Merge pull request #1723 from zRzRzRzRzRzRzR/master

支持ZhipuAI GLM系列模型和画图代码

README.md

@@ -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
 

bot/bot_factory.py

@@ -52,8 +52,9 @@ def create_bot(bot_type):
  from bot.gemini.google_gemini_bot import GoogleGeminiBot
  return GoogleGeminiBot()
 
- elif bot_type == const.CHATGLM:
- from bot.zhipu.chat_glm_bot import ChatGLMBot
- return ChatGLMBot()
+ elif bot_type == const.ZHIPU_AI:
+ from bot.zhipuai.zhipuai_bot import ZHIPUAIBot
+ return ZHIPUAIBot()
+
 
  raise RuntimeError

bot/zhipuai/zhipu_ai_image.py

@@ -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"

bot/zhipuai/zhipu_ai_session.py

@@ -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

bot/zhipuai/zhipuai_bot.py

@@ -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

bridge/bridge.py

@@ -31,8 +31,8 @@ def __init__(self):
  self.btype["chat"] = const.QWEN
  if model_type in [const.GEMINI]:
  self.btype["chat"] = const.GEMINI
- if model_type in [const.CHATGLM]:
- self.btype["chat"] = const.CHATGLM
+ 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

common/const.py

@@ -8,7 +8,8 @@
 CLAUDEAI = "claude"
 QWEN = "qwen"
 GEMINI = "gemini"
-CHATGLM = "chatglm"
+ZHIPU_AI = "glm-4"
+
 
 # model
 GPT35 = "gpt-3.5-turbo"
@@ -20,7 +21,7 @@
 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, CHATGLM]
+ "gpt-4-turbo-preview", "gpt-4-1106-preview", GPT4_TURBO_PREVIEW, QWEN, GEMINI, ZHIPU_AI]
 
 # channel
 FEISHU = "feishu"

config.py

@@ -150,15 +150,14 @@
  "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": "",
  "linkai_app_code": "",
  "linkai_api_base": "https://api.link-ai.chat", # linkAI服务地址，若国内无法访问或延迟较高可改为 https://api.link-ai.tech
-
-# # 智谱AI
- "zhipu_ai_api_key": "",
- "zhipu_ai_api_base": "https://open.bigmodel.cn/api/paas/v4",
 }
 
 

requirements-optional.txt

@@ -38,5 +38,5 @@ linkai
 # dingtalk
 dingtalk_stream
 
-# zhipu
-zhipuai
+# zhipuai
+zhipuai>=2.0.1