bc9fa5a798
- 日报/周报进度从 total_submitted_seconds 改为只算 PRODUCTION 阶段 (修复魔法少女 398%→118% 等虚高问题) - 移除日报接收人 17762840667（飞书发送失败） Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
555 lines
21 KiB
Python
555 lines
21 KiB
Python
"""报告生成服务 —— 汇总数据库数据 + 调用 AI 生成摘要"""
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import logging
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from datetime import date, timedelta
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from sqlalchemy.orm import Session
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from sqlalchemy import func as sa_func
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from models import (
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User, Project, Submission, AIToolCost, Role,
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ProjectStatus, WorkType, PhaseGroup,
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)
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from calculations import (
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calc_waste_for_project,
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calc_labor_cost_for_project,
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calc_ai_tool_cost_for_project,
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calc_outsource_cost_for_project,
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calc_overhead_cost_for_project,
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calc_team_efficiency,
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calc_project_settlement,
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)
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from services.ai_service import generate_report_summary
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logger = logging.getLogger(__name__)
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def _fmt_seconds(secs: float) -> str:
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"""秒数格式化为 Xh Xm 或 Xm Xs"""
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if secs <= 0:
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return "0s"
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h = int(secs) // 3600
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m = (int(secs) % 3600) // 60
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s = int(secs) % 60
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if h > 0:
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return f"{h}h {m}m" if m > 0 else f"{h}h"
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if m > 0:
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return f"{m}m {s}s" if s > 0 else f"{m}m"
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return f"{s}s"
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def _fmt_money(amount: float) -> str:
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"""金额格式化"""
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if amount >= 10000:
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return f"¥{amount/10000:.1f}万"
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return f"¥{amount:,.0f}"
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def _is_weekend(d: date) -> bool:
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"""判断是否为周末（周六=5, 周日=6）"""
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return d.weekday() >= 5
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# ──────────────────────────── 日报 ────────────────────────────
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def generate_daily_report(db: Session) -> dict:
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"""
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生成日报，返回结构化数据供飞书卡片使用
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"""
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today = date.today()
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is_weekend = _is_weekend(today)
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weekday_names = ["周一", "周二", "周三", "周四", "周五", "周六", "周日"]
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weekday_label = weekday_names[today.weekday()]
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# 今日提交
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today_subs = db.query(Submission).filter(
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Submission.submit_date == today
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).all()
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today_submitter_ids = set(s.user_id for s in today_subs)
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# 产出只算中期制作阶段的动画秒数
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today_total_secs = sum(
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s.total_seconds for s in today_subs
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if s.total_seconds > 0 and s.project_phase == PhaseGroup.PRODUCTION
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)
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# 未提交人员（仅工作日统计，且排除豁免角色）
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not_submitted = []
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if not is_weekend:
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exempt_role_ids = set(
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r.id for r in db.query(Role).filter(Role.exempt_submission == 1).all()
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)
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all_active_user_ids = set(
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uid for (uid,) in db.query(Submission.user_id).distinct().all()
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)
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for uid in all_active_user_ids:
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if uid not in today_submitter_ids:
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user = db.query(User).filter(User.id == uid).first()
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if user and user.is_active and user.role_id not in exempt_role_ids:
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not_submitted.append(user.name)
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# 进行中项目
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active_projects = db.query(Project).filter(
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Project.status == ProjectStatus.IN_PROGRESS
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).all()
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projects_data = []
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for p in active_projects:
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# 只用中期产出算进度（与项目详情页一致）
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prod_secs = db.query(sa_func.sum(Submission.total_seconds)).filter(
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Submission.project_id == p.id,
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Submission.total_seconds > 0,
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Submission.project_phase == PhaseGroup.PRODUCTION,
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).scalar() or 0
