Update app.py
Browse files
app.py
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@@ -1,8 +1,10 @@
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from flask import Flask, request, make_response
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from openai import OpenAI
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from dotenv import load_dotenv
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app = Flask(__name__)
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# 配置
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TOKEN = os.getenv('
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API_KEY = os.getenv("OPENAI_API_KEY")
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BASE_URL = os.getenv("OPENAI_BASE_URL")
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client = OpenAI(api_key=API_KEY, base_url=BASE_URL)
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@@ -27,16 +29,21 @@ AVAILABLE_MODELS = {
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# 存储用户会话信息
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user_sessions = {}
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def get_openai_response(messages, model="gpt-3.5-turbo"):
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model=model,
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messages=messages
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)
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return response.choices[0].message.content
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except Exception as e:
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print(f"调用OpenAI API时出错: {str(e)}")
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return "抱歉,我遇到了一些问题,无法回答您的问题。"
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def split_message(message, max_length=500):
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return [message[i:i+max_length] for i in range(0, len(message), max_length)]
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@@ -44,58 +51,53 @@ def split_message(message, max_length=500):
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def list_available_models():
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return "\n".join([f"{key}: {value}" for key, value in AVAILABLE_MODELS.items()])
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@app.route('/', methods=['GET', 'POST'])
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def
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if request.method == 'GET':
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if content.lower() == '/models':
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return create_reply(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", msg).render()
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if content.lower().startswith('/model'):
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model = content.split(' ')[1]
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if model in AVAILABLE_MODELS:
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user_sessions[user_id] = {'model': model, 'messages': []}
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return create_reply(f'模型已切换为 {AVAILABLE_MODELS[model]}', msg).render()
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else:
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session['messages'].append({"role": "assistant", "content":
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response_parts = split_message(
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for part in response_parts[:-1]:
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create_reply(part, msg).render()
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return
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if __name__ == '__main__':
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app.run(host='0.0.0.0', port=7860)
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#!/usr/bin/env python
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# -*- coding: utf-8 -*-
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from flask import Flask, request, make_response
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import hashlib
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import time
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import xml.etree.ElementTree as ET
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import os
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from openai import OpenAI
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from dotenv import load_dotenv
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app = Flask(__name__)
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# 配置
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TOKEN = os.getenv('WECHAT_TOKEN')
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API_KEY = os.getenv("OPENAI_API_KEY")
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BASE_URL = os.getenv("OPENAI_BASE_URL")
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client = OpenAI(api_key=API_KEY, base_url=BASE_URL)
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# 存储用户会话信息
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user_sessions = {}
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def verify_wechat(request):
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# 验证逻辑保持不变
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...
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def getUserMessageContentFromXML(xml_content):
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# XML解析逻辑保持不变
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...
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def generate_response_xml(from_user_name, to_user_name, output_content):
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# XML生成逻辑保持不变
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...
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def get_openai_response(messages, model="gpt-3.5-turbo"):
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# OpenAI API调用逻辑保持不变
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...
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def split_message(message, max_length=500):
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return [message[i:i+max_length] for i in range(0, len(message), max_length)]
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def list_available_models():
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return "\n".join([f"{key}: {value}" for key, value in AVAILABLE_MODELS.items()])
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@app.route('/api/wx', methods=['GET', 'POST'])
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def wechatai():
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if request.method == 'GET':
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return verify_wechat(request)
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else:
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# 处理POST请求
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print("user request data: ", request.data)
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user_message_content, from_user_name, to_user_name = getUserMessageContentFromXML(request.data)
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print("user message content: ", user_message_content)
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if user_message_content.lower() == '/models':
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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"
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elif user_message_content.lower().startswith('/model'):
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model = user_message_content.split(' ')[1]
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if model in AVAILABLE_MODELS:
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user_sessions[from_user_name] = {'model': model, 'messages': [], 'pending_response': []}
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response_content = f'模型已切换为 {AVAILABLE_MODELS[model]}'
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else:
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response_content = f'无效的模型名称。可用的模型有:\n{list_available_models()}'
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elif user_message_content.lower() == '继续':
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if from_user_name in user_sessions and user_sessions[from_user_name]['pending_response']:
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response_content = user_sessions[from_user_name]['pending_response'].pop(0)
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if user_sessions[from_user_name]['pending_response']:
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response_content += "\n\n回复"继续"获取下一部分。"
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else:
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response_content += "\n\n回复结束。"
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else:
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response_content = "没有待发送的消息。"
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else:
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if from_user_name not in user_sessions:
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user_sessions[from_user_name] = {'model': 'gpt-3.5-turbo', 'messages': [], 'pending_response': []}
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session = user_sessions[from_user_name]
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session['messages'].append({"role": "user", "content": user_message_content})
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gpt_response = get_openai_response(session['messages'], session['model'])
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session['messages'].append({"role": "assistant", "content": gpt_response})
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response_parts = split_message(gpt_response)
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if len(response_parts) > 1:
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response_content = response_parts[0] + "\n\n回复"继续"获取下一部分。"
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session['pending_response'] = response_parts[1:]
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else:
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response_content = response_parts[0]
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return generate_response_xml(from_user_name, to_user_name, response_content)
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if __name__ == '__main__':
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app.run(host='0.0.0.0', port=7860, debug=True)
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