diff --git a/chatglm/README.MD b/chatglm/README.MD new file mode 100644 index 0000000..3003ca9 --- /dev/null +++ b/chatglm/README.MD @@ -0,0 +1,41 @@ +# ChatGLM3集成使用说明 + +* 1.需要取消配置中 chatglm 的注释， 并配置对应信息，使用ChatGLM3,启用最新版ChatGLM3根目录下openai_api.py获取api地址： +```yaml +# 如果要使用 chatglm，取消下面的注释并填写相关内容 +chatglm: + key: xxx #根据需要自己做key校验 + api: http://localhost:8000/v1 # 根据自己的chatglm地址修改 + 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 + prompt: 你是智能聊天机器人，你叫小薇 # 根据需要对角色进行设定 + file_path: F:/Pictures/temp #设定生成图片和代码使用的文件夹路径 +``` +* 2.修改chatglm/tool_registry.py工具里面的一下配置，comfyUI地址或者根据需要自己配置一些工具,函数名上需要加@register_tool,函数里面需要叫'''函数描述'''，参数需要用Annotated[str,'',True]修饰，分别是类型，参数说明，是否必填，再加->加上对应的返回类型 +```python +@register_tool +def get_confyui_image(prompt: Annotated[str, '要生成图片的提示词,注意必须是英文', True]) -> dict: + ''' + 生成图片 + ''' + with open("func_chatglm\\base.json", "r", encoding="utf-8") as f: + data2 = json.load(f) + data2['prompt']['3']['inputs']['seed'] = ''.join( + random.sample('123456789012345678901234567890', 14)) + # 模型名称 + data2['prompt']['4']['inputs']['ckpt_name'] = 'chilloutmix_NiPrunedFp32Fix.safetensors' + data2['prompt']['6']['inputs']['text'] = prompt # 正向提示词 + # data2['prompt']['7']['inputs']['text']='' #反向提示词 + cfui = ComfyUIApi(server_address="127.0.0.1:8188") # 根据自己comfyUI地址修改 + images = cfui.get_images(data2['prompt']) + return {'res': images[0]['image'], 'res_type': 'image', 'filename': images[0]['filename']} + +``` +* 3 使用 Code Interpreter 还需要安装 Jupyter 内核,默认名称叫chatglm3： +``` +ipython kernel install --name chatglm3 --user +``` +如果名称需要自定义，可以配置系统环境变量：IPYKERNEL 或者修改 chatglm/code_kernel.py +``` +IPYKERNEL = os.environ.get('IPYKERNEL', 'chatglm3') +``` +* 4 启动后，发送 #帮助 可以查看 模式和常用指令 diff --git a/chatglm/__init__.py b/chatglm/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/chatglm/base.json b/chatglm/base.json new file mode 100644 index 0000000..6bfcd3f --- /dev/null +++ b/chatglm/base.json @@ -0,0 +1,88 @@ +{ + "prompt": { + "3": { + "inputs": { + "seed": 1000573256060686, + "steps": 20, + "cfg": 8, + "sampler_name": "euler", + "scheduler": "normal", + "denoise": 1, + "model": [ + "4", + 0 + ], + "positive": [ + "6", + 0 + ], + "negative": [ + "7", + 0 + ], + "latent_image": [ + "5", + 0 + ] + }, + "class_type": "KSampler" + }, + "4": { + "inputs": { + "ckpt_name": "(修复)512-inpainting-ema.safetensors" + }, + "class_type": "CheckpointLoaderSimple" + }, + "5": { + "inputs": { + "width": 512, + "height": 512, + "batch_size": 1 + }, + "class_type": "EmptyLatentImage" + }, + "6": { + "inputs": { + "text": "beautiful scenery nature glass bottle landscape, , purple galaxy bottle,dress, ", + "clip": [ + "4", + 1 + ] + }, + "class_type": "CLIPTextEncode" + }, + "7": { + "inputs": { + "text": "text, watermark", + "clip": [ + "4", + 1 + ] + }, + "class_type": "CLIPTextEncode" + }, + "8": { + "inputs": { + "samples": [ + "3", + 0 + ], + "vae": [ + "4", + 2 + ] + }, + "class_type": "VAEDecode" + }, + "9": { + "inputs": { + "filename_prefix": "ComfyUI", + "images": [ + "8", + 0 + ] + }, + "class_type": "SaveImage" + } + } +} \ No newline at end of file diff --git a/chatglm/code_kernel.py b/chatglm/code_kernel.py new file mode 100644 index 0000000..cc4c6ec --- /dev/null +++ b/chatglm/code_kernel.py @@ -0,0 +1,201 @@ +import base64 +import os +import queue +import re +import time +from io import BytesIO +from pprint import pprint +from subprocess import PIPE +from typing import Dict, Optional, Tuple, Union + +import jupyter_client +from PIL import Image + +IPYKERNEL = os.environ.get('IPYKERNEL', 