7d9d31b6f3
- Introduced a new session history feature that tracks and manages conversation history across multiple chat sessions. - Implemented REST API endpoints for creating, listing, retrieving, and deleting chat sessions. - Enhanced error handling and logging for session management operations. - Updated README.md to include documentation for the new session history feature and its usage.
65 lines
2.7 KiB
Python
65 lines
2.7 KiB
Python
"""
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Session History Models for LightRAG API
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This module provides database models for storing chat session history, including:
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- Chat sessions for organizing conversations
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- Chat messages for storing user/assistant interactions
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- Message citations for tracking source references
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"""
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import uuid
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from sqlalchemy import Column, String, Boolean, DateTime, ForeignKey, Text, Integer, Float, JSON
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from sqlalchemy.dialects.postgresql import UUID
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from sqlalchemy.orm import relationship, declarative_base
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from sqlalchemy.sql import func
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Base = declarative_base()
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class ChatSession(Base):
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"""Chat session model for grouping related conversations."""
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__tablename__ = "lightrag_chat_sessions_history"
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id = Column(UUID(as_uuid=True), primary_key=True, default=uuid.uuid4)
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user_id = Column(String(255), nullable=False, index=True)
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title = Column(String(255), nullable=True)
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rag_config = Column(JSON, default={})
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summary = Column(Text, nullable=True)
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last_message_at = Column(DateTime(timezone=True), server_default=func.now(), index=True)
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created_at = Column(DateTime(timezone=True), server_default=func.now())
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messages = relationship("ChatMessage", back_populates="session", cascade="all, delete-orphan")
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class ChatMessage(Base):
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"""Chat message model for storing individual messages in a session."""
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__tablename__ = "lightrag_chat_messages_history"
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id = Column(UUID(as_uuid=True), primary_key=True, default=uuid.uuid4)
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session_id = Column(UUID(as_uuid=True), ForeignKey("lightrag_chat_sessions_history.id", ondelete="CASCADE"), nullable=False)
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role = Column(String(20), nullable=False) # user, assistant, system
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content = Column(Text, nullable=False)
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token_count = Column(Integer, nullable=True)
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processing_time = Column(Float, nullable=True)
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created_at = Column(DateTime(timezone=True), server_default=func.now())
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session = relationship("ChatSession", back_populates="messages")
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citations = relationship("MessageCitation", back_populates="message", cascade="all, delete-orphan")
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class MessageCitation(Base):
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"""Message citation model for tracking source references."""
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__tablename__ = "lightrag_message_citations_history"
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id = Column(UUID(as_uuid=True), primary_key=True, default=uuid.uuid4)
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message_id = Column(UUID(as_uuid=True), ForeignKey("lightrag_chat_messages_history.id", ondelete="CASCADE"), nullable=False)
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source_doc_id = Column(String(255), nullable=False, index=True)
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file_path = Column(Text, nullable=False)
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chunk_content = Column(Text, nullable=True)
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relevance_score = Column(Float, nullable=True)
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message = relationship("ChatMessage", back_populates="citations")
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