import { Context } from "../../types"
import llm from "../../utils/llm"
import getChatHistory from "./chatHistory"

const agent = async (ctx: Context.Data) => {
  const {
    logger,
    requestId,
    larkCard,
    larkService,
    larkBody: { messageId, msgText, chatId, mentions, rawMsgText },
  } = ctx
  const cardGender = larkCard.child("groupAgent")
  // 回复一个loading的卡片
  const {
    data: { message_id },
  } = await larkService.message.replyCard(
    messageId,
    cardGender.genPendingCard("分析中，请稍等...")
  )
  const updateCard = (content: any) =>
    larkService.message.update(message_id, content)

  // 使用大模型解析用户输入
  const { startTime, endTime } = await llm.timeParser(msgText, requestId)
  logger.info(`Parsed time: startTime: ${startTime}, endTime: ${endTime}`)
  // 更新卡片
  updateCard(cardGender.genPendingCard("正在爬楼中，请稍等..."))
  // 获取聊天记录
  const chatHistory = await getChatHistory(ctx, {
    chatId,
    startTime,
    endTime,
    mentions,
  })
  // 如果没有聊天记录，返回错误信息
  if (chatHistory.length === 0) {
    logger.info("No chat history found")
    return await updateCard(cardGender.genErrorCard("未找到聊天记录"))
  }
  logger.debug(`Chat history: ${JSON.stringify(chatHistory)}`)

  // 根据Mention，拼装原始消息
  let userInput = rawMsgText
  for (const mention of mentions ?? []) {
    if (mention.id.user_id) {
      userInput = userInput.replace(mention.key, mention.name)
    }
  }

  // 调用大模型
  try {
    const llmRes = await llm.invoke(
      "groupAgent",
      {
        userInput,
        chatHistory: JSON.stringify(chatHistory),
        time: new Date().toLocaleString("zh-CN", { timeZone: "Asia/Shanghai" }),
      },
      requestId
    )
    logger.info(
      `LLM invoked successfully, see detail: http://langfuse.ai.srv/project/cm1j2tkj9001gukrgdvc1swuw/sessions/${requestId}`
    )
    await updateCard(cardGender.genSuccessCard(llmRes))
  } catch (error: any) {
    logger.error(`Failed to invoke llm: ${error.message}`)
    await updateCard(cardGender.genErrorCard("LLM调用失败: " + error.message))
  }
}

export default agent