184 lines
8.6 KiB
Python
184 lines
8.6 KiB
Python
#! /usr/bin/env python3
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# -*- coding: utf-8 -*-
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from datetime import datetime
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import openai
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import json
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import os
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import random
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from tool.tool_registry import get_tools, dispatch_tool,extract_code
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from tool.code_kernel import execute,CodeKernel
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from wcferry import Wcf, WxMsg
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functions=get_tools()
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class ChatGLM():
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def __init__(self, wcf: Wcf, config={},max_retry=5) -> None:
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openai.api_key = config.get('key')
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# 自己搭建或第三方代理的接口
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openai.api_base = config.get('api')
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if config.get('proxy',None):
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openai.proxy = {"http": config.get('proxy',None), "https": config.get('proxy',None)}
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self.conversation_list = {}
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self.chat_type={}
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self.max_retry=max_retry
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self.wcf=wcf
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self.filePath=config.get('file_path')
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self.kernel = CodeKernel()
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self.system_content_msg = {"chat":[{"role": "system", "content": config.get('prompt')}],
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"tool":[{"role": "system", "content": "Answer the following questions as best as you can. You have access to the following tools:"}],
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"code":[{"role": "system", "content": "你是一位智能AI助手，你叫ChatGLM，你连接着一台电脑，但请注意不能联网。在使用Python解决任务时，你可以运行代码并得到结果，如果运行结果有错误，你需要尽可能对代码进行改进。你可以处理用户上传到电脑上的文件，文件默认存储路径是{}。".format(self.filePath)}]}
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code0='''
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import matplotlib.pyplot as plt
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import numpy as np
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x = np.linspace(-1, 1, 50)
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y = x * x + 1
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plt.plot(x, y)
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plt.show()
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'''
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res_type, res = execute(code0, self.kernel) #第一次画图不返回图片问题
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print(res_type, res)
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def get_answer(self, question: str, wxid: str) -> str:
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# wxid或者roomid,个人时为微信id，群消息时为群id
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if '#帮助'==question:
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return '本助手有三种模式，#聊天模式 = #1 ，#工具模式 = #2 ，#代码模式 = #3 , #清除模式会话 = #4 , #清除全部会话 = #5 可用发送#对应模式 或者 #编号 进行切换'
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elif '#聊天模式'==question or '#1'==question:
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self.chat_type[wxid]='chat'
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return '已切换#聊天模式'
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elif '#工具模式'==question or '#2'==question:
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self.chat_type[wxid]='tool'
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return '已切换#工具模式 \n工具有：查看天气，日期，新闻,comfyUI文生图。例如：\n帮我生成一张小鸟的图片，提示词必须是英文'
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elif '#代码模式'==question or '#3'==question:
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self.chat_type[wxid]='code'
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return '已切换#代码模式 \n代码模式可以用于写python代码，例如：\n用python画一个爱心'
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elif '#清除模式会话'==question or '#4'==question:
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self.conversation_list[wxid][self.chat_type[wxid]]=self.system_content_msg[self.chat_type[wxid]]
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return '已清除'
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elif '#清除全部会话'==question or '#5'==question:
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self.conversation_list[wxid]=self.system_content_msg
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return '已清除'
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self.updateMessage(wxid, question, "user")
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try:
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params = dict(model="chatglm3",temperature=1.0, messages=self.conversation_list[wxid][self.chat_type[wxid]], stream=False)
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if 'tool'==self.chat_type[wxid]:
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params["functions"] = functions
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response = openai.ChatCompletion.create(**params)
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for _ in range(self.max_retry):
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if response.choices[0].message.get("function_call"):
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function_call = response.choices[0].message.function_call
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print(f"Function Call Response: {function_call.to_dict_recursive()}")
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function_args = json.loads(function_call.arguments)
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observation = dispatch_tool(function_call.name, function_args)
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if isinstance(observation,dict):
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res_type=observation['res_type'] if 'res_type' in observation else 'text'
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res=observation['res'] if 'res_type' in observation else str(observation )
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if res_type == 'image':
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filename= observation['filename']
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filePath=os.path.join(self.filePath,filename)
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res.save(filePath)
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self.wcf.send_image(filePath,wxid)
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tool_response='[Image]' if res_type == 'image' else res
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else:
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tool_response=observation if isinstance(observation,str) else str(observation)
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print(f"Tool Call Response: {tool_response}")
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params["messages"].append(response.choices[0].message)
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params["messages"].append(
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{
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"role": "function",
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"name": function_call.name,
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"content": tool_response, # 调用函数返回结果
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}
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)
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self.updateMessage(wxid, tool_response, "function")
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response = openai.ChatCompletion.create(**params)
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elif response.choices[0].message.content.find('interpreter')!=-1:
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output_text=response.choices[0].message.content
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code = extract_code(output_text)
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self.wcf.send_text('代码如下：\n'+code,wxid)
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self.wcf.send_text('执行代码...',wxid)
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try:
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res_type, res = execute(code, self.kernel)
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except Exception as e:
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rsp=f'代码执行错误: {e}'
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break
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if res_type == 'image':
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filename= '{}.png'.format(''.join(random.sample('abcdefghijklmnopqrstuvwxyz1234567890',8)))
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filePath=os.path.join(self.filePath,filename)
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res.save(filePath)
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self.wcf.send_image(filePath,wxid)
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else:
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self.wcf.send_text("执行结果:\n"+res,wxid)
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tool_response='[Image]' if res_type == 'image' else res
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print("Received:", res_type, res)
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params["messages"].append(response.choices[0].message)
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params["messages"].append(
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{
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"role": "function",
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"name": "interpreter",
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"content": tool_response, # 调用函数返回结果
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}
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)
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self.updateMessage(wxid, tool_response, "function")
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response = openai.ChatCompletion.create(**params)
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else:
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rsp = response.choices[0].message.content
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break
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self.updateMessage(wxid, rsp, "assistant")
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except Exception as e0:
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rsp = "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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# 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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self.conversation_list[wxid] = self.system_content_msg
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if wxid not in self.chat_type.keys():
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self.chat_type[wxid]='chat'
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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][self.chat_type[wxid]].append(content_question_)
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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][self.chat_type[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][self.chat_type[wxid]][1]
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if __name__ == "__main__":
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from configuration import Config
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config = Config().CHATGPT
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if not config:
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exit(0)
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key = config.get("key")
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api = config.get("api")
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proxy = config.get("proxy")
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prompt = config.get("prompt")
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chat = ChatGLM(key, api, proxy, prompt)
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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, "wxid"))
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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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