selfrelease
1278 lines
96 KiB
Python
1278 lines
96 KiB
Python
"""演示种子数据 — 按 5 个业务场景生成完整示例数据。
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覆盖模型：Tenant / User / Company / MonthlyReport / HealthScore / RiskEvent /
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WeakSignal / Task / OKR / MilestoneTree / SynergyOpportunity / DecisionSentinel /
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NudgeRecord / MajorEvent / InvestmentAgreement / BoardMeeting / FinancialData /
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Hypothesis / AARRecord / TeamMember / TalentProfile / AuditLog。
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运行方式：
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cd backend && python -m scripts.seed_demo_data
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"""
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import asyncio
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import json
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import random
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from datetime import datetime, timedelta, timezone
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from sqlalchemy import text
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from sqlalchemy.ext.asyncio import AsyncSession
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from app.core.database import async_session_factory, engine, Base
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from app.core.security import hash_password
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from app.models import (
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AARRecord, AgentExecution, AuditLog, BoardMeeting, Company, CompanyFundLink,
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CustomerAcquisitionPlan, DataSource, DecisionSentinel, DigitalTwinModel,
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EvaluationTemplate, ExitPrediction, FinancialData, FirmProfile, Fund,
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FundProfile, HealthScore, Hypothesis, InquiryList, InterventionEvent,
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InterventionResult, InvestmentAgreement, KnowledgeChunk, KnowledgeNode,
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MajorEvent, ManagerProfile, MilestoneTree, MonteCarloSimulation, MonthlyReport,
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NudgeRecord, OKR, PeerLearningCircle, PortfolioRebalancing, PreMortemRecord,
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ProductDiagnostic, RedTeamRecord, RiskEvent, SynergyOpportunity, Task,
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TalentProfile, TeamMember, Tenant, User, WeakSignal,
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)
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UTC = timezone.utc
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# ─── 固定 ID（方便跨表引用） ──────────────────────────────────────────
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TENANT_ID = "00000000-0000-0000-0000-000000000001"
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ADMIN_ID = "00000000-0000-0000-0000-000000000002"
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GP_ID = "00000000-0000-0000-0000-000000000003"
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LEAD_ID = "00000000-0000-0000-0000-000000000004"
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MGR_ID = "00000000-0000-0000-0000-000000000005"
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FOUNDER_A = "00000000-0000-0000-0000-000000000006"
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FOUNDER_B = "00000000-0000-0000-0000-000000000007"
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FOUNDER_C = "00000000-0000-0000-0000-000000000008"
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COMP_A = "aaaaaaaa-aaaa-aaaa-aaaa-aaaaaaaaaaa1"
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COMP_B = "bbbbbbbb-bbbb-bbbb-bbbb-bbbbbbbbbbb2"
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COMP_C = "cccccccc-cccc-cccc-cccc-ccccccccccc3"
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COMP_D = "dddddddd-dddd-dddd-dddd-ddddddddddd4"
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COMP_E = "eeeeeeee-eeee-eeee-eeee-eeeeeeeeeee5"
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NOW = datetime.now(UTC)
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D = lambda days: NOW - timedelta(days=days) # noqa: E731
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async def seed() -> None:
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"""生成全部演示数据。"""
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async with engine.begin() as conn:
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await conn.run_sync(Base.metadata.drop_all)
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await conn.run_sync(Base.metadata.create_all)
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async with async_session_factory() as db:
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await _seed_tenant_users(db)
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await _seed_companies(db)
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await _seed_funds(db)
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await _seed_profiles(db)
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await _seed_evaluation_templates(db)
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await _seed_financial(db)
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await _seed_reports(db)
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await _seed_inquiries(db)
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await _seed_health(db)
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await _seed_health_history(db)
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await _seed_risks(db)
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await _seed_weak_signals(db)
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await _seed_tasks(db)
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await _seed_okrs(db)
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await _seed_milestones(db)
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await _seed_synergies(db)
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await _seed_sentinels(db)
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await _seed_nudges(db)
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await _seed_events(db)
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await _seed_agreements(db)
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await _seed_boards(db)
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await _seed_hypotheses(db)
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await _seed_aars(db)
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await _seed_team_members(db)
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await _seed_talents(db)
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await _seed_agent_executions(db)
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await _seed_customer_plans(db)
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await _seed_exit_predictions(db)
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await _seed_pre_mortems(db)
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await _seed_product_diagnostics(db)
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await _seed_peer_circles(db)
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await _seed_digital_twins(db)
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await _seed_interventions(db)
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await _seed_portfolio_simulations(db)
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await _seed_knowledge_graph(db)
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await _seed_data_sources(db)
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await _seed_audit_logs(db)
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await db.commit()
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print("✅ 演示数据生成完成")
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print(f" 租户: {TENANT_ID}")
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print(f" 用户: admin/gp/lead/mgr/founder_a/founder_b/founder_c")
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print(f" 企业: 智链科技/云栈数据/深瞳智能/量子芯微/光合生物")
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print(" 登录密码均为: demo123456")
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# ─── 租户 + 用户 ───────────────────────────────────────────────────────
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async def _seed_tenant_users(db: AsyncSession) -> None:
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tenant = Tenant(
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id=TENANT_ID,
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name="远见资本",
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type="vc",
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config_json={"fund_name": "远见三期", "fund_size": "5亿人民币"},
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)
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db.add(tenant)
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users = [
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User(id=ADMIN_ID, tenant_id=TENANT_ID, email="admin@demo.com", password_hash=hash_password("demo123456"), name="系统管理员", role="admin", is_active=True),
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User(id=GP_ID, tenant_id=TENANT_ID, email="gp@demo.com", password_hash=hash_password("demo123456"), name="张远见", role="gp", is_active=True),
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User(id=LEAD_ID, tenant_id=TENANT_ID, email="lead@demo.com", password_hash=hash_password("demo123456"), name="李投后", role="post_invest_lead", is_active=True),
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User(id=MGR_ID, tenant_id=TENANT_ID, email="mgr@demo.com", password_hash=hash_password("demo123456"), name="王经理", role="investor", is_active=True),
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User(id=FOUNDER_A, tenant_id=TENANT_ID, email="founder_a@demo.com", password_hash=hash_password("demo123456"), name="陈智链", role="founder", is_active=True),
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User(id=FOUNDER_B, tenant_id=TENANT_ID, email="founder_b@demo.com", password_hash=hash_password("demo123456"), name="刘云栈", role="founder", is_active=True),
