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WXBizMsgCrypt.py
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283
WXBizMsgCrypt.py
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#!/usr/bin/env python
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#-*- encoding:utf-8 -*-
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""" 对企业微信发送给企业后台的消息加解密示例代码.
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@copyright: Copyright (c) 1998-2014 Tencent Inc.
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"""
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# ------------------------------------------------------------------------
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import base64
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import string
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import random
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import hashlib
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import time
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import struct
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from Crypto.Cipher import AES
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import xml.etree.cElementTree as ET
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import sys
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import socket
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import ierror
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"""
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关于Crypto.Cipher模块，ImportError: No module named 'Crypto'解决方案
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请到官方网站 https://www.dlitz.net/software/pycrypto/ 下载pycrypto。
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下载后，按照README中的“Installation”小节的提示进行pycrypto安装。
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"""
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class FormatException(Exception):
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pass
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def throw_exception(message, exception_class=FormatException):
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"""my define raise exception function"""
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raise exception_class(message)
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class SHA1:
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def getSHA1(self, token, timestamp, nonce, encrypt):
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try:
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# 确保所有输入都是字符串类型
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token = str(token)
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timestamp = str(timestamp)
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nonce = str(nonce)
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encrypt = str(encrypt)
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sortlist = [token, timestamp, nonce, encrypt]
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sortlist.sort()
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# 将列表转换为字符串并编码
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str_to_hash = "".join(sortlist).encode('utf-8')
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sha = hashlib.sha1()
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sha.update(str_to_hash)
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return ierror.WXBizMsgCrypt_OK, sha.hexdigest()
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except Exception as e:
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print(f"[ERROR] SHA1计算失败: {str(e)}")
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return ierror.WXBizMsgCrypt_ComputeSignature_Error, None
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class XMLParse:
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"""提供提取消息格式中的密文及生成回复消息格式的接口"""
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# xml消息模板
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AES_TEXT_RESPONSE_TEMPLATE = """<xml>
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<Encrypt><![CDATA[%s]]></Encrypt>
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<MsgSignature><![CDATA[%s]]></MsgSignature>
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<TimeStamp>%s</TimeStamp>
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<Nonce><![CDATA[%s]]></Nonce>
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</xml>"""
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def extract(self, xmltext):
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"""提取出xml数据包中的加密消息
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@param xmltext: 待提取的xml字符串
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@return: 提取出的加密消息字符串
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"""
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try:
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xml_tree = ET.fromstring(xmltext)
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encrypt = xml_tree.find("Encrypt")
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return ierror.WXBizMsgCrypt_OK, encrypt.text
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except Exception as e:
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print (e)
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return ierror.WXBizMsgCrypt_ParseXml_Error,None
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def generate(self, encrypt, signature, timestamp, nonce):
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"""生成xml消息
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@param encrypt: 加密后的消息密文
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@param signature: 安全签名
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@param timestamp: 时间戳
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@param nonce: 随机字符串
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@return: 生成的xml字符串
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"""
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return self.AES_TEXT_RESPONSE_TEMPLATE % (
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encrypt,
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signature,
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timestamp,
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nonce
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)
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class PKCS7Encoder():
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"""提供基于PKCS7算法的加解密接口"""
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block_size = 32
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def encode(self, text):
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if isinstance(text, str):
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text = text.encode('utf-8')
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# 计算需要填充的位数
