加入了新的模型,使用更强的模型玩
This commit is contained in:
121
base/func_claude.py
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121
base/func_claude.py
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import requests
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import json
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import logging
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from datetime import datetime
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class Claude():
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def __init__(self, conf: dict) -> None:
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self.key = conf.get("key")
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self.api = conf.get("api")
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prompt = conf.get("prompt")
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self.model = conf.get("model", "windsurf/claude-3-5-sonnet")
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self.LOG = logging.getLogger("Claude")
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self.conversation_list = {}
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self.system_content_msg = {"role": "system", "content": prompt}
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def __repr__(self):
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return 'Claude'
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def get_answer(self, question: str, wxid: str) -> str:
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# 设置请求头
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self.updateMessage(wxid, question, "user")
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rsp = ""
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try:
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headers = {
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"Content-Type": "application/json; charset=utf-8",
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"Authorization": self.key
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}
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# 设置请求的payload
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data = {
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"model": self.model,
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"messages": [
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{
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"role": "user",
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"content": f"{question}"
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}
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]
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}
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# 发送POST请求
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response = requests.post(self.api, headers=headers, data=json.dumps(data), )
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response.encoding = 'utf-8'
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# 输出响应内容
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print(response.status_code)
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# print(response.text)
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rsp = extract_content(response.text)
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self.updateMessage(wxid, rsp, "assistant")
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except Exception as e0:
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self.LOG.error(f"发生未知错误:{str(e0)}")
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return rsp
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def updateMessage(self, wxid: str, question: str, role: str) -> None:
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now_time = str(datetime.now().strftime("%Y-%m-%d %H:%M:%S"))
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time_mk = "当需要回答时间时请直接参考回复:"
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# 初始化聊天记录,组装系统信息
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if wxid not in self.conversation_list.keys():
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question_ = [
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self.system_content_msg,
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{"role": "system", "content": "" + time_mk + now_time}
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]
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self.conversation_list[wxid] = question_
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# 当前问题
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content_question_ = {"role": role, "content": question}
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self.conversation_list[wxid].append(content_question_)
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for cont in self.conversation_list[wxid]:
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if cont["role"] != "system":
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continue
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if cont["content"].startswith(time_mk):
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cont["content"] = time_mk + now_time
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# 只存储10条记录,超过滚动清除
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i = len(self.conversation_list[wxid])
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if i > 10:
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print("滚动清除微信记录:" + wxid)
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# 删除多余的记录,倒着删,且跳过第一个的系统消息
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del self.conversation_list[wxid][1]
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@staticmethod
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def value_check(conf: dict) -> bool:
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if conf:
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if conf.get("key") and conf.get("api") and conf.get("prompt"):
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return True
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return False
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# 解析JSON
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def extract_content(data_string):
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try:
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data = json.loads(data_string)
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# 提取content字段
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content = data["choices"][0]["message"].get("content", "")
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return content
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except json.JSONDecodeError:
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print("Invalid JSON")
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return None
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if __name__ == '__main__':
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from configuration import Config
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config = Config().CLAUDE
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if not config:
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exit(0)
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chat = Claude(config)
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while True:
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q = input(">>> ")
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try:
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time_start = datetime.now() # 记录开始时间
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print(chat.get_answer(q, "Jyunere"))
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time_end = datetime.now() # 记录结束时间
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print(f"{round((time_end - time_start).total_seconds(), 2)}s") # 计算的时间差为程序的执行时间,单位为秒/s
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except Exception as e:
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print(e)
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18
config.yaml
18
config.yaml
@@ -48,15 +48,11 @@ report_reminder:
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receivers: [ ] # 定时日报周报月报提醒(roomid 或者 wxid)
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receivers: [ ] # 定时日报周报月报提醒(roomid 或者 wxid)
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chatgpt: # -----chatgpt配置这行不填-----
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chatgpt: # -----chatgpt配置这行不填-----
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key: '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'# 填写你 ChatGPT 的 key
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key: # 填写你 ChatGPT 的 key
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api: https://api.openai.com/v1 # 如果你不知道这是干嘛的,就不要改
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api: https://api.openai.com/v1 # 如果你不知道这是干嘛的,就不要改
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model: gpt-3.5-turbo
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model: gpt-3.5-turbo
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proxy: # 如果你在国内,你可能需要魔法,大概长这样:http://域名或者IP地址:端口号
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proxy: # 如果你在国内,你可能需要魔法,大概长这样:http://域名或者IP地址:端口号
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prompt: '你是一个信息归纳分析工程师,你叫小牛,你根据提问会搜索相关资料。经过信息精炼之后返回内容。
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prompt: 你是智能聊天机器人,你叫 wcferry # 根据需要对角色进行设定
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请回复时以以下格式进行返回:
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- 问题:回顾提问内容
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- 问题评价:分析问题的提出角度,如(财经、彩票、房产、股票、家居、教育、科技、社会、时尚、时政、体育、星座、游戏、娱乐)等
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- 总结:经过200个字以内的优化返回' # 根据需要对角色进行设定
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chatglm: # -----chatglm配置这行不填-----
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chatglm: # -----chatglm配置这行不填-----
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key: sk-012345678901234567890123456789012345678901234567 # 这个应该不用动
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key: sk-012345678901234567890123456789012345678901234567 # 这个应该不用动
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@@ -91,3 +87,13 @@ bard: # -----bard配置这行不填-----
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zhipu: # -----zhipu配置这行不填-----
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zhipu: # -----zhipu配置这行不填-----
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api_key: #api key
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api_key: #api key
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model: # 模型类型
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model: # 模型类型
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claude:
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key: 46a5674a-e978-491b-a810-5d54605f2c36
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api: http://127.0.0.1:8080/v1/chat/completions # 如果你不知道这是干嘛的,就不要改
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model: windsurf/claude-3-5-sonnet
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prompt: '你是一个信息归纳分析工程师,你根据提问会搜索相关资料。经过信息精炼之后返回内容。
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请回复时以以下格式进行返回:
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- 问题:回顾提问内容
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- 问题评价:分析问题的提出角度,如(财经、彩票、房产、股票、家居、教育、科技、社会、时尚、时政、体育、星座、游戏、娱乐)等
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- 总结:经过200个字以内的优化返回' # 根据需要对角色进行设定
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@@ -37,3 +37,4 @@ class Config(object):
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self.CHATGLM = yconfig.get("chatglm", {})
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self.CHATGLM = yconfig.get("chatglm", {})
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self.BardAssistant = yconfig.get("bard", {})
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self.BardAssistant = yconfig.get("bard", {})
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self.ZhiPu = yconfig.get("zhipu", {})
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self.ZhiPu = yconfig.get("zhipu", {})
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self.CLAUDE = yconfig.get("claude", {})
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@@ -10,12 +10,13 @@ class ChatType(IntEnum):
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CHATGLM = 4 # ChatGLM
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CHATGLM = 4 # ChatGLM
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BardAssistant = 5 # Google Bard
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BardAssistant = 5 # Google Bard
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ZhiPu = 6 # ZhiPu
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ZhiPu = 6 # ZhiPu
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CLAUDE = 7 # CLAUDE
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@staticmethod
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@staticmethod
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def is_in_chat_types(chat_type: int) -> bool:
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def is_in_chat_types(chat_type: int) -> bool:
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if chat_type in [ChatType.TIGER_BOT.value, ChatType.CHATGPT.value,
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if chat_type in [ChatType.TIGER_BOT.value, ChatType.CHATGPT.value,
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ChatType.XINGHUO_WEB.value, ChatType.CHATGLM.value,
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ChatType.XINGHUO_WEB.value, ChatType.CHATGLM.value,
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ChatType.BardAssistant.value, ChatType.ZhiPu.value]:
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ChatType.BardAssistant.value, ChatType.ZhiPu.value, ChatType.CLAUDE.value]:
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return True
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return True
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return False
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return False
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@@ -1,6 +1,6 @@
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import redis
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import redis
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from datetime import datetime
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from datetime import datetime
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import re
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from wcferry import WxMsg
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from wcferry import WxMsg
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@@ -1,5 +1,6 @@
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import pymysql
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import pymysql
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from datetime import datetime, timedelta
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from datetime import datetime, timedelta
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import redis
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# 配置数据库连接
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# 配置数据库连接
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db_config = {
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db_config = {
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@@ -9,6 +10,9 @@ db_config = {
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'database': 'message_archive'
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'database': 'message_archive'
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}
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}
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# 连接到Redis