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User(id=FOUNDER_C, tenant_id=TENANT_ID, email="founder_c@demo.com", password_hash=hash_password("demo123456"), name="赵深瞳", role="founder", is_active=True),
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]
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for u in users:
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db.add(u)
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await db.flush()
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print(" ✓ 租户 + 7 用户")
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# ─── 企业 ──────────────────────────────────────────────────────────────
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async def _seed_companies(db: AsyncSession) -> None:
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companies = [
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Company(id=COMP_A, tenant_id=TENANT_ID, name="智链科技有限公司", industry="AI/供应链", stage="b",
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description="利用大模型优化供应链决策，服务制造业客户。",
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founded_at=datetime(2021, 3, 1, tzinfo=UTC), total_funding="1.2亿人民币", website="https://zhilian.example.com"),
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Company(id=COMP_B, tenant_id=TENANT_ID, name="云栈数据科技", industry="AI/数据平台", stage="a",
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description="企业级数据治理与 AI 训练数据管理平台。",
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founded_at=datetime(2022, 1, 1, tzinfo=UTC), total_funding="5000万人民币", website="https://yunzhan.example.com"),
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Company(id=COMP_C, tenant_id=TENANT_ID, name="深瞳智能", industry="AI/计算机视觉", stage="b",
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description="工业质检视觉 AI，服务半导体和新能源行业。",
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founded_at=datetime(2020, 6, 1, tzinfo=UTC), total_funding="2亿人民币", website="https://shentong.example.com"),
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Company(id=COMP_D, tenant_id=TENANT_ID, name="量子芯微电子", industry="芯片/AI算力", stage="seed",
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description="AI 推理芯片设计，边缘端低功耗 NPU。",
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founded_at=datetime(2023, 9, 1, tzinfo=UTC), total_funding="1500万人民币", website="https://quantumchip.example.com"),
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Company(id=COMP_E, tenant_id=TENANT_ID, name="光合生物医疗", industry="AI/医疗", stage="a",
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description="AI 辅助药物发现，聚焦小分子靶点筛选。",
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founded_at=datetime(2022, 9, 1, tzinfo=UTC), total_funding="8000万人民币", website="https://guanghe.example.com"),
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]
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for c in companies:
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db.add(c)
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await db.flush()
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print(" ✓ 5 企业")
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# ─── 财务数据 ──────────────────────────────────────────────────────────
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async def _seed_financial(db: AsyncSession) -> None:
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"""每家企业生成近 6 个月利润表 + 现金流。"""
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for comp_id, revenue, burn, cash in [
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(COMP_A, 800, 350, 4200), # 月营收800万, 消耗350万, 现金4200万
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(COMP_B, 150, 120, 1800),
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(COMP_C, 1200, 480, 6500),
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(COMP_D, 0, 80, 600),
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(COMP_E, 80, 200, 2400),
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]:
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for i in range(6):
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y, m = (NOW.year, NOW.month - i) if NOW.month - i > 0 else (NOW.year - 1, 12 + NOW.month - i)
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# 营收逐月递减（历史数据），展示增长趋势
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hist_revenue = int(revenue * (1 - 0.03 * i)) if revenue > 0 else 0
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db.add(FinancialData(
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company_id=comp_id, period_year=y, period_month=m,
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statement_type="income",
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data_json={"revenue": hist_revenue, "cogs": int(hist_revenue * 0.4), "gross_profit": int(hist_revenue * 0.6), "opex": burn, "net_income": hist_revenue - burn - int(hist_revenue * 0.4)},
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source="monthly_report", credibility_score=85.0 - i * 5,
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))
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db.add(FinancialData(
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company_id=comp_id, period_year=y, period_month=m,
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statement_type="cash_flow",
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data_json={"operating_cf": hist_revenue - burn, "investing_cf": -50, "financing_cf": 0, "net_cf": hist_revenue - burn - 50, "cash_balance": cash - i * burn},
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source="monthly_report", credibility_score=85.0 - i * 5,
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))
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await db.flush()
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print(" ✓ 财务数据 (5 企业 x 6 月)")
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# ─── 月报 ──────────────────────────────────────────────────────────────
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async def _seed_reports(db: AsyncSession) -> None:
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reports = [
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# 智链科技 — 已提交 + AI 解析
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MonthlyReport(company_id=COMP_A, period_year=NOW.year, period_month=NOW.month - 1 if NOW.month > 1 else 12,
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status="ai_parsed", submitted_by=FOUNDER_A, submitted_at=D(10),
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raw_content="本月营收800万，环比增长15%。新签客户3家，流失1家。团队新增5人。AI模型推理成本降低12%。",
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structured_data={"revenue": 800, "mom_growth": 0.15, "new_customers": 3, "churned": 1, "headcount": 45, "ai_cost_reduction": 0.12},
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ai_summary="智链科技本月表现良好，营收增长15%，AI推理成本优化显著。客户净增2家，团队扩张至45人。",
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ai_concerns=[{"level": "medium", "item": "客户流失率环比上升", "detail": "本月流失1家年合同客户"}, {"level": "low", "item": "现金Runway 12个月", "detail": "按当前消耗速度可维持12个月"}]),
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# 云栈数据 — 已提交
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MonthlyReport(company_id=COMP_B, period_year=NOW.year, period_month=NOW.month - 1 if NOW.month > 1 else 12,
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status="ai_parsed", submitted_by=FOUNDER_B, submitted_at=D(8),
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raw_content="本月营收150万，环比持平。完成数据治理平台v2.0发布。新签1家金融客户。",
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structured_data={"revenue": 150, "mom_growth": 0.0, "new_customers": 1, "churned": 0, "headcount": 22},
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ai_summary="云栈数据营收持平，产品迭代正常。金融客户拓展是亮点。",
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ai_concerns=[{"level": "high", "item": "营收增长停滞", "detail": "连续2个月环比0%增长"}, {"level": "medium", "item": "现金Runway 15个月", "detail": "需关注融资节奏"}]),
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# 深瞳智能 — 已提交
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MonthlyReport(company_id=COMP_C, period_year=NOW.year, period_month=NOW.month - 1 if NOW.month > 1 else 12,
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status="reviewed", submitted_by=FOUNDER_C, submitted_at=D(12), reviewed_by=MGR_ID, reviewed_at=D(5),
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raw_content="本月营收1200万，环比增长22%。半导体客户占比提升至60%。新增专利2项。",
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structured_data={"revenue": 1200, "mom_growth": 0.22, "new_customers": 2, "churned": 0, "headcount": 68, "patents": 2},
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ai_summary="深瞳智能强劲增长，半导体行业渗透加深。专利积累构建技术壁垒。",
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ai_concerns=[{"level": "low", "item": "客户集中度风险", "detail": "半导体行业占比60%"}]),
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# 量子芯微 — 草稿
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MonthlyReport(company_id=COMP_D, period_year=NOW.year, period_month=NOW.month - 1 if NOW.month > 1 else 12,
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status="draft", submitted_by=None,
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raw_content="", structured_data=None, ai_summary=None, ai_concerns=None),
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# 光合生物 — 延迟提交
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MonthlyReport(company_id=COMP_E, period_year=NOW.year, period_month=NOW.month - 2 if NOW.month > 2 else 11,
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status="ai_parsed", submitted_by=FOUNDER_A, submitted_at=D(40),
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raw_content="本月营收80万，来自2个合作药企里程碑付款。研发进展：3个靶点进入先导化合物阶段。",
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structured_data={"revenue": 80, "milestone_payment": 80, "targets": 3, "headcount": 18},
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ai_summary="光合生物收入来自里程碑付款，研发管线推进正常。",
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ai_concerns=[{"level": "high", "item": "月报延迟提交", "detail": "延迟20天"}, {"level": "medium", "item": "现金消耗快", "detail": "月消耗200万，Runway 12月"}]),
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]
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for r in reports:
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db.add(r)