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amount_to_pad = self.block_size - (len(text) % self.block_size)
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if amount_to_pad == 0:
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amount_to_pad = self.block_size
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# 填充
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pad_chr = chr(amount_to_pad).encode('utf-8')
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padding = pad_chr * amount_to_pad
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return text + padding
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def decode(self, decrypted):
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"""删除解密后明文的补位字符
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@param decrypted: 解密后的明文(bytes类型)
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@return: 删除补位字符后的明文
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"""
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if isinstance(decrypted, bytes):
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pad = decrypted[-1]
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else:
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pad = ord(decrypted[-1])
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if pad < 1 or pad > 32:
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pad = 0
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return decrypted[:-pad]
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class Prpcrypt(object):
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"""提供接收和推送给企业微信消息的加解密接口"""
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def __init__(self,key):
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#self.key = base64.b64decode(key+"=")
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self.key = key
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# 设置加解密模式为AES的CBC模式
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self.mode = AES.MODE_CBC
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def encrypt(self, text, receiveid):
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try:
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# 统一处理输入为bytes
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text = text.encode('utf-8') if isinstance(text, str) else text
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receiveid = receiveid.encode('utf-8') if isinstance(receiveid, str) else receiveid
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# 生成16位随机字符串
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random_str = self.get_random_str().encode('utf-8')
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# 打包文本长度
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text_len = struct.pack("I", socket.htonl(len(text)))
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# 拼接内容
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content = b''.join([random_str, text_len, text, receiveid])
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# PKCS7填充
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pkcs7 = PKCS7Encoder()
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padding_text = pkcs7.encode(content)
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# AES加密
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cryptor = AES.new(self.key, self.mode, self.key[:16])
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ciphertext = cryptor.encrypt(padding_text)
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# Base64编码
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return ierror.WXBizMsgCrypt_OK, base64.b64encode(ciphertext)
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except Exception as e:
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print(f"[ERROR] 加密失败: {str(e)}")
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return ierror.WXBizMsgCrypt_EncryptAES_Error, None
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def decrypt(self,text,receiveid):
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try:
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cryptor = AES.new(self.key,self.mode,self.key[:16])
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plain_text = cryptor.decrypt(base64.b64decode(text))
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# 获取补位值
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pad = plain_text[-1]
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# 去除补位字符
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content = plain_text[16:-pad]
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xml_len = socket.ntohl(struct.unpack("I",content[ : 4])[0])
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xml_content = content[4 : xml_len+4]
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from_receiveid = content[xml_len+4:]
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except Exception as e:
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print(f"[ERROR] 解密失败: {str(e)}")
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return ierror.WXBizMsgCrypt_IllegalBuffer,None
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if from_receiveid != receiveid.encode('utf-8'):
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return ierror.WXBizMsgCrypt_ValidateCorpid_Error,None
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return 0,xml_content.decode('utf-8')
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def get_random_str(self):
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""" 随机生成16位字符串
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@return: 16位字符串
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"""
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rule = string.ascii_letters + string.digits # 修改这里
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str = random.sample(rule, 16)
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return "".join(str)
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class WXBizMsgCrypt(object):
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#构造函数
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def __init__(self,sToken,sEncodingAESKey,sReceiveId):
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try:
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self.key = base64.b64decode(sEncodingAESKey+"=")
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assert len(self.key) == 32
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except:
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throw_exception("[error]: EncodingAESKey unvalid !", FormatException)
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# return ierror.WXBizMsgCrypt_IllegalAesKey,None
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self.m_sToken = sToken
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self.m_sReceiveId = sReceiveId
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#验证URL
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#@param sMsgSignature: 签名串，对应URL参数的msg_signature