'chatglm3') + + +class CodeKernel(object): + def __init__(self, + kernel_name='kernel', + kernel_id=None, + kernel_config_path="", + python_path=None, + ipython_path=None, + init_file_path="./startup.py", + verbose=1): + + self.kernel_name = kernel_name + self.kernel_id = kernel_id + self.kernel_config_path = kernel_config_path + self.python_path = python_path + self.ipython_path = ipython_path + self.init_file_path = init_file_path + self.verbose = verbose + + if python_path is None and ipython_path is None: + env = None + else: + env = {"PATH": self.python_path + ":$PATH", + "PYTHONPATH": self.python_path} + + # Initialize the backend kernel + self.kernel_manager = jupyter_client.KernelManager(kernel_name=IPYKERNEL, + connection_file=self.kernel_config_path, + exec_files=[ + self.init_file_path], + env=env) + if self.kernel_config_path: + self.kernel_manager.load_connection_file() + self.kernel_manager.start_kernel(stdout=PIPE, stderr=PIPE) + print("Backend kernel started with the configuration: {}".format( + self.kernel_config_path)) + else: + self.kernel_manager.start_kernel(stdout=PIPE, stderr=PIPE) + print("Backend kernel started with the configuration: {}".format( + self.kernel_manager.connection_file)) + + if verbose: + print(self.kernel_manager.get_connection_info()) + + # Initialize the code kernel + self.kernel = self.kernel_manager.blocking_client() + # self.kernel.load_connection_file() + self.kernel.start_channels() + print("Code kernel started.") + + def execute(self, code): + self.kernel.execute(code) + try: + shell_msg = self.kernel.get_shell_msg(timeout=40) + io_msg_content = self.kernel.get_iopub_msg(timeout=40)['content'] + while True: + msg_out = io_msg_content + # Poll the message + try: + io_msg_content = self.kernel.get_iopub_msg(timeout=40)[ + 'content'] + if 'execution_state' in io_msg_content and io_msg_content['execution_state'] == 'idle': + break + except queue.Empty: + break + + return shell_msg, msg_out + except Exception as e: + print(e) + return None + + def execute_interactive(self, code, verbose=False): + shell_msg = self.kernel.execute_interactive(code) + if shell_msg is queue.Empty: + if verbose: + print("Timeout waiting for shell message.") + self.check_msg(shell_msg, verbose=verbose) + + return shell_msg + + def inspect(self, code, verbose=False): + msg_id = self.kernel.inspect(code) + shell_msg = self.kernel.get_shell_msg(timeout=30) + if shell_msg is queue.Empty: + if verbose: + print("Timeout waiting for shell message.") + self.check_msg(shell_msg, verbose=verbose) + + return shell_msg + + def get_error_msg(self, msg, verbose=False) -> Optional[str]: + if msg['content']['status'] == 'error': + try: + error_msg = msg['content']['traceback'] + except BaseException: + try: + error_msg = msg['content']['traceback'][-1].strip() + except BaseException: + error_msg = "Traceback Error" + if verbose: + print("Error: ", error_msg) + return error_msg + return None + + def check_msg(self, msg, verbose=False): + status = msg['content']['status'] + if status == 'ok': + if verbose: + print("Execution succeeded.") + elif status == 'error': + for line in msg['content']['traceback']: + if verbose: + print(line) + + def shutdown(self): + # Shutdown the backend kernel + self.kernel_manager.shutdown_kernel() + print("Backend kernel shutdown.") + # Shutdown the code kernel + self.kernel.shutdown() + print("Code kernel shutdown.") + + def restart(self): + # Restart the backend kernel + self.kernel_manager.restart_kernel() + # print("Backend kernel restarted.") + + def interrupt(self): + # Interrupt the backend kernel + self.kernel_manager.interrupt_kernel() + # print("Backend kernel interrupted.") + + def is_alive(self): + return self.kernel.is_alive() + + +def b64_2_img(data): + buff = BytesIO(base64.b64decode(data)) + return Image.open(buff) + + +def clean_ansi_codes(input_string): + ansi_escape = re.compile(r'(\x9B|\x1B\[|\u001b\[)[0-?]