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代码优化

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严浪
2023-11-13 14:29:57 +08:00
parent db3ff14c71
commit 9ca9d31fee
10 changed files with 210 additions and 143 deletions
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41
chatglm/README.MD Normal file
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@@ -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

0
tool/__init__.py → chatglm/__init__.py
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0
tool/base.json → chatglm/base.json
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45
tool/code_kernel.py → chatglm/code_kernel.py
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@@ -5,12 +5,14 @@ from pprint import pprint
import queue
import re
from subprocess import PIPE
from typing import Dict, Union, Optional, Tuple
import jupyter_client
from PIL import Image
import time
IPYKERNEL = os.environ.get('IPYKERNEL', 'chatglm3')
class CodeKernel(object):
def __init__(self,
kernel_name='kernel',
@@ -28,16 +30,18 @@ class CodeKernel(object):
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 + ":$PATH", "PYTHONPATH": self.python_path}
env = {"PATH": self.python_path + ":$PATH",
"PYTHONPATH": self.python_path}
# Initialize the backend kernel
self.kernel_manager = jupyter_client.KernelManager(kernel_name=IPYKERNEL,
self.kernel_manager = jupyter_client.KernelManager(kernel_name=IPYKERNEL,
connection_file=self.kernel_config_path,
exec_files=[self.init_file_path],
exec_files=[
self.init_file_path],
env=env)
if self.kernel_config_path:
self.kernel_manager.load_connection_file()
@@ -65,14 +69,15 @@ class CodeKernel(object):
io_msg_content = self.kernel.get_iopub_msg(timeout=40)['content']
while True:
msg_out = io_msg_content
### Poll the message
# Poll the message
try:
io_msg_content = self.kernel.get_iopub_msg(timeout=40)['content']
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)
@@ -97,14 +102,14 @@ class CodeKernel(object):
return shell_msg
def get_error_msg(self, msg, verbose=False) -> str | None:
def get_error_msg(self, msg, verbose=False) -> Optional[str]:
if msg['content']['status'] == 'error':
try:
error_msg = msg['content']['traceback']
except:
except BaseException:
try:
error_msg = msg['content']['traceback'][-1].strip()
except:
except BaseException:
error_msg = "Traceback Error"
if verbose:
print("Error: ", error_msg)
@@ -141,16 +146,19 @@ class CodeKernel(object):
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, str | Image.Image]:
def execute(code, kernel: CodeKernel) -> tuple[str, Union[str, Image.Image]]:
res = ""
res_type = None
code = code.replace("<|observation|>", "")
@@ -159,12 +167,12 @@ def execute(code, kernel: CodeKernel) -> tuple[str, str | Image.Image]:
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']
@@ -177,17 +185,16 @@ def execute(code, kernel: CodeKernel) -> tuple[str, str | Image.Image]:
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]

55
tool/comfyUI_api.py → chatglm/comfyUI_api.py
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@@ -1,7 +1,8 @@
#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
# 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 websocket #NOTE: websocket-client (https://github.com/websocket-client/websocket-client)
# NOTE: websocket-client (https://github.com/websocket-client/websocket-client)
import websocket
import uuid
import json
import requests
@@ -13,35 +14,39 @@ 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.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))
self.ws.connect(
"ws://{}/ws?clientId={}".format(server_address, self.client_id))
def queue_prompt(self,prompt):
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)
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}
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}
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):
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):
def get_images(self, prompt, isUrl=False):
prompt_id = self.queue_prompt(prompt)['prompt_id']
output_images = []
while True:
@@ -51,9 +56,9 @@ class ComfyUIApi():
if message['type'] == 'executing':
data = message['data']
if data['node'] is None and data['prompt_id'] == prompt_id:
break #Execution is done
break # Execution is done
else:
continue #previews are binary data
continue # previews are binary data
history = self.get_history(prompt_id)[prompt_id]
for o in history['outputs']:
@@ -61,12 +66,14 @@ class ComfyUIApi():
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
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": {
@@ -157,16 +164,17 @@ prompt_text = """
"""
if __name__ == '__main__':
prompt = json.loads(prompt_text)
#set the text prompt for our positive CLIPTextEncode
# 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))
# set the seed for our KSampler node
prompt["3"]["inputs"]["seed"] = ''.join(
random.sample('123456789012345678901234567890', 14))
cfui=ComfyUIApi()
cfui = ComfyUIApi()
images = cfui.get_images(prompt)
#Commented out code to display the output images:
# Commented out code to display the output images:
for node_id in images:
for image_data in images[node_id]:
@@ -174,4 +182,3 @@ if __name__ == '__main__':
import io
image = Image.open(io.BytesIO(image_data))
image.show()