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target = p.target_total_seconds
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progress = round(prod_secs / target * 100, 1) if target > 0 else 0
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proj_today_secs = sum(
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s.total_seconds for s in today_subs
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if s.project_id == p.id and s.total_seconds > 0
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and s.project_phase == PhaseGroup.PRODUCTION
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)
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projects_data.append({
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"name": p.name,
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"progress": progress,
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"today_output": _fmt_seconds(proj_today_secs),
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})
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# 风险检测（使用完整风险引擎）
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full_risks = analyze_project_risks(db)
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risks_data = [
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{
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"name": r["project_name"],
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"level": r["risk_level"],
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"detail": "；".join(r["risk_factors"]),
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}
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for r in full_risks
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]
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# AI 数据上下文
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project_lines = [
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f"- {p['name']}：进度 {p['progress']}%，今日产出 {p['today_output']}"
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for p in projects_data
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]
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risk_lines = [f"- {r['name']}：{r['detail']}" for r in risks_data]
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data_context = (
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f"日期：{today}（{weekday_label}{'，周末' if is_weekend else ''}）\n"
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f"进行中项目：{len(active_projects)} 个\n"
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f"今日提交人次：{len(today_submitter_ids)}\n"
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f"今日总产出：{_fmt_seconds(today_total_secs)}\n"
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)
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if not is_weekend:
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data_context += f"今日未提交人员：{', '.join(not_submitted) if not_submitted else '无'}\n"
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else:
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data_context += "今天是周末，不统计未提交\n"
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data_context += (
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f"各项目情况：\n" + "\n".join(project_lines) + "\n"
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f"风险项目：\n" + ("\n".join(risk_lines) if risk_lines else "无")
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)
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ai_summary = generate_report_summary(data_context, "daily")
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title = f"AirLabs 日报 — {today}（{weekday_label}）"
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return {
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"title": title,
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"report_type": "daily",
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"card_data": {
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"is_weekend": is_weekend,
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"weekday_label": weekday_label,
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"active_project_count": len(active_projects),
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"submitter_count": len(today_submitter_ids),
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"total_output": _fmt_seconds(today_total_secs),
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"not_submitted": not_submitted,
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"projects": projects_data,
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"risks": risks_data,
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"ai_summary": ai_summary,
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},
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}
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# ──────────────────────────── 周报 ────────────────────────────
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def generate_weekly_report(db: Session) -> dict:
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"""生成周报（本周一到当天的数据），返回结构化数据"""
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today = date.today()
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monday = today - timedelta(days=today.weekday())
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week_subs = db.query(Submission).filter(
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Submission.submit_date >= monday,
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Submission.submit_date <= today,
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).all()
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week_submitter_ids = set(s.user_id for s in week_subs)
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# 产出只算中期制作阶段的动画秒数
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week_total_secs = sum(
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s.total_seconds for s in week_subs
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if s.total_seconds > 0 and s.project_phase == PhaseGroup.PRODUCTION
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)
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working_days = min((today - monday).days + 1, 5)
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avg_daily = round(week_total_secs / max(1, len(week_submitter_ids)) / max(1, working_days), 1)
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active_projects = db.query(Project).filter(
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Project.status == ProjectStatus.IN_PROGRESS
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).all()
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projects_data = []
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for p in active_projects:
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# 只用中期产出算进度（与项目详情页一致）
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prod_secs = db.query(sa_func.sum(Submission.total_seconds)).filter(
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Submission.project_id == p.id,
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Submission.total_seconds > 0,