*[ -/]*[@-~]') + return ansi_escape.sub('', input_string) + + +def execute(code, kernel: CodeKernel) -> tuple[str, Union[str, Image.Image]]: + res = "" + res_type = None + code = code.replace("<|observation|>", "") + code = code.replace("<|assistant|>interpreter", "") + code = code.replace("<|assistant|>", "") + code = code.replace("<|user|>", "") + code = code.replace("<|system|>", "") + msg, output = kernel.execute(code) + + if msg['metadata']['status'] == "timeout": + return res_type, 'Timed out' + elif msg['metadata']['status'] == 'error': + return res_type, clean_ansi_codes('\n'.join(kernel.get_error_msg(msg, verbose=True))) + + if 'text' in output: + res_type = "text" + res = output['text'] + elif 'data' in output: + for key in output['data']: + if 'image/png' in key: + res_type = "image" + res = output['data'][key] + break + elif 'text/plain' in key: + res_type = "text" + res = output['data'][key] + + if res_type == "image": + return res_type, b64_2_img(res) + elif res_type == "text" or res_type == "traceback": + res = res + + return res_type, res + + +def extract_code(text: str) -> str: + pattern = r'```([^\n]*)\n(.*?)```' + matches = re.findall(pattern, text, re.DOTALL) + return matches[-1][1] diff --git a/chatglm/comfyUI_api.py b/chatglm/comfyUI_api.py new file mode 100644 index 0000000..aefe6cc --- /dev/null +++ b/chatglm/comfyUI_api.py @@ -0,0 +1,186 @@ +# This is an example that uses the websockets api to know when a prompt execution is done +# Once the prompt execution is done it downloads the images using the /history endpoint + +import io +import json +import random +import urllib +import uuid + +import requests +# NOTE: websocket-client (https://github.com/websocket-client/websocket-client) +import websocket +from PIL import Image + + +class ComfyUIApi(): + def __init__(self, server_address="127.0.0.1:8188"): + self.server_address = server_address + self.client_id = str(uuid.uuid4()) + self.ws = websocket.WebSocket() + self.ws.connect( + "ws://{}/ws?clientId={}".format(server_address, self.client_id)) + + def queue_prompt(self, prompt): + p = {"prompt": prompt, "client_id": self.client_id} + data = json.dumps(p).encode('utf-8') + req = requests.post( + "http://{}/prompt".format(self.server_address), data=data) + print(req.text) + return json.loads(req.text) + + def get_image(self, filename, subfolder, folder_type): + data = {"filename": filename, + "subfolder": subfolder, "type": folder_type} + url_values = urllib.parse.urlencode(data) + with requests.get("http://{}/view?{}".format(self.server_address, url_values)) as response: + image = Image.open(io.BytesIO(response.content)) + return image + + def get_image_url(self, filename, subfolder, folder_type): + data = {"filename": filename, + "subfolder": subfolder, "type": folder_type} + url_values = urllib.parse.urlencode(data) + return "http://{}/view?