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await db.flush()
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# 历史月报 — 每家企业再补 5 个月，展示趋势
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historical_data = [
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# (company_id, founder_id, months_ago, revenue, growth, new_cust, churned, headcount, summary, concerns)
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(COMP_A, FOUNDER_A, 2, 696, 0.08, 2, 0, 40, "营收稳步增长，新签2家客户。", []),
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(COMP_A, FOUNDER_A, 3, 644, 0.05, 1, 1, 38, "营收增长5%，客户流失1家。", [{"level": "low", "item": "客户流失", "detail": "流失1家小客户"}]),
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(COMP_A, FOUNDER_A, 4, 613, 0.03, 1, 0, 37, "营收小幅增长，团队稳定。", []),
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(COMP_A, FOUNDER_A, 5, 595, 0.02, 0, 0, 35, "营收微增，无新签客户。", [{"level": "medium", "item": "增长放缓", "detail": "环比仅2%"}]),
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(COMP_A, FOUNDER_A, 6, 583, 0.01, 1, 1, 34, "基本持平，团队新增1人。", []),
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(COMP_B, FOUNDER_B, 2, 150, 0.0, 0, 0, 22, "营收持平，产品迭代中。", []),
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(COMP_B, FOUNDER_B, 3, 150, 0.02, 1, 0, 21, "营收微增，新签1家客户。", []),
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(COMP_B, FOUNDER_B, 4, 147, -0.01, 0, 1, 21, "营收微降，流失1家小客户。", [{"level": "medium", "item": "客户流失", "detail": "流失1家"}]),
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(COMP_B, FOUNDER_B, 5, 149, 0.03, 1, 0, 20, "营收回升，新签1家。", []),
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(COMP_B, FOUNDER_B, 6, 145, 0.0, 0, 0, 20, "持平，团队稳定。", []),
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(COMP_C, FOUNDER_C, 2, 984, 0.18, 3, 0, 62, "强劲增长，半导体客户+3。", []),
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(COMP_C, FOUNDER_C, 3, 834, 0.15, 2, 0, 58, "持续增长，新增专利1项。", []),
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(COMP_C, FOUNDER_C, 4, 725, 0.12, 1, 0, 55, "稳定增长，团队扩张。", []),
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(COMP_C, FOUNDER_C, 5, 647, 0.10, 1, 0, 52, "增速放缓，但趋势向上。", []),
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(COMP_C, FOUNDER_C, 6, 588, 0.08, 0, 0, 50, "基线月份，稳步起步。", []),
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(COMP_E, FOUNDER_A, 2, 75, 0.0, 0, 0, 17, "里程碑收入稳定。", []),
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(COMP_E, FOUNDER_A, 3, 80, 0.07, 0, 0, 18, "小幅增长，靶点推进。", []),
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(COMP_E, FOUNDER_A, 4, 75, 0.0, 0, 0, 17, "持平，研发正常。", []),
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(COMP_E, FOUNDER_A, 5, 70, -0.07, 0, 0, 16, "收入微降，无里程碑。", [{"level": "low", "item": "收入波动", "detail": "依赖里程碑付款"}]),
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(COMP_E, FOUNDER_A, 6, 75, 0.04, 0, 0, 16, "基线月份，稳定。", []),
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]
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for comp_id, founder_id, months_ago, revenue, growth, new_c, churned, hc, summary, concerns in historical_data:
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m = NOW.month - months_ago
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y = NOW.year
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if m <= 0:
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m += 12
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y -= 1
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db.add(MonthlyReport(
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company_id=comp_id, period_year=y, period_month=m,
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status="reviewed", submitted_by=founder_id, submitted_at=D(months_ago * 30 + 10),
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reviewed_by=MGR_ID, reviewed_at=D(months_ago * 30 + 5),
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raw_content=f"本月营收{revenue}万，环比{'增长' if growth > 0 else '持平' if growth == 0 else '下降'}{abs(growth)*100:.0f}%。",
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structured_data={"revenue": revenue, "mom_growth": growth, "new_customers": new_c, "churned": churned, "headcount": hc},
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ai_summary=summary,
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ai_concerns=concerns if concerns else None,
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))
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await db.flush()
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print(" ✓ 月报 (5 当月 + 20 历史 = 25 份)")
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# ─── 健康度评分 ────────────────────────────────────────────────────────
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async def _seed_health(db: AsyncSession) -> None:
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"""最新一期健康度评分 — 14 维度完整评分。"""
|
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scores = [
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# 智链科技 — 良好
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||
HealthScore(company_id=COMP_A, total_score=78.5,
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financial_score=82, operational_score=75, ai_commercial_score=80, ai_cost_score=85,
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||
org_talent_score=72, product_tech_score=80, market_compete_score=78, governance_score=75, financing_score=80,
|
||
synergy_score=76, ai_model_product_score=82, data_compliance_score=88, team_tech_score=74, customer_success_score=68,
|
||
trend="up", evidence_json={"financial": "营收增长15%，现金流健康", "ai_cost": "推理成本降低12%", "data_compliance": "通过等保三级", "ai_poc_count": 3, "compliance_issues": 0},
|
||
recommendations_json={"action": "关注客户流失率", "owner": MGR_ID, "review_at": D(-30).isoformat()},
|
||
fund_type="early_vc", fund_lifecycle="investment", company_stage="b", industry="ai", strategy="growth"),
|
||
# 云栈数据 — 中等
|
||
HealthScore(company_id=COMP_B, total_score=62.0,
|
||
financial_score=55, operational_score=68, ai_commercial_score=60, ai_cost_score=65,
|
||
org_talent_score=70, product_tech_score=72, market_compete_score=58, governance_score=65, financing_score=50,
|
||
synergy_score=64, ai_model_product_score=68, data_compliance_score=85, team_tech_score=72, customer_success_score=60,
|
||
trend="stable", evidence_json={"financial": "营收持平，需突破", "financing": "Runway 15月，需启动融资", "ai_poc_count": 1, "compliance_issues": 1},
|
||
recommendations_json={"action": "加速融资节奏", "owner": LEAD_ID, "review_at": D(-14).isoformat()},
|
||
fund_type="early_vc", fund_lifecycle="investment", company_stage="a", industry="ai", strategy="growth"),
|
||
# 深瞳智能 — 优秀
|
||
HealthScore(company_id=COMP_C, total_score=85.5,
|
||
financial_score=88, operational_score=85, ai_commercial_score=90, ai_cost_score=82,
|
||
org_talent_score=83, product_tech_score=88, market_compete_score=86, governance_score=82, financing_score=85,
|
||
synergy_score=80, ai_model_product_score=86, data_compliance_score=90, team_tech_score=85, customer_success_score=82,
|
||
trend="up", evidence_json={"financial": "营收增长22%", "market": "半导体渗透加深", "ai_poc_count": 5, "compliance_issues": 0},
|
||
recommendations_json={"action": "关注客户集中度", "owner": MGR_ID, "review_at": D(-30).isoformat()},
|
||
fund_type="early_vc", fund_lifecycle="growth", company_stage="b", industry="ai", strategy="growth"),
|
||
# 量子芯微 — 早期风险
|
||
HealthScore(company_id=COMP_D, total_score=48.0,
|
||
financial_score=35, operational_score=50, ai_commercial_score=45, ai_cost_score=55,
|
||
org_talent_score=52, product_tech_score=60, market_compete_score=42, governance_score=55, financing_score=40,
|
||
synergy_score=45, ai_model_product_score=58, data_compliance_score=65, team_tech_score=62, customer_success_score=38,
|
||
trend="down", evidence_json={"financial": "无营收，现金紧张", "financing": "Runway 7月", "ai_poc_count": 0, "compliance_issues": 2},
|
||
recommendations_json={"action": "紧急启动天使+轮融资", "owner": GP_ID, "review_at": D(-7).isoformat()},
|
||
fund_type="angel", fund_lifecycle="investment", company_stage="seed", industry="hardware", strategy="growth"),
|
||
# 光合生物 — 中等偏上
|
||
HealthScore(company_id=COMP_E, total_score=68.5,
|
||
financial_score=60, operational_score=72, ai_commercial_score=70, ai_cost_score=65,
|
||
org_talent_score=68, product_tech_score=75, market_compete_score=65, governance_score=70, financing_score=62,
|
||
synergy_score=66, ai_model_product_score=72, data_compliance_score=80, team_tech_score=70, customer_success_score=65,
|
||
trend="stable", evidence_json={"financial": "里程碑收入稳定", "product": "3靶点推进中", "ai_poc_count": 2, "compliance_issues": 0},
|
||
recommendations_json={"action": "月报提交及时性改善", "owner": MGR_ID, "review_at": D(-30).isoformat()},
|
||
fund_type="early_vc", fund_lifecycle="investment", company_stage="a", industry="biotech", strategy="growth"),
|
||
]
|
||
for s in scores:
|
||
s.calculated_at = D(5)
|
||
db.add(s)
|
||
await db.flush()
|
||
print(" ✓ 健康度评分 (5 企业 x 14 维度)")
|
||
|
||
|
||
# ─── 风险事件 ──────────────────────────────────────────────────────────
|
||
async def _seed_risks(db: AsyncSession) -> None:
|
||
risks = [
|
||
# COMP_A — 智链科技
|
||
RiskEvent(company_id=COMP_A, type="operational", severity="medium", status="in_progress",
|
||
title="客户流失率环比上升", description="本月流失1家年合同客户，流失率从2%升至4%",
|
||
evidence_json={"metric": "churn_rate", "current": 0.04, "previous": 0.02, "threshold": 0.03},
|
||
suggested_action="联系流失客户了解原因，加强客户成功团队", assigned_to=MGR_ID, due_at=D(-7)),
|
||
RiskEvent(company_id=COMP_A, type="ai_specific", severity="low", status="closed",
|
||
title="AI模型推理成本超标", description="上月推理成本占营收比12%，超10%阈值",
|
||
evidence_json={"metric": "ai_cost_ratio", "current": 0.12, "threshold": 0.10},
|
||
suggested_action="优化模型量化策略", assigned_to=MGR_ID, closed_at=D(-5)),
|
||
RiskEvent(company_id=COMP_A, type="market", severity="medium", status="open",
|
||
title="竞品低价策略冲击", description="杉数科技以低于我方30%的价格争夺制造业客户",
|
||
evidence_json={"competitor": "杉数科技", "price_diff": -0.30, "affected_customers": 3},
|
||
suggested_action="强化差异化话术，加速多模态产品迭代", assigned_to=LEAD_ID),
|
||
RiskEvent(company_id=COMP_A, type="financial", severity="low", status="resolved",
|
||
title="应收账款周期延长", description="2家客户付款周期从30天延至45天",
|
||
evidence_json={"metric": "ar_days", "current": 45, "previous": 30, "threshold": 60},
|
||
suggested_action="与客户协商缩短账期", assigned_to=MGR_ID, closed_at=D(-15)),
|
||
# COMP_B — 云栈数据
|
