Refactoring

base/func_chatglm.py

@@ -0,0 +1,190 @@
+#! /usr/bin/env python3
+# -*- coding: utf-8 -*-
+
+import json
+import os
+import random
+from datetime import datetime
+from typing import Optional
+
+import openai
+from base.chatglm.code_kernel import CodeKernel, execute
+from base.chatglm.tool_registry import dispatch_tool, extract_code, get_tools
+from wcferry import Wcf
+
+functions = get_tools()
+
+
+class ChatGLM:
+
+    def __init__(self, config={}, wcf: Optional[Wcf] = None, max_retry=5) -> None:
+        openai.api_key = config.get("key", "empty")
+        # 自己搭建或第三方代理的接口
+        openai.api_base = config["api"]
+        proxy = config.get("proxy")
+        if proxy:
+            openai.proxy = {"http": proxy, "https": proxy}
+        self.conversation_list = {}
+        self.chat_type = {}
+        self.max_retry = max_retry
+        self.wcf = wcf
+        self.filePath = config["file_path"]
+        self.kernel = CodeKernel()
+        self.system_content_msg = {"chat": [{"role": "system", "content": config["prompt"]}],
+                                   "tool": [{"role": "system", "content": "Answer the following questions as best as you can. You have access to the following tools:"}],
+                                   "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)}]}
+
+    def __repr__(self):
+        return 'ChatGLM'
+
+    @staticmethod
+    def value_check(conf: dict) -> bool:
+        if conf:
+            if conf.get("api") and conf.get("prompt") and conf.get("file_path"):
+                return True
+        return False
+
+    def get_answer(self, question: str, wxid: str) -> str:
+        # wxid或者roomid,个人时为微信id，群消息时为群id
+        if '#帮助' == question:
+            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'
+        elif '#聊天模式' == question or '#1' == question:
+            self.chat_type[wxid] = 'chat'
+            return '已切换#聊天模式'
+        elif '#工具模式' == question or '#2' == question:
+            self.chat_type[wxid] = 'tool'
+            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'
+        elif '#代码模式' == question or '#3' == question:
+            self.chat_type[wxid] = 'code'
+            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'
+        elif '#清除模式会话' == question or '#4' == question:
+            self.conversation_list[wxid][self.chat_type[wxid]
+                                         ] = self.system_content_msg[self.chat_type[wxid]]
+            return '已清除'
+        elif '#清除全部会话' == question or '#5' == question:
+            self.conversation_list[wxid] = self.system_content_msg
+            return '已清除'
+
+        self.updateMessage(wxid, question, "user")
+
+        try:
+            params = dict(model="chatglm3", temperature=1.0,
+                          messages=self.conversation_list[wxid][self.chat_type[wxid]], stream=False)
+            if 'tool' == self.chat_type[wxid]:
+                params["functions"] = functions
+            response = openai.ChatCompletion.create(**params)
+            for _ in range(self.max_retry):
+                if response.choices[0].message.get("function_call"):
+                    function_call = response.choices[0].message.function_call
+                    print(
+                        f"Function Call Response: {function_call.to_dict_recursive()}")
+
+                    function_args = json.loads(function_call.arguments)
+                    observation = dispatch_tool(
+                        function_call.name, function_args)
+                    if isinstance(observation, dict):
+                        res_type = observation['res_type'] if 'res_type' in observation else 'text'
+                        res = observation['res'] if 'res_type' in observation else str(
+                            observation)
+                        if res_type == 'image':
+                            filename = observation['filename']
+                            filePath = os.path.join(self.filePath, filename)
+                            res.save(filePath)
+                            self.wcf and self.wcf.send_image(filePath, wxid)
+                        tool_response = '[Image]' if res_type == 'image' else res
+                    else:
+                        tool_response = observation if isinstance(
+                            observation, str) else str(observation)
+                    print(f"Tool Call Response: {tool_response}")
+
+                    params["messages"].append(response.choices[0].message)
+                    params["messages"].append(
+                        {
+                            "role": "function",
+                            "name": function_call.name,
+                            "content": tool_response,  # 调用函数返回结果
+                        }
+                    )
+                    self.updateMessage(wxid, tool_response, "function")
+                    response = openai.ChatCompletion.create(**params)
+                elif response.choices[0].message.content.find('interpreter') != -1:
+                    output_text = response.choices[0].message.content
+                    code = extract_code(output_text)
+                    self.wcf and self.wcf.send_text('代码如下：\n' + code, wxid)
+                    self.wcf and self.wcf.send_text('执行代码...', wxid)
+                    try:
+                        res_type, res = execute(code, self.kernel)
+                    except Exception as e:
+                        rsp = f'代码执行错误: {e}'
+                        break
+                    if res_type == 'image':
+                        filename = '{}.png'.format(''.join(random.sample(
+                            'abcdefghijklmnopqrstuvwxyz1234567890', 8)))
+                        filePath = os.path.join(self.filePath, filename)
+                        res.save(filePath)
+                        self.wcf and self.wcf.send_image(filePath, wxid)
+                    else:
+                        self.wcf and self.wcf.send_text("执行结果:\n" + res, wxid)
+                    tool_response = '[Image]' if res_type == 'image' else res
+                    print("Received:", res_type, res)
+                    params["messages"].append(response.choices[0].message)
+                    params["messages"].append(
+                        {
+                            "role": "function",
+                            "name": "interpreter",
+                            "content": tool_response,  # 调用函数返回结果
+                        }
+                    )
+                    self.updateMessage(wxid, tool_response, "function")
+                    response = openai.ChatCompletion.create(**params)
+                else:
+                    rsp = response.choices[0].message.content
+                    break
+
+            self.updateMessage(wxid, rsp, "assistant")
+        except Exception as e0:
+            rsp = "发生未知错误：" + str(e0)
+
+        return rsp
+
+    def updateMessage(self, wxid: str, question: str, role: str) -> None:
+        now_time = str(datetime.now().strftime("%Y-%m-%d %H:%M:%S"))
+
+        # 初始化聊天记录,组装系统信息
+        if wxid not in self.conversation_list.keys():
+            self.conversation_list[wxid] = self.system_content_msg
+        if wxid not in self.chat_type.keys():
+            self.chat_type[wxid] = 'chat'
+
+        # 当前问题
+        content_question_ = {"role": role, "content": question}
+        self.conversation_list[wxid][self.chat_type[wxid]].append(
+            content_question_)
+
+        # 只存储10条记录，超过滚动清除
+        i = len(self.conversation_list[wxid][self.chat_type[wxid]])
+        if i > 10:
+            print("滚动清除微信记录：" + wxid)
+            # 删除多余的记录，倒着删，且跳过第一个的系统消息
+            del self.conversation_list[wxid][self.chat_type[wxid]][1]
+
+
+if __name__ == "__main__":
+    from configuration import Config
+    config = Config().CHATGLM
+    if not config:
+        exit(0)
+
+    chat = ChatGLM(config)
+
+    while True:
+        q = input(">>> ")
+        try:
+            time_start = datetime.now()  # 记录开始时间
+            print(chat.get_answer(q, "wxid"))
+            time_end = datetime.now()  # 记录结束时间
+
+            # 计算的时间差为程序的执行时间，单位为秒/s
+            print(f"{round((time_end - time_start).total_seconds(), 2)}s")
+        except Exception as e:
+            print(e)