55
tool/tool_registry.py → chatglm/tool_registry.py
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@@ -9,7 +9,7 @@ import requests
import random
import time
import re
from tool.comfyUI_api import ComfyUIApi
from chatglm.comfyUI_api import ComfyUIApi
from func_news import News
from zhdate import ZhDate
from datetime import datetime
@@ -17,6 +17,7 @@ from datetime import datetime
_TOOL_HOOKS = {}
_TOOL_DESCRIPTIONS = {}
def extract_code(text: str) -> str:
pattern = r'```([^\n]*)\n(.*?)```'
matches = re.findall(pattern, text, re.DOTALL)
@@ -33,8 +34,9 @@ def register_tool(func: callable):
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")
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):
@@ -54,22 +56,24 @@ def register_tool(func: callable):
"params": tool_params
}
#print("[registered tool] " + pformat(tool_def))
# 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:
ret = tool_call(**tool_params)
except BaseException:
ret = traceback.format_exc()
return ret
def get_tools() -> dict:
return deepcopy(_TOOL_DESCRIPTIONS)
@@ -77,7 +81,7 @@ def get_tools() -> dict:
# @register_tool
# def random_number_generator(
# seed: Annotated[int, 'The random seed used by the generator', True],
# seed: Annotated[int, 'The random seed used by the generator', True],
# range: Annotated[tuple[int, int], 'The range of the generated numbers', True],
# ) -> int:
# """
@@ -93,6 +97,7 @@ def get_tools() -> dict:
# 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],
@@ -104,34 +109,39 @@ def get_weather(
raise TypeError("City name must be a string")
key_selection = {
"current_condition": ["temp_C", "FeelsLikeC", "humidity", "weatherDesc", "observation_time"],
"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:
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()
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("tool\\base.json", "r", encoding="utf-8") as f:
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))
data2['prompt']['4']['inputs']['ckpt_name']='chilloutmix_NiPrunedFp32Fix.safetensors' #模型名称
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
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']}
return {'res': images[0]['image'], 'res_type': 'image', 'filename': images[0]['filename']}
@register_tool
def get_news() -> str:
@@ -141,16 +151,17 @@ def get_news() -> str:
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()
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())
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__":

12
config.yaml.template
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@@ -54,12 +54,12 @@ 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
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
#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

139
func_chatglm.py
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@@ -7,85 +7,84 @@ import openai
import json
import os
import random
from tool.tool_registry import get_tools, dispatch_tool,extract_code
from tool.code_kernel import execute,CodeKernel
from wcferry import Wcf, WxMsg
from chatglm.tool_registry import get_tools, dispatch_tool, extract_code
from chatglm.code_kernel import execute, CodeKernel
from typing import Dict, Union, Optional, Tuple
from wcferry import Wcf
functions = get_tools()
functions=get_tools()
class ChatGLM():
def __init__(self, wcf: Wcf, config={},max_retry=5) -> None:
openai.api_key = config.get('key')
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')
if config.get('proxy',None):
openai.proxy = {"http": config.get('proxy',None), "https": config.get('proxy',None)}
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')
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')}],
"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)}]}
code0='''
import matplotlib.pyplot as plt
import numpy as np
x = np.linspace(-1, 1, 50)
y = x * x + 1
plt.plot(x, y)
plt.show()
'''
res_type, res = execute(code0, self.kernel) #第一次画图不返回图片问题
print(res_type, res)
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:
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'
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'
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'
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]]
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
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 = 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()}")
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 )
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)
filename = observation['filename']
filePath = os.path.join(self.filePath, filename)
res.save(filePath)
self.wcf.send_image(filePath,wxid)
tool_response='[Image]' if res_type == 'image' else res
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)
tool_response = observation if isinstance(
observation, str) else str(observation)
print(f"Tool Call Response: {tool_response}")
params["messages"].append(response.choices[0].message)
@@ -98,24 +97,25 @@ plt.show()
)
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
elif response.choices[0].message.content.find('interpreter') != -1:
output_text = response.choices[0].message.content
code = extract_code(output_text)
self.wcf.send_text('代码如下：\n'+code,wxid)
self.wcf.send_text('执行代码...',wxid)
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}'
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)
filename = '{}.png'.format(''.join(random.sample(
'abcdefghijklmnopqrstuvwxyz1234567890', 8)))
filePath = os.path.join(self.filePath, filename)
res.save(filePath)
self.wcf.send_image(filePath,wxid)
self.wcf and self.wcf.send_image(filePath, wxid)
else:
self.wcf.send_text("执行结果:\n"+res,wxid)
tool_response='[Image]' if res_type == 'image' else res
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(
@@ -144,11 +144,12 @@ plt.show()
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'
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_)
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]])
@@ -160,16 +161,11 @@ plt.show()
if __name__ == "__main__":
from configuration import Config
config = Config().CHATGPT
config = Config().CHATGLM
if not config:
exit(0)
key = config.get("key")
api = config.get("api")
proxy = config.get("proxy")
prompt = config.get("prompt")
chat = ChatGLM(key, api, proxy, prompt)
chat = ChatGLM(config)
while True:
q = input(">>> ")
@@ -178,6 +174,7 @@ if __name__ == "__main__":
print(chat.get_answer(q, "wxid"))
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
# 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)

4
requirements.txt
View File

@@ -8,3 +8,7 @@ schedule
pyhandytools
sparkdesk-api==1.3.0
wcferry>=39.0.3.0
websocket
pillow
jupyter_client
zhdate

2
robot.py
View File

@@ -38,7 +38,7 @@ class Robot(Job):
elif self.config.XINGHUO_WEB:
self.chat = XinghuoWeb(self.config.XINGHUO_WEB)
elif self.config.CHATGLM:
self.chat = ChatGLM(wcf, self.config.CHATGLM)
self.chat = ChatGLM(self.config.CHATGLM,wcf)
else:
self.chat = None