hankin
815cbf9d8c
- 更新 .gitignore：全面覆盖环境变量、数据库、日志、缓存、上传文件 - 移除误跟踪的 server/venv/、crm_data.db、.env 文件 - 新增 server/.env.example 模板 - 新增合同管理、利润核算、AI教练等功能模块 - 新增 Playwright e2e 测试套件 - 前后端多项功能升级和 bug 修复
81 lines
4.1 KiB
Python
81 lines
4.1 KiB
Python
"""
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新增 ORM 模型 — ai_chat_sessions / sales_logs / ai_report_drafts
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"""
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from __future__ import annotations
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import uuid
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from datetime import date, datetime
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from sqlalchemy import Boolean, Date, DateTime, ForeignKey, SmallInteger, String, Text, func
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from sqlalchemy.dialects.postgresql import UUID, JSONB, ARRAY
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from sqlalchemy.orm import Mapped, mapped_column
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from app.models.base import Base
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class AiChatSession(Base):
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__tablename__ = "ai_chat_sessions"
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id: Mapped[uuid.UUID] = mapped_column(UUID(as_uuid=True), primary_key=True, default=uuid.uuid4)
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user_id: Mapped[uuid.UUID] = mapped_column(UUID(as_uuid=True), ForeignKey("sys_users.id"), nullable=False)
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role: Mapped[str] = mapped_column(String(10), nullable=False)
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content: Mapped[str] = mapped_column(Text, nullable=False)
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msg_type: Mapped[str] = mapped_column(String(20), default="text")
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metadata_: Mapped[dict | None] = mapped_column("metadata", JSONB, default=dict)
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created_at: Mapped[datetime] = mapped_column(DateTime, server_default=func.now())
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class SalesLog(Base):
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__tablename__ = "sales_logs"
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id: Mapped[uuid.UUID] = mapped_column(UUID(as_uuid=True), primary_key=True, default=uuid.uuid4)
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salesperson_id: Mapped[uuid.UUID] = mapped_column(UUID(as_uuid=True), ForeignKey("sys_users.id"), nullable=False)
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involved_company_ids: Mapped[list] = mapped_column(
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ARRAY(UUID(as_uuid=True)), nullable=False, default=list,
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comment="该篇日志涉及的公司ID列表"
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)
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customer_id: Mapped[uuid.UUID | None] = mapped_column(UUID(as_uuid=True), ForeignKey("crm_customers.id"), nullable=True)
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content: Mapped[str] = mapped_column(Text, nullable=False)
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log_date: Mapped[date] = mapped_column(Date, default=date.today)
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contact_ids: Mapped[list | None] = mapped_column(JSONB, default=list, nullable=True)
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ai_processed: Mapped[bool] = mapped_column(Boolean, default=False)
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ai_coaching_feedback: Mapped[dict | None] = mapped_column(
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JSONB, default=dict, nullable=True,
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comment="AI 教练引擎回写的指导反馈"
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)
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created_at: Mapped[datetime] = mapped_column(DateTime, server_default=func.now())
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updated_at: Mapped[datetime] = mapped_column(DateTime, server_default=func.now(), onupdate=func.now())
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is_deleted: Mapped[bool] = mapped_column(Boolean, default=False)
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class AiReportDraft(Base):
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__tablename__ = "ai_report_drafts"
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id: Mapped[uuid.UUID] = mapped_column(UUID(as_uuid=True), primary_key=True, default=uuid.uuid4)
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author_id: Mapped[uuid.UUID] = mapped_column(UUID(as_uuid=True), ForeignKey("sys_users.id"), nullable=False)
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report_type: Mapped[str] = mapped_column(String(20), nullable=False)
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period_start: Mapped[date] = mapped_column(Date, nullable=False)
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period_end: Mapped[date] = mapped_column(Date, nullable=False)
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content_md: Mapped[str] = mapped_column(Text, nullable=False)
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status: Mapped[str] = mapped_column(String(20), default="draft")
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created_at: Mapped[datetime] = mapped_column(DateTime, server_default=func.now())
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updated_at: Mapped[datetime] = mapped_column(DateTime, server_default=func.now(), onupdate=func.now())
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is_deleted: Mapped[bool] = mapped_column(Boolean, default=False)
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class KbObsidianVector(Base):
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"""知识库向量表 —— pgvector 存储 Obsidian 文档分块向量"""
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__tablename__ = "kb_obsidian_vectors"
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id: Mapped[uuid.UUID] = mapped_column(UUID(as_uuid=True), primary_key=True, default=uuid.uuid4)
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company_id: Mapped[uuid.UUID] = mapped_column(
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UUID(as_uuid=True), ForeignKey("sys_companies.id"), nullable=False, index=True
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)
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source_path: Mapped[str] = mapped_column(String(500), nullable=False, comment="源文件路径")
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chunk_index: Mapped[int] = mapped_column(SmallInteger, default=0)
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content: Mapped[str] = mapped_column(Text, nullable=False)
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metadata_: Mapped[dict | None] = mapped_column("metadata", JSONB, default=dict)
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# 向量字段使用 raw SQL 创建（vector(1536)）因 SQLAlchemy 无原生 pgvector 类型
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created_at: Mapped[datetime] = mapped_column(DateTime, server_default=func.now())
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is_deleted: Mapped[bool] = mapped_column(Boolean, default=False)
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