{}".format(self.server_address, url_values) + + def get_history(self, prompt_id): + with requests.get("http://{}/history/{}".format(self.server_address, prompt_id)) as response: + return json.loads(response.text) + + def get_images(self, prompt, isUrl=False): + prompt_id = self.queue_prompt(prompt)['prompt_id'] + output_images = [] + while True: + out = self.ws.recv() + if isinstance(out, str): + message = json.loads(out) + if message['type'] == 'executing': + data = message['data'] + if data['node'] is None and data['prompt_id'] == prompt_id: + break # Execution is done + else: + continue # previews are binary data + + history = self.get_history(prompt_id)[prompt_id] + for o in history['outputs']: + for node_id in history['outputs']: + node_output = history['outputs'][node_id] + if 'images' in node_output: + for image in node_output['images']: + image_data = self.get_image_url(image['filename'], image['subfolder'], image['type']) if isUrl else self.get_image( + image['filename'], image['subfolder'], image['type']) + image['image'] = image_data + output_images.append(image) + + return output_images + + +prompt_text = """ +{ + "3": { + "class_type": "KSampler", + "inputs": { + "cfg": 8, + "denoise": 1, + "latent_image": [ + "5", + 0 + ], + "model": [ + "4", + 0 + ], + "negative": [ + "7", + 0 + ], + "positive": [ + "6", + 0 + ], + "sampler_name": "euler", + "scheduler": "normal", + "seed": 8566257, + "steps": 20 + } + }, + "4": { + "class_type": "CheckpointLoaderSimple", + "inputs": { + "ckpt_name": "chilloutmix_NiPrunedFp32Fix.safetensors" + } + }, + "5": { + "class_type": "EmptyLatentImage", + "inputs": { + "batch_size": 1, + "height": 512, + "width": 512 + } + }, + "6": { + "class_type": "CLIPTextEncode", + "inputs": { + "clip": [ + "4", + 1 + ], + "text": "masterpiece best quality girl" + } + }, + "7": { + "class_type": "CLIPTextEncode", + "inputs": { + "clip": [ + "4", + 1 + ], + "text": "bad hands" + } + }, + "8": { + "class_type": "VAEDecode", + "inputs": { + "samples": [ + "3", + 0 + ], + "vae": [ + "4", + 2 + ] + } + }, + "9": { + "class_type": "SaveImage", + "inputs": { + "filename_prefix": "ComfyUI", + "images": [ + "8", + 0 + ] + } + } +} +""" +if __name__ == '__main__': + prompt = json.loads(prompt_text) + # set the text prompt for our positive CLIPTextEncode + prompt["6"]["inputs"]["text"] = "masterpiece best quality man" + + # set the seed for our KSampler node + prompt["3"]["inputs"]["seed"] = ''.join( + random.sample('123456789012345678901234567890', 14)) + + cfui = ComfyUIApi() + images = cfui.get_images(prompt) + + # Commented out code to display the output images: + + for node_id in images: + for image_data in images[node_id]: + import io + + from PIL import Image + image = Image.open(io.BytesIO(image_data)) + image.show() diff --git a/chatglm/tool_registry.py b/chatglm/tool_registry.py new file mode 100644 index 0000000..8758b16 --- /dev/null +++ b/chatglm/tool_registry.py @@ -0,0 +1,171 @@ +import inspect +import json +import random +import re +import time +import traceback +from copy import deepcopy +from datetime import datetime +from pprint import pformat +from types import GenericAlias +from typing import Annotated, get_origin + +import requests +from func_news import News +from zhdate import ZhDate + +from chatglm.comfyUI_api import ComfyUIApi + +_TOOL_HOOKS = {} +_TOOL_DESCRIPTIONS = {} + + +def extract_code(text: str) -> str: + pattern = r'```([^\n]*)\n(.*?)```' + matches = re.findall(pattern, text, re.DOTALL) + return matches[-1][1] + + +def register_tool(func: callable): + tool_name = func.