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#@param sTimeStamp: 时间戳，对应URL参数的timestamp
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#@param sNonce: 随机串，对应URL参数的nonce
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#@param sEchoStr: 随机串，对应URL参数的echostr
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#@param sReplyEchoStr: 解密之后的echostr，当return返回0时有效
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#@return：成功0，失败返回对应的错误码
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def VerifyURL(self, sMsgSignature, sTimeStamp, sNonce, sEchoStr):
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sha1 = SHA1()
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ret,signature = sha1.getSHA1(self.m_sToken, sTimeStamp, sNonce, sEchoStr)
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if ret != 0:
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return ret, None
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if not signature == sMsgSignature:
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return ierror.WXBizMsgCrypt_ValidateSignature_Error, None
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pc = Prpcrypt(self.key)
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ret,sReplyEchoStr = pc.decrypt(sEchoStr,self.m_sReceiveId)
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return ret,sReplyEchoStr
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def EncryptMsg(self, sReplyMsg, sNonce, timestamp = None):
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#将企业回复用户的消息加密打包
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#@param sReplyMsg: 企业号待回复用户的消息，xml格式的字符串
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#@param sTimeStamp: 时间戳，可以自己生成，也可以用URL参数的timestamp,如为None则自动用当前时间
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#@param sNonce: 随机串，可以自己生成，也可以用URL参数的nonce
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#sEncryptMsg: 加密后的可以直接回复用户的密文，包括msg_signature, timestamp, nonce, encrypt的xml格式的字符串,
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#return：成功0，sEncryptMsg,失败返回对应的错误码None
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pc = Prpcrypt(self.key)
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ret,encrypt = pc.encrypt(sReplyMsg, self.m_sReceiveId)
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if ret != 0:
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return ret,None
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if timestamp is None:
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timestamp = str(int(time.time()))
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# 生成安全签名
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sha1 = SHA1()
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ret, signature = sha1.getSHA1(self.m_sToken, timestamp, sNonce, encrypt.decode('utf-8'))
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if ret != 0:
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return ret, None
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xmlParse = XMLParse()
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return ret, xmlParse.generate(encrypt.decode('utf-8'), signature, timestamp, sNonce)
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def DecryptMsg(self, sPostData, sMsgSignature, sTimeStamp, sNonce):
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# 检验消息的真实性，并且获取解密后的明文
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# @param sMsgSignature: 签名串，对应URL参数的msg_signature
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# @param sTimeStamp: 时间戳，对应URL参数的timestamp
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# @param sNonce: 随机串，对应URL参数的nonce
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# @param sPostData: 密文，对应POST请求的数据
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# xml_content: 解密后的原文，当return返回0时有效
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# @return: 成功0，失败返回对应的错误码
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# 验证安全签名
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xmlParse = XMLParse()
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ret,encrypt = xmlParse.extract(sPostData)
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if ret != 0:
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return ret, None
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sha1 = SHA1()
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ret,signature = sha1.getSHA1(self.m_sToken, sTimeStamp, sNonce, encrypt)
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if ret != 0:
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return ret, None
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if not signature == sMsgSignature:
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return ierror.WXBizMsgCrypt_ValidateSignature_Error, None
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pc = Prpcrypt(self.key)
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ret,xml_content = pc.decrypt(encrypt,self.m_sReceiveId)
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return ret,xml_content
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452
ai_service.py
Normal file
452
ai_service.py
Normal file
@ -0,0 +1,452 @@
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# ai_service.py 优化版本
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import requests
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import logging
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from typing import Dict, Optional
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from functools import lru_cache
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from config import OLLAMA_MODEL, OPENAI_API_KEY, OPENAI_MODEL,OPENAI_BASE_URL # 确保config.py中有这些配置
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import time
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# 配置日志
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logging.basicConfig(
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format='%(asctime)s - %(name)s - %(levelname)s - %(message)s',
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level=logging.INFO
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)
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logger = logging.getLogger(__name__)
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class AIService:
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"""AI服务抽象基类"""
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def generate_response(self, prompt: str) -> str:
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"""
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生成AI回复
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:param prompt: 用户输入的提示文本
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:return: 生成的回复文本
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"""
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raise NotImplementedError
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class OllamaService(AIService):
