Update app.py

app.py

@@ -1,18 +1,12 @@
-#!/usr/bin/env python
-# -*- coding: utf-8 -*-
-from flask import Flask, request, make_response
+import os
+import json
 import hashlib
 import time
 import xml.etree.ElementTree as ET
-import os
-import json
+from flask import Flask, request, make_response
 from openai import OpenAI
 from dotenv import load_dotenv
-from duckduckgo_search import DDGS
-import requests
-import smtplib
-from email.mime.text import MIMEText
-from email.mime.multipart import MIMEMultipart
+from functions import FUNCTIONS, FUNCTIONS_GROUP_1, FUNCTIONS_GROUP_2, process_function_call
 
 # 加载环境变量
 load_dotenv()
@@ -23,138 +17,36 @@ app = Flask(__name__)
 TOKEN = os.getenv('TOKEN')
 API_KEY = os.getenv("API_KEY")
 BASE_URL = os.getenv("OPENAI_BASE_URL")
-emailkey = os.getenv("EMAIL_KEY")
 client = OpenAI(api_key=API_KEY, base_url=BASE_URL)
 
 # 定义可用的模型列表
 AVAILABLE_MODELS = {
-    'gpt-3.5-turbo': 'GPT-3.5 Turbo',
-    'gpt-4o': 'GPT-4o',
-    'gpt-4o-mini': 'GPT-4o-mini',
+    'gpt-4o-mini': 'gpt-4o-mini',
+    'gpt-4o-mini': 'gpt-4o-mini',
+    'gpt-4o-mini': 'gpt-4o-mini',
 }
 
 # 存储用户会话信息
 user_sessions = {}
 
-# 定义函数
-def search_duckduckgo(keywords):
-    search_term = " ".join(keywords)
-    with DDGS() as ddgs:
-        results = list(ddgs.text(keywords=search_term, region="cn-zh", safesearch="on", max_results=5))
-        return [{"title": result['title'], "body": result['body'].replace('\n', ' ')} for result in results]
-
-def search_papers(query):
-    url = f"https://api.crossref.org/works?query={query}"
-    response = requests.get(url)
-    if response.status_code == 200:
-        data = response.json()
-        papers = data['message']['items']
-        processed_papers = []
-        for paper in papers:
-            processed_paper = {
-                "标题": paper.get('title', [''])[0],
-                "作者": ", ".join([f"{author.get('given', '')} {author.get('family', '')}" for author in paper.get('author', [])]),
-                "DOI": paper.get('DOI', ''),
-                "摘要": paper.get('abstract', '').replace('<p>', '').replace('</p>', '').replace('<italic>', '*').replace('</italic>', '*')
-            }
-            processed_papers.append(processed_paper)
-        return processed_papers
-    else:
-        return []
-
-def send_email(to, subject, content):
-    try:
-        with smtplib.SMTP('106.15.184.28', 8025) as smtp:
-            smtp.login("jwt", emailkey)
-            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
-
-# 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": "search_papers",
-        "description": "使用Crossref API搜索学术论文。",
-        "parameters": {
-            "type": "object",
-            "properties": {
-                "query": {
-                    "type": "string",
-                    "description": "搜索查询字符串。例如：'climate change'。"
-                }
-            },
-            "required": ["query"]
-        }
-    },
-    {
-        "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
@@ -187,179 +79,11 @@ def get_openai_response(messages, model="gpt-4o-mini", functions=None, function_
         print(f"调用OpenAI API时出错: {str(e)}")
         return None
 
-def process_function_call(function_name, function_args):
-    if function_name == "search_duckduckgo":
-        keywords = function_args.get('keywords', [])
-        if not keywords:
-            return "搜索关键词为空，无法执行搜索。"
-        return search_duckduckgo(keywords)
-    elif function_name == "search_papers":
-        query = function_args.get('query', '')
-        if not query:
-            return "搜索查询为空，无法执行论文搜索。"
-        return search_papers(query)
-    elif function_name == "send_email":
-        to = function_args.get('to', '')
-        subject = function_args.get('subject', '')
-        content = function_args.get('content', '')
-        if not to or not subject or not content:
-            return "邮件信息不完整，无法发送邮件。"
-        success = send_email(to, subject, content)
-        return {
-            "success": success,
-            "message": "邮件发送成功" if success else "邮件发送失败",
-            "to": to,
-            "subject": subject,
-            "content": content,
-            "is_email": True
-        }
-    else:
-        return "未知的函数调用。"
-
 def split_message(message, max_length=500):
     return [message[i:i+max_length] for i in range(0, len(message), max_length)]
 