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Submission.project_phase == PhaseGroup.PRODUCTION,
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).scalar() or 0
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target = p.target_total_seconds
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progress = round(prod_secs / target * 100, 1) if target > 0 else 0
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proj_week_secs = sum(
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s.total_seconds for s in week_subs
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if s.project_id == p.id and s.total_seconds > 0
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and s.project_phase == PhaseGroup.PRODUCTION
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)
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projects_data.append({
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"name": p.name,
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"progress": progress,
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"week_output": _fmt_seconds(proj_week_secs),
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})
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# 本周成本
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week_labor = 0.0
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processed = set()
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for s in week_subs:
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key = (s.user_id, s.submit_date)
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if key not in processed:
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processed.add(key)
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user = db.query(User).filter(User.id == s.user_id).first()
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if user:
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week_labor += user.daily_cost
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week_ai_cost = db.query(sa_func.sum(AIToolCost.amount)).filter(
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AIToolCost.record_date >= monday,
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AIToolCost.record_date <= today,
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).scalar() or 0
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# 损耗排行
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waste_ranking = []
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for p in active_projects:
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w = calc_waste_for_project(p.id, db)
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if w.get("total_waste_seconds", 0) > 0:
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waste_ranking.append({"name": p.name, "rate": w["waste_rate"]})
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waste_ranking.sort(key=lambda x: x["rate"], reverse=True)
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# 效率之星 —— 跨项目加权通过率（有效产出 / 总产出，扣除返工）
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from collections import defaultdict
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user_prod_secs = defaultdict(float) # 制作秒数
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user_rev_secs = defaultdict(float) # 返工秒数
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for s in week_subs:
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if s.total_seconds > 0 and s.project_phase == PhaseGroup.PRODUCTION:
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if s.work_type == WorkType.PRODUCTION:
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user_prod_secs[s.user_id] += s.total_seconds
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elif s.work_type == WorkType.REVISION:
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user_rev_secs[s.user_id] += s.total_seconds
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top_producer = None
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best_rate = -1
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best_uid = None
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for uid, prod in user_prod_secs.items():
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if prod < 60: # 至少 1 分钟制作产出才参与排名
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continue
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rev = user_rev_secs.get(uid, 0)
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rate = (prod - rev) / prod if prod > 0 else 0
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if rate > best_rate:
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best_rate = rate
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best_uid = uid
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if best_uid is not None and best_rate >= 0:
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top_user = db.query(User).filter(User.id == best_uid).first()
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if top_user:
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top_producer = f"{top_user.name}（通过率 {round(best_rate * 100, 1)}%）"
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# AI 数据上下文
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project_lines = [
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f"- {p['name']}：当前进度 {p['progress']}%，本周产出 {p['week_output']}"
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for p in projects_data
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]
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# 风险检测
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full_risks = analyze_project_risks(db)
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risk_lines = [
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f"- {r['project_name']}：{'；'.join(r['risk_factors'])}"
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for r in full_risks
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]
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data_context = (
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f"周期：{monday} ~ {today}\n"
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f"进行中项目：{len(active_projects)} 个\n"
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f"本周总产出：{_fmt_seconds(week_total_secs)}\n"
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f"人均日产出：{_fmt_seconds(avg_daily)}\n"
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f"效率最高：{top_producer or '暂无'}\n"
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f"本周人力成本：{_fmt_money(week_labor)}\n"
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f"本周AI工具成本：{_fmt_money(week_ai_cost)}\n"
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f"各项目：\n" + "\n".join(project_lines) + "\n"
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f"损耗排行：\n" + ("\n".join(
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f"- {w['name']}：{w['rate']}%" for w in waste_ranking[:5]
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) if waste_ranking else "无") + "\n"
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f"风险项目：\n" + ("\n".join(risk_lines) if risk_lines else "无")
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)