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"""Ollama本地模型服务实现"""
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def __init__(
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self,
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endpoint: str = "http://localhost:11434/api/generate",
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model: str = OLLAMA_MODEL,
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timeout: int = 10
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):
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self.endpoint = endpoint
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self.default_model = model
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self.timeout = timeout
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@lru_cache(maxsize=100)
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def generate_response(self, prompt: str) -> str:
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try:
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response = requests.post(
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self.endpoint,
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json={
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'model': self.default_model,
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'prompt': prompt,
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'stream': False
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},
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timeout=self.timeout
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)
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response.raise_for_status()
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result = response.json()
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return result.get('response', '收到您的消息')
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except requests.exceptions.ConnectionError:
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logger.error("无法连接Ollama服务，请检查服务状态")
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return "本地模型服务未启动"
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except requests.exceptions.Timeout:
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logger.warning("Ollama请求超时")
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return "响应超时，请简化问题"
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except Exception as e:
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logger.error(f"Ollama处理异常: {str(e)}", exc_info=True)
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return "本地模型服务异常"
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class DifyService(AIService):
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"""Dify API客户端封装"""
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def __init__(
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self,
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api_key: str,
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base_url: str = "http://localhost/v1",
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timeout: int = 100,
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default_user: str = "system"
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):
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"""
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:param api_key: 应用API密钥
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:param base_url: API基础地址 (默认: http://localhost/v1)
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:param timeout: 请求超时时间 (秒)
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:param default_user: 默认用户标识
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"""
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self._validate_config(api_key, base_url)
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self.api_key = api_key
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self.base_url = base_url.rstrip('/')
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self.timeout = timeout
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self.default_user = default_user
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self.logger = logging.getLogger(self.__class__.__name__)
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self.session = requests.Session()
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self.headers = {
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"Authorization": f"Bearer {self.api_key}",
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"Content-Type": "application/json"
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}
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def _validate_config(self, api_key: str, base_url: str):
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"""配置校验"""
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if not api_key.startswith('app-'):
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raise ValueError("Invalid API key format")
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if not base_url.startswith(('http://', 'https://')):
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raise ValueError("Invalid base URL protocol")
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@lru_cache(maxsize=100)
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def generate_response(
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self,
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query: str,
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response_mode: str = "blocking",
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conversation_id: Optional[str] = None,
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user: Optional[str] = None,
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**additional_inputs
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) -> str:
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"""
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生成对话响应
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:param query: 用户查询内容
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:param response_mode: 响应模式 (blocking/streaming)
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:param conversation_id: 会话ID (为空时创建新会话)
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:param user: 用户标识 (默认使用初始化参数"""
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try:
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response = requests.post(
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f"{self.base_url}/chat-messages",
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headers=self.headers,
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json={
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"inputs": {},
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"query": query,
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"response_mode": "blocking",
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"conversation_id": "",
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"user": "abc-123"
