Update app.py

app.py

@@ -5,117 +5,174 @@ import hashlib
 import time
 import xml.etree.ElementTree as ET
 import os
+import json
 from openai import OpenAI
 from dotenv import load_dotenv
+from markdown import markdown
+import re
+from functools import lru_cache
 
 # 加载环境变量
 load_dotenv()
 
 app = Flask(__name__)
 
-# 配置
+# 基础配置
 TOKEN = os.getenv('TOKEN')
 API_KEY = os.getenv("API_KEY")
 BASE_URL = os.getenv("OPENAI_BASE_URL")
 client = OpenAI(api_key=API_KEY, base_url=BASE_URL)
 
-# 存储用户会话信息
+# 用户会话管理
 user_sessions = {}
 
+def convert_markdown_to_wechat(md_text):
+    """将Markdown转换为微信友好的文本格式"""
+    # 转换标题
+    md_text = re.sub(r'^# (.*?)$', r'【标题】\1', md_text, flags=re.MULTILINE)
+    md_text = re.sub(r'^## (.*?)$', r'【子标题】\1', md_text, flags=re.MULTILINE)
+    
+    # 转换粗体和斜体
+    md_text = re.sub(r'\*\*(.*?)\*\*', r'『\1』', md_text)
+    md_text = re.sub(r'\*(.*?)\*', r'「\1」', md_text)
+    
+    # 转换列表
+    md_text = re.sub(r'^\- ', '• ', md_text, flags=re.MULTILINE)
+    md_text = re.sub(r'^\d\. ', '○ ', md_text, flags=re.MULTILINE)
+    
+    # 转换代码块
+    md_text = re.sub(r'```(.*?)```', r'【代码】\n\1\n【代码结束】', md_text, flags=re.DOTALL)
+    
+    # 转换引用
+    md_text = re.sub(r'^> (.*?)$', r'▎\1', md_text, flags=re.MULTILINE)
+    
+    return md_text
+
 def verify_wechat(request):
-    # 获取微信服务器发送过来的参数
+    """验证微信服务器请求"""
     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):
+    if hashlib.sha1(temp.encode('utf8')).hexdigest() == signature:
         return echostr
-    else:
-        return 'error', 403
+    return 'error', 403
 
-def getUserMessageContentFromXML(xml_content):
-    # 解析XML字符串
+def parse_xml_message(xml_content):
+    """解析微信XML消息"""
     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
+    return {
+        'content': root.find('Content').text,
+        'from_user': root.find('FromUserName').text,
+        'to_user': root.find('ToUserName').text,
+        'msg_id': root.find('MsgId').text,
+        'create_time': root.find('CreateTime').text
+    }
 
-def generate_response_xml(from_user_name, to_user_name, output_content):
-    output_xml = '''
+def generate_response_xml(to_user, from_user, content):
+    """生成回复的XML消息"""
+    response_content = convert_markdown_to_wechat(content)
+    xml_template = '''
     <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))
+    </xml>
+    '''
+    response = make_response(
+        xml_template % (to_user, from_user, str(int(time.time())), response_content)
+    )
     response.content_type = 'application/xml'
     return response
 
-def get_openai_response(messages):
+def get_openai_response(messages, timeout=30):
+    """获取OpenAI API响应"""
     try:
         response = client.chat.completions.create(
             model="gpt-4o-mini",
-            messages=messages
+            messages=messages,
+            timeout=timeout
         )
         return response.choices[0].message.content
     except Exception as e:
-        print(f"调用OpenAI API时出错: {str(e)}")
-        return "抱歉，我遇到了一些问题，无法回答您的问题。"
+        print(f"OpenAI API错误: {str(e)}")
+        return "抱歉，我暂时无法回答，请稍后再试。"
 
 def split_message(message, max_length=500):
+    """将长消息分段"""
     return [message[i:i+max_length] for i in range(0, len(message), max_length)]
 
+def cache_response_parts(user_id, parts):
+    """缓存分段消息"""
+    if not parts:
+        return
+    user_sessions[user_id] = {
+        'pending_parts': parts,
+        'timestamp': time.time()
+    }
+
+def get_cached_response(user_id):
+    """获取缓存的消息"""
+    session = user_sessions.get(user_id)
+    if not session or not session['pending_parts']:
+        return None
+    
+    # 检查缓存是否过期（1小时后过期）
+    if time.time() - session['timestamp'] > 3600:
+        del user_sessions[user_id]
+        return None
+        
+    next_part = session['pending_parts'].pop(0)
+    if not session['pending_parts']:
+        del user_sessions[user_id]
+    return next_part
+
 @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 user_message_content.lower() == '继续':
-            if from_user_name in user_sessions and user_sessions[from_user_name]['pending_response']:
-                response_content = user_sessions[from_user_name]['pending_response'].pop(0)
-                if user_sessions[from_user_name]['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:
-            if from_user_name not in user_sessions:
-                user_sessions[from_user_name] = {'messages': [], 'pending_response': []}
-
-            session = user_sessions[from_user_name]
-            session['messages'].append({"role": "user", "content": user_message_content})
-            
-            gpt_response = get_openai_response(session['messages'])
-            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)
+    
+    try:
+        message_data = parse_xml_message(request.data)
+        user_content = message_data['content']
+        from_user = message_data['from_user']
+        to_user = message_data['to_user']
+        
+        # 处理"继续"指令
+        if user_content.strip() == '继续':
+            cached_response = get_cached_response(from_user)
+            if cached_response:
+                return generate_response_xml(
+                    from_user,
+                    to_user,
+                    f"{cached_response}\n\n{'回复"继续"查看下一部分' if user_sessions.get(from_user) else '全部内容已发送完毕'}"
+                )
+        
+        # 处理普通消息
+        response = get_openai_response([{"role": "user", "content": user_content}])
+        if len(response) > 500:
+            parts = split_message(response)
+            first_part = parts.pop(0)
+            cache_response_parts(from_user, parts)
+            response = f"{first_part}\n\n回复"继续"查看下一部分"
+        
+        return generate_response_xml(from_user, to_user, response)
+        
+    except Exception as e:
+        print(f"处理请求时出错: {str(e)}")
+        return generate_response_xml(
+            message_data['from_user'],
+            message_data['to_user'],
+            "抱歉，系统暂时出现问题，请稍后重试。"
+        )
 
 if __name__ == '__main__':
     app.run(host='0.0.0.0', port=7860, debug=True)