支持openai,baidu,google,pytts(offline),azure,elevenlabs,edge(online) | |||
"text_to_voice_model": "tts-1", | |||
"tts_voice_id": "alloy", | |||
# baidu 语音api配置, 使用百度语音识别和语音合成时需要 | |||
@@ -150,6 +150,9 @@ available_setting = { | |||
"use_global_plugin_config": False, | |||
"max_media_send_count": 3, # 单次最大发送媒体资源的个数 | |||
"media_send_interval": 1, # 发送图片的事件间隔,单位秒 | |||
# 智谱AI 平台配置 | |||
"zhipu_ai_api_key": "", | |||
"zhipu_ai_api_base": "https://open.bigmodel.cn/api/paas/v4", | |||
# LinkAI平台配置 | |||
"use_linkai": False, | |||
"linkai_api_key": "", | |||
@@ -475,3 +475,11 @@ class Godcmd(Plugin): | |||
if model == "gpt-4-turbo": | |||
return const.GPT4_TURBO_PREVIEW | |||
return model | |||
def reload(self): | |||
gconf = plugin_config[self.name] | |||
if gconf: | |||
if gconf.get("password"): | |||
self.password = gconf["password"] | |||
if gconf.get("admin_users"): | |||
self.admin_users = gconf["admin_users"] |
@@ -46,3 +46,6 @@ class Plugin: | |||
def get_help_text(self, **kwargs): | |||
return "暂无帮助信息" | |||
def reload(self): | |||
pass |
@@ -99,7 +99,7 @@ class PluginManager: | |||
try: | |||
self.current_plugin_path = plugin_path | |||
if plugin_path in self.loaded: | |||
if self.loaded[plugin_path] == None: | |||
if plugin_name.upper() != 'GODCMD': | |||
logger.info("reload module %s" % plugin_name) | |||
self.loaded[plugin_path] = importlib.reload(sys.modules[import_path]) | |||
dependent_module_names = [name for name in sys.modules.keys() if name.startswith(import_path + ".")] | |||
@@ -141,19 +141,21 @@ class PluginManager: | |||
failed_plugins = [] | |||
for name, plugincls in self.plugins.items(): | |||
if plugincls.enabled: | |||
if name not in self.instances: | |||
try: | |||
instance = plugincls() | |||
except Exception as e: | |||
logger.warn("Failed to init %s, diabled. %s" % (name, e)) | |||
self.disable_plugin(name) | |||
failed_plugins.append(name) | |||
continue | |||
self.instances[name] = instance | |||
for event in instance.handlers: | |||
if event not in self.listening_plugins: | |||
self.listening_plugins[event] = [] | |||
self.listening_plugins[event].append(name) | |||
if 'GODCMD' in self.instances and name == 'GODCMD': | |||
continue | |||
# if name not in self.instances: | |||
try: | |||
instance = plugincls() | |||
except Exception as e: | |||
logger.warn("Failed to init %s, diabled. %s" % (name, e)) | |||
self.disable_plugin(name) | |||
failed_plugins.append(name) | |||
continue | |||
self.instances[name] = instance | |||
for event in instance.handlers: | |||
if event not in self.listening_plugins: | |||
self.listening_plugins[event] = [] | |||
self.listening_plugins[event].append(name) | |||
self.refresh_order() | |||
return failed_plugins | |||
@@ -20,5 +20,9 @@ | |||
"url": "https://github.com/6vision/Apilot.git", | |||
"desc": "通过api直接查询早报、热榜、快递、天气等实用信息的插件" | |||
} | |||
"pictureChange": { | |||
"url": "https://github.com/Yanyutin753/pictureChange.git", | |||
"desc": "利用stable-diffusion和百度Ai进行图生图或者画图的插件" | |||
} | |||
} | |||
} |
@@ -137,7 +137,7 @@ class Tool(Plugin): | |||
return { | |||
# 全局配置相关 | |||
"log": True, # tool 日志开关 | |||
"log": False, # tool 日志开关 | |||