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},
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timeout=self.timeout
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)
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response.raise_for_status()
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#response.json()["answer"]
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return response.json()["answer"]
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except requests.exceptions.ConnectionError:
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logger.error("无法连接dify服务，请检查服务状态")
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return "本地模型服务未启动"
|
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|
||||
except requests.exceptions.Timeout:
|
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logger.warning("dify请求超时")
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return "响应超时，请简化问题"
|
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|
||||
except Exception as e:
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logger.error(f"dify处理异常: {str(e)}", exc_info=True)
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return "本地模型服务异常"
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|
||||
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class OpenAIService(AIService):
|
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"""OpenAI官方接口服务实现"""
|
||||
def __init__(
|
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self,
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api_key: str = OPENAI_API_KEY,
|
||||
model: str = OPENAI_MODEL,
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base_url: str = OPENAI_BASE_URL,
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timeout: int = 15,
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temperature: float = 0.7,
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max_conversation_length: int = 10,
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max_time_gap: int = 30
|
||||
):
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self._validate_config(api_key, model)
|
||||
|
||||
self.api_key = api_key
|
||||
self.default_model = model
|
||||
self.base_url = base_url
|
||||
self.timeout = timeout
|
||||
self.temperature = temperature
|
||||
self.headers = {
|
||||
"Authorization": f"Bearer {self.api_key}",
|
||||
"Content-Type": "application/json"
|
||||
}
|
||||
# 新增会话管理相关属性
|
||||
self.conversation_history = {}
|
||||
self.max_conversation_length = max_conversation_length
|
||||
self.max_time_gap = max_time_gap
|
||||
self.system_prompt = '''你是路桥设计院智能助手。你的使命是尽可能地用详尽的、温暖的、友善的话语帮助企业员工，在各种方面提供帮助和支持。无论我需要什么帮助或建议，你都会尽力提供详尽信息。'''
|
||||
|
||||
def _validate_config(self, api_key: str, model: str) -> None:
|
||||
"""
|
||||
验证OpenAI配置参数
|
||||
:param api_key: OpenAI API密钥
|
||||
:param model: 模型名称
|
||||
:raises ValueError: 当配置参数无效时抛出
|
||||
"""
|
||||
if not api_key:
|
||||
raise ValueError("OpenAI API密钥不能为空")
|
||||
|
||||
if not model:
|
||||
raise ValueError("模型名称不能为空")
|
||||
|
||||
if not isinstance(api_key, str) or not isinstance(model, str):
|
||||
raise ValueError("API密钥和模型名称必须是字符串类型")
|
||||
|
||||
# 可选：验证API密钥格式
|
||||
# if not api_key.startswith('sk-'):
|
||||
# raise ValueError("无效的OpenAI API密钥格式")
|
||||
|
||||
def _manage_conversation_history(self, user_id: str, message: str):
|
||||
"""管理会话历史"""
|
||||
current_timestamp = int(time.time())
|
||||
|
||||
# 检查会话是否超时
|
||||
if (user_id in self.conversation_history and
|
||||
current_timestamp - self.conversation_history[user_id]["last_timestamp"] >= self.max_time_gap * 60):
|
||||
del self.conversation_history[user_id]
|
||||
|
||||
# 初始化或更新会话历史
|
||||
if user_id not in self.conversation_history:
|
||||
self.conversation_history[user_id] = {
|
||||
"messages": [],
|
||||
"last_timestamp": current_timestamp
|
||||
}
|
||||
else:
|
||||
self.conversation_history[user_id]["last_timestamp"] = current_timestamp
|
||||
|
||||
# 限制会话历史长度
|
||||
if len(self.conversation_history[user_id]["messages"]) > self.max_conversation_length:
|
||||
self.conversation_history[user_id]["messages"] = (
|
||||
self.conversation_history[user_id]["messages"][-self.max_conversation_length:]
|
||||
)
|
||||
|
||||
# 添加新消息
|
||||
self.conversation_history[user_id]["messages"].append({
|
||||
"role": "user",
|
||||
"content": message
|
||||
})
|
||||
|
||||
def generate_response(self, prompt: str, user_id: str = "default_user") -> str:
|
||||
"""
|
||||
生成带有会话历史的回复
|
||||
:param prompt: 用户输入的提示文本
|
||||
:param user_id: 用户标识符
|
||||
:return: 生成的回复文本
|
||||
"""
|
||||
try:
|
||||
self._manage_conversation_history(user_id, prompt)
|
||||
|
||||
# 构建完整的消息历史
|
||||
messages = [{"role": "system", "content": self.system_prompt}]
|
||||
messages.extend(self.conversation_history[user_id]["messages"])
|
||||
|
||||
response = requests.post(
|
||||
f"{self.base_url}/chat/completions",
|
||||
headers=self.headers,
|
||||
json={
|
||||
"model": self.default_model,
|
||||
"messages": messages,
|
||||
"temperature": self.temperature
|
||||
},
|
||||
timeout=self.timeout
|
||||
)
|
||||
response.raise_for_status()
|
||||
|
||||
result = response.json()
|
||||
if 'choices' not in result:
|
||||
logger.error(f"OpenAI响应格式异常: {result}")
|
||||
return "响应解析失败"
|
||||
|
||||
response_text = result['choices'][0]['message']['content']
|
||||
|
||||
# 保存助手的回复到会话历史
|
||||
self.conversation_history[user_id]["messages"].append({
|
||||
"role": "assistant",
|
||||
"content": response_text
|
||||
})
|
||||
|
||||
return response_text
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"OpenAI处理异常: {str(e)}", exc_info=True)
|
||||
return "服务暂时不可用"
|
||||
|
||||
class FastGptService(AIService):
|
||||
"""FastGPT API客户端封装"""
|
||||
|
||||
def __init__(
|
||||
self,
|
||||
api_key: str,
|
||||
base_url: str = "http://localhost:3000/api/v1",
|
||||
timeout: int = 30,
|
||||
max_conversation_length: int = 10,
|
||||
max_time_gap: int = 30
|
||||
):
|
||||
"""
|
||||
初始化FastGPT服务
|
||||
:param api_key: FastGPT API密钥
|
||||
:param base_url: API基础地址
|
||||
:param timeout: 请求超时时间(秒)
|
||||
:param max_conversation_length: 最大会话长度
|
||||
:param max_time_gap: 会话超时时间(分钟)
|
||||
"""
|
||||
self._validate_config(api_key, base_url)
|
||||
|
||||
self.api_key = api_key
|
||||
self.base_url = base_url.rstrip('/')
|
||||
self.timeout = timeout
|
||||
self.headers = {
|
||||
"Authorization": f"Bearer {api_key}",
|
||||
"Content-Type": "application/json"
|
||||
}
|
||||
|
||||
# 会话管理相关属性
|
||||
self.conversation_history = {}
|
||||
self.max_conversation_length = max_conversation_length
|
||||
self.max_time_gap = max_time_gap
|
||||
|
||||
def _validate_config(self, api_key: str, base_url: str):
|
||||
"""配置校验"""
|
||||
if not api_key:
|
||||
raise ValueError("FastGPT API密钥不能为空")
|
||||
if not base_url.startswith(('http://', 'https://')):
|
||||
raise ValueError("无效的基础URL协议")
|
||||
|
||||
def _manage_conversation_history(self, user_id: str, message: str):