||
RiskEvent(company_id=COMP_B, type="financial", severity="high", status="assigned",
|
||
title="营收增长停滞", description="连续2个月环比0%增长，未达预期",
|
||
evidence_json={"metric": "revenue_growth", "current": 0.0, "expected": 0.15, "months": 2},
|
||
suggested_action="与创始人讨论增长策略，评估产品定价和市场拓展", assigned_to=LEAD_ID, due_at=D(-3)),
|
||
RiskEvent(company_id=COMP_B, type="financial", severity="high", status="open",
|
||
title="现金Runway缩短至15个月", description="按当前消耗速度，现金仅可维持15个月",
|
||
evidence_json={"metric": "runway_months", "current": 15, "threshold": 18},
|
||
suggested_action="启动A+轮融资准备，控制招聘节奏", assigned_to=GP_ID),
|
||
RiskEvent(company_id=COMP_B, type="market", severity="medium", status="open",
|
||
title="金融行业准入门槛高", description="银行客户POC周期长达6-12月，转化率低",
|
||
evidence_json={"metric": "poc_conversion", "current": 0.15, "expected": 0.30},
|
||
suggested_action="调整目标客户画像，探索保险/证券赛道", assigned_to=MGR_ID),
|
||
# COMP_C — 深瞳智能
|
||
RiskEvent(company_id=COMP_C, type="org", severity="medium", status="open",
|
||
title="核心技术人员稳定性下降", description="CTO提及外部机会，稳定性评分从0.85降至0.65",
|
||
evidence_json={"metric": "cto_stability", "current": 0.65, "previous": 0.85},
|
||
suggested_action="了解CTO诉求，评估股权激励调整", assigned_to=LEAD_ID),
|
||
RiskEvent(company_id=COMP_C, type="market", severity="medium", status="in_progress",
|
||
title="客户集中度过高", description="半导体行业占比60%，周期下行风险大",
|
||
evidence_json={"metric": "customer_concentration", "current": 0.60, "threshold": 0.50, "industry": "semiconductor"},
|
||
suggested_action="拓展新能源、消费电子等新行业客户", assigned_to=MGR_ID, due_at=D(-30)),
|
||
RiskEvent(company_id=COMP_C, type="operational", severity="low", status="closed",
|
||
title="产品交付延迟", description="1条产线视觉系统部署延迟2周",
|
||
evidence_json={"metric": "delivery_delay_days", "current": 14, "threshold": 7},
|
||
suggested_action="增加现场实施人员", assigned_to=MGR_ID, closed_at=D(-20)),
|
||
# COMP_D — 量子芯微
|
||
RiskEvent(company_id=COMP_D, type="financial", severity="critical", status="open",
|
||
title="现金Runway不足7个月", description="按当前消耗速度，现金仅可维持7个月",
|
||
evidence_json={"metric": "runway_months", "current": 7, "threshold": 9},
|
||
suggested_action="紧急启动天使+轮融资，准备BP和财务预测", assigned_to=GP_ID, due_at=D(-14)),
|
||
RiskEvent(company_id=COMP_D, type="technical", severity="high", status="in_progress",
|
||
title="NPU流片进度风险", description="EDA工具链兼容性问题可能导致流片延迟1-2月",
|
||
evidence_json={"metric": "tapeout_delay_risk", "risk_level": "high", "eta_impact": "1-2月"},
|
||
suggested_action="协调备用EDA工具，增加验证人力", assigned_to=GP_ID, due_at=D(-7)),
|
||
RiskEvent(company_id=COMP_D, type="market", severity="medium", status="open",
|
||
title="边缘NPU赛道巨头入场", description="英伟达发布边缘端Jetson新品，可能挤压创业公司空间",
|
||
evidence_json={"competitor": "NVIDIA", "product": "Jetson Orin Nano", "threat_level": "medium"},
|
||
suggested_action="强化低功耗差异化，加速客户绑定", assigned_to=LEAD_ID),
|
||
# COMP_E — 光合生物
|
||
RiskEvent(company_id=COMP_E, type="operational", severity="medium", status="resolved",
|
||
title="月报延迟提交", description="上月月报延迟20天提交",
|
||
evidence_json={"metric": "report_delay_days", "current": 20, "threshold": 5},
|
||
suggested_action="与创始人沟通提交规范，设置自动提醒", assigned_to=MGR_ID, due_at=D(-10), closed_at=D(-3)),
|
||
RiskEvent(company_id=COMP_E, type="financial", severity="medium", status="open",
|
||
title="研发投入产出周期长", description="3靶点尚处先导化合物阶段，距临床还需12-18月",
|
||
evidence_json={"metric": "time_to_clinic", "current": 18, "threshold": 12, "targets": 3},
|
||
suggested_action="评估是否引入大药企联合开发", assigned_to=LEAD_ID),
|
||
]
|
||
for r in risks:
|
||
r.identified_at = D(15)
|
||
db.add(r)
|
||
await db.flush()
|
||
print(" ✓ 风险事件 (15 条)")
|
||
|
||
|
||
# ─── 弱信号 ────────────────────────────────────────────────────────────
|
||
async def _seed_weak_signals(db: AsyncSession) -> None:
|
||
signals = [
|
||
WeakSignal(company_id=COMP_B, signal_type="market", source="行业论坛", content="竞品发布类似数据治理产品，定价低30%",
|
||
confidence=0.72, risk_probability=0.65, status="alerted",
|
||
correlation_result={"related_signals": 2, "pattern": "竞品压力增加"}),
|
||
WeakSignal(company_id=COMP_C, signal_type="org", source="LinkedIn", content="CTO 更新简历，标注'开放看机会'",
|
||
confidence=0.85, risk_probability=0.78, status="alerted",
|
||
correlation_result={"related_signals": 1, "pattern": "核心人员流失风险"}),
|
||
WeakSignal(company_id=COMP_D, signal_type="technical", source="GitHub", content="核心开源依赖库停止维护，需迁移",
|
||
confidence=0.68, risk_probability=0.45, status="correlated"),
|
||
WeakSignal(company_id=COMP_A, signal_type="sentiment", source="客户反馈", content="大客户提及预算削减计划",
|
||
confidence=0.60, risk_probability=0.55, status="new"),
|
||
WeakSignal(company_id=COMP_E, signal_type="market", source="FDA新闻", content="同类靶点药物获FDA快速审批",
|
||
confidence=0.75, risk_probability=0.30, status="new"),
|
||
WeakSignal(company_id=COMP_C, signal_type="market", source="半导体行业协会", content="半导体周期指标连续2月下行",
|
||
confidence=0.70, risk_probability=0.62, status="correlated",
|
||
correlation_result={"related_signals": 1, "pattern": "行业周期风险"}),
|
||
WeakSignal(company_id=COMP_A, signal_type="technical", source="GitHub", content="竞品开源多模态决策引擎，star数暴涨",
|
||
confidence=0.65, risk_probability=0.40, status="new"),
|
||
WeakSignal(company_id=COMP_B, signal_type="org", source="脉脉", content="云栈数据销售总监更新简历",
|
||
confidence=0.78, risk_probability=0.60, status="alerted",
|
||
correlation_result={"related_signals": 1, "pattern": "销售负责人不稳定"}),
|
||
WeakSignal(company_id=COMP_D, signal_type="market", source="英伟达发布会", content="英伟达发布边缘端Jetson Orin Nano，价格下探",
|
||
confidence=0.82, risk_probability=0.70, status="alerted",
|
||
correlation_result={"related_signals": 2, "pattern": "巨头入场边缘AI"}),
|
||
]
|
||
for s in signals:
|
||
s.detected_at = D(7)
|
||
db.add(s)
|
||
await db.flush()
|
||
print(" ✓ 弱信号 (9 条)")
|
||
|
||
|
||
# ─── 任务 ──────────────────────────────────────────────────────────────
|
||
async def _seed_tasks(db: AsyncSession) -> None:
|
||
tasks = [
|
||
Task(tenant_id=TENANT_ID, company_id=COMP_A, title="联系流失客户进行回访", description="了解客户流失原因，制定挽留方案",
|
||
status="in_progress", priority="high", assigned_to=MGR_ID, source_type="risk", due_at=D(-3)),
|
||
Task(tenant_id=TENANT_ID, company_id=COMP_B, title="与云栈数据创始人讨论增长策略", description="评估产品定价和市场拓展方案",
|
||
status="todo", priority="high", assigned_to=LEAD_ID, source_type="risk", due_at=D(-1)),
|
||
Task(tenant_id=TENANT_ID, company_id=COMP_D, title="准备天使+轮BP", description="包含财务预测和产品路线图",
|
||
status="todo", priority="urgent", assigned_to=GP_ID, source_type="risk", due_at=D(-14)),
|
||
Task(tenant_id=TENANT_ID, company_id=COMP_C, title="评估CTO股权激励调整方案", description="了解CTO诉求，设计retention package",
|
||
status="todo", priority="medium", assigned_to=LEAD_ID, source_type="manual", due_at=D(-7)),
|
||
Task(tenant_id=TENANT_ID, company_id=COMP_A, title="审阅智链科技本月月报", description="关注AI成本降低和客户流失",
|
||
status="done", priority="medium", assigned_to=MGR_ID, source_type="report", completed_at=D(-3)),
|
||
Task(tenant_id=TENANT_ID, company_id=COMP_E, title="跟进光合生物月报提交及时性", description="设置自动提醒，沟通提交规范",
|
||
status="done", priority="medium", assigned_to=MGR_ID, source_type="manual", completed_at=D(-2)),
|
||
]
|
||
for t in tasks:
|
||
db.add(t)
|
||
await db.flush()
|
||
print(" ✓ 任务 (6 条)")
|
||
|
||
|
||
# ─── OKR ───────────────────────────────────────────────────────────────
|
||
async def _seed_okrs(db: AsyncSession) -> None:
|
||
okrs = [
|
||
OKR(company_id=COMP_A, quarter=f"{NOW.year}-Q{(NOW.month - 1) // 3 + 1}",
|
||
objective="实现季度营收3000万，客户净增8家",
|
||
key_results=[{"kr": "季度营收达3000万", "current": 2400, "target": 3000, "progress": 0.80},
|
||
{"kr": "新签客户8家", "current": 5, "target": 8, "progress": 0.625},
|
||
{"kr": "客户流失率<3%", "current": 0.04, "target": 0.03, "progress": 0.75}],
|
||
alignment_score=82.0, status="active",
|
||
deviation_alerts=[{"kr": "客户流失率", "current": "4%", "target": "<3%", "severity": "medium"}]),
|
||
OKR(company_id=COMP_B, quarter=f"{NOW.year}-Q{(NOW.month - 1) // 3 + 1}",
|
||
objective="完成A+轮融资，营收突破500万/月",
|
||
key_results=[{"kr": "月营收达500万", "current": 150, "target": 500, "progress": 0.30},
|
||
{"kr": "完成A+轮融资", "current": 0, "target": 1, "progress": 0.0},
|
||
{"kr": "签约3家金融客户", "current": 1, "target": 3, "progress": 0.33}],
|
||
alignment_score=55.0, status="active",
|
||
deviation_alerts=[{"kr": "月营收", "current": "150万", "target": "500万", "severity": "high"},
|
||
{"kr": "融资进度", "current": "未启动", "target": "完成", "severity": "high"}]),
|
||
OKR(company_id=COMP_C, quarter=f"{NOW.year}-Q{(NOW.month - 1) // 3 + 1}",
|
||
objective="半导体行业营收占比70%，新增专利5项",
|
||
key_results=[{"kr": "半导体营收占比70%", "current": 0.60, "target": 0.70, "progress": 0.857},
|
||
{"kr": "新增专利5项", "current": 2, "target": 5, "progress": 0.40}],
|
||
alignment_score=88.0, status="active", deviation_alerts=[]),
|
||
]
|
||
for o in okrs:
|
||
db.add(o)
|
||
await db.flush()
|
||
print(" ✓ OKR (3 条)")
|
||
|
||
|
||
# ─── 里程碑 ────────────────────────────────────────────────────────────
|
||
async def _seed_milestones(db: AsyncSession) -> None:
|
||
# 智链科技里程碑树
|
||
m1 = MilestoneTree(company_id=COMP_A, name="B轮融资", is_current=True, status="in_progress", target_date=D(-90), description="B轮1亿人民币，估值8亿")
|
||
db.add(m1); await db.flush()
|
||
m2 = MilestoneTree(company_id=COMP_A, name="产品v3.0发布", parent_id=m1.id, is_current=True, status="completed", actual_date=D(-20), description="多模态供应链决策引擎")
|
||
m3 = MilestoneTree(company_id=COMP_A, name="客户数突破50", parent_id=m1.id, is_current=True, status="in_progress", target_date=D(-60))
|
||
m4 = MilestoneTree(company_id=COMP_A, name="海外市场拓展", parent_id=m1.id, is_current=False, status="planned", target_date=D(-180), description="东南亚试点 — 备选路径",
|
||
ai_analysis={"risk": "海外合规成本高", "opportunity": "市场先发优势"})
|
||
for m in [m2, m3, m4]:
|
||
db.add(m)
|
||
|
||
# 云栈数据里程碑
|
||
m5 = MilestoneTree(company_id=COMP_B, name="A+轮融资", is_current=True, status="in_progress", target_date=D(-45), description="A+轮3000万人民币")
|
||
db.add(m5); await db.flush()
|
||
m6 = MilestoneTree(company_id=COMP_B, name="数据治理平台v2.0", parent_id=m5.id, is_current=True, status="completed", actual_date=D(-10))
|
||
m7 = MilestoneTree(company_id=COMP_B, name="金融行业突破", parent_id=m5.id, is_current=True, status="in_progress", target_date=D(-30))
|
||
for m in [m6, m7]:
|
||
db.add(m)
|
||
|
||
await db.flush()
|
||
print(" ✓ 里程碑 (7 节点)")
|
||
|
||
|
||
# ─── 协同机会 ──────────────────────────────────────────────────────────
|
||
async def _seed_synergies(db: AsyncSession) -> None:
|
||
synergies = [
|
||
