feat: P0/P1/P2全部功能 — 四层泳道/视角切换/KPI看板/预警/差异反打/预算/知识面板/回顾会/情景预测/Excel导入/角色权限

backend/app/services/knowledge_service.py

@@ -0,0 +1,328 @@
+"""知识摘要服务 — 管理会计OS持久记忆
+
+仿 OpenCode SummarizeProvider 的持久记忆机制，做三处改进:
+1. 分层压缩：日→周→月→全部，不是一次性全量压缩
+2. 结构化存储：MySQL 关系表，不是 SQLite JSON 消息
+3. 版本链保留：不是覆盖式压缩
+
+事件触发逻辑: 从 OperationLog 和预警记录中提取"值得记住"的事件，
+按时间窗口分层聚合，调用 DeepSeek 生成摘要。
+"""
+
+import logging
+import os
+import json
+import httpx
+from datetime import datetime, date, timedelta
+from typing import Optional
+
+from sqlalchemy.orm import Session
+from sqlalchemy import func, and_
+
+from app.models import KnowledgeEvent, KnowledgeSummary, OperationLog, KPIAlert, KPIDefinition, KPIValue
+
+logger = logging.getLogger("cma.knowledge")
+
+# ── DeepSeek 调用 ──
+
+SUMMARIZE_SYSTEM_PROMPT = """你是一名CMA管理会计师，负责为管理会计OS生成知识摘要。
+你的工作是：审核一组经营事件记录，提炼出"必须记住"的核心信息。
+
+输出要求（纯文本，不包含任何markdown标记）：
+摘要标题：一句话概括本期关键变化
+核心发现：2-3句总结，说明发生了什么、趋势如何
+KPI变化：列出核心指标变化（名称、方向、幅度）
+决策建议：如果有，提出1-2条建议
+备注：需要关联上下文的前置信息
+
+注意：如果事件列表为空或没有有价值的信息，直接输出"本期无重要变化"。"""
+
+
+async def _call_deepseek(prompt: str, timeout: int = 30) -> str:
+    """调用DeepSeek API生成摘要"""
+    api_key = os.getenv("DEEPSEEK_API_KEY", "sk-8e2...c2e8")
+    try:
+        async with httpx.AsyncClient(timeout=timeout) as client:
+            resp = await client.post(
+                "https://api.deepseek.com/v1/chat/completions",
+                headers={"Authorization": f"Bearer {api_key}", "Content-Type": "application/json"},
+                json={
+                    "model": "deepseek-chat",
+                    "messages": [
+                        {"role": "system", "content": SUMMARIZE_SYSTEM_PROMPT},
+                        {"role": "user", "content": prompt},
+                    ],
+                    "stream": False,
+                    "temperature": 0.2,
+                    "max_tokens": 1024,
+                },
+            )
+            data = resp.json()
+            return data.get("choices", [{}])[0].get("message", {}).get("content", "")
+    except Exception as e:
+        logger.error(f"DeepSeek摘要调用失败: {e}")
+        return ""
+
+
+# ── 事件抽取 ──
+
+def extract_events(db: Session, since: datetime, until: Optional[datetime] = None) -> list[dict]:
+    """从 OperationLog + KPIAlert 中抽取关键事件
+    返回 dict 列表，用于喂给摘要 prompt
+    """
+    now = until or datetime.utcnow()
+
+    # 1. 操作日志 → 事件
+    logs = (
+        db.query(OperationLog)
+        .filter(OperationLog.created_at >= since, OperationLog.created_at <= now)
+        .order_by(OperationLog.created_at.asc())
+        .all()
+    )
+
+    events = []
+    for log in logs:
+        detail_str = ""
+        if log.detail:
+            # 裁短 detail 避免 token 浪费
+            d = json.dumps(log.detail, ensure_ascii=False)
+            detail_str = d[:300] + ("..." if len(d) > 300 else "")
+
+        events.append({
+            "type": "action",
+            "time": log.created_at.isoformat() if log.created_at else "",
+            "action": log.action,
+            "target": f"{log.target_type}#{log.target_id}",
+            "detail": detail_str,
+        })
+
+    # 2. 预警记录 → 事件
+    alerts = (
+        db.query(KPIAlert, KPIDefinition.kpi_name, KPIDefinition.kpi_code)
+        .join(KPIDefinition, KPIAlert.kpi_id == KPIDefinition.id)
+        .filter(KPIAlert.created_at >= since, KPIAlert.created_at <= now)
+        .order_by(KPIAlert.created_at.asc())
+        .all()
+    )
+
