Update app.py

app.py

@@ -5,8 +5,14 @@ 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 requests
+import smtplib
+from email.mime.text import MIMEText
+from email.mime.multipart import MIMEMultipart
 
 # 加载环境变量
 load_dotenv()
@@ -14,21 +20,118 @@ load_dotenv()
 app = Flask(__name__)
 
 # 配置
-TOKEN = os.getenv('TOKEN')
-API_KEY = os.getenv("API_KEY")
+TOKEN = os.getenv('WECHAT_TOKEN')
+API_KEY = os.getenv("OPENAI_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-4': 'GPT-4',
+    'gpt-4-turbo': 'GPT-4 Turbo',
 }
 
 # 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
@@ -71,70 +174,124 @@ def generate_response_xml(from_user_name, to_user_name, output_content):
     response.content_type = 'application/xml'
     return response
 
-def get_openai_response(messages, model="gpt-4o-mini"):
+def get_openai_response(messages, model="gpt-3.5-turbo", functions=None, function_call=None):
     try:
         response = client.chat.completions.create(
             model=model,
-            messages=messages
+            messages=messages,
+            functions=functions,
+            function_call=function_call
         )
-        return response.choices[0].message.content
+        return response.choices[0].message
     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。"
+        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)]
 
-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():
     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)
+        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-3.5-turbo', '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:
-                user_sessions[from_user_name] = {'model': model, 'messages': [], 'pending_response': []}
+                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 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']:
+            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:
-            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]
-            session['messages'].append({"role": "user", "content": user_message_content})
+            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)
             
-            gpt_response = get_openai_response(session['messages'], session['model'])
-            session['messages'].append({"role": "assistant", "content": gpt_response})
-
-            response_parts = split_message(gpt_response)
+            session['messages'].append(ai_response.model_dump())
+            session['messages'].append({
+                "role": "function",
+                "name": function_name,
+                "content": json.dumps(function_result, ensure_ascii=False)
+            })
             
-            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]
-
+            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()])
+
 if __name__ == '__main__':
     app.run(host='0.0.0.0', port=7860, debug=True)