|
||||
"""管理会话历史"""
|
||||
current_timestamp = int(time.time())
|
||||
|
||||
# 检查会话是否超时
|
||||
if (user_id in self.conversation_history and
|
||||
current_timestamp - self.conversation_history[user_id]["last_timestamp"] >= self.max_time_gap * 60):
|
||||
del self.conversation_history[user_id]
|
||||
|
||||
# 初始化或更新会话历史
|
||||
if user_id not in self.conversation_history:
|
||||
self.conversation_history[user_id] = {
|
||||
"chat_id": f"chat_{user_id}_{current_timestamp}",
|
||||
"messages": [],
|
||||
"last_timestamp": current_timestamp
|
||||
}
|
||||
else:
|
||||
self.conversation_history[user_id]["last_timestamp"] = current_timestamp
|
||||
|
||||
# 限制会话历史长度
|
||||
if len(self.conversation_history[user_id]["messages"]) >= self.max_conversation_length:
|
||||
self.conversation_history[user_id]["messages"] = (
|
||||
self.conversation_history[user_id]["messages"][-self.max_conversation_length:]
|
||||
)
|
||||
|
||||
# 添加新消息
|
||||
msg_id = f"msg_{current_timestamp}"
|
||||
self.conversation_history[user_id]["messages"].append({
|
||||
"role": "user",
|
||||
"content": message
|
||||
})
|
||||
return msg_id
|
||||
|
||||
def generate_response(
|
||||
self,
|
||||
prompt: str,
|
||||
user_id: str = "default_user",
|
||||
variables: dict = None,
|
||||
detail: bool = False
|
||||
) -> str:
|
||||
"""
|
||||
生成回复
|
||||
:param prompt: 用户输入
|
||||
:param user_id: 用户标识
|
||||
:param variables: 模块变量
|
||||
:param detail: 是否返回详细信息
|
||||
:return: 生成的回复文本
|
||||
"""
|
||||
try:
|
||||
msg_id = self._manage_conversation_history(user_id, prompt)
|
||||
chat_info = self.conversation_history.get(user_id, {})
|
||||
|
||||
payload = {
|
||||
"chatId": chat_info.get("chat_id"),
|
||||
"stream": False,
|
||||
"detail": detail,
|
||||
"responseChatItemId": msg_id,
|
||||
"variables": variables or {},
|
||||
"messages": [{"role": "user", "content": prompt}]
|
||||
}
|
||||
|
||||
response = requests.post(
|
||||
f"{self.base_url}/chat/completions",
|
||||
headers=self.headers,
|
||||
json=payload,
|
||||
timeout=self.timeout
|
||||
)
|
||||
response.raise_for_status()
|
||||
|
||||
result = response.json()
|
||||
|
||||
# 处理响应
|
||||
if detail:
|
||||
response_text = result.get("responseData", {}).get("content", "响应解析失败")
|
||||
else:
|
||||
response_text = result.get("content", "响应解析失败")
|
||||
|
||||
# 保存助手回复到会话历史
|
||||
if user_id in self.conversation_history:
|
||||
self.conversation_history[user_id]["messages"].append({
|
||||
"role": "assistant",
|
||||
"content": response_text
|
||||
})
|
||||
|
||||
return response_text
|
||||
|
||||
except requests.exceptions.ConnectionError:
|
||||
logger.error("无法连接FastGPT服务")
|
||||
return "服务连接失败"
|
||||
|
||||
except requests.exceptions.Timeout:
|
||||
logger.warning("FastGPT请求超时")
|
||||
return "响应超时"
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"FastGPT处理异常: {str(e)}", exc_info=True)
|
||||
return "服务暂时不可用"
|
||||
|
||||
class HybridAIService(AIService):
|
||||
"""混合AI服务（故障转移模式）"""
|
||||
def __init__(self, services: list[AIService]):
|
||||
self.services = services
|
||||
|
||||
def generate_response(self, prompt: str) -> str:
|
||||
for service in self.services:
|
||||
try:
|
||||
return service.generate_response(prompt)
|
||||
except Exception as e:
|
||||
logger.warning(f"{type(service).__name__} 服务失败: {str(e)}")
|
||||
continue
|
||||
return "所有AI服务不可用"
|
||||
|
||||
class MessageHandler:
|
||||
"""智能消息处理器"""
|
||||
def __init__(self, keyword_config: Dict, ai_service: AIService):
|
||||
"""
|
||||
:param keyword_config: 关键词配置字典
|
||||
:param ai_service: AI服务实例
|
||||
"""
|
||||
self.keyword_config = keyword_config
|
||||
self.ai_service = ai_service
|
||||
|
||||
def get_reply(self, content: str) -> str:
|
||||
# 优先全匹配关键词
|
||||
for rule in self.keyword_config.values():
|
||||
if any(kw == content.strip() for kw in rule['keywords']):
|
||||
return rule['reply']
|
||||
|
||||
# 其次模糊匹配
|
||||
for rule in self.keyword_config.values():
|
||||
if any(kw in content for kw in rule['keywords']):
|
||||
return rule['reply']
|
||||
|
||||
# 无匹配时调用AI
|
||||
return self.ai_service.generate_response(content)
|
||||
219
callback1.py
Normal file
219
callback1.py
Normal file
@ -0,0 +1,219 @@
|
||||
from config import AgentId,Secret,corpid,token,encodingAESKey
|
||||
#import xml.etree.ElementTree as ET
|
||||
from flask import Flask,request
|
||||
from WXBizMsgCrypt import WXBizMsgCrypt
|
||||
import base64,hashlib
|
||||
from Crypto.Cipher import AES
|
||||
import time
|
||||
from xml.etree import ElementTree
|
||||
from keyword_config import KEYWORD_REPLIES
|
||||
from ai_service import OllamaService,MessageHandler,DifyService
|
||||
from typing import Dict
|
||||
from config import OPENAI_API_KEY, OPENAI_MODEL, OPENAI_BASE_URL,DIFY_API_KEY,DIFY_BASE_URL
|
||||
from config import FASTAPI_BASE_URL, FASTAPI_API_KEY
|
||||
import re
|
||||
|
||||
from ai_service import OpenAIService,FastGptService
|
||||
app =Flask(__name__)
|
||||
wxcpt = WXBizMsgCrypt(token,encodingAESKey,corpid)
|
||||
#ai_service = OllamaService()
|
||||
ai_service = OpenAIService(OPENAI_API_KEY, OPENAI_MODEL, OPENAI_BASE_URL)
|
||||
#ai_service = DifyService(DIFY_API_KEY,DIFY_BASE_URL)
|
||||
#ai_service = FastGptService(FASTAPI_API_KEY, FASTAPI_BASE_URL)
|
||||
|
||||
# 检查base64编码后数据位数是否正确
|
||||
def check_base64_len(base64_str):
|
||||
len_remainder = 4 - (len(base64_str) % 4)
|
||||
if len_remainder == 0:
|
||||
return base64_str
|
||||
else:
|
||||
for temp in range(0,len_remainder):
|
||||
base64_str = base64_str + "="
|
||||
return base64_str
|
||||
# 解密并提取消息正文
|
||||
def msg_base64_decrypt(ciphertext_base64,key_base64):
|
||||
# 处理密文、密钥和iv
|
||||
ciphertext_bytes = base64.b64decode(check_base64_len(ciphertext_base64))
|
||||
key_bytes = base64.b64decode(check_base64_len(key_base64))
|
||||
iv_bytes = key_bytes[:16]
|
||||
|
||||
# 解密
|
||||
decr = AES.new(key_bytes,AES.MODE_CBC,iv_bytes)
|
||||
plaintext_bytes = decr.decrypt(ciphertext_bytes)
|
||||
|
||||
# 截取数据，判断消息正文字节数
|
||||
msg_len_bytes = plaintext_bytes[16:20]
|
||||
msg_len = int.from_bytes(msg_len_bytes,byteorder='big', signed=False)
|
||||
|
||||
# 根据消息正文字节数截取消息正文，并转为字符串格式
|
||||
msg_bytes = plaintext_bytes[20:20+msg_len]
|
||||
msg = str(msg_bytes,encoding='utf-8')
|
||||
|
||||
return msg
|
||||
# 消息体签名校验
|
||||
def check_msg_signature(msg_signature,token,timestamp,nonce,echostr):
|
||||
# 使用sort()从小到大排序[].sort()是在原地址改值的，所以如果使用li_s = li.sort()，li_s是空的，li的值变为排序后的值]
|
||||
li = [token,timestamp,nonce,echostr]
|
||||
li.sort()
|
||||
# 将排序结果拼接
|
||||
li_str = li[0]+li[1]+li[2]+li[3]
|
||||
|
||||
# 计算SHA-1值
|
||||
sha1 = hashlib.sha1()
|
||||
# update()要指定加密字符串字符代码，不然要报错：
|
||||
# "Unicode-objects must be encoded before hashing"
|
||||
sha1.update(li_str.encode("utf8"))
|
||||
sha1_result = sha1.hexdigest()
|
||||
|
||||
# 比较并返回比较结果
|
||||
if sha1_result == msg_signature:
|
||||
return True
|
||||
else:
|
||||
return False
|
||||
@app.route('/hello', methods=['GET'])
|
||||
def hello():
|
||||
return "Hello, Flask!"