SynergyOpportunity(tenant_id=TENANT_ID, type="customer", company_a_id=COMP_A, company_b_id=COMP_C,
|
||
title="智链科技 → 深瞳智能：制造业客户共享",
|
||
description="智链科技的3家制造业客户有质检需求，可引荐深瞳智能。",
|
||
match_reason="AI分析：客户行业重叠度高，需求互补",
|
||
status="confirmed", authorized=True),
|
||
SynergyOpportunity(tenant_id=TENANT_ID, type="tech", company_a_id=COMP_B, company_b_id=COMP_D,
|
||
title="云栈数据 → 量子芯微：数据平台支持芯片设计仿真",
|
||
description="云栈数据平台可处理量子芯微的仿真数据集。",
|
||
match_reason="技术栈匹配，数据平台可降低芯片仿真IT成本40%",
|
||
status="discovered", authorized=False),
|
||
SynergyOpportunity(tenant_id=TENANT_ID, type="talent", company_a_id=COMP_C, company_b_id=COMP_E,
|
||
title="深瞳智能 → 光合生物：AI算法人才推荐",
|
||
description="深瞳智能有CV算法人才储备，光合生物需AI药物筛选算法工程师。",
|
||
match_reason="技能匹配度85%，工作地点同城",
|
||
status="executing", authorized=True,
|
||
effect_result={"candidates_referred": 3, "interviewed": 2, "offered": 1}),
|
||
]
|
||
for s in synergies:
|
||
db.add(s)
|
||
await db.flush()
|
||
print(" ✓ 协同机会 (3 条)")
|
||
|
||
|
||
# ─── 决策前哨 ──────────────────────────────────────────────────────────
|
||
async def _seed_sentinels(db: AsyncSession) -> None:
|
||
sentinels = [
|
||
DecisionSentinel(company_id=COMP_B, decision_type="funding",
|
||
title="A+轮融资时机选择：现在 vs 等待产品验证",
|
||
description="营收增长停滞，但产品v2.0刚发布。是否现在融资还是等Q2数据验证后融资？",
|
||
signals=[{"source": "月报", "signal": "营收停滞2月"}, {"source": "市场", "signal": "竞品定价低30%"}],
|
||
scenarios={"A": {"name": "现在融资", "pros": "现金充裕", "cons": "估值可能偏低", "probability": 0.6},
|
||
"B": {"name": "等待Q2验证", "pros": "估值更高", "cons": "现金Runway风险", "probability": 0.4}},
|
||
status="analyzed"),
|
||
DecisionSentinel(company_id=COMP_C, decision_type="hiring",
|
||
title="CTO retention：股权激励 vs 替换",
|
||
description="CTO稳定性下降，需决定加大股权激励还是提前寻找替代者。",
|
||
signals=[{"source": "LinkedIn", "signal": "CTO更新简历"}, {"source": "弱信号", "signal": "稳定性评分0.65"}],
|
||
scenarios={"A": {"name": "加大股权激励", "pros": "保留技术连续性", "cons": "股权稀释", "probability": 0.7},
|
||
"B": {"name": "启动替换搜索", "pros": "降低单点风险", "cons": "过渡期风险", "probability": 0.3}},
|
||
status="identified"),
|
||
DecisionSentinel(company_id=COMP_D, decision_type="funding",
|
||
title="天使+轮 vs Pre-A：融资策略选择",
|
||
description="现金Runway 7月，需快速融资。天使+轮快但金额小，Pre-A慢但可支撑更长。",
|
||
signals=[{"source": "财务", "signal": "Runway 7月"}, {"source": "产品", "signal": "NPU原型流片在即"}],
|
||
scenarios={"A": {"name": "天使+轮 1500万", "pros": "3个月内close", "cons": "只够6月", "probability": 0.55},
|
||
"B": {"name": "Pre-A 5000万", "pros": "支撑18月", "cons": "需6月", "probability": 0.45}},
|
||
status="acted"),
|
||
]
|
||
for s in sentinels:
|
||
s.identified_at = D(10)
|
||
db.add(s)
|
||
await db.flush()
|
||
print(" ✓ 决策前哨 (3 条)")
|
||
|
||
|
||
# ─── 行为助推 ──────────────────────────────────────────────────────────
|
||
async def _seed_nudges(db: AsyncSession) -> None:
|
||
nudges = [
|
||
NudgeRecord(company_id=COMP_A, nudge_type="anchoring",
|
||
context="月报审阅 — 客户流失率",
|
||
message="同类AI供应链企业平均客户流失率为2.5%，智链科技本月4%高于基准。",
|
||
target_user_id=MGR_ID, accepted=True,
|
||
effect_result={"action": "联系流失客户", "result": "挽留1家"}),
|
||
NudgeRecord(company_id=COMP_B, nudge_type="loss_aversion",
|
||
context="融资时机提醒",
|
||
message="如果不启动A+轮融资，预计6个月后现金耗尽，错失产品验证窗口。",
|
||
target_user_id=LEAD_ID, accepted=True,
|
||
effect_result={"action": "约见创始人讨论融资", "result": "启动BP准备"}),
|
||
NudgeRecord(company_id=COMP_D, nudge_type="social_proof",
|
||
context="融资策略",
|
||
message="Portfolio中3家类似阶段企业选择了Pre-A路线，平均估值高于天使+轮2倍。",
|
||
target_user_id=GP_ID, accepted=False,
|
||
effect_result={"action": "选择天使+轮", "result": "快速close"}),
|
||
NudgeRecord(company_id=COMP_C, nudge_type="timing",
|
||
context="CTO稳定性",
|
||
message="融资前是关键人才挽留的最佳时机，建议在B+轮前完成CTO股权激励调整。",
|
||
target_user_id=LEAD_ID, accepted=True,
|
||
effect_result={"action": "设计retention package", "result": "进行中"}),
|
||
]
|
||
for n in nudges:
|
||
db.add(n)
|
||
await db.flush()
|
||
print(" ✓ 行为助推 (4 条)")
|
||
|
||
|
||
# ─── 重大事项 ──────────────────────────────────────────────────────────
|
||
async def _seed_events(db: AsyncSession) -> None:
|
||
events = [
|
||
MajorEvent(company_id=COMP_A, event_type="product", title="产品v3.0多模态引擎发布", severity="high",
|
||
description="支持文本+图像+时序数据的多模态供应链决策引擎上线",
|
||
source="monthly_report", status="addressed", occurred_at=D(20)),
|
||
MajorEvent(company_id=COMP_C, event_type="personnel", title="CTO更新简历", severity="high",
|
||
description="CTO在LinkedIn更新简历，标注'开放看机会'",
|
||
source="weak_signal", status="confirmed", occurred_at=D(7)),
|
||
MajorEvent(company_id=COMP_D, event_type="funding", title="天使+轮融资启动", severity="critical",
|
||
description="现金Runway不足7月，启动天使+轮融资",
|
||
source="manual", status="addressed", occurred_at=D(3)),
|
||
MajorEvent(company_id=COMP_E, event_type="product", title="3个靶点进入先导化合物阶段", severity="medium",
|
||
description="AI药物筛选管线推进，3个靶点通过虚拟筛选进入实验验证",
|
||
source="monthly_report", status="confirmed", occurred_at=D(15)),
|
||
]
|
||
for e in events:
|
||
db.add(e)
|
||
await db.flush()
|
||
print(" ✓ 重大事项 (4 条)")
|
||
|
||
|
||
# ─── 投资协议 ──────────────────────────────────────────────────────────
|
||
async def _seed_agreements(db: AsyncSession) -> None:
|
||
agreements = [
|
||
InvestmentAgreement(company_id=COMP_A, title="B轮投资协议", signed_at=datetime(2023, 6, 1, tzinfo=UTC),
|
||
key_clauses={"valuation": "8亿人民币", "investment": "1亿", "board_seat": "1席", "anti_dilution": "加权平均", "liquidation_pref": "1x非参与"},
|
||
monitoring_rules=[{"clause": "反稀释", "trigger": "下一轮估值低于8亿", "action": "通知GP"}],
|
||
status="active"),
|
||
InvestmentAgreement(company_id=COMP_B, title="A轮投资协议", signed_at=datetime(2023, 3, 1, tzinfo=UTC),
|
||
key_clauses={"valuation": "3亿", "investment": "5000万", "board_seat": "1席", "redemption_right": "5年后可要求回购"},
|
||
monitoring_rules=[{"clause": "回购权", "trigger": "2028-03-01", "action": "提前6月提醒"}],
|
||
status="active"),
|
||
InvestmentAgreement(company_id=COMP_C, title="B轮投资协议", signed_at=datetime(2022, 12, 1, tzinfo=UTC),
|
||
key_clauses={"valuation": "10亿", "investment": "2亿", "board_seat": "1席", "info_rights": "月报+季度财务"},
|
||
monitoring_rules=[{"clause": "信息权", "trigger": "月报延迟>5天", "action": "通知投后负责人"}],
|
||
status="active"),
|
||
]
|
||
for a in agreements:
|
||
db.add(a)
|
||
await db.flush()
|
||
print(" ✓ 投资协议 (3 份)")
|
||
|
||
|
||
# ─── 董事会 ────────────────────────────────────────────────────────────
|
||
async def _seed_boards(db: AsyncSession) -> None:
|
||
boards = [
|
||
BoardMeeting(company_id=COMP_A, title="2025年Q2董事会", meeting_at=D(-7), status="scheduled",
|
||
agenda=[{"item": "Q2经营汇报", "duration": "30min"}, {"item": "B轮融资进展", "duration": "20min"}, {"item": "客户流失分析", "duration": "15min"}],
|
||
materials_summary="AI摘要：Q2营收2400万(完成80%)，客户净增5家但流失率上升，B轮估值预期8-10亿。",
|
||
questions=[{"q": "客户流失率上升的原因是什么？", "priority": "high"}, {"q": "B轮预计何时close？", "priority": "medium"}]),
|
||
BoardMeeting(company_id=COMP_C, title="2025年Q2董事会", meeting_at=D(-14), status="completed",
|
||
agenda=[{"item": "Q2经营汇报", "duration": "30min"}, {"item": "半导体行业拓展", "duration": "20min"}],
|
||
minutes="Q2营收3600万超预期，半导体占比60%。专利新增2项。CTO稳定性需关注。",
|
||
resolutions=[{"item": "批准CTO股权激励调整方案", "status": "执行中"}, {"item": "Q3启动半导体行业专项销售", "status": "已启动"}]),
|
||
]
|
||
for b in boards:
|
||
db.add(b)
|
||
await db.flush()
|
||
print(" ✓ 董事会 (2 场)")
|
||
|
||
|
||
# ─── BML 假设 ──────────────────────────────────────────────────────────
|
||
async def _seed_hypotheses(db: AsyncSession) -> None:
|
||
hypotheses = [
|
||
Hypothesis(company_id=COMP_A, hypothesis="降低定价10%可提升客户签约率30%",
|
||
experiment="对3家潜在客户提供10%折扣试用",
|
||
data={"customers_tested": 3, "signed": 2, "conversion_rate": 0.67},
|
||
conclusion="部分验证：签约率提升67%（超预期30%），但需观察折扣结束后续约率",
|
||
status="validated"),
|
||
Hypothesis(company_id=COMP_B, hypothesis="金融行业客户愿意为数据合规功能支付20%溢价",
|
||
experiment="向2家金融客户展示合规模块并报价溢价20%",
|
||
data={"customers_tested": 2, "interested": 1, "signed": 0},
|
||
conclusion="待验证：1家表示感兴趣但需内部审批，尚未签约",
|
||
status="measuring"),
|
||
Hypothesis(company_id=COMP_C, hypothesis="半导体客户对边缘端质检需求年增长50%",
|
||
experiment="调研5家半导体客户未来12月质检预算",
|
||
data={"surveyed": 3, "budget_increase_avg": 0.35},
|
||
conclusion="未达预期：平均预算增长35%低于50%假设，但基础需求强劲",
|
||
status="learning"),
|
||
]
|
||
for h in hypotheses:
|
||
db.add(h)
|
||
await db.flush()
|
||
print(" ✓ BML 假设 (3 条)")
|
||
|
||
|
||
# ─── AAR 复盘 ──────────────────────────────────────────────────────────
|
||
async def _seed_aars(db: AsyncSession) -> None:
|
||
aars = [
|
||
AARRecord(company_id=COMP_A, trigger_event="Q1客户流失率升至4%",
|
||
original_plan="Q1客户流失率控制在2%以内",
|
||
actual_result="Q1流失率4%，流失2家年合同客户",
|
||
gap_analysis="客户成功团队响应延迟，流失客户反馈'技术支持不够及时'。竞品以低价策略抢客。",
|
||
lessons={"what_expected": "流失率2%", "what_happened": "4%", "why_gap": "客户成功人手不足+竞品低价", "what_learned": "需主动客户健康度监控", "what_to_change": "增加客户成功HC，建立预警机制"},
|
||
improvements=[{"action": "增加2名客户成功经理", "status": "已完成", "owner": "创始人"}, {"action": "建立客户健康度周报", "status": "进行中", "owner": "投资经理"}]),
|
||
AARRecord(company_id=COMP_C, trigger_event="CTO稳定性下降",
|
||
original_plan="核心技术团队稳定，无关键人员流失",
|
||
actual_result="CTO更新简历，稳定性评分0.65",
|
||
gap_analysis="CTO反馈股权激励不足，技术路线存在分歧。",
|
||
lessons={"what_expected": "CTO长期稳定", "what_happened": "稳定性下降", "why_gap": "股权激励未随估值增长调整", "what_learned": "关键人才激励需动态调整", "what_to_change": "建立定期激励review机制"},
|
||
improvements=[{"action": "CTO股权激励调整方案", "status": "设计中", "owner": "投后负责人"}]),
|
||
]
|
||
for a in aars:
|
||
db.add(a)
|
||
await db.flush()
|
||
print(" ✓ AAR 复盘 (2 条)")
|
||
|
||
|
||
# ─── 团队成员 ──────────────────────────────────────────────────────────
|
||
async def _seed_team_members(db: AsyncSession) -> None:
|
||
members = [
|
||
TeamMember(company_id=COMP_A, name="陈智链", role="CEO/创始人", is_key_person=True, joined_at=datetime(2021, 3, 1, tzinfo=UTC), stability_score=0.92),
|
||
TeamMember(company_id=COMP_A, name="张技术", role="CTO", is_key_person=True, joined_at=datetime(2021, 4, 1, tzinfo=UTC), stability_score=0.85),
|
||
TeamMember(company_id=COMP_A, name="李销售", role="VP销售", is_key_person=True, joined_at=datetime(2022, 1, 1, tzinfo=UTC), stability_score=0.80),
|
||
TeamMember(company_id=COMP_C, name="赵深瞳", role="CEO/创始人", is_key_person=True, joined_at=datetime(2020, 6, 1, tzinfo=UTC), stability_score=0.90),
|
||
TeamMember(company_id=COMP_C, name="孙算法", role="CTO", is_key_person=True, joined_at=datetime(2020, 7, 1, tzinfo=UTC), stability_score=0.65),
|
||
TeamMember(company_id=COMP_C, name="周产品", role="产品总监", is_key_person=False, joined_at=datetime(2021, 3, 1, tzinfo=UTC), stability_score=0.78),
|
||