__name__ + tool_description = inspect.getdoc(func).strip() + python_params = inspect.signature(func).parameters + tool_params = [] + for name, param in python_params.items(): + annotation = param.annotation + if annotation is inspect.Parameter.empty: + raise TypeError(f"Parameter `{name}` missing type annotation") + if get_origin(annotation) != Annotated: + raise TypeError( + f"Annotation type for `{name}` must be typing.Annotated") + + typ, (description, required) = annotation.__origin__, annotation.__metadata__ + typ: str = str(typ) if isinstance(typ, GenericAlias) else typ.__name__ + if not isinstance(description, str): + raise TypeError(f"Description for `{name}` must be a string") + if not isinstance(required, bool): + raise TypeError(f"Required for `{name}` must be a bool") + + tool_params.append({ + "name": name, + "description": description, + "type": typ, + "required": required + }) + tool_def = { + "name": tool_name, + "description": tool_description, + "params": tool_params + } + + # print("[registered tool] " + pformat(tool_def)) + _TOOL_HOOKS[tool_name] = func + _TOOL_DESCRIPTIONS[tool_name] = tool_def + + return func + + +def dispatch_tool(tool_name: str, tool_params: dict) -> str: + if tool_name not in _TOOL_HOOKS: + return f"Tool `{tool_name}` not found. Please use a provided tool." + tool_call = _TOOL_HOOKS[tool_name] + try: + ret = tool_call(**tool_params) + except BaseException: + ret = traceback.format_exc() + return ret + + +def get_tools() -> dict: + return deepcopy(_TOOL_DESCRIPTIONS) + +# Tool Definitions + +# @register_tool +# def random_number_generator( +# seed: Annotated[int, 'The random seed used by the generator', True], +# range: Annotated[tuple[int, int], 'The range of the generated numbers', True], +# ) -> int: +# """ +# Generates a random number x, s.t. range[0] <= x < range[1] +# """ +# if not isinstance(seed, int): +# raise TypeError("Seed must be an integer") +# if not isinstance(range, tuple): +# raise TypeError("Range must be a tuple") +# if not isinstance(range[0], int) or not isinstance(range[1], int): +# raise TypeError("Range must be a tuple of integers") + +# import random +# return random.Random(seed).randint(*range) + + +@register_tool +def get_weather( + city_name: Annotated[str, 'The name of the city to be queried', True], +) -> str: + """ + Get the current weather for `city_name` + """ + if not isinstance(city_name, str): + raise TypeError("City name must be a string") + + key_selection = { + "current_condition": ["temp_C", "FeelsLikeC", "humidity", "weatherDesc", "observation_time"], + } + import requests + try: + resp = requests.get(f"https://wttr.in/{city_name}?format=j1") + resp.raise_for_status() + resp = resp.json() + ret = {k: {_v: resp[k][0][_v] for _v in v} + for k, v in key_selection.items()} + except BaseException: + import traceback + ret = "Error encountered while fetching weather data!\n" + traceback.format_exc() + + return str(ret) + + +@register_tool +def get_confyui_image(prompt: Annotated[str, '要生成图片的提示词,注意必须是英文', True]) -> dict: + ''' + 生成图片 + ''' + with open("chatglm\\base.json", "r", encoding="utf-8") as f: + data2 = json.load(f) + data2['prompt']['3']['inputs']['seed'] = ''.join( + random.sample('123456789012345678901234567890', 14)) + # 模型名称 + data2['prompt']['4']['inputs']['ckpt_name'] = 'chilloutmix_NiPrunedFp32Fix.safetensors' + data2['prompt']['6']['inputs']['text'] = prompt # 正向提示词 + # data2['prompt']['7']['inputs']['text']='' #反向提示词 + cfui = ComfyUIApi(server_address="127.0.0.1:8188") # 根据自己comfyUI地址修改 + images = cfui.get_images(data2['prompt']) + return {'res': images[0]['image'], 'res_type': 'image', 'filename': images[0]['filename']} + + +@register_tool +def get_news() -> str: + ''' + 获取最新新闻 + ''' + news = News() + return