-# @app.route('/api/wx', methods=['GET', 'POST'])
-# def wechatai():
-#     if request.method == 'GET':
-#         return verify_wechat(request)
-#     else:
-#         # 处理POST请求
-#         xml_str = request.data
-#         if not xml_str:
-#             return ""
-        
-#         user_message_content, from_user_name, to_user_name = getUserMessageContentFromXML(xml_str)
-        
-#         if from_user_name not in user_sessions:
-#             user_sessions[from_user_name] = {'model': 'gpt-4o-mini', 'messages': [], 'pending_response': []}
-
-#         session = user_sessions[from_user_name]
-        
-#         if user_message_content.lower() == '/models':
-#             response_content = f"可用的模型列表：\n{list_available_models()}\n\n使用 /model 模型名称 来切换模型"
-#             return generate_response_xml(from_user_name, to_user_name, response_content)
-#         elif user_message_content.lower().startswith('/model'):
-#             model = user_message_content.split(' ')[1]
-#             if model in AVAILABLE_MODELS:
-#                 session['model'] = model
-#                 response_content = f'模型已切换为 {AVAILABLE_MODELS[model]}'
-#             else:
-#                 response_content = f'无效的模型名称。可用的模型有：\n{list_available_models()}'
-#             return generate_response_xml(from_user_name, to_user_name, response_content)
-#         elif 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。"
-#             return generate_response_xml(from_user_name, to_user_name, response_content)
-        
-#         session['messages'].append({"role": "user", "content": user_message_content})
-        
-#         # 调用OpenAI API
-#         ai_response = get_openai_response(session['messages'], model=session['model'], functions=FUNCTIONS, function_call="auto")
-        
-#         if ai_response.function_call:
-#             function_name = ai_response.function_call.name
-#             function_args = json.loads(ai_response.function_call.arguments)
-#             function_result = process_function_call(function_name, function_args)
-            
-#             session['messages'].append(ai_response.model_dump())
-#             session['messages'].append({
-#                 "role": "function",
-#                 "name": function_name,
-#                 "content": json.dumps(function_result, ensure_ascii=False)
-#             })
-            
-#             final_response = get_openai_response(session['messages'], model=session['model'])
-#             response_content = final_response.content
-#         else:
-#             response_content = ai_response.content
-        
-#         session['messages'].append({"role": "assistant", "content": response_content})
-        
-#         # 处理长消息
-#         response_parts = split_message(response_content)
-#         if len(response_parts) > 1:
-#             session['pending_response'] = response_parts[1:]
-#             response_content = response_parts[0] + '\n\n回复"继续"获取下一部分。'
-        
-#         return generate_response_xml(from_user_name, to_user_name, response_content)
-# @app.route('/api/wx', methods=['GET', 'POST'])
-# def wechatai():
-#     if request.method == 'GET':
-#         return verify_wechat(request)
-#     else:
-#         # 处理POST请求
-#         xml_str = request.data
-#         if not xml_str:
-#             return ""
-        
-#         user_message_content, from_user_name, to_user_name = getUserMessageContentFromXML(xml_str)
-        
-#         if from_user_name not in user_sessions:
-#             user_sessions[from_user_name] = {'model': 'gpt-4o-mini', 'messages': [], 'pending_response': []}
-
-#         session = user_sessions[from_user_name]
-        
-#         if user_message_content.lower() == '/models':
-#             response_content = f"可用的模型列表：\n{list_available_models()}\n\n使用 /model 模型名称 来切换模型"
-#             return generate_response_xml(from_user_name, to_user_name, response_content)
-#         elif user_message_content.lower().startswith('/model'):
-#             model = user_message_content.split(' ')[1]
-#             if model in AVAILABLE_MODELS:
-#                 session['model'] = model
-#                 response_content = f'模型已切换为 {AVAILABLE_MODELS[model]}'
-#             else:
-#                 response_content = f'无效的模型名称。可用的模型有：\n{list_available_models()}'
-#             return generate_response_xml(from_user_name, to_user_name, response_content)
-#         elif 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。"
-#             return generate_response_xml(from_user_name, to_user_name, response_content)
-        
-#         session['messages'].append({"role": "user", "content": user_message_content})
-        
-#         # 调用OpenAI API
-#         ai_response = get_openai_response(session['messages'], model=session['model'], functions=FUNCTIONS, function_call="auto")
-        
-#         if ai_response.function_call:
-#             function_name = ai_response.function_call.name
-#             function_args = json.loads(ai_response.function_call.arguments)
-#             function_result = process_function_call(function_name, function_args)
-            
-#             session['messages'].append(ai_response.model_dump())
-#             session['messages'].append({
-#                 "role": "function",
-#                 "name": function_name,
-#                 "content": json.dumps(function_result, ensure_ascii=False)
-#             })
-            
-#             # 再次调用OpenAI API，将函数执行结果作为上下文
-#             final_response = get_openai_response(session['messages'], model=session['model'])
-#             response_content = final_response.content
-#         else:
-#             response_content = ai_response.content
-        
-#         session['messages'].append({"role": "assistant", "content": response_content})
-        
-#         # 处理长消息
-#         response_parts = split_message(response_content)
-#         if len(response_parts) > 1:
-#             session['pending_response'] = response_parts[1:]
-#             response_content = response_parts[0] + '\n\n回复"继续"获取下一部分。'
-        
-#         return generate_response_xml(from_user_name, to_user_name, response_content)
+def list_available_models():
+    return "\n".join([f"{key}: {value}" for key, value in AVAILABLE_MODELS.items()])
 
 @app.route('/api/wx', methods=['GET', 'POST'])
 def wechatai():
@@ -377,7 +101,6 @@ def wechatai():
 
         session = user_sessions[from_user_name]
         
-        # 处理特殊命令
         if user_message_content.lower() == '/models':
             response_content = f"可用的模型列表：\n{list_available_models()}\n\n使用 /model 模型名称 来切换模型"
             return generate_response_xml(from_user_name, to_user_name, response_content)
@@ -451,9 +174,6 @@ def wechatai():
             response_content = response_parts[0] + '\n\n回复"继续"获取下一部分。'
         
         return generate_response_xml(from_user_name, to_user_name, response_content)
-        
-def list_available_models():
-    return "\n".join([f"{key}: {value}" for key, value in AVAILABLE_MODELS.items()])
 
 if __name__ == '__main__':
     app.run(host='0.0.0.0', port=7860, debug=True)