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r = redis.Redis(host='192.168.2.32', port=6379, db=0)
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def archive_message(group_id, timestamp_str, sender, content, message_type, attachment_url=None):
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def archive_message(group_id, timestamp_str, sender, content, message_type, attachment_url=None):
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# 连接到数据库
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# 连接到数据库
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@@ -41,13 +45,21 @@ def get_messages(group_id, all_contacts: dict):
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connection = pymysql.connect(**db_config)
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connection = pymysql.connect(**db_config)
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try:
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try:
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with connection.cursor() as cursor:
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# 获取redis 中的上次总结时间,本次从上次开始算,弱没有,则从8小时之前开始计算
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# 生成Redis key
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key = f"{group_id}:summary_time"
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last_summary_time = r.get(key)
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if last_summary_time is None:
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# 获取当前时间并计算8小时前的时间
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# 获取当前时间并计算8小时前的时间
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current_time = datetime.now()
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current_time = datetime.now()
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eight_hours_ago = current_time - timedelta(hours=8)
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eight_hours_ago = current_time - timedelta(hours=8)
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# 转换为数据库中存储的时间格式 (假设timestamp是DATETIME类型)
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# 转换为数据库中存储的时间格式 (假设timestamp是DATETIME类型)
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eight_hours_ago_str = eight_hours_ago.strftime('%Y-%m-%d %H:%M:%S')
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last_summary_time = eight_hours_ago.strftime('%Y-%m-%d %H:%M:%S')
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current_date = current_time.strftime('%Y-%m-%d %H:%M:%S')
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r.set(key, current_date)
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with connection.cursor() as cursor:
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# 执行查询,获取最近8小时的消息
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# 执行查询,获取最近8小时的消息
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query = """
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query = """
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@@ -55,7 +67,7 @@ def get_messages(group_id, all_contacts: dict):
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FROM messages
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FROM messages
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WHERE timestamp >= %s AND message_type =1 and group_id = %s
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WHERE timestamp >= %s AND message_type =1 and group_id = %s
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"""
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"""
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cursor.execute(query, (eight_hours_ago_str, group_id))
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cursor.execute(query, (last_summary_time, group_id))
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# 提取结果并组成带逗号的字符串
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# 提取结果并组成带逗号的字符串
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result = []
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result = []
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5
robot.py
5
robot.py
@@ -20,6 +20,7 @@ from base.func_chengyu import cy
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from base.func_news import News
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from base.func_news import News
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from base.func_tigerbot import TigerBot
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from base.func_tigerbot import TigerBot
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from base.func_xinghuo_web import XinghuoWeb
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from base.func_xinghuo_web import XinghuoWeb
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from base.func_claude import Claude
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from configuration import Config
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from configuration import Config
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from constants import ChatType
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from constants import ChatType
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from job_mgmt import Job
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from job_mgmt import Job
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@@ -57,6 +58,8 @@ class Robot(Job):
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self.chat = BardAssistant(self.config.BardAssistant)
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self.chat = BardAssistant(self.config.BardAssistant)
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elif chat_type == ChatType.ZhiPu.value and ZhiPu.value_check(self.config.ZhiPu):
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elif chat_type == ChatType.ZhiPu.value and ZhiPu.value_check(self.config.ZhiPu):
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self.chat = ZhiPu(self.config.ZhiPu)
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self.chat = ZhiPu(self.config.ZhiPu)
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elif chat_type == ChatType.CLAUDE.value and Claude.value_check(self.config.CLAUDE):
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self.chat = Claude(self.config.CLAUDE)
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else:
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else:
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self.LOG.warning("未配置模型")
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self.LOG.warning("未配置模型")
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self.chat = None
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self.chat = None
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@@ -73,6 +76,8 @@ class Robot(Job):
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self.chat = BardAssistant(self.config.BardAssistant)
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self.chat = BardAssistant(self.config.BardAssistant)
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elif ZhiPu.value_check(self.config.ZhiPu):
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elif ZhiPu.value_check(self.config.ZhiPu):
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self.chat = ZhiPu(self.config.ZhiPu)
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self.chat = ZhiPu(self.config.ZhiPu)
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elif Claude.value_check(self.config.CLAUDE):
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self.chat = Claude(self.config.CLAUDE)
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else:
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else:
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self.LOG.warning("未配置模型")
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self.LOG.warning("未配置模型")
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self.chat = None
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self.chat = None
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