news.get_important_news() + + +@register_tool +def get_time() -> str: + ''' + 获取当前日期，时间，农历日期，星期几 + ''' + time = datetime.now() + date2 = ZhDate.from_datetime(time) + week_list = ["星期一", "星期二", "星期三", "星期四", "星期五", "星期六", "星期日"] + + return '{} {} {}'.format(time.strftime("%Y年%m月%d日 %H:%M:%S"), week_list[time.weekday()], '农历:' + date2.chinese()) + + +if __name__ == "__main__": + print(dispatch_tool("get_weather", {"city_name": "beijing"})) + print(get_tools()) diff --git a/config.yaml.template b/config.yaml.template index e23de14..4520880 100644 --- a/config.yaml.template +++ b/config.yaml.template @@ -54,6 +54,13 @@ report_reminder: # 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 # prompt: 你是智能聊天机器人，你叫wcferry # 根据需要对角色进行设定 +#chatglm: +# key: key #暂时没有 +# api: http://localhost:8000/v1 # 根据自己的chatglm地址修改 +# 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 +# prompt: 你是智能聊天机器人，你叫小薇 # 根据需要对角色进行设定 +# file_path: F:/Pictures/temp #设定生成图片和代码使用的文件夹路径 + tigerbot: key: key model: tigerbot-7b-sft diff --git a/configuration.py b/configuration.py index afc2b04..b0a4bcf 100644 --- a/configuration.py +++ b/configuration.py @@ -33,3 +33,4 @@ class Config(object): self.REPORT_REMINDERS = yconfig["report_reminder"]["receivers"] self.TIGERBOT = yconfig.get("tigerbot") self.XINGHUO_WEB = yconfig.get("xinghuo_web") + self.CHATGLM = yconfig.get("chatglm") diff --git a/func_chatglm.py b/func_chatglm.py new file mode 100644 index 0000000..9fe57f3 --- /dev/null +++ b/func_chatglm.py @@ -0,0 +1,181 @@ +#! /usr/bin/env python3 +# -*- coding: utf-8 -*- + +import json +import os +import random +from datetime import datetime +from typing import Dict, Optional, Tuple, Union + +import openai +from wcferry import Wcf + +from chatglm.code_kernel import CodeKernel, execute +from chatglm.tool_registry import dispatch_tool, extract_code, get_tools + +functions = get_tools() + + +class ChatGLM(): + + def __init__(self, config={}, wcf: Optional[Wcf] = None, max_retry=5) -> None: + openai.api_key = config.get('key', 'XXX') + # 自己搭建或第三方代理的接口 + openai.api_base = config.get('api', 'http://localhost:8000/v1') + if config.get('proxy', None): + openai.proxy = {"http": config.get( + 'proxy', None), "https": config.get('proxy', None)} + self.conversation_list = {} + self.chat_type = {} + self.max_retry = max_retry + self.wcf = wcf + self.filePath = config.get('file_path', 'temp') + self.kernel = CodeKernel() + self.system_content_msg = {"chat": [{"role": "system", "content": config.get('prompt', '你是智能聊天机器人，你叫小薇')}], + "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 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) diff --git a/requirements.txt b/requirements.txt index 0394075..5950519 100644 --- a/requirements.txt +++ b/requirements.txt @@ -8,3 +8,8 @@ schedule pyhandytools sparkdesk-api==1.3.0 wcferry>=39.0.3.0 +websocket +pillow +jupyter_client +zhdate +ipykernel \ No newline at end of file diff --git a/robot.py b/robot.py index c635b19..2447807 100644 --- a/robot.py +++ b/robot.py @@ -11,6 +11,7 @@ from wcferry import Wcf, WxMsg from configuration import Config from func_chatgpt import ChatGPT +from func_chatglm import ChatGLM from func_chengyu import cy from func_news import News from func_tigerbot import TigerBot @@ -36,6 +37,8 @@ class Robot(Job): self.chat = ChatGPT(cgpt.get("key"), cgpt.get("api"), cgpt.get("proxy"), cgpt.get("prompt")) elif self.config.XINGHUO_WEB: self.chat = XinghuoWeb(self.config.XINGHUO_WEB) + elif self.config.CHATGLM: + self.chat = ChatGLM(self.config.CHATGLM,wcf) else: self.chat = None