|
||||
|
||||
@app.route('/', methods=['GET', 'POST'])
|
||||
def reply():
|
||||
try:
|
||||
# 处理GET请求(验证URL)部分保持不变
|
||||
if request.method == 'GET':
|
||||
msg_signature = request.args.to_dict().get("msg_signature")
|
||||
timestamp = request.args.to_dict().get("timestamp")
|
||||
nonce = request.args.to_dict().get("nonce")
|
||||
echostr = request.args.to_dict().get("echostr")
|
||||
print(msg_signature,timestamp,nonce,echostr)
|
||||
# 获取消息体签名校验结果
|
||||
check_result = check_msg_signature(msg_signature,token,timestamp,nonce,echostr)
|
||||
if check_result:
|
||||
decrypt_result = msg_base64_decrypt(echostr,encodingAESKey)
|
||||
print("通过")
|
||||
return decrypt_result
|
||||
else:
|
||||
return ""
|
||||
|
||||
# 处理POST请求(消息处理)
|
||||
elif request.method == 'POST':
|
||||
try:
|
||||
# 获取并解析原始数据部分保持不变
|
||||
raw_data = request.get_data()
|
||||
if isinstance(raw_data, bytes):
|
||||
raw_data = raw_data.decode('utf-8')
|
||||
|
||||
# 获取参数验证部分保持不变
|
||||
msg_signature = request.args.get('msg_signature', '')
|
||||
timestamp = str(request.args.get('timestamp', ''))
|
||||
nonce = request.args.get('nonce', '')
|
||||
|
||||
if not all([msg_signature, timestamp, nonce]):
|
||||
return "缺少必要参数", 400
|
||||
|
||||
# 解密消息部分保持不变
|
||||
ret, xml_content = wxcpt.DecryptMsg(
|
||||
raw_data,
|
||||
msg_signature,
|
||||
timestamp,
|
||||
nonce
|
||||
)
|
||||
|
||||
if ret != 0:
|
||||
print(f"[ERROR] 解密失败，错误码: {ret}")
|
||||
return "消息解密失败", 500
|
||||
|
||||
# 解析XML
|
||||
xml_tree = ElementTree.fromstring(xml_content)
|
||||
|
||||
def get_text(element):
|
||||
if element is None:
|
||||
return ''
|
||||
text = element.text
|
||||
if text is None:
|
||||
return ''
|
||||
return text.decode('utf-8') if isinstance(text, bytes) else str(text)
|
||||
|
||||
# 获取用户ID和消息内容
|
||||
from_user_name = get_text(xml_tree.find('FromUserName'))
|
||||
msg_content = get_text(xml_tree.find('Content'))
|
||||
|
||||
# 处理刷新对话的关键词
|
||||
refresh_keywords = ["new", "refresh", "00", "restart", "刷新", "新话题", "退下", "结束", "over"]
|
||||
if msg_content.strip().lower() in refresh_keywords:
|
||||
if hasattr(ai_service, 'conversation_history') and from_user_name in ai_service.conversation_history:
|
||||
del ai_service.conversation_history[from_user_name]
|
||||
re_text = "会话已重置"
|
||||
else:
|
||||
# 使用用户ID生成回复
|
||||
msg_handler = MessageHandler(KEYWORD_REPLIES, ai_service)
|
||||
re_text = msg_handler.get_reply(msg_content)
|
||||
if isinstance(ai_service, OpenAIService):
|
||||
re_text = ai_service.generate_response(msg_content, user_id=from_user_name)
|
||||
|
||||
# 处理回复文本
|
||||
re_text = process_text(re_text)
|
||||
|
||||
# 构造回复消息
|
||||
reply_dict = {
|
||||
'ToUserName': from_user_name,
|
||||
'FromUserName': get_text(xml_tree.find('ToUserName')),
|
||||
'CreateTime': str(int(time.time())),
|
||||
'MsgType': 'text',
|
||||
'Content': re_text
|
||||
}
|
||||
|
||||
# 构造XML回复并加密
|
||||
reply_msg = ResponseMessage(reply_dict).xml
|
||||
|
||||
if isinstance(reply_msg, bytes):
|
||||
reply_msg = reply_msg.decode('utf-8')
|
||||
|
||||
ret, encrypt_xml = wxcpt.EncryptMsg(reply_msg, nonce, timestamp)
|
||||
|
||||
if ret != 0:
|
||||
print(f"[ERROR] 加密回复消息失败，错误码: {ret}")
|
||||
return "加密回复消息失败", 500
|
||||
|
||||
return encrypt_xml
|
||||
|
||||
except Exception as e:
|
||||
print(f"[ERROR] 处理消息时发生异常: {str(e)}")
|
||||
