删除无用的AI调用逻辑
This commit is contained in:
liuwei
30903
base/chengyu.csv
30903
base/chengyu.csv
File diff suppressed because it is too large
Load Diff
@@ -1,79 +0,0 @@
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# -*- coding: utf-8 -*-
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import os
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import random
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import pandas as pd
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class Chengyu(object):
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def __init__(self) -> None:
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root = os.path.dirname(os.path.abspath(__file__))
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self.df = pd.read_csv(f"{root}/chengyu.csv", delimiter="\t")
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self.cys, self.zis, self.yins = self._build_data()
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def _build_data(self):
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df = self.df.copy()
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df["shouzi"] = df["chengyu"].apply(lambda x: x[0])
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df["mozi"] = df["chengyu"].apply(lambda x: x[-1])
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df["shouyin"] = df["pingyin"].apply(lambda x: x.split(" ")[0])
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df["moyin"] = df["pingyin"].apply(lambda x: x.split(" ")[-1])
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cys = dict(zip(df["chengyu"], df["moyin"]))
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zis = df.groupby("shouzi").agg({"chengyu": set})["chengyu"].to_dict()
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yins = df.groupby("shouyin").agg({"chengyu": set})["chengyu"].to_dict()
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return cys, zis, yins
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def isChengyu(self, cy: str) -> bool:
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return self.cys.get(cy, None) is not None
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def getNext(self, cy: str, tongyin: bool = True) -> str:
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"""获取下一个成语
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cy: 当前成语
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tongyin: 是否允许同音字
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"""
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zi = cy[-1]
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ansers = list(self.zis.get(zi, {}))
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try:
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ansers.remove(cy) # 移除当前成语
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except Exception as e:
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pass # Just ignore...
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if ansers:
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return random.choice(ansers)
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# 如果找不到同字，允许同音
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if tongyin:
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yin = self.cys.get(cy)
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ansers = list(self.yins.get(yin, {}))
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try:
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ansers.remove(cy) # 移除当前成语
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except Exception as e:
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pass # Just ignore...
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if ansers:
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return random.choice(ansers)
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return None
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def getMeaning(self, cy: str) -> str:
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ress = self.df[self.df["chengyu"] == cy].to_dict(orient="records")
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if ress:
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res = ress[0]
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rsp = res["chengyu"] + "\n" + res["pingyin"] + "\n" + res["jieshi"]
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if res["chuchu"] and res["chuchu"] != "无":
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rsp += "\n出处：" + res["chuchu"]
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if res["lizi"] and res["lizi"] != "无":
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rsp += "\n例子：" + res["lizi"]
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return rsp
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return None
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cy = Chengyu()
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if __name__ == "__main__":
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answer = cy.getNext("便宜行事")
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print(answer)
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@@ -1,132 +0,0 @@
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import requests
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import json
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from loguru import logger
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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")
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self.LOG = logger
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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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self.system_content_msg,
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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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#
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# [
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# "windsurf/claude-3-5-sonnet",
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# "windsurf/gpt4o",
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# "windsurf/deepseek-chat",
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# "windsurf/deepseek-reasoner",
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# "windsurf/gpt4-o3-mini",
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# "windsurf/gemini-2.0-flash",
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# ]
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@@ -1,132 +0,0 @@
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import requests
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import json
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from loguru import logger
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from datetime import datetime
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class DeepSeek():
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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")
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self.LOG = logger("deepseek")
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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 'DeepSeek'
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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": f"Bearer {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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self.system_content_msg,
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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().DEEPSEEK
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if not config:
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exit(0)
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chat = DeepSeek(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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#
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# [
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# "windsurf/claude-3-5-sonnet",
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# "windsurf/gpt4o",
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# "windsurf/deepseek-chat",
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# "windsurf/deepseek-reasoner",
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# "windsurf/gpt4-o3-mini",
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# "windsurf/gemini-2.0-flash",
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# ]
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@@ -1,160 +0,0 @@
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import requests
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import json
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from loguru import logger
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from datetime import datetime
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class Doubao():
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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")
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self.LOG = logger
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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 'Doubao'
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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": f"Bearer {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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self.system_content_msg,
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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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|
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time_mk = "当需要回答时间时请直接参考回复:"
|
||||
# 初始化聊天记录,组装系统信息
|
||||
if wxid not in self.conversation_list.keys():
|
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question_ = [
|
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self.system_content_msg,
|
||||
{"role": "system", "content": "" + time_mk + now_time}
|
||||
]
|
||||
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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|
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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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|
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# 只存储10条记录，超过滚动清除
|
||||
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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|
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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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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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# 提取tokens相关内容，加入容错处理
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tokens_usage = data.get("usage", {})
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# 确保tokens_usage是字典类型
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if isinstance(tokens_usage, dict):
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prompt_tokens = tokens_usage.get("prompt_tokens", 0)
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completion_tokens = tokens_usage.get("completion_tokens", 0)
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total_tokens = tokens_usage.get("total_tokens", 0)
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else:
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prompt_tokens = completion_tokens = total_tokens = 0
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# 如果tokens信息为空，提供默认值或提示
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||||
if prompt_tokens == 0 and completion_tokens == 0 and total_tokens == 0:
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tokens_info = "\n\n【tokens】暂无数据"
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else:
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tokens_info = (f"\n\n【tokens】输入: {prompt_tokens} 生成: {completion_tokens} 总: {total_tokens}")
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# 将tokens信息添加到content后面，返回为字符串
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content_with_tokens = content + tokens_info
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||||
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||||
return content_with_tokens
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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__':
|
||||
from configuration import Config
|
||||
|
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config = Config().DOUBAO
|
||||
if not config:
|
||||
exit(0)
|
||||
|
||||
chat = Doubao(config)
|
||||
|
||||
while True:
|
||||
q = input(">>> ")
|
||||
try:
|
||||
time_start = datetime.now() # 记录开始时间
|
||||
print(chat.get_answer(q, "Jyunere"))
|
||||
time_end = datetime.now() # 记录结束时间
|
||||
|
||||
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
|
||||
except Exception as e:
|
||||
print(e)
|
||||
|
||||
# curl
|
||||
# https: // ark.cn - beijing.volces.com / api / v3 / chat / completions \
|
||||
# - H
|
||||
# "Content-Type: application/json" \
|
||||
# - H
|
||||
# "Authorization: Bearer b8586595-eb81-483d-8e91-a35cc789729e" \
|
||||
# - d
|
||||
# '{
|
||||
# "model": "doubao-1-5-lite-32k-250115",
|
||||
# "messages": [
|
||||
# {"role": "system", "content": "你是人工智能助手."},
|
||||
# {"role": "user", "content": "常见的十字花科植物有哪些？"}
|
||||
# ]
|
||||
#
|
||||
# }'
|
||||
34
config.yaml
34
config.yaml
@@ -1,37 +1,3 @@
|
||||
|
||||
|
||||
claude:
|
||||
key: 46a5674a-e978-491b-a810-5d54605f2c36
|
||||
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
|
||||
model: windsurf/gpt4o #
|
||||
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。
|
||||
请回复时以以下格式进行返回：
|
||||
- 问题描述：
|
||||
- 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
|
||||
- 总结：经过300个字以内的优化返回，返回内容请进行一定程度的结构化，方便快速阅读' # 根据需要对角色进行设定
|
||||
# DEEPSEEK
|
||||
#
|
||||
deepseek:
|
||||
key: sk-14bf1893e78040989a43b6f05c07974a
|
||||
api: https://api.deepseek.com/chat/completions # 如果你不知道这是干嘛的，就不要改
|
||||
model: deepseek-chat #
|
||||
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。
|
||||
请回复时以以下格式进行返回：
|
||||
- 问题描述：
|
||||
- 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
|
||||
- 总结：经过300个字以内的优化返回，返回内容请进行一定程度的结构化，方便快速阅读' # 根据需要对角色进行设定
|
||||
|
||||
doubao:
|
||||
key: b8586595-eb81-483d-8e91-a35cc789729e
|
||||
api: https://ark.cn-beijing.volces.com/api/v3/chat/completions # 如果你不知道这是干嘛的，就不要改
|
||||
model: doubao-1-5-lite-32k-250115 #
|
||||
prompt: '你是一个信息归纳分析工程师，根据提问进行相关资料搜索，并经过精炼后返回内容。请根据以下格式进行返回：
|
||||
- 问题描述[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]：
|
||||
- 总结：根据搜索的资料，对问题进行500字以内的结构化总结，确保内容清晰、简洁且有深度，便于快速阅读。分析的总结要具有逻辑性，突出关键点，并避免冗余信息。
|
||||
请确保500字以内的总结能准确表达问题的背景、现状和可能的解决方案，以便读者迅速理解核心内容。' # 根据需要对角色进行设定
|
||||
|
||||
# config.yaml
|
||||
|
||||
db_config:
|
||||
pool_name: "wechat_boot_pool"
|
||||
pool_size: 10
|
||||
|
||||
@@ -20,10 +20,6 @@ class Config(object):
|
||||
def reload(self) -> None:
|
||||
yconfig = self._load_config()
|
||||
|
||||
self.CLAUDE = yconfig.get("claude", {})
|
||||
self.DEEPSEEK = yconfig.get("deepseek", {})
|
||||
self.DOUBAO = yconfig.get("doubao", {})
|
||||
|
||||
# DB config
|
||||
self.mariadb = yconfig.get("db_config", {})
|
||||
self.redis = yconfig.get("redis_config", {})
|
||||
|
||||
Reference in New Issue
Block a user