Initial commit: 国土空间规划课程智能体 v1.0

单容器 Docker 架构的国土空间规划课程智能问答系统，集成 FastAPI 后端与 Next.js 前端。

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>

backend/src/models/document.py

@@ -0,0 +1,62 @@
+"""
+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)  # 所属知识库
+    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)
+    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})>"