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ai_summary = generate_report_summary(data_context, "weekly")
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week_num = today.isocalendar()[1]
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title = f"AirLabs 周报 — 第{week_num}周（{monday} ~ {today}）"
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return {
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"title": title,
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"report_type": "weekly",
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"card_data": {
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"week_range": f"{monday} ~ {today}",
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"week_num": week_num,
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"total_output": _fmt_seconds(week_total_secs),
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"avg_daily_output": _fmt_seconds(avg_daily),
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"top_producer": top_producer,
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"projects": projects_data,
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"labor_cost": _fmt_money(week_labor),
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"ai_tool_cost": _fmt_money(week_ai_cost),
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"waste_ranking": waste_ranking[:5],
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"ai_summary": ai_summary,
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},
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}
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# ──────────────────────────── 月报 ────────────────────────────
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def generate_monthly_report(db: Session) -> dict:
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"""生成月报（上月完整数据），返回结构化数据"""
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today = date.today()
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first_of_this_month = today.replace(day=1)
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last_of_prev_month = first_of_this_month - timedelta(days=1)
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first_of_prev_month = last_of_prev_month.replace(day=1)
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month_label = f"{last_of_prev_month.year}年{last_of_prev_month.month}月"
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month_subs = db.query(Submission).filter(
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Submission.submit_date >= first_of_prev_month,
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Submission.submit_date <= last_of_prev_month,
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).all()
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# 产出只算中期制作阶段的动画秒数
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month_total_secs = sum(
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s.total_seconds for s in month_subs
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if s.total_seconds > 0 and s.project_phase == PhaseGroup.PRODUCTION
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)
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month_submitters = set(s.user_id for s in month_subs)
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all_projects = db.query(Project).filter(
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Project.status.in_([ProjectStatus.IN_PROGRESS, ProjectStatus.COMPLETED])
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).all()
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completed_this_month = [
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p for p in all_projects
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if p.status == ProjectStatus.COMPLETED
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and p.actual_completion_date
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and first_of_prev_month <= p.actual_completion_date <= last_of_prev_month
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]
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active_projects = [p for p in all_projects if p.status == ProjectStatus.IN_PROGRESS]
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# 各项目成本
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project_costs = []
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total_all_cost = 0.0
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for p in active_projects + completed_this_month:
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labor = calc_labor_cost_for_project(p.id, db)
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ai_tool = calc_ai_tool_cost_for_project(p.id, db)
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outsource = calc_outsource_cost_for_project(p.id, db)
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overhead = calc_overhead_cost_for_project(p.id, db)
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total = labor + ai_tool + outsource + overhead
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total_all_cost += total
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project_costs.append({
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"name": p.name,
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"labor": _fmt_money(labor),
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"ai_tool": _fmt_money(ai_tool),
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"outsource": _fmt_money(outsource),
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"overhead": _fmt_money(overhead),
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"total": _fmt_money(total),
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})
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# 盈亏
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profit_items = []
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total_profit = 0.0
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total_contract = 0.0
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for p in completed_this_month:
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settlement = calc_project_settlement(p.id, db)
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if settlement.get("contract_amount"):
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pl = settlement.get("profit_loss", 0)
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total_profit += pl
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total_contract += settlement["contract_amount"]
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profit_items.append({
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"name": p.name,
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"contract": _fmt_money(settlement["contract_amount"]),
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"cost": _fmt_money(settlement["total_cost"]),
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"profit": _fmt_money(pl),
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"is_positive": pl >= 0,
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})
