"""AI AAR Agent — 五问复盘。"""

from app.services.llm_client import LLMClient


async def generate_aar(trigger_event: str, original_plan: str, actual_result: str) -> dict:
    """AI 生成五问复盘。"""
    llm = LLMClient()
    prompt = f"""请进行 AAR 五问复盘：

触发事件：{trigger_event}
原计划：{original_plan}
实际结果：{actual_result}

以 JSON 格式返回：
{{"what_happened": "发生了什么", "why_happened": "为什么发生", "what_worked": "什么做得好", "what_failed": "什么没做好", "what_to_change": "下次怎么改", "lessons": ["教训1", "教训2"], "improvements": [{{"action": "改进措施", "owner": "负责人", "deadline": "截止日期"}}]}}"""
    result = await llm.chat(prompt, temperature=0.4)
    return result if isinstance(result, dict) else {}


async def check_aar_triggers(company_id: str, recent_events: list[dict]) -> list[dict]:
    """检测 AAR 触发条件。"""
    triggers: list[dict] = []
    for event in recent_events:
        if event.get("type") in ["risk_resolved", "funding_completed", "funding_failed", "talent_joined", "talent_left"]:
            triggers.append({
                "trigger_event": event.get("title", ""),
                "trigger_type": event.get("type", ""),
            })
    return triggers