app.py

#!/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
from openai import OpenAI
from dotenv import load_dotenv

# 加载环境变量
load_dotenv()

app = Flask(__name__)

# 配置
TOKEN = os.getenv('WECHAT_TOKEN')
API_KEY = os.getenv("OPENAI_API_KEY")
BASE_URL = os.getenv("OPENAI_BASE_URL")
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-4': 'GPT-4',
    'gpt-4-turbo': 'GPT-4 Turbo',
}

# 存储用户会话信息
user_sessions = {}

def verify_wechat(request):
    # 验证逻辑保持不变
    ...

def getUserMessageContentFromXML(xml_content):
    # XML解析逻辑保持不变
    ...

def generate_response_xml(from_user_name, to_user_name, output_content):
    # XML生成逻辑保持不变
    ...

def get_openai_response(messages, model="gpt-3.5-turbo"):
    # OpenAI API调用逻辑保持不变
    ...

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)

        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"
        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': []}
                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()}'
        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']:
                    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-3.5-turbo', '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['model'])
            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)