memind/rain-service/llm-analysis.mjs

function stripRainSkillPrefix(text) {
  let next = String(text ?? '').trim();
  next = next.replace(/^【Rain[^】]*】\s*/u, '');
  next = next.replace(/^请使用\s+rain\s+技能[:：]\s*/iu, '');
  if (/^请描述要分析的时间区间/u.test(next)) {
    const marker = '我的问题是：';
    const idx = next.indexOf(marker);
    if (idx >= 0) next = next.slice(idx + marker.length);
  }
  return next.trim();
}

function parseRainLlmJson(raw) {
  const text = String(raw ?? '').trim();
  const fenced = text.match(/```(?:json)?\s*([\s\S]*?)```/i);
  const candidate = fenced?.[1]?.trim() || text;
  try {
    return JSON.parse(candidate);
  } catch {
    return null;
  }
}

/**
 * @param {{ llmProviderService: object, userQuery: string, meinputBlock: string, timeRangeLabel: string, recordCount: number }} input
 */
export async function runRainLlmAnalysis(input) {
  const userQuery = stripRainSkillPrefix(input.userQuery);
  const system = [
    '你是 TKMind Rain 分析层。只能依据【MeInput 原始输入】块中的内容做归纳，禁止引用或编造长期记忆、聊天历史、日程等外部信息。',
    '输出必须是单个 JSON 对象，不要 markdown，不要代码围栏，字段如下：',
    '{"needs_clarification":boolean,"clarification_question":string|null,"user_goal":string,"meinput_analysis":string,"suggested_next_steps":string[],"user_reply":string}',
    '- needs_clarification=true 时：clarification_question 必填，user_reply 用自然语言向用户追问；meinput_analysis 可为空。',
    '- needs_clarification=false 时：meinput_analysis 按时间线归纳用户在各 App 的输入活动；user_reply 是可直接展示给用户的中文回复（含区间说明）；suggested_next_steps 供下游 Agent 参考（如生成报告页、继续追问）。',
    '- 不要把内部排序分数、source 字段名暴露给用户。',
  ].join('\n');

  const user = [
    `时间区间：${input.timeRangeLabel}`,
    `记录条数：${input.recordCount}`,
    '',
    input.meinputBlock,
    '',
    `用户诉求：${userQuery || '请总结我在上述区间的输入活动'}`,
  ].join('\n');

  const completion = await input.llmProviderService.createChatCompletion({
    messages: [
      { role: 'system', content: system },
      { role: 'user', content: user },
    ],
  });

  if (!completion?.ok) {
    const err = new Error(completion?.message ?? 'Rain LLM 分析失败');
    err.code = 'RAIN_LLM_FAILED';
    throw err;
  }

  const parsed = parseRainLlmJson(completion.reply);
  if (!parsed || typeof parsed !== 'object') {
    return {
      needs_clarification: false,
      clarification_question: null,
      user_goal: userQuery || '回顾 MeInput 输入',
      meinput_analysis: String(completion.reply ?? '').trim(),
      suggested_next_steps: [],
      user_reply: String(completion.reply ?? '').trim(),
      raw: completion.reply,
    };
  }

  return {
    needs_clarification: Boolean(parsed.needs_clarification),
    clarification_question: parsed.clarification_question ?? null,
    user_goal: String(parsed.user_goal ?? userQuery ?? '').trim(),
    meinput_analysis: String(parsed.meinput_analysis ?? '').trim(),
    suggested_next_steps: Array.isArray(parsed.suggested_next_steps)
      ? parsed.suggested_next_steps.map((s) => String(s).trim()).filter(Boolean)
      : [],
    user_reply: String(parsed.user_reply ?? '').trim(),
    raw: completion.reply,
  };
}

export function buildRainGooseHandoffText({
  userQuery,
  timeRangeLabel,
  recordCount,
  analysis,
  userGoal,
  suggestedNextSteps = [],
}) {
  const steps =
    suggestedNextSteps.length > 0
      ? suggestedNextSteps.map((s) => `- ${s}`).join('\n')
      : '- （无明确工具动作，先给用户文字总结）';

  return [
    '[Rain · MeInput 分析简报]',
    '以下简报由 Rain 分析层基于 MeInput 全量原始输入生成。请据此决定如何回复用户、是否调用工具或 skill；不要重复询问时间区间。',
    '',
    `时间区间：${timeRangeLabel}`,
    `原始记录条数：${recordCount}`,
    `用户诉求：${userGoal || stripRainSkillPrefix(userQuery)}`,
    '',
    '【分析归纳】',
    analysis || '（无）',
    '',
    '【建议下一步】',
    steps,
    '',
    '【用户原始问题】',
    stripRainSkillPrefix(userQuery),
  ].join('\n');
}

export { stripRainSkillPrefix };