"""
知识仪表盘 API — 瓶颈分析、知识条目查询、趋势统计
"""
from __future__ import annotations

import logging
from datetime import datetime, timedelta
from typing import Optional

from fastapi import APIRouter, Depends, Query
from sqlalchemy import func
from sqlalchemy.orm import Session

from app.core.database import get_db
from app.api.auth import get_current_user
from app.models.user import User
from app.models.knowledge_entry import KnowledgeEntry
from app.services.bottleneck_detector import bottleneck_detector
from app.services.optimization_engine import optimization_engine

logger = logging.getLogger(__name__)

router = APIRouter(prefix="/api/v1/knowledge-dashboard", tags=["knowledge-dashboard"])


@router.get("/bottlenecks")
def get_bottlenecks(
    hours: int = Query(168, ge=1, le=2160, description="分析时长（小时）"),
    current_user: User = Depends(get_current_user),
):
    """瓶颈分析 — 检测工作流性能瓶颈并生成优化建议。"""
    analysis = bottleneck_detector.run_full_analysis(hours=hours)
    optimizations = optimization_engine.generate_optimizations(analysis.get("bottlenecks", []))
    # Build recommendations dict keyed by node_type for frontend lookup
    recommendations_map = {}
    for opt in optimizations:
        recommendations_map[opt["node_type"]] = {
            "node_type": opt["node_type"],
            "severity": opt["severity"],
            "current_state": opt.get("current_metrics", {}),
            "changes": opt.get("changes", []),
        }
    return {
        **analysis,
        "recommendations": list(optimizations),
        "optimizations": recommendations_map,
    }


@router.get("/entries")
def get_knowledge_entries(
    days: int = Query(7, ge=1, le=365, description="统计天数"),
    limit: int = Query(50, ge=1, le=200, description="返回条数"),
    db: Session = Depends(get_db),
    current_user: User = Depends(get_current_user),
):
    """获取知识条目列表，按创建时间倒序。"""
    since = datetime.now() - timedelta(days=days)
    entries = (
        db.query(KnowledgeEntry)
        .filter(
            KnowledgeEntry.created_at >= since,
            KnowledgeEntry.is_active == True,
        )
        .order_by(KnowledgeEntry.created_at.desc())
        .limit(limit)
        .all()
    )
    return [e.to_dict() for e in entries]


@router.get("/trend")
def get_knowledge_trend(
    days: int = Query(7, ge=1, le=365, description="统计天数"),
    db: Session = Depends(get_db),
    current_user: User = Depends(get_current_user),
):
    """知识条目增长趋势 — 按天统计新增数量。"""
    since = datetime.now() - timedelta(days=days)

    # GROUP BY date(created_at)
    rows = (
        db.query(
            func.date(KnowledgeEntry.created_at).label("date"),
            func.count(KnowledgeEntry.id).label("count"),
        )
        .filter(
            KnowledgeEntry.created_at >= since,
            KnowledgeEntry.is_active == True,
        )
        .group_by(func.date(KnowledgeEntry.created_at))
        .order_by(func.date(KnowledgeEntry.created_at).asc())
        .all()
    )

    # Fill in missing dates with 0 count
    trend = []
    current_date = since.date()
    end_date = datetime.now().date()
    date_counts = {row.date: row.count for row in rows}

    while current_date <= end_date:
        trend.append({
            "date": current_date.isoformat(),
            "count": date_counts.get(current_date, 0),
        })
        current_date += timedelta(days=1)

    return trend