"debug": kwargs.get("debug", False), # 输出更多日志 | |||
"no_default": kwargs.get("no_default", False), # 不要默认的工具,只加载自己导入的工具 | |||
"think_depth": kwargs.get("think_depth", 2), # 一个问题最多使用多少次工具 | |||
@@ -7,6 +7,7 @@ gTTS>=2.3.1 # google text to speech | |||
pyttsx3>=2.90 # pytsx text to speech | |||
baidu_aip>=4.16.10 # baidu voice | |||
azure-cognitiveservices-speech # azure voice | |||
edge-tts # edge-tts | |||
numpy<=1.24.2 | |||
langid # language detect | |||
@@ -33,7 +34,10 @@ broadscope_bailian | |||
google-generativeai | |||
# linkai | |||
linkai | |||
linkai>=0.0.3.5 | |||
# dingtalk | |||
dingtalk_stream | |||
# zhipuai | |||
zhipuai>=2.0.1 |
@@ -64,7 +64,9 @@ def any_to_wav(any_path, wav_path): | |||
if any_path.endswith(".sil") or any_path.endswith(".silk") or any_path.endswith(".slk"): | |||
return sil_to_wav(any_path, wav_path) | |||
audio = AudioSegment.from_file(any_path) | |||
audio.export(wav_path, format="wav") | |||
audio.set_frame_rate(8000) # 百度语音转写支持8000采样率, pcm_s16le, 单通道语音识别 | |||
audio.set_channels(1) | |||
audio.export(wav_path, format="wav", codec='pcm_s16le') | |||
def any_to_sil(any_path, sil_path): | |||
@@ -62,7 +62,7 @@ class BaiduVoice(Voice): | |||
# 识别本地文件 | |||
logger.debug("[Baidu] voice file name={}".format(voice_file)) | |||
pcm = get_pcm_from_wav(voice_file) | |||
res = self.client.asr(pcm, "pcm", 16000, {"dev_pid": self.dev_id}) | |||
res = self.client.asr(pcm, "pcm", 8000, {"dev_pid": self.dev_id}) | |||
if res["err_no"] == 0: | |||
logger.info("百度语音识别到了:{}".format(res["result"])) | |||
text = "".join(res["result"]) | |||
@@ -0,0 +1,50 @@ | |||
import time | |||
import edge_tts | |||
import asyncio | |||
from bridge.reply import Reply, ReplyType | |||
from common.log import logger | |||
from common.tmp_dir import TmpDir | |||
from voice.voice import Voice | |||
class EdgeVoice(Voice): | |||
def __init__(self): | |||
''' | |||
# 普通话 | |||
zh-CN-XiaoxiaoNeural | |||
zh-CN-XiaoyiNeural | |||
zh-CN-YunjianNeural | |||
zh-CN-YunxiNeural | |||
zh-CN-YunxiaNeural | |||
zh-CN-YunyangNeural | |||
# 地方口音 | |||
zh-CN-liaoning-XiaobeiNeural | |||
zh-CN-shaanxi-XiaoniNeural | |||
# 粤语 | |||
zh-HK-HiuGaaiNeural | |||
zh-HK-HiuMaanNeural | |||
zh-HK-WanLungNeural | |||
# 湾湾腔 | |||
zh-TW-HsiaoChenNeural | |||
zh-TW-HsiaoYuNeural | |||
zh-TW-YunJheNeural | |||
''' | |||
self.voice = "zh-CN-YunjianNeural" | |||
def voiceToText(self, voice_file): | |||
pass | |||
async def gen_voice(self, text, fileName): | |||
communicate = edge_tts.Communicate(text, self.voice) | |||
await communicate.save(fileName) | |||
def textToVoice(self, text): | |||
fileName = TmpDir().path() + "reply-" + str(int(time.time())) + "-" + str(hash(text) & 0x7FFFFFFF) + ".mp3" | |||
asyncio.run(self.gen_voice(text, fileName)) | |||
logger.info("[EdgeTTS] textToVoice text={} voice file name={}".format(text, fileName)) | |||
return Reply(ReplyType.VOICE, fileName) |
@@ -42,4 +42,8 @@ def create_voice(voice_type): | |||
from voice.ali.ali_voice import AliVoice | |||
return AliVoice() | |||
elif voice_type == "edge": | |||
from voice.edge.edge_voice import EdgeVoice | |||
return EdgeVoice() | |||
raise RuntimeError |