"""
文档数据模型
"""
from sqlalchemy import Column, Integer, String, DateTime, Text, ForeignKey, Boolean, Float
from sqlalchemy.sql import func
from sqlalchemy.orm import relationship

from ..core.database import Base


class Document(Base):
    """文档模型"""
    __tablename__ = "documents"
    
    id = Column(Integer, primary_key=True, index=True)
    user_id = Column(Integer, ForeignKey("users.id"), nullable=True)  # None表示系统文档
    knowledge_base_id = Column(Integer, ForeignKey("knowledge_bases.id"), nullable=True, index=True)
    filename = Column(String(255), nullable=False)
    original_filename = Column(String(255), nullable=False)
    file_path = Column(String(500), nullable=False)
    file_size = Column(Integer, nullable=False)
    file_type = Column(String(50), nullable=False)
    title = Column(String(200), nullable=True)
    description = Column(Text, nullable=True)
    is_processed = Column(Boolean, default=False)
    is_public = Column(Boolean, default=False)
    
    # 新增字段：知识库管理
    source_type = Column(String(50), default="upload")  # upload, knowledge_base
    last_modified = Column(DateTime(timezone=True), nullable=True)  # 文件最后修改时间
    file_hash = Column(String(64), nullable=True)  # 文件内容哈希
    
    created_at = Column(DateTime(timezone=True), server_default=func.now())
    updated_at = Column(DateTime(timezone=True), onupdate=func.now())
    
    # 关联关系
    user = relationship("User", back_populates="documents")
    knowledge_base = relationship("KnowledgeBase", back_populates="documents")
    chunks = relationship("DocumentChunk", back_populates="document", cascade="all, delete-orphan")
    
    def __repr__(self):
        return f"<Document(id={self.id}, filename='{self.filename}', title='{self.title}')>"


class DocumentChunk(Base):
    """文档分块模型"""
    __tablename__ = "document_chunks"
    
    id = Column(Integer, primary_key=True, index=True)
    document_id = Column(Integer, ForeignKey("documents.id"), nullable=False, index=True)
    chunk_index = Column(Integer, nullable=False)
    content = Column(Text, nullable=False)
    content_hash = Column(String(64), nullable=False)  # 内容哈希
    embedding_vector = Column(Text, nullable=True)  # 向量嵌入（JSON格式）
    chunk_metadata = Column(Text, nullable=True)  # 分块元数据（JSON格式）
    created_at = Column(DateTime(timezone=True), server_default=func.now())
    
    # 关联关系
    document = relationship("Document", back_populates="chunks")
    
    def __repr__(self):
        return f"<DocumentChunk(id={self.id}, document_id={self.document_id}, chunk_index={self.chunk_index})>"