renjianbo
beff3fac8d
- Fix delete agent 500: clean up FK records (agent_llm_logs, permissions, schedules, executions, team_members) and unbind goals/tasks before delete - Remove hardcoded personality templates in Android, replace with dynamic system prompt generation from name + description - Set promptSectionsEnabled=false to bypass PromptComposer for personality - Add Tencent Cloud Linux deployment guide (Docker Compose) - Accumulated backend service updates, frontend UI fixes, Android app changes Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
110 lines
3.5 KiB
Python
110 lines
3.5 KiB
Python
"""
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知识仪表盘 API — 瓶颈分析、知识条目查询、趋势统计
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"""
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from __future__ import annotations
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import logging
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from datetime import datetime, timedelta
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from typing import Optional
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from fastapi import APIRouter, Depends, Query
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from sqlalchemy import func
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from sqlalchemy.orm import Session
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from app.core.database import get_db
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from app.api.auth import get_current_user
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from app.models.user import User
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from app.models.knowledge_entry import KnowledgeEntry
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from app.services.bottleneck_detector import bottleneck_detector
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from app.services.optimization_engine import optimization_engine
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logger = logging.getLogger(__name__)
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router = APIRouter(prefix="/api/v1/knowledge-dashboard", tags=["knowledge-dashboard"])
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@router.get("/bottlenecks")
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def get_bottlenecks(
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hours: int = Query(168, ge=1, le=2160, description="分析时长（小时）"),
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current_user: User = Depends(get_current_user),
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):
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"""瓶颈分析 — 检测工作流性能瓶颈并生成优化建议。"""
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analysis = bottleneck_detector.run_full_analysis(hours=hours)
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optimizations = optimization_engine.generate_optimizations(analysis.get("bottlenecks", []))
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# Build recommendations dict keyed by node_type for frontend lookup
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recommendations_map = {}
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for opt in optimizations:
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recommendations_map[opt["node_type"]] = {
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"node_type": opt["node_type"],
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"severity": opt["severity"],
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"current_state": opt.get("current_metrics", {}),
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"changes": opt.get("changes", []),
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}
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return {
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**analysis,
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"recommendations": list(optimizations),
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"optimizations": recommendations_map,
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}
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@router.get("/entries")
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def get_knowledge_entries(
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days: int = Query(7, ge=1, le=365, description="统计天数"),
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limit: int = Query(50, ge=1, le=200, description="返回条数"),
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db: Session = Depends(get_db),
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current_user: User = Depends(get_current_user),
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):
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"""获取知识条目列表，按创建时间倒序。"""
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since = datetime.now() - timedelta(days=days)
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entries = (
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db.query(KnowledgeEntry)
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.filter(
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KnowledgeEntry.created_at >= since,
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KnowledgeEntry.is_active == True,
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)
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.order_by(KnowledgeEntry.created_at.desc())
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.limit(limit)
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.all()
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)
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return [e.to_dict() for e in entries]
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@router.get("/trend")
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def get_knowledge_trend(
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days: int = Query(7, ge=1, le=365, description="统计天数"),
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db: Session = Depends(get_db),
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current_user: User = Depends(get_current_user),
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):
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"""知识条目增长趋势 — 按天统计新增数量。"""
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since = datetime.now() - timedelta(days=days)
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# GROUP BY date(created_at)
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rows = (
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db.query(
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func.date(KnowledgeEntry.created_at).label("date"),
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func.count(KnowledgeEntry.id).label("count"),
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)
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.filter(
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KnowledgeEntry.created_at >= since,
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KnowledgeEntry.is_active == True,
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)
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.group_by(func.date(KnowledgeEntry.created_at))
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.order_by(func.date(KnowledgeEntry.created_at).asc())
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.all()
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)
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# Fill in missing dates with 0 count
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trend = []
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current_date = since.date()
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end_date = datetime.now().date()
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date_counts = {row.date: row.count for row in rows}
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while current_date <= end_date:
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trend.append({
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"date": current_date.isoformat(),
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"count": date_counts.get(current_date, 0),
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})
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current_date += timedelta(days=1)
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return trend
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