return "服务器内部错误", 500
|
||||
|
||||
except Exception as e:
|
||||
print(f"处理异常: {str(e)}")
|
||||
return "服务器错误", 500
|
||||
|
||||
return "success"
|
||||
|
||||
# ResponseMessage类修改
|
||||
class ResponseMessage(object):
|
||||
def __init__(self, dict_data):
|
||||
self.dict_data = {k: str(v) for k, v in dict_data.items()}
|
||||
|
||||
@property
|
||||
def xml(self):
|
||||
xml = "<xml>"
|
||||
for k, v in self.dict_data.items():
|
||||
xml += f"<{k}><![CDATA[{v}]]></{k}>"
|
||||
xml += "</xml>"
|
||||
return xml
|
||||
|
||||
|
||||
def process_text(text):
|
||||
# 1. 把所有的 "\n" 替换为 "__lineFeed__"
|
||||
text = text.replace('\n', '__lineFeed__')
|
||||
|
||||
# 2. 删除所有换行符（包括 \r 等）
|
||||
text = re.sub(r'[^\S]+', '', text)
|
||||
|
||||
# 3. 把所有的 "__lineFeed__" 替换回 "\n"
|
||||
text = text.replace('__lineFeed__', '\n')
|
||||
# 4. 删除多余的换行符
|
||||
text = re.sub(r'\n+', '\n', text)
|
||||
return text.strip()
|
||||
|
||||
|
||||
|
||||
|
||||
if __name__ == '__main__':
|
||||
app.run(host='0.0.0.0', port=5000, debug=True)
|
||||
20
ierror.py
Normal file
20
ierror.py
Normal file
@ -0,0 +1,20 @@
|
||||
#!/usr/bin/env python
|
||||
# -*- coding: utf-8 -*-
|
||||
#########################################################################
|
||||
# Author: jonyqin
|
||||
# Created Time: Thu 11 Sep 2014 01:53:58 PM CST
|
||||
# File Name: ierror.py
|
||||
# Description:定义错误码含义
|
||||
#########################################################################
|
||||
WXBizMsgCrypt_OK = 0
|
||||
WXBizMsgCrypt_ValidateSignature_Error = -40001
|
||||
WXBizMsgCrypt_ParseXml_Error = -40002
|
||||
WXBizMsgCrypt_ComputeSignature_Error = -40003
|
||||
WXBizMsgCrypt_IllegalAesKey = -40004
|
||||
WXBizMsgCrypt_ValidateCorpid_Error = -40005
|
||||
WXBizMsgCrypt_EncryptAES_Error = -40006
|
||||
WXBizMsgCrypt_DecryptAES_Error = -40007
|
||||
WXBizMsgCrypt_IllegalBuffer = -40008
|
||||
WXBizMsgCrypt_EncodeBase64_Error = -40009
|
||||
WXBizMsgCrypt_DecodeBase64_Error = -40010
|
||||
WXBizMsgCrypt_GenReturnXml_Error = -40011
|
||||
23
keyword_config.py
Normal file
23
keyword_config.py
Normal file
@ -0,0 +1,23 @@
|
||||
KEYWORD_REPLIES = {
|
||||
'invoice': {
|
||||
'keywords': ['开票', '发票'],
|
||||
'reply': '名 称：厦门路桥勘察设计院有限公司\n纳税人识别号：91350200MAD0EHH44J\n电 话：0592-5828192\n地 址：厦门市湖里区槟城道289号701室\n开户行及账号：中国农业银行厦门市分行营业部40379001040059157'
|
||||
},
|
||||
'price': {
|
||||
'keywords': ['价格', '多少钱'],
|
||||
'reply': '请联系销售人员获取价格信息'
|
||||
},
|
||||
'help': {
|
||||
'keywords': ['帮助', '使用说明'],
|
||||
'reply': '您可以咨询以下内容：\n1. 开票信息\n2. 价格查询\n3. 使用说明'
|
||||
},
|
||||
'test': {
|
||||
'keywords': ['test', '测试'],
|
||||
#'reply': '高空作业有以下规定：\n\n1. 人员必须正确佩戴安全帽、安全带等劳动防护用品，并经过培训持证上岗，否则不准进入作业现场。\n2. 酒后、过度疲劳或患有高血压、心脏病等疾病的人员不准进行高空作业。\n3. 临边洞口、沟槽、坑、屋面周边等边沿未设置临边防护或未采取安全防护措施的，不准进行高空作业。\n4. 未固定或无防护设施的构件及管道上不准作业或通行。\n5. 各类操作平台、载人装置未确认稳定可靠，周边未设置临边防护的，不准上人作业。\n6. 直梯、人字梯、伸缩梯防滑动措施不牢靠、架体不稳定的，不准上人作业。\n\n这些规定旨在确保高空作业的安全性，防止事故发生。'
|
||||
'reply': '''高空作业有以下规定
|
||||
：\n\n1. 人员必须正确佩戴安全帽、安全带等劳动防护用品，并经过培训持证上岗，否则不准进入作业现场。\n2. 酒后、过度疲劳或患有高血压、心脏病等疾病的人员不准进行高空作业。\n3. 临边洞口、沟槽、坑、屋面周边等边沿未设置临边防护或未采取安全防护措施的，不准进行高空作业。\n4. 未固定或无
|
||||
防护设施的构件及管道上不准作业或通行。\n5. 各类操作平台、载人装置未确认稳定可靠，周边未设置临边防护的，不准上人作业。\n6. 直梯、人字梯、伸缩梯防滑动措施不牢靠、架体不稳定的，不准上人作业。\n\n这些规定旨在确保高空作业的安全性，防止事故发生。'''
|
||||
|
||||
# 删除所有空白字符（包括空格、\t、\r），但保留换行符 \n
|
||||
},
|
||||
}
|
||||
Loading…
x
Reference in New Issue
Block a user