File size: 8,700 Bytes
89bf662
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
#!/usr/bin/env python
# -*- coding: utf-8 -*-
from flask import Flask, request, make_response
import hashlib
import time
import xml.etree.ElementTree as ET
import os
import json
from openai import OpenAI
from dotenv import load_dotenv
from duckduckgo_search import DDGS
import smtplib
from email.mime.text import MIMEText
from email.mime.multipart import MIMEMultipart

# 加载环境变量
load_dotenv()

app = Flask(__name__)

# 配置
TOKEN = os.getenv('TOKEN')
API_KEY = os.getenv("API_KEY")
BASE_URL = os.getenv("OPENAI_BASE_URL")
EMAIL_KEY = os.getenv("EMAIL_KEY")
client = OpenAI(api_key=API_KEY, base_url=BASE_URL)

# 存储用户会话信息
user_sessions = {}

# 定义函数列表
FUNCTIONS = [
    {
        "name": "search_duckduckgo",
        "description": "使用DuckDuckGo搜索引擎查询信息。可以搜索最新新闻、文章、博客等内容。",
        "parameters": {
            "type": "object",
            "properties": {
                "keywords": {
                    "type": "array",
                    "items": {"type": "string"},
                    "description": "搜索的关键词列表。例如:['Python', '机器学习', '最新进展']。"
                }
            },
            "required": ["keywords"]
        }
    },
    {
        "name": "send_email",
        "description": "发送电子邮件。",
        "parameters": {
            "type": "object",
            "properties": {
                "to": {
                    "type": "string",
                    "description": "收件人邮箱地址"
                },
                "subject": {
                    "type": "string",
                    "description": "邮件主题"
                },
                "content": {
                    "type": "string",
                    "description": "邮件内容"
                }
            },
            "required": ["to", "subject", "content"]
        }
    }
]

def verify_wechat(request):
    # 获取微信服务器发送过来的参数
    data = request.args
    signature = data.get('signature')
    timestamp = data.get('timestamp')
    nonce = data.get('nonce')
    echostr = data.get('echostr')
    
    # 对参数进行字典排序,拼接字符串
    temp = [timestamp, nonce, TOKEN]
    temp.sort()
    temp = ''.join(temp)
    
    # 加密
    if (hashlib.sha1(temp.encode('utf8')).hexdigest() == signature):
        return echostr
    else:
        return 'error', 403

def getUserMessageContentFromXML(xml_content):
    # 解析XML字符串
    root = ET.fromstring(xml_content)
    # 提取数据
    content = root.find('Content').text
    from_user_name = root.find('FromUserName').text
    to_user_name = root.find('ToUserName').text
    return content, from_user_name, to_user_name

def generate_response_xml(from_user_name, to_user_name, output_content):
    output_xml = '''
    <xml>
        <ToUserName><![CDATA[%s]]></ToUserName>
        <FromUserName><![CDATA[%s]]></FromUserName>
        <CreateTime>%s</CreateTime>
        <MsgType><![CDATA[text]]></MsgType>
        <Content><![CDATA[%s]]></Content>
    </xml>'''
    
    response = make_response(output_xml % (from_user_name, to_user_name, str(int(time.time())), output_content))
    response.content_type = 'application/xml'
    return response

def get_openai_response(messages, functions=None, function_call=None):
    try:
        response = client.chat.completions.create(
            model="gpt-4o-mini",
            messages=messages,
            functions=functions,
            function_call=function_call
        )
        return response.choices[0].message
    except Exception as e:
        print(f"调用OpenAI API时出错: {str(e)}")
        return None

def split_message(message, max_length=500):
    return [message[i:i+max_length] for i in range(0, len(message), max_length)]

def search_duckduckgo(keywords):
    search_term = " ".join(keywords)
    with DDGS() as ddgs:
        return list(ddgs.text(keywords=search_term, region="cn-zh", safesearch="on", max_results=5))

def send_email(to, subject, content):
    try:
        with smtplib.SMTP('106.15.184.28', 8025) as smtp:
            smtp.login("jwt", EMAIL_KEY)
            message = MIMEMultipart()
            message['From'] = "Me <[email protected]>"
            message['To'] = to
            message['Subject'] = subject
            message.attach(MIMEText(content, 'html'))
            smtp.sendmail("[email protected]", to, message.as_string())
        return True
    except Exception as e:
        print(f"发送邮件时出错: {str(e)}")
        return False

def process_function_call(response_message, session):
    function_name = response_message.function_call.name
    function_args = json.loads(response_message.function_call.arguments)
    print(f"\n模型选择调用函数: {function_name}")
    
    if function_name == "search_duckduckgo":
        keywords = function_args.get('keywords', [])
        if not keywords:
            print("错误:模型没有提供搜索关键词")
            return None
        print(f"关键词: {', '.join(keywords)}")
        return search_duckduckgo(keywords)
    elif function_name == "send_email":
        to = function_args.get('to')
        subject = function_args.get('subject')
        content = function_args.get('content')
        if not session.get('email_sent', False):
            if send_email(to, subject, content):
                session['email_sent'] = True
                return "邮件发送成功"
            else:
                return "邮件发送失败"
        else:
            return "邮件已经发送过,不再重复发送。"
    else:
        print(f"未知的函数名称: {function_name}")
        return None

@app.route('/api/wx', methods=['GET', 'POST'])
def wechatai():
    if request.method == 'GET':
        return verify_wechat(request)
    else:
        # 处理POST请求
        print("user request data: ", request.data)
        user_message_content, from_user_name, to_user_name = getUserMessageContentFromXML(request.data)
        print("user message content: ", user_message_content)

        if from_user_name not in user_sessions:
            user_sessions[from_user_name] = {'messages': [], 'pending_response': [], 'email_sent': False}

        session = user_sessions[from_user_name]

        if user_message_content.lower() == '继续':
            if session['pending_response']:
                response_content = session['pending_response'].pop(0)
                if session['pending_response']:
                    response_content += '\n\n回复"继续"获取下一部分。'
                else:
                    response_content += '\n\n回复结束。'
            else:
                response_content = "没有待发送的消息。"
        else:
            session['messages'].append({"role": "user", "content": user_message_content})
            
            response_message = get_openai_response(session['messages'], functions=FUNCTIONS, function_call="auto")
            
            if response_message.function_call:
                function_response = process_function_call(response_message, session)
                if function_response:
                    session['messages'].extend([
                        response_message.model_dump(),
                        {
                            "role": "function",
                            "name": response_message.function_call.name,
                            "content": json.dumps(function_response, ensure_ascii=False)
                        }
                    ])
                    final_response = get_openai_response(session['messages'])
                    if final_response:
                        gpt_response = final_response.content
                    else:
                        gpt_response = "抱歉,我遇到了一些问题,无法回答您的问题。"
                else:
                    gpt_response = "抱歉,我在执行任务时遇到了问题。"
            else:
                gpt_response = response_message.content

            session['messages'].append({"role": "assistant", "content": gpt_response})

            response_parts = split_message(gpt_response)
            
            if len(response_parts) > 1:
                response_content = response_parts[0] + '\n\n回复"继续"获取下一部分。'
                session['pending_response'] = response_parts[1:]
            else:
                response_content = response_parts[0]

        return generate_response_xml(from_user_name, to_user_name, response_content)

if __name__ == '__main__':
    app.run(host='0.0.0.0', port=7860, debug=True)