'use strict';

const crypto = require('crypto');
const axios = require('axios');
const { COS } = require('./cos-bridge');
const { validateSession } = require('./email-auth');

// ─── 常量 ───
const TRAINING_INTERVAL = 6 * 60 * 60 * 1000; // 6小时训练一次
const COS_TRAINING_PATH = 'agent-training/v1/';
const MODEL_VERSION = 'glada-v1.0';

// ─── 训练状态存储 ───
const trainingState = {
  lastRun: null,
  nextRun: Date.now() + TRAINING_INTERVAL,
  isRunning: false
};

// ─── 训练执行器 ───
async function runTraining(sessionToken) {
  if (trainingState.isRunning) return;
  
  trainingState.isRunning = true;
  trainingState.lastRun = Date.now();
  trainingState.nextRun = Date.now() + TRAINING_INTERVAL;
  
  try {
    // 验证会话
    const session = validateSession(sessionToken);
    if (!session.valid) throw new Error('Invalid session');
    
    // 获取训练数据
    const trainingData = await fetchTrainingData();
    
    // 训练模型
    const modelSnapshot = await trainModel(trainingData);
    
    // 存储到COS
    const cosKey = `${COS_TRAINING_PATH}${MODEL_VERSION}/${Date.now()}.model`;
    await COS.upload(cosKey, modelSnapshot);
    
    console.log(`[Agent Training] 训练完成，模型已存储: ${cosKey}`);
  } catch (err) {
    console.error(`[Agent Training] 训练失败: ${err.message}`);
  } finally {
    trainingState.isRunning = false;
  }
}

// ─── 获取训练数据 ───
async function fetchTrainingData() {
  // 从聊天日志、记忆系统等获取数据
  // 实际实现需要根据具体数据源调整
  return {};
}

// ─── 模型训练 ───
async function trainModel(data) {
  // 这里实现实际的模型训练逻辑
  // 返回训练好的模型快照
  return Buffer.from(JSON.stringify({}));
}

// ─── 定时训练任务 ───
function scheduleTraining() {
  setInterval(() => {
    if (Date.now() >= trainingState.nextRun && !trainingState.isRunning) {
      runTraining();
    }
  }, 60 * 1000); // 每分钟检查一次
}

// 启动定时器
scheduleTraining();

module.exports = {
  runTraining,
  getTrainingState: () => trainingState
};