TeamMember(company_id=COMP_B, name="刘云栈", role="CEO/创始人", is_key_person=True, joined_at=datetime(2022, 1, 1, tzinfo=UTC), stability_score=0.88),
|
||
]
|
||
for m in members:
|
||
db.add(m)
|
||
await db.flush()
|
||
print(" ✓ 团队成员 (7 人)")
|
||
|
||
|
||
# ─── 人才画像 ──────────────────────────────────────────────────────────
|
||
async def _seed_talents(db: AsyncSession) -> None:
|
||
talents = [
|
||
TalentProfile(tenant_id=TENANT_ID, name="孙算法", current_role="CTO", current_company="深瞳智能",
|
||
skills=["计算机视觉", "PyTorch", "团队管理", "边缘计算"], experience_years=12,
|
||
performance_rating=4.5, potential_rating=4.0, nine_box="star",
|
||
flow_prediction={"probability": 0.65, "timeline": "3-6月", "triggers": ["股权激励不足", "技术路线分歧"]},
|
||
status="active"),
|
||
TalentProfile(tenant_id=TENANT_ID, name="李销售", current_role="VP销售", current_company="智链科技",
|
||
skills=["B2B销售", "制造业客户", "团队管理"], experience_years=10,
|
||
performance_rating=4.2, potential_rating=3.8, nine_box="high_potential",
|
||
flow_prediction={"probability": 0.20, "timeline": "12月+", "triggers": []},
|
||
status="active"),
|
||
TalentProfile(tenant_id=TENANT_ID, name="吴架构", current_role="首席架构师", current_company="云栈数据",
|
||
skills=["分布式系统", "数据治理", "Kubernetes"], experience_years=15,
|
||
performance_rating=4.8, potential_rating=4.5, nine_box="star",
|
||
flow_prediction={"probability": 0.15, "timeline": "稳定", "triggers": []},
|
||
status="active"),
|
||
]
|
||
for t in talents:
|
||
db.add(t)
|
||
await db.flush()
|
||
print(" ✓ 人才画像 (3 人)")
|
||
|
||
|
||
# ─── 审计日志 ──────────────────────────────────────────────────────────
|
||
async def _seed_audit_logs(db: AsyncSession) -> None:
|
||
logs = [
|
||
AuditLog(tenant_id=TENANT_ID, user_id=MGR_ID, action="login", resource_type="auth", ip="192.168.1.100", created_at=D(0)),
|
||
AuditLog(tenant_id=TENANT_ID, user_id=MGR_ID, action="view", resource_type="company", resource_id=COMP_A, ip="192.168.1.100", created_at=D(0)),
|
||
AuditLog(tenant_id=TENANT_ID, user_id=MGR_ID, action="view", resource_type="report", resource_id="report_001", ip="192.168.1.100", created_at=D(0)),
|
||
AuditLog(tenant_id=TENANT_ID, user_id=LEAD_ID, action="view", resource_type="risk", resource_id="risk_001", ip="192.168.1.101", created_at=D(1)),
|
||
AuditLog(tenant_id=TENANT_ID, user_id=LEAD_ID, action="update", resource_type="risk", resource_id="risk_001", detail_json={"field": "status", "old": "open", "new": "assigned"}, ip="192.168.1.101", created_at=D(1)),
|
||
AuditLog(tenant_id=TENANT_ID, user_id=GP_ID, action="view", resource_type="dashboard", ip="192.168.1.102", created_at=D(2)),
|
||
AuditLog(tenant_id=TENANT_ID, user_id=GP_ID, action="ai_call", resource_type="weekly_brief", detail_json={"tokens": 3500, "model": "qwen-max"}, ip="192.168.1.102", created_at=D(2)),
|
||
AuditLog(tenant_id=TENANT_ID, user_id=ADMIN_ID, action="view", resource_type="audit_logs", ip="192.168.1.103", created_at=D(3)),
|
||
AuditLog(tenant_id=TENANT_ID, user_id=FOUNDER_A, action="create", resource_type="monthly_report", detail_json={"company": "智链科技", "period": f"{NOW.year}-{NOW.month-1}"}, ip="10.0.0.50", created_at=D(10)),
|
||
AuditLog(tenant_id=TENANT_ID, user_id=FOUNDER_B, action="create", resource_type="monthly_report", detail_json={"company": "云栈数据", "period": f"{NOW.year}-{NOW.month-1}"}, ip="10.0.0.51", created_at=D(8)),
|
||
]
|
||
for l in logs:
|
||
db.add(l)
|
||
await db.flush()
|
||
print(" ✓ 审计日志 (10 条)")
|
||
|
||
|
||
# ─── 健康度历史趋势（近 6 个月） ──────────────────────────────────────
|
||
async def _seed_health_history(db: AsyncSession) -> None:
|
||
"""每家企业近 6 个月健康度趋势，用于趋势图展示。"""
|
||
# 基线分数和月度变化趋势
|
||
trends = [
|
||
# (company_id, base_score, monthly_deltas)
|
||
(COMP_A, 70.0, [+1.5, +2.0, +1.5, +2.0, +1.5, +0.0]), # 上升趋势
|
||
(COMP_B, 65.0, [-0.5, -0.5, +0.0, -0.5, -1.0, +0.0]), # 下降趋势
|
||
(COMP_C, 75.0, [+1.5, +2.0, +2.5, +2.0, +1.5, +1.0]), # 强上升
|
||
(COMP_D, 58.0, [-2.0, -2.0, -2.5, -1.5, -1.0, -1.0]), # 持续下降
|
||
(COMP_E, 65.0, [+0.5, +1.0, +0.5, +1.0, +0.5, +0.0]), # 缓慢上升
|
||
]
|
||
for comp_id, base, deltas in trends:
|
||
score = base
|
||
for i, delta in enumerate(deltas):
|
||
score += delta
|
||
m = (NOW.month - i - 1) if (NOW.month - i - 1) > 0 else (12 + NOW.month - i - 1)
|
||
y = NOW.year if (NOW.month - i - 1) > 0 else NOW.year - 1
|
||
db.add(HealthScore(
|
||
company_id=comp_id, total_score=round(score, 1),
|
||
financial_score=round(score * 1.05, 1), operational_score=round(score * 0.95, 1),
|
||
ai_commercial_score=round(score * 1.02, 1), ai_cost_score=round(score * 1.08, 1),
|
||
org_talent_score=round(score * 0.92, 1), product_tech_score=round(score * 1.03, 1),
|
||
market_compete_score=round(score * 0.98, 1), governance_score=round(score * 0.96, 1),
|
||
financing_score=round(score * 0.94, 1),
|
||
synergy_score=round(score * 0.97, 1), ai_model_product_score=round(score * 1.04, 1),
|
||
data_compliance_score=round(score * 1.12, 1), team_tech_score=round(score * 0.95, 1),
|
||
customer_success_score=round(score * 0.87, 1),
|
||
trend="up" if delta > 0 else "down" if delta < 0 else "stable",
|
||
evidence_json={"historical": True, "month": f"{y}-{m:02d}"},
|
||
calculated_at=datetime(y, m, 1, tzinfo=UTC),
|
||
fund_type="early_vc", fund_lifecycle="investment", company_stage="b", industry="ai", strategy="growth",
|
||
))
|
||
await db.flush()
|
||
print(" ✓ 健康度历史趋势 (5 企业 x 6 月)")
|
||
|
||
|
||
# ─── 基金 ──────────────────────────────────────────────────────────────
|
||
async def _seed_funds(db: AsyncSession) -> None:
|
||
"""基金信息 + 企业-基金关联。"""
|
||
fund1 = Fund(tenant_id=TENANT_ID, name="远见三期人民币基金", fund_type="early_vc", strategy="growth",
|
||
established_date=datetime(2023, 1, 1).date(), total_lifespan_months=84, investment_period_months=48,
|
||
lp_composition_json={"government": 30, "market": 50, "corporate": 20}, primary_market="china_mainland")
|
||
fund2 = Fund(tenant_id=TENANT_ID, name="远见天使基金", fund_type="angel", strategy="growth",
|
||
established_date=datetime(2024, 1, 1).date(), total_lifespan_months=72, investment_period_months=36,
|
||
lp_composition_json={"government": 20, "market": 60, "corporate": 20}, primary_market="china_mainland")
|
||
for f in [fund1, fund2]:
|
||
db.add(f)
|
||
await db.flush()
|
||
|
||
links = [
|
||
CompanyFundLink(company_id=COMP_A, fund_id=fund1.id, investment_date=datetime(2023, 6, 1).date(),
|
||
investment_stage="b", round="B轮", amount=5000, ownership_pct=12.5, is_current=True),
|
||
CompanyFundLink(company_id=COMP_B, fund_id=fund1.id, investment_date=datetime(2023, 3, 1).date(),
|
||
investment_stage="a", round="A轮", amount=2000, ownership_pct=15.0, is_current=True),
|
||
CompanyFundLink(company_id=COMP_C, fund_id=fund1.id, investment_date=datetime(2022, 12, 1).date(),
|
||
investment_stage="b", round="B轮", amount=8000, ownership_pct=20.0, is_current=True),
|
||
CompanyFundLink(company_id=COMP_E, fund_id=fund1.id, investment_date=datetime(2023, 9, 1).date(),
|
||
investment_stage="a", round="A轮", amount=3000, ownership_pct=10.0, is_current=True),
|
||
CompanyFundLink(company_id=COMP_D, fund_id=fund2.id, investment_date=datetime(2024, 3, 1).date(),
|
||
investment_stage="seed", round="天使轮", amount=500, ownership_pct=8.0, is_current=True),
|
||
]
|
||
for l in links:
|
||
db.add(l)
|
||
await db.flush()
|
||
print(" ✓ 基金 (2 支) + 关联 (5 条)")
|
||
|
||
|
||
# ─── 多主体画像 ────────────────────────────────────────────────────────
|
||
async def _seed_profiles(db: AsyncSession) -> None:
|
||
"""投资机构、基金、投资经理画像。"""
|
||
firm = FirmProfile(tenant_id=TENANT_ID, name="远见资本",
|
||
focus_areas={"sectors": ["AI", "硬科技", "生物医药"], "stages": ["seed", "A", "B"]},
|
||
stage_preference="seed-B", description="专注早期科技投资，管理规模15亿人民币。")
|
||
db.add(firm)
|
||
await db.flush()
|
||
|
||
db.add(FundProfile(firm_id=firm.id, name="远见三期人民币基金", fund_size="5亿人民币", vintage_year=2023,
|
||
strategy="早期科技，AI+硬科技为主，赋能式投后管理。"))
|
||
db.add(FundProfile(firm_id=firm.id, name="远见天使基金", fund_size="1亿人民币", vintage_year=2024,
|
||
strategy="天使阶段，聚焦AI应用和芯片设计。"))
|
||
|
||
db.add(ManagerProfile(firm_id=firm.id, user_id=MGR_ID, name="王经理",
|
||
focus_areas={"sectors": ["AI/供应链", "AI/数据平台"], "companies": [COMP_A, COMP_B]},
|
||
portfolio_count=2))
|
||
db.add(ManagerProfile(firm_id=firm.id, user_id=LEAD_ID, name="李投后",
|
||
focus_areas={"sectors": ["AI/计算机视觉", "AI/医疗"], "companies": [COMP_C, COMP_E]},
|
||
portfolio_count=2))
|
||
await db.flush()
|
||
print(" ✓ 画像 (机构1 + 基金2 + 经理2)")
|
||
|
||
|
||
# ─── 评价模板 ──────────────────────────────────────────────────────────
|
||
async def _seed_evaluation_templates(db: AsyncSession) -> None:
|
||
"""6 轴动态评价模板 — 覆盖常见组合。"""
|
||
templates = [
|
||
EvaluationTemplate(tenant_id=TENANT_ID, name="早期VC-AI-B轮-成长策略",
|
||
fund_type="early_vc", fund_lifecycle="investment", company_stage="b",
|
||
industry="ai", strategy="growth", investor_type="investor",
|
||
weights_json={"financial": 0.12, "operational": 0.10, "ai_commercial": 0.12, "ai_cost": 0.08,
|
||
"org_talent": 0.10, "product_tech": 0.12, "market_compete": 0.10, "governance": 0.06,
|
||
"financing": 0.08, "synergy": 0.04, "ai_model_product": 0.04, "data_compliance": 0.02,
|
||
"team_tech": 0.01, "customer_success": 0.01},
|
||
enabled_dimensions=["financial", "operational", "ai_commercial", "ai_cost", "org_talent",
|
||
"product_tech", "market_compete", "governance", "financing", "synergy",
|
||
"ai_model_product", "data_compliance", "team_tech", "customer_success"],
|
||
disabled_dimensions=[],
|
||
custom_metrics_json={"ai_poc_count": {"label": "AI PoC 数量", "source": "月报"}, "compliance_issues": {"label": "合规整改项", "source": "审计"}},
|
||
is_default=True),
|
||
EvaluationTemplate(tenant_id=TENANT_ID, name="天使-硬件-种子期-成长策略",
|
||
fund_type="angel", fund_lifecycle="investment", company_stage="seed",
|
||
industry="hardware", strategy="growth", investor_type="gp",
|
||
weights_json={"financial": 0.06, "operational": 0.08, "ai_commercial": 0.08, "ai_cost": 0.06,
|
||
"org_talent": 0.15, "product_tech": 0.20, "market_compete": 0.10, "governance": 0.05,
|
||
"financing": 0.12, "synergy": 0.03, "ai_model_product": 0.04, "data_compliance": 0.01,
|
||
"team_tech": 0.02, "customer_success": 0.00},
|
||
enabled_dimensions=["financial", "operational", "ai_commercial", "ai_cost", "org_talent",
|
||
"product_tech", "market_compete", "governance", "financing", "synergy",
|
||
"ai_model_product", "data_compliance", "team_tech"],
|
||
disabled_dimensions=["customer_success"],
|
||
is_default=True),
|
||