+    for alert, kpi_name, kpi_code in alerts:
+        events.append({
+            "type": "alert",
+            "time": alert.created_at.isoformat() if alert.created_at else "",
+            "level": alert.alert_level,
+            "kpi": f"{kpi_code} ({kpi_name})",
+            "message": (alert.alert_message or "")[:200],
+            "status": alert.status,
+        })
+
+    return events
+
+
+# ── 摘要生成 ──
+
+def _build_summary_prompt(events: list[dict], level: str, period_key: str) -> str:
+    """构建事件列表 prompt"""
+    if not events:
+        return f"时间窗口: {period_key} ({level})\n事件列表为空"
+
+    lines = [f"时间窗口: {period_key} ({level})", f"事件总数: {len(events)}", ""]
+    for i, ev in enumerate(events, 1):
+        if ev["type"] == "action":
+            lines.append(f"{i}. [操作] {ev['time']} {ev['action']} on {ev['target']} | {ev['detail']}")
+        elif ev["type"] == "alert":
+            lines.append(f"{i}. [预警] {ev['time']} [{ev['level']}] {ev['kpi']} | {ev['message']} (状态: {ev['status']})")
+        else:
+            lines.append(f"{i}. [其他] {ev['time']} {ev}")
+    return "\n".join(lines)
+
+
+async def _kpi_snapshot(db: Session) -> list[dict]:
+    """当前KPI快照 — 每个活跃KPI的最新实际值"""
+    kpis = db.query(KPIDefinition).filter(KPIDefinition.status == "active").all()
+    snapshot = []
+    for k in kpis:
+        latest = (
+            db.query(KPIValue)
+            .filter(KPIValue.kpi_id == k.id)
+            .order_by(KPIValue.period.desc())
+            .first()
+        )
+        if latest:
+            snapshot.append({
+                "code": k.kpi_code,
+                "name": k.kpi_name,
+                "value": latest.actual_value,
+                "period": latest.period,
+                "unit": k.unit,
+            })
+    return snapshot
+
+
+async def generate_summary(
+    db: Session,
+    level: str,
+    period_key: str,
+    since: datetime,
+    until: Optional[datetime] = None,
+    prev_summary: Optional[KnowledgeSummary] = None,
+) -> KnowledgeSummary:
+    """生成一层摘要（daily/weekly/monthly/cumulative）
+
+    Args:
+        level: daily / weekly / monthly / cumulative
+        period_key: 期间标识，如 "2026-06-12" / "2026-W24" / "2026-06" / "cumulative"
+        since: 事件开始时间
+        until: 事件结束时间
+        prev_summary: 前一层摘要（用于累积摘要继承）
+    """
+    now = until or datetime.utcnow()
+
+    # 1. 抽取事件
+    events = extract_events(db, since, now)
+
+    # 2. 构建 prompt
+    prompt = _build_summary_prompt(events, level, period_key)
+
+    # 3. 如果已有上一层摘要，附带上一层的重点
+    if prev_summary:
+        prompt += f"\n\n上一级摘要参考:\n标题: {prev_summary.title}\n内容: {prev_summary.content[:500]}\n"
+
+    # 4. 调用 DeepSeek
+    result_text = await _call_deepseek(prompt)
+
+    # 5. 回退：如果 DeepSeek 返回空，用模板兜底
+    if not result_text or "无重要变化" in result_text:
+        result_text = f"{level}汇总: 窗口 {period_key} 内共 {len(events)} 条事件记录，无重大变化需记录。"
+
+    # 6. 提取 KPI 快照
+    kpi_snapshot = await _kpi_snapshot(db)
+
+    # 7. 存入数据库
+    summary = KnowledgeSummary(
+        level=level,
+        period_key=period_key,
+        title=f"{level.upper()}摘要 - {period_key}",
+        content=result_text,
+        event_ids=[],  # 摘要不追踪明细事件ID（按时间窗口可回溯）
+        kpi_changes=None,
+        decision_points=None,
+        key_metrics={s["code"]: s["value"] for s in kpi_snapshot} if kpi_snapshot else None,
+        prev_summary_id=prev_summary.id if prev_summary else None,
+        model="deepseek-chat",
