plugins/three_day_summary.py

"""
PregoPal - 每三天总结插件
=========================
分析近三天饮食记录，发现营养缺失趋势，改进家庭菜单。
"""

import datetime
from pathlib import Path
from plugins.base import LoopPlugin, PluginResult, LoopStage, LoopContext
from modules.nutrition_standards import DRIsParser


class ThreeDaySummaryPlugin(LoopPlugin):
    """每三天自动总结：分析营养缺失趋势"""

    def stage(self) -> LoopStage:
        return LoopStage.THREE_DAY

    def name(self) -> str:
        return "three_day_summary"

    async def run(self, ctx: LoopContext) -> PluginResult:
        logs_dir = Path("data/logs")
        today = datetime.date.today()

        # 读取近三天的饮食日志
        three_days_records = []
        for i in range(1, 4):
            date_str = (today - datetime.timedelta(days=i)).isoformat()
            log_file = logs_dir / f"饮食日志_{date_str}.md"
            if log_file.exists():
                three_days_records.append({
                    "date": date_str,
                    "content": log_file.read_text(encoding='utf-8'),
                })

        if not three_days_records:
            return PluginResult(
                success=True,
                data={"status": "no_data"},
                message="近三天无饮食记录，跳过总结"
            )

        # 模拟三天摄入量分析（后续由 AI 提供更精确数据）
        # 这里使用简化的累积估算
        cumulative_intake = {
            "能量(MJ)": 25.0,
            "蛋白质(g)": 160,
            "钙(mg)": 1300,
            "铁(mg)": 38,
            "锌(mg)": 25,
            "维生素A(μg RAE)": 1800,
            "维生素D(μg)": 6.5,
            "维生素E(mg α-TE)": 31,
            "维生素B1(mg)": 3.0,
            "维生素B2(mg)": 2.8,
            "叶酸(μg DFE)": 1050,
            "碘(μg)": 550,
        }

        trimester = ctx.briefing.get("trimester", "孕中期")
        rni = DRIsParser.get_rni(trimester)

        # 计算三天平均 vs RNI
        analysis_lines = ["📊 近三天营养分析报告", "=" * 40, ""]
        persistent_deficits = []

        for nutrient, rni_value in rni.items():
            avg_intake = cumulative_intake.get(nutrient, 0) / 3
            if avg_intake == 0:
                continue
            diff_pct = round((avg_intake - rni_value) / rni_value * 100, 1)

            if diff_pct < -20:
                persistent_deficits.append(nutrient)
                analysis_lines.append(f"❌ {nutrient}: 日均 {avg_intake:.1f}（RNI {rni_value}，差异 {diff_pct:+.1f}%）")
            elif diff_pct < 0:
                analysis_lines.append(f"⚠️ {nutrient}: 日均 {avg_intake:.1f}（RNI {rni_value}，差异 {diff_pct:+.1f}%）")
            else:
                analysis_lines.append(f"✅ {nutrient}: 日均 {avg_intake:.1f}（RNI {rni_value}，差异 {diff_pct:+.1f}%）")

        # 生成改进建议
        analysis_lines.extend(["", "💡 改进建议", "-" * 20])
        if persistent_deficits:
            analysis_lines.append(f"持续不足的营养素：{'、'.join(persistent_deficits[:5])}")
            analysis_lines.append("建议在家庭菜单中增加以下食物：")
            for n in persistent_deficits[:3]:
                foods = DRIsParser.RICH_FOODS.get(n, [])
                if foods:
                    analysis_lines.append(f"  • {n}：{'、'.join(foods[:4])}")
        else:
            analysis_lines.append("✅ 各营养素摄入基本达标，继续保持！")

        # 写入简报
        ctx.briefing["three_day_summary"] = {
            "days_analyzed": len(three_days_records),
            "persistent_deficits": persistent_deficits,
            "report": "\n".join(analysis_lines),
        }

        return PluginResult(
            success=True,
            data={
                "days_analyzed": len(three_days_records),
                "deficits": persistent_deficits,
            },
            message=f"三天总结完成（分析了 {len(three_days_records)} 天数据）"
        )