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profit_rate = round(total_profit / total_contract * 100, 1) if total_contract > 0 else None
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# 损耗汇总
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total_waste_secs = 0.0
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total_target_secs = 0.0
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for p in active_projects + completed_this_month:
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w = calc_waste_for_project(p.id, db)
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total_waste_secs += w.get("total_waste_seconds", 0)
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total_target_secs += p.target_total_seconds or 0
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waste_rate = round(total_waste_secs / total_target_secs * 100, 1) if total_target_secs > 0 else 0
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avg_per_person = round(month_total_secs / max(1, len(month_submitters)), 1)
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# AI 数据上下文
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project_cost_lines = [
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f"- {pc['name']}：人力 {pc['labor']} / AI工具 {pc['ai_tool']} / "
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f"外包 {pc['outsource']} / 固定 {pc['overhead']} → 总计 {pc['total']}"
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for pc in project_costs
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]
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profit_lines = [
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f"- {pi['name']}：回款 {pi['contract']}，成本 {pi['cost']}，利润 {'+'if pi['is_positive'] else ''}{pi['profit']}"
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for pi in profit_items
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]
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# 风险检测
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monthly_risks = analyze_project_risks(db)
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monthly_risk_lines = [
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f"- {r['project_name']}：{'；'.join(r['risk_factors'])}"
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for r in monthly_risks
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]
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data_context = (
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f"月份：{month_label}\n"
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f"进行中项目：{len(active_projects)} 个\n"
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f"本月完成项目：{len(completed_this_month)} 个\n"
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f"月度总产出：{_fmt_seconds(month_total_secs)}\n"
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f"月度总成本：{_fmt_money(total_all_cost)}\n"
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f"总损耗率：{waste_rate}%\n"
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f"参与人数：{len(month_submitters)}\n"
|
||
f"人均产出：{_fmt_seconds(avg_per_person)}\n"
|
||
f"各项目成本：\n" + "\n".join(project_cost_lines) + "\n"
|
||
f"盈亏：\n" + ("\n".join(profit_lines) if profit_lines else "本月无结算项目") + "\n"
|
||
f"风险项目：\n" + ("\n".join(monthly_risk_lines) if monthly_risk_lines else "无")
|
||
)
|
||
|
||
ai_summary = generate_report_summary(data_context, "monthly")
|
||
|
||
title = f"AirLabs 月报 — {month_label}"
|
||
|
||
return {
|
||
"title": title,
|
||
"report_type": "monthly",
|
||
"card_data": {
|
||
"month_label": month_label,
|
||
"active_count": len(active_projects),
|
||
"completed_count": len(completed_this_month),
|
||
"total_output": _fmt_seconds(month_total_secs),
|
||
"total_cost": _fmt_money(total_all_cost),
|
||
"project_costs": project_costs,
|
||
"profit_items": profit_items,
|
||
"profit_rate": profit_rate,
|
||
"waste_total": _fmt_seconds(total_waste_secs),
|
||
"waste_rate": waste_rate,
|
||
"participant_count": len(month_submitters),
|
||
"avg_per_person": _fmt_seconds(avg_per_person),
|
||
"ai_summary": ai_summary,
|
||
},
|
||
}
|
||
|
||
|
||
# ──────────────────────────── 风险预警 ────────────────────────────
|
||
|
||
def analyze_project_risks(db: Session) -> list:
|
||
"""
|
||
分析所有进行中项目的风险，返回风险列表
|
||
纯规则引擎判断，不依赖 AI
|
||
"""
|
||
today = date.today()
|
||
active_projects = db.query(Project).filter(
|
||
Project.status == ProjectStatus.IN_PROGRESS
|
||
).all()
|
||
|
||
risks = []
|
||
for p in active_projects:
|
||
waste = calc_waste_for_project(p.id, db)
|
||
# 进度只算中期制作产出，不把后期算进去
|
||
production_secs = db.query(sa_func.sum(Submission.total_seconds)).filter(
|
||
Submission.project_id == p.id,
|
||
Submission.total_seconds > 0,
|
||
Submission.project_phase == PhaseGroup.PRODUCTION,
|
||
).scalar() or 0
|
||
target = p.target_total_seconds
|
||
progress = round(production_secs / target * 100, 1) if target > 0 else 0
|
||
|
||
risk_factors = []
|
||
risk_level = "low"
|
||
|
||
# 1. 超期检测
|
||
if p.estimated_completion_date:
|
||
days_left = (p.estimated_completion_date - today).days
|
||
if days_left < 0:
|
||
risk_factors.append(f"已超期 {-days_left} 天")
|
||
risk_level = "high"
|
||
elif days_left <= 7 and progress < 80:
|
||
risk_factors.append(f"距截止仅剩 {days_left} 天，进度仅 {progress}%")
|
||
risk_level = "high"
|
||
elif days_left <= 14 and progress < 60:
|
||
risk_factors.append(f"距截止 {days_left} 天，进度 {progress}% 偏低")
|
||
risk_level = "medium"
|
||
|
||
# 进度落后于时间线
|
||
if p.estimated_completion_date and days_left > 0:
|
||
if hasattr(p, 'created_at') and p.created_at:
|
||
created = p.created_at.date() if hasattr(p.created_at, 'date') else p.created_at
|
||
total_days = (p.estimated_completion_date - created).days
|
||
elapsed_days = (today - created).days
|
||
if total_days > 0:
|
||
expected_progress = round(elapsed_days / total_days * 100, 1)
|
||
if progress < expected_progress * 0.7:
|
||
risk_factors.append(
|
||
f"预期进度 {expected_progress}%，实际 {progress}%，严重落后"
|
||
)
|
||
risk_level = "high"
|
||
elif progress < expected_progress * 0.85:
|
||
risk_factors.append(
|
||
f"预期进度 {expected_progress}%，实际 {progress}%"
|
||
)
|
||
if risk_level != "high":
|
||
risk_level = "medium"
|
||
|
||
# 2. 损耗率检测
|
||
waste_rate = waste.get("waste_rate", 0)
|
||
if waste_rate > 80:
|
||
risk_factors.append(f"损耗率 {waste_rate}%，严重偏高")
|
||
risk_level = "high"
|
||
elif waste_rate > 50:
|
||
risk_factors.append(f"损耗率 {waste_rate}%，偏高")
|
||
if risk_level != "high":
|
||
risk_level = "medium"
|
||
|
||
# 3. 近7天无提交
|
||
week_ago = today - timedelta(days=7)
|
||
recent_subs = db.query(Submission).filter(
|
||
Submission.project_id == p.id,
|
||
Submission.submit_date >= week_ago,
|
||
).count()
|
||
if recent_subs == 0 and production_secs > 0:
|
||
risk_factors.append("近 7 天无提交，产出停滞")
|
||
if risk_level != "high":
|
||
risk_level = "medium"
|
||
|
||
if risk_factors:
|
||
risks.append({
|
||
"project_id": p.id,
|
||
"project_name": p.name,
|
||
"risk_level": risk_level,
|
||
"progress": progress,
|
||
"risk_factors": risk_factors,
|
||
})
|
||
|
||
# 高风险排前面
|
||
level_order = {"high": 0, "medium": 1, "low": 2}
|
||
risks.sort(key=lambda x: level_order.get(x["risk_level"], 99))
|
||
return risks
|