EvaluationTemplate(tenant_id=TENANT_ID, name="早期VC-生物医疗-A轮-成长策略",
|
||
fund_type="early_vc", fund_lifecycle="investment", company_stage="a",
|
||
industry="biotech", strategy="growth", investor_type="investor",
|
||
weights_json={"financial": 0.08, "operational": 0.10, "ai_commercial": 0.10, "ai_cost": 0.06,
|
||
"org_talent": 0.12, "product_tech": 0.18, "market_compete": 0.08, "governance": 0.08,
|
||
"financing": 0.10, "synergy": 0.03, "ai_model_product": 0.04, "data_compliance": 0.03,
|
||
"team_tech": 0.00, "customer_success": 0.00},
|
||
enabled_dimensions=["financial", "operational", "ai_commercial", "ai_cost", "org_talent",
|
||
"product_tech", "market_compete", "governance", "financing", "synergy",
|
||
"ai_model_product", "data_compliance"],
|
||
disabled_dimensions=["team_tech", "customer_success"],
|
||
is_default=True),
|
||
]
|
||
for t in templates:
|
||
db.add(t)
|
||
await db.flush()
|
||
print(" ✓ 评价模板 (3 套)")
|
||
|
||
|
||
# ─── 追问清单 ──────────────────────────────────────────────────────────
|
||
async def _seed_inquiries(db: AsyncSession) -> None:
|
||
"""月报追问清单 — AI 生成补充问题。"""
|
||
inquiries = [
|
||
InquiryList(company_id=COMP_A,
|
||
questions=[{"q": "本月流失客户的具体原因是什么？", "a": "客户反馈技术支持响应慢，竞品以低价策略抢客。"},
|
||
{"q": "AI推理成本降低12%的具体措施？", "a": "采用模型量化+推理优化，单次调用成本从0.05元降至0.044元。"},
|
||
{"q": "新签3家客户的年合同金额？", "a": "合计约480万/年，平均160万/家。"}],
|
||
status="answered", sent_at=D(9), answered_at=D(5)),
|
||
InquiryList(company_id=COMP_B,
|
||
questions=[{"q": "营收连续2个月持平的原因？", "a": "现有客户续约稳定，但新客户拓展速度放缓。"},
|
||
{"q": "金融客户拓展进展？", "a": "1家银行已进POC阶段，预计Q3签约。"},
|
||
{"q": "A+轮融资准备情况？", "a": "BP初稿完成，正在整理财务预测。"}],
|
||
status="answered", sent_at=D(7), answered_at=D(3)),
|
||
InquiryList(company_id=COMP_D,
|
||
questions=[{"q": "NPU原型流片时间表？", "a": "预计下月流片，Q4出工程样片。"},
|
||
{"q": "天使+轮BP何时可以准备好？", "a": "正在准备中，预计2周内完成。"}],
|
||
status="sent", sent_at=D(2)),
|
||
]
|
||
for i in inquiries:
|
||
db.add(i)
|
||
await db.flush()
|
||
print(" ✓ 追问清单 (3 条)")
|
||
|
||
|
||
# ─── Agent 执行记录 ────────────────────────────────────────────────────
|
||
async def _seed_agent_executions(db: AsyncSession) -> None:
|
||
"""AI Agent L1-L4 分级执行记录。"""
|
||
agents = [
|
||
AgentExecution(tenant_id=TENANT_ID, agent_name="月报解析Agent", autonomy_level="L3",
|
||
input_summary="智链科技2025-06月报", output_summary="解析完成：营收800万(+15%)，客户净增2家",
|
||
output_detail={"revenue": 800, "mom_growth": 0.15, "new_customers": 3, "churned": 1},
|
||
review_status="auto_approved", model_version="gpt-4o-2024", duration_ms=3200),
|
||
AgentExecution(tenant_id=TENANT_ID, agent_name="风险预警Agent", autonomy_level="L2",
|
||
input_summary="量子芯微财务数据扫描", output_summary="发现1项critical风险：Runway不足7月",
|
||
output_detail={"risks_found": 1, "severity": "critical", "metric": "runway", "value": 7},
|
||
review_status="approved", reviewer_id=MGR_ID, reviewed_at=D(3), model_version="gpt-4o-2024", duration_ms=1800),
|
||
AgentExecution(tenant_id=TENANT_ID, agent_name="弱信号监测Agent", autonomy_level="L3",
|
||
input_summary="深瞳智能外部信号扫描", output_summary="LinkedIn检测到CTO更新简历",
|
||
output_detail={"signal_type": "org", "source": "LinkedIn", "confidence": 0.85},
|
||
review_status="auto_approved", model_version="gpt-4o-2024", duration_ms=2400),
|
||
AgentExecution(tenant_id=TENANT_ID, agent_name="协同匹配Agent", autonomy_level="L2",
|
||
input_summary="Portfolio协同分析", output_summary="发现3个协同机会",
|
||
output_detail={"matches": 3, "types": ["customer", "tech", "talent"]},
|
||
review_status="approved", reviewer_id=LEAD_ID, reviewed_at=D(5), model_version="gpt-4o-2024", duration_ms=5600),
|
||
AgentExecution(tenant_id=TENANT_ID, agent_name="健康度计算Agent", autonomy_level="L4",
|
||
input_summary="5家企业健康度季度评估", output_summary="14维度评分完成，2家上升1家下降",
|
||
output_detail={"companies": 5, "trends": {"up": 2, "stable": 2, "down": 1}},
|
||
review_status="auto_approved", model_version="gpt-4o-2024", duration_ms=8200),
|
||
AgentExecution(tenant_id=TENANT_ID, agent_name="月报解析Agent", autonomy_level="L3",
|
||
input_summary="云栈数据2025-06月报", output_summary="解析完成：营收150万(持平)",
|
||
output_detail={"revenue": 150, "mom_growth": 0.0},
|
||
review_status="auto_approved", model_version="gpt-4o-2024", duration_ms=2800),
|
||
AgentExecution(tenant_id=TENANT_ID, agent_name="决策哨兵Agent", autonomy_level="L2",
|
||
input_summary="云栈数据融资时机分析", output_summary="建议现在启动A+轮融资",
|
||
output_detail={"decision": "funding", "recommendation": "now", "confidence": 0.72},
|
||
review_status="pending", model_version="gpt-4o-2024", duration_ms=4200),
|
||
AgentExecution(tenant_id=TENANT_ID, agent_name="数据校验Agent", autonomy_level="L4",
|
||
input_summary="5家企业财务数据交叉校验", output_summary="校验通过，数据一致性98.5%",
|
||
output_detail={"checked": 30, "passed": 29, "inconsistencies": 1},
|
||
review_status="auto_approved", model_version="gpt-4o-2024", duration_ms=1500),
|
||
]
|
||
for idx, a in enumerate(agents):
|
||
a.created_at = D(10 - idx)
|
||
db.add(a)
|
||
await db.flush()
|
||
print(" ✓ Agent 执行记录 (8 条)")
|
||
|
||
|
||
# ─── 客户获取计划 ──────────────────────────────────────────────────────
|
||
async def _seed_customer_plans(db: AsyncSession) -> None:
|
||
"""AI 客户增长引擎 — LP 资源匹配 + 客户获取方案。"""
|
||
plans = [
|
||
CustomerAcquisitionPlan(company_id=COMP_A, target_customer="年营收10-50亿制造业CIO/供应链总监",
|
||
entry_angle="从供应链预测场景切入，ROI 3个月可见",
|
||
decision_chain={"roles": ["CIO", "供应链VP", "采购总监"], "influence": {"CIO": 0.4, "供应链VP": 0.4, "采购总监": 0.2}, "cycle": "3-6月"},
|
||
pricing_strategy="SaaS订阅：年费80-200万，按模块阶梯定价",
|
||
competitive_analysis={"direct": ["杉数科技", "京东物流AI"], "advantage": "多模态决策引擎，部署快3倍", "weakness": "品牌知名度低"},
|
||
lp_resources={"lp_company": "某制造业LP", "intro_channel": "GP引荐", "warmth": "high"},
|
||
execution_status="executing",
|
||
result={"customers_contacted": 5, "poc_started": 2, "signed": 1, "revenue": 160}),
|
||
CustomerAcquisitionPlan(company_id=COMP_B, target_customer="金融机构数据治理负责人",
|
||
entry_angle="合规驱动+AI训练数据管理，从数据治理切入",
|
||
decision_chain={"roles": ["数据治理总监", "合规负责人", "CTO"], "influence": {"数据治理总监": 0.5, "合规负责人": 0.3, "CTO": 0.2}, "cycle": "6-12月"},
|
||
pricing_strategy="平台授权+实施服务：首年120万+实施80万",
|
||
competitive_analysis={"direct": ["亿信华辰", "数美科技"], "advantage": "AI原生，支持大模型训练数据管理", "weakness": "金融行业案例少"},
|
||
lp_resources={"lp_company": "某银行LP", "intro_channel": "GP引荐", "warmth": "medium"},
|
||
execution_status="planned",
|
||
result=None),
|
||
CustomerAcquisitionPlan(company_id=COMP_C, target_customer="半导体晶圆厂质检负责人",
|
||
entry_angle="替代人工目检，从良率提升切入",
|
||
decision_chain={"roles": ["质量总监", "生产VP", "CIO"], "influence": {"质量总监": 0.5, "生产VP": 0.3, "CIO": 0.2}, "cycle": "3-6月"},
|
||
pricing_strategy="设备+软件：单条产线200-400万",
|
||
competitive_analysis={"direct": ["康代智能", "奥普特"], "advantage": "AI算法精度99.2%，行业领先", "weakness": "硬件成本偏高"},
|
||
lp_resources={"lp_company": "某半导体LP", "intro_channel": "LP直接引荐", "warmth": "high"},
|
||
execution_status="completed",
|
||
result={"customers_contacted": 8, "poc_started": 5, "signed": 3, "revenue": 800}),
|
||
]
|
||
for p in plans:
|
||
db.add(p)
|
||
await db.flush()
|
||
print(" ✓ 客户获取计划 (3 条)")
|
||
|
||
|
||
# ─── 退出预测 ──────────────────────────────────────────────────────────
|
||
async def _seed_exit_predictions(db: AsyncSession) -> None:
|
||
"""退出时机预测 — IPO/并购/二手份额。"""
|
||
predictions = [
|
||
ExitPrediction(company_id=COMP_C, exit_path="ipo",
|
||
timing_window={"earliest": "2027-Q1", "latest": "2028-Q3"},
|
||
expected_return=4.2, hold_return=2.8, confidence=0.75,
|
||
signals={"positive": ["营收年增50%+", "半导体赛道热度高", "专利壁垒"], "negative": ["客户集中度60%", "CTO稳定性"]},
|
||
recommendation="建议2027年Q1启动IPO准备，当前应解决客户集中度和CTO retention问题。"),
|
||
ExitPrediction(company_id=COMP_A, exit_path="acquisition",
|
||
timing_window={"earliest": "2026-Q3", "latest": "2027-Q4"},
|
||
expected_return=3.5, hold_return=3.0, confidence=0.65,
|
||
signals={"positive": ["多模态技术差异化", "制造业客户基础"], "negative": ["客户流失率上升", "竞争加剧"]},
|
||
recommendation="建议关注产业并购机会，优先接触京东物流、菜鸟等供应链平台。"),
|
||
ExitPrediction(company_id=COMP_E, exit_path="acquisition",
|
||
timing_window={"earliest": "2028-Q1", "latest": "2030-Q4"},
|
||
expected_return=5.0, hold_return=3.5, confidence=0.55,
|
||
signals={"positive": ["AI药物发现赛道升温", "3靶点进入先导"], "negative": ["研发周期长", "现金流压力"]},
|
||
recommendation="建议继续持有，等待靶点临床验证结果后评估并购机会。"),
|
||
]
|
||
for p in predictions:
|
||
db.add(p)
|
||
await db.flush()
|
||
print(" ✓ 退出预测 (3 条)")
|
||
|
||
|
||
# ─── Pre-mortem + Red Team ─────────────────────────────────────────────
|
||
async def _seed_pre_mortems(db: AsyncSession) -> None:
|
||
"""失败推演 + 对抗分析。"""
|
||
pre_mortems = [
|
||
PreMortemRecord(company_id=COMP_D, decision_context="天使+轮融资1500万，估值8000万",
|
||
failure_paths=[{"path": "流片失败导致估值缩水", "probability": 0.25, "impact": "high"},
|
||
{"path": "融资周期超3月，现金耗尽", "probability": 0.15, "impact": "critical"},
|
||
{"path": "竞品发布同类NPU，差异化丧失", "probability": 0.20, "impact": "medium"}],
|
||
risk_checklist={"items": ["流片进度", "现金Runway", "竞品动态", "核心团队稳定性"], "checked": 3, "total": 4},
|
||
mitigations={"actions": ["准备过桥贷款方案", "与2家竞品做技术对标", "CTO股权激励绑定"]}),
|
||
PreMortemRecord(company_id=COMP_B, decision_context="A+轮融资3000万 vs 等待Q2数据验证",
|
||
failure_paths=[{"path": "现在融资估值偏低，稀释过多", "probability": 0.40, "impact": "medium"},
|
||
{"path": "等待期间现金耗尽", "probability": 0.20, "impact": "critical"},
|
||
{"path": "Q2数据不及预期，融资更难", "probability": 0.30, "impact": "high"}],
|
||
risk_checklist={"items": ["现金Runway", "Q2营收预期", "竞品定价压力", "金融客户签约"], "checked": 2, "total": 4},
|
||
mitigations={"actions": ["准备两套BP", "与现有股东沟通过桥", "加速金融客户POC"]}),
|
||
]
|
||
for p in pre_mortems:
|
||
db.add(p)
|
||
|
||
red_teams = [
|
||
RedTeamRecord(company_id=COMP_A, perspective="competitor",
|
||
analysis="如果我是杉数科技，会以低价+行业深耕策略抢智链科技的制造业客户。智链的多模态优势在具体场景中并未形成壁垒。",
|
||
vulnerabilities={"areas": ["客户成功团队薄弱", "品牌知名度低", "定价偏高"], "severity": "medium"},
|
||
counterarguments={"defense": ["多模态技术差异化", "客户切换成本高"]}),
|
||
RedTeamRecord(company_id=COMP_C, perspective="pessimistic_investor",
|
||
analysis="深瞳智能半导体占比60%是定时炸弹。半导体周期下行时营收将大幅缩水。CTO稳定性问题如果恶化，技术优势可能丧失。",
|
||
vulnerabilities={"areas": ["客户集中度60%", "CTO稳定性0.65", "半导体周期风险"], "severity": "high"},
|
||
counterarguments={"defense": ["正在拓展新能源客户", "CTO激励方案设计中"]}),
|
||
RedTeamRecord(company_id=COMP_D, perspective="devils_advocate",
|
||
analysis="量子芯微的NPU在边缘端确实有需求，但巨头(英伟达/高通)一旦下沉，创业公司很难竞争。7月Runway意味着没有试错空间。",
|
||
vulnerabilities={"areas": ["巨头竞争风险", "Runway 7月", "无营收"], "severity": "critical"},
|
||
counterarguments={"defense": ["边缘端低功耗是差异化", "已有3家潜在客户"]}),
|
||
]
|
||
for r in red_teams:
|
||
db.add(r)
|
||
await db.flush()
|
||
print(" ✓ Pre-mortem (2) + Red Team (3)")
|
||
|
||
|
||
# ─── 产品竞争力诊断 ────────────────────────────────────────────────────
|
||
async def _seed_product_diagnostics(db: AsyncSession) -> None:
|
||
"""产品竞争力诊断 — 热力图 + 竞品对比。"""
|
||
diagnostics = [
|
||
ProductDiagnostic(company_id=COMP_A, product_name="多模态供应链决策引擎",
|
||
dimensions={"技术壁垒": 82, "产品成熟度": 75, "用户体验": 70, "生态集成": 65, "定价竞争力": 60, "客户支持": 55},
|
||
heatmap_data={"strengths": ["技术壁垒", "产品成熟度"], "weaknesses": ["客户支持", "定价竞争力"], "neutral": ["用户体验", "生态集成"]},
|
||
competitors=[{"name": "杉数科技", "scores": {"技术壁垒": 78, "产品成熟度": 85, "用户体验": 80, "生态集成": 75, "定价竞争力": 70, "客户支持": 82}},
|
||
{"name": "京东物流AI", "scores": {"技术壁垒": 70, "产品成熟度": 88, "用户体验": 85, "生态集成": 90, "定价竞争力": 65, "客户支持": 78}}],
|
||
roadmap_suggestions="建议优先提升客户支持能力（增加2名CSM）和优化定价策略（引入阶梯定价），同时加强生态集成（对接ERP系统）。"),
|
||
ProductDiagnostic(company_id=COMP_C, product_name="工业质检视觉AI平台",
|
||
dimensions={"技术壁垒": 88, "产品成熟度": 85, "用户体验": 78, "生态集成": 72, "定价竞争力": 65, "客户支持": 80},
|
||
heatmap_data={"strengths": ["技术壁垒", "产品成熟度", "客户支持"], "weaknesses": ["定价竞争力", "生态集成"], "neutral": ["用户体验"]},
|
||
competitors=[{"name": "康代智能", "scores": {"技术壁垒": 82, "产品成熟度": 90, "用户体验": 82, "生态集成": 85, "定价竞争力": 75, "客户支持": 85}},
|
||
{"name": "奥普特", "scores": {"技术壁垒": 75, "产品成熟度": 82, "用户体验": 78, "生态集成": 80, "定价竞争力": 82, "客户支持": 80}}],
|
||
roadmap_suggestions="技术优势明显，建议降低硬件成本（考虑国产替代方案）并加强生态集成（对接MES系统）。"),
|
||
]
|
||
for d in diagnostics:
|
||
db.add(d)
|
||
await db.flush()
|
||
print(" ✓ 产品诊断 (2 条)")
|
||
|
||
|
||
# ─── 同行学习圈 ────────────────────────────────────────────────────────
|
||
async def _seed_peer_circles(db: AsyncSession) -> None:
|
||
"""同行学习圈 — AI 匹配面临类似挑战的创始人。"""
|
||
circles = [
|
||
PeerLearningCircle(tenant_id=TENANT_ID, topic="融资时机选择：现在 vs 等待验证",
|
||
description="云栈数据和量子芯微创始人均面临融资时机决策，AI匹配讨论。",
|
||
members=[{"founder_id": FOUNDER_B, "company_id": COMP_B, "name": "刘云栈"},
|
||
{"founder_id": FOUNDER_C, "company_id": COMP_D, "name": "赵深瞳(代)"}],
|
||
discussion_framework={"steps": ["各自分享融资困境", "分析共同风险", "讨论应对策略", "制定行动承诺"]},
|
||
conclusions="两位创始人一致认为：在营收未达预期时，应优先保证现金Runway > 12月，融资宁可早不要晚。",
|
||
action_commitments=[{"founder": "刘云栈", "action": "2周内完成BP", "deadline": "14天"},
|
||
{"founder": "赵深瞳(代)", "action": "启动天使+轮", "deadline": "7天"}],
|
||
status="completed"),
|
||
PeerLearningCircle(tenant_id=TENANT_ID, topic="客户集中度风险管理",
|
||
description="深瞳智能和智链科技都面临客户集中度/流失问题。",
|
||
members=[{"founder_id": FOUNDER_A, "company_id": COMP_A, "name": "陈智链"},
|
||
{"founder_id": FOUNDER_C, "company_id": COMP_C, "name": "赵深瞳"}],
|
||
discussion_framework={"steps": ["分享客户结构", "分析流失原因", "讨论多元化策略", "制定行动承诺"]},
|
||
conclusions="深瞳：半导体占比60%需降低；智链：流失率4%需降至3%以下。共同策略：建立客户健康度预警机制。",
|
||
action_commitments=[{"founder": "陈智链", "action": "建立客户健康度周报", "deadline": "30天"},
|
||
{"founder": "赵深瞳", "action": "启动新能源客户拓展", "deadline": "60天"}],
|
||
status="active"),
|
||
]
|
||
for c in circles:
|
||
db.add(c)
|
||
await db.flush()
|
||
print(" ✓ 同行学习圈 (2 个)")
|
||
|
||
|
||
# ─── 数字孪生 ──────────────────────────────────────────────────────────
|
||
async def _seed_digital_twins(db: AsyncSession) -> None:
|
||
"""数字孪生模型。"""
|
||
twins = [
|
||
DigitalTwinModel(company_id=COMP_A, model_params={"revenue_model": "saaS_subscription", "churn_rate": 0.03, "growth_rate": 0.15, "cac": 50, "ltv": 400},
|
||
scenarios=[{"name": "乐观", "revenue_y0": 800, "revenue_y1": 1200, "runway_months": 18},
|
||
{"name": "基准", "revenue_y0": 800, "revenue_y1": 1000, "runway_months": 14},
|
||
{"name": "悲观", "revenue_y0": 800, "revenue_y1": 700, "runway_months": 10}],
|
||
accuracy_score=0.82, last_calibrated_at=D(7)),
|
||
DigitalTwinModel(company_id=COMP_C, model_params={"revenue_model": "hardware+software", "semi_ratio": 0.60, "growth_rate": 0.22, "gross_margin": 0.55},
|
||
scenarios=[{"name": "乐观", "revenue_y0": 1200, "revenue_y1": 1800, "valuation": "15亿"},
|
||
{"name": "基准", "revenue_y0": 1200, "revenue_y1": 1500, "valuation": "12亿"},
|
||
{"name": "悲观", "revenue_y0": 1200, "revenue_y1": 1000, "valuation": "8亿"}],
|
||
accuracy_score=0.78, last_calibrated_at=D(14)),
|
||
]
|
||
for t in twins:
|
||
db.add(t)
|
||
await db.flush()
|
||
print(" ✓ 数字孪生 (2 个)")
|
||
|
||
|
||
# ─── 干预事件 + 结果（Alpha 归因） ─────────────────────────────────────
|
||
async def _seed_interventions(db: AsyncSession) -> None:
|
||
"""投后管理 Alpha 归因 — 干预 → 指标变化 → 估值影响。"""
|
||
interventions = [
|
||
InterventionEvent(company_id=COMP_A, intervention_type="customer_intro",
|
||
title="引荐LP制造业客户给智链科技", description="通过LP关系引荐3家制造业客户，加速客户拓展。",
|
||
executed_by=GP_ID, executed_at=D(30)),
|
||
InterventionEvent(company_id=COMP_C, intervention_type="strategy",
|
||
title="建议深瞳智能拓展新能源客户", description="降低半导体客户集中度，拓展新能源赛道。",
|
||
executed_by=LEAD_ID, executed_at=D(45)),
|
||
InterventionEvent(company_id=COMP_A, intervention_type="governance",
|
||
title="推动智链科技建立客户成功团队", description="增加2名CSM，建立客户健康度周报机制。",
|
||
executed_by=MGR_ID, executed_at=D(60)),
|
||
InterventionEvent(company_id=COMP_D, intervention_type="funding",
|
||
title="协助量子芯微准备天使+轮融资", description="GP直接参与BP打磨和投资人对接。",
|
||
executed_by=GP_ID, executed_at=D(10)),
|
||
]
|
||
for i in interventions:
|
||
db.add(i)
|
||
await db.flush()
|
||
|
||
results = [
|
||
InterventionResult(intervention_id=interventions[0].id,
|
||
metric_changes={"customers_new": 2, "revenue_increase": 320, "sales_cycle_reduction": 30},
|
||
valuation_impact=0.5, return_contribution=0.15, alpha_score=0.82,
|
||
evidence={"before": {"customers": 48, "revenue": 800}, "after": {"customers": 50, "revenue": 960}}),
|
||
InterventionResult(intervention_id=interventions[1].id,
|
||
metric_changes={"semi_ratio": -0.05, "new_customers": 1, "revenue_diversification": 0.10},
|
||
valuation_impact=0.3, return_contribution=0.08, alpha_score=0.68,
|
||
evidence={"before": {"semi_ratio": 0.65, "customers": 20}, "after": {"semi_ratio": 0.60, "customers": 21}}),
|
||
InterventionResult(intervention_id=interventions[2].id,
|
||
metric_changes={"churn_rate": -0.01, "csat": 8, "response_time": -40},
|
||
valuation_impact=0.2, return_contribution=0.06, alpha_score=0.72,
|
||
evidence={"before": {"churn_rate": 0.04, "csat": 7.2}, "after": {"churn_rate": 0.03, "csat": 8.0}}),
|
||
]
|
||
for r in results:
|
||
db.add(r)
|
||
await db.flush()
|
||
print(" ✓ 干预事件 (4) + 结果 (3) — Alpha 归因")
|
||
|
||
|
||
# ─── 组合再平衡 + Monte Carlo ──────────────────────────────────────────
|
||
async def _seed_portfolio_simulations(db: AsyncSession) -> None:
|
||
"""组合再平衡建议 + Monte Carlo 模拟结果。"""
|
||
db.add(PortfolioRebalancing(
|
||
tenant_id=TENANT_ID,
|
||
marginal_returns={"COMP_A": 0.25, "COMP_B": 0.08, "COMP_C": 0.35, "COMP_D": -0.05, "COMP_E": 0.15},
|
||
reallocation_plan={"reduce": [{"company": "COMP_B", "amount": 500, "reason": "边际回报低"}],
|
||
"increase": [{"company": "COMP_C", "amount": 300, "reason": "高增长高回报"}, {"company": "COMP_A", "amount": 200, "reason": "上升趋势明确"}]},
|
||
irr_impact=0.03, dpi_impact=0.02, status="proposed",
|
||
))
|
||
|
||
# Monte Carlo — 生成 IRR/DPI 概率分布
|
||
random.seed(42)
|
||
irr_samples = [random.gauss(0.22, 0.08) for _ in range(10000)]
|
||
irr_buckets = {}
|
||
for s in irr_samples:
|
||
bucket = round(s * 2) / 2 # 0.5% 区间
|
||
irr_buckets[str(bucket)] = irr_buckets.get(str(bucket), 0) + 1
|
||
|
||
dpi_samples = [max(0, random.gauss(1.8, 0.4)) for _ in range(10000)]
|
||
dpi_buckets = {}
|
||
for s in dpi_samples:
|
||
bucket = round(s * 2) / 2
|
||
dpi_buckets[str(bucket)] = dpi_buckets.get(str(bucket), 0) + 1
|
||
|
||
db.add(MonteCarloSimulation(
|
||
tenant_id=TENANT_ID, iterations=10000,
|
||
irr_distribution=irr_buckets, dpi_distribution=dpi_buckets,
|
||
percentile_p5=0.08, percentile_p50=0.22, percentile_p95=0.36,
|
||
))
|
||
await db.flush()
|
||
print(" ✓ 组合再平衡 (1) + Monte Carlo (1)")
|
||
|
||
|
||
# ─── 知识图谱 ──────────────────────────────────────────────────────────
|
||
async def _seed_knowledge_graph(db: AsyncSession) -> None:
|
||
"""知识图谱节点 — 企业特征 + 管理动作 + 环境上下文 → 结果 → 回报影响。"""
|
||
nodes = [
|
||
KnowledgeNode(tenant_id=TENANT_ID, entity_type="company", entity_id=COMP_A,
|
||
attributes={"name": "智链科技", "industry": "AI/供应链", "stage": "B"},
|
||
relations=[{"target": "action_1", "type": "received"}, {"target": "context_1", "type": "in"}]),
|
||
KnowledgeNode(tenant_id=TENANT_ID, entity_type="action", entity_id="action_1",
|
||
attributes={"type": "customer_intro", "title": "引荐LP制造业客户"},
|
||
relations=[{"target": "result_1", "type": "led_to"}]),
|
||
KnowledgeNode(tenant_id=TENANT_ID, entity_type="context", entity_id="context_1",
|
||
attributes={"type": "market", "description": "制造业数字化转型加速"},
|
||
relations=[{"target": "result_1", "type": "influenced"}]),
|
||
KnowledgeNode(tenant_id=TENANT_ID, entity_type="result", entity_id="result_1",
|
||
attributes={"metric": "revenue", "change": "+20%", "duration": "3月"},
|
||
relations=[{"target": "return_1", "type": "contributed_to"}]),
|
||
KnowledgeNode(tenant_id=TENANT_ID, entity_type="return", entity_id="return_1",
|
||
attributes={"irr_impact": 0.15, "alpha_score": 0.82},
|
||
relations=[]),
|
||
]
|
||
for n in nodes:
|
||
db.add(n)
|
||
await db.flush()
|
||
print(" ✓ 知识图谱 (5 节点)")
|
||
|
||
|
||
# ─── 数据源 ────────────────────────────────────────────────────────────
|
||
async def _seed_data_sources(db: AsyncSession) -> None:
|
||
"""外部数据源配置。"""
|
||
sources = [
|
||
DataSource(tenant_id=TENANT_ID, source_type="crunchbase", name="Crunchbase API",
|
||
api_endpoint="https://api.crunchbase.com/v3.1", status="active", last_synced_at=D(1),
|
||
config={"sync_frequency": "daily"}),
|
||
DataSource(tenant_id=TENANT_ID, source_type="github", name="GitHub 活跃度监测",
|
||
api_endpoint="https://api.github.com", status="active", last_synced_at=D(1),
|
||
config={"repos": ["zhilian/ai-engine", "yunzhan/data-platform"]}),
|
||
DataSource(tenant_id=TENANT_ID, source_type="business_registry", name="工商信息同步",
|
||
api_endpoint="https://api.qcc.com/v2", status="active", last_synced_at=D(3),
|
||
config={"sync_frequency": "weekly"}),
|
||
DataSource(tenant_id=TENANT_ID, company_id=COMP_C, source_type="custom", name="半导体行业数据库",
|
||
api_endpoint="https://semi-data.example.com/api", status="active", last_synced_at=D(2),
|
||
config={"metrics": ["industry_growth", "competitor_funding"]}),
|
||
]
|
||
for s in sources:
|
||
db.add(s)
|
||
await db.flush()
|
||
print(" ✓ 数据源 (4 个)")
|
||
|
||
|
||
if __name__ == "__main__":
|
||
asyncio.run(seed())
|