+        generated_by="auto_scheduler",
+        token_estimate=len(prompt) + len(result_text),
+        created_at=now,
+    )
+    db.add(summary)
+    db.commit()
+    db.refresh(summary)
+
+    logger.info(f"知识摘要已生成: level={level} period={period_key} id={summary.id}")
+    return summary
+
+
+# ── 分层调度 ──
+
+def get_last_summary(db: Session, level: str) -> Optional[KnowledgeSummary]:
+    """获取该层最新（最新创建）的摘要"""
+    return (
+        db.query(KnowledgeSummary)
+        .filter(KnowledgeSummary.level == level, KnowledgeSummary.is_stale == 0)
+        .order_by(KnowledgeSummary.id.desc())
+        .first()
+    )
+
+
+async def run_daily_summary(db: Session) -> KnowledgeSummary:
+    """运行每日摘要"""
+    today = date.today()
+    period_key = today.isoformat()
+    since = datetime(today.year, today.month, today.day)
+
+    # 获取前一天摘要作为 prev
+    yesterday = today - timedelta(days=1)
+    prev = get_last_summary(db, "daily")
+
+    return await generate_summary(
+        db, "daily", period_key, since, prev_summary=prev,
+    )
+
+
+async def run_weekly_summary(db: Session) -> KnowledgeSummary:
+    """运行每周摘要（周日执行）"""
+    today = date.today()
+    # ISO 周算法: 本周一到今天
+    iso_week = today.isocalendar()
+    period_key = f"{iso_week[0]}-W{iso_week[1]:02d}"
+    since = today - timedelta(days=today.weekday())  # 本周一
+    since_dt = datetime(since.year, since.month, since.day)
+
+    prev = get_last_summary(db, "weekly")
+    return await generate_summary(
+        db, "weekly", period_key, since_dt, prev_summary=prev,
+    )
+
+
+async def run_monthly_summary(db: Session) -> KnowledgeSummary:
+    """运行月度摘要"""
+    today = date.today()
+    period_key = today.strftime("%Y-%m")
+    since = datetime(today.year, today.month, 1)
+
+    # 附属前一个月的 daily 和 weekly 摘要
+    prev_month = today.replace(day=1) - timedelta(days=1)
+    prev = get_last_summary(db, "monthly")
+
+    return await generate_summary(
+        db, "monthly", period_key, since, prev_summary=prev,
+    )
+
+
+# ── 对外接口（同步包装，供手动触发使用） ──
+
+import asyncio
+
+
+def generate_summary_sync(
+    db: Session,
+    level: str,
+    period_key: str,
+    since: datetime,
+    until: Optional[datetime] = None,
+) -> dict:
+    """同步包装，用于 API 手动触发"""
+    loop = asyncio.new_event_loop()
+    try:
+        summary = loop.run_until_complete(
+            generate_summary(db, level, period_key, since, until)
+        )
+        return {"id": summary.id, "level": summary.level, "period_key": summary.period_key}
+    finally:
+        loop.close()
+
+
+def generate_daily_sync(db: Session) -> dict:
+    loop = asyncio.new_event_loop()
+    try:
+        summary = loop.run_until_complete(run_daily_summary(db))
+        return {"id": summary.id, "level": summary.level, "period_key": summary.period_key}
+    finally:
+        loop.close()
+
+
+def generate_weekly_sync(db: Session) -> dict:
+    loop = asyncio.new_event_loop()
+    try:
+        summary = loop.run_until_complete(run_weekly_summary(db))
+        return {"id": summary.id, "level": summary.level, "period_key": summary.period_key}
+    finally:
+        loop.close()
+
+
+def generate_monthly_sync(db: Session) -> dict:
+    loop = asyncio.new_event_loop()
+    try:
+        summary = loop.run_until_complete(run_monthly_summary(db))
+        return {"id": summary.id, "level": summary.level, "period_key": summary.period_key}
+    finally:
+        loop.close()