89 lines
4.9 KiB
Python
89 lines
4.9 KiB
Python
import datetime
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from sqlalchemy import Column, String, Boolean, DateTime, Integer, Float
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from sqlalchemy.dialects.postgresql import UUID
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from app.db import Base
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class MemoryConfig(Base):
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"""记忆配置表 - 用于存储记忆系统的配置参数"""
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__tablename__ = "memory_config"
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# 主键
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config_id = Column(UUID(as_uuid=True), primary_key=True, comment="配置ID")
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# 基本信息
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config_name = Column(String, nullable=False, comment="配置名称")
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config_desc = Column(String, nullable=True, comment="配置描述")
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# 组织信息
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workspace_id = Column(UUID(as_uuid=True), nullable=True, comment="工作空间ID")
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end_user_id = Column(String, nullable=True, comment="组ID")
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user_id = Column(String, nullable=True, comment="用户ID")
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apply_id = Column(String, nullable=True, comment="应用ID")
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# 模型选择（从workspace继承）
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llm_id = Column(String, nullable=True, comment="LLM模型配置ID")
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embedding_id = Column(String, nullable=True, comment="嵌入模型配置ID")
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rerank_id = Column(String, nullable=True, comment="重排序模型配置ID")
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# 记忆萃取引擎配置
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enable_llm_dedup_blockwise = Column(Boolean, default=True, comment="启用LLM决策去重")
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enable_llm_disambiguation = Column(Boolean, default=True, comment="启用LLM决策消歧")
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deep_retrieval = Column(Boolean, default=True, comment="深度检索开关")
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# 阈值配置 (0-1 之间的浮点数)
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t_type_strict = Column(Float, default=0.8, comment="类型严格阈值")
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t_name_strict = Column(Float, default=0.8, comment="名称严格阈值")
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t_overall = Column(Float, default=0.8, comment="综合阈值")
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# 状态配置
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state = Column(Boolean, default=False, comment="配置使用状态")
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# 分块策略
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chunker_strategy = Column(String, default="RecursiveChunker", comment="分块策略")
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# 剪枝配置
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pruning_enabled = Column(Boolean, default=False, comment="是否启动智能语义剪枝")
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pruning_scene = Column(String, nullable=True, comment="智能剪枝场景：education/online_service/outbound")
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pruning_threshold = Column(Float, nullable=True, comment="智能语义剪枝阈值（0-0.9）")
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# 自我反思配置
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enable_self_reflexion = Column(Boolean, default=False, comment="是否启用自我反思")
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iteration_period = Column(String, default="3", comment="反思迭代周期")
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reflexion_range = Column(String, default="partial", comment="反思范围：部分/全部")
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baseline = Column(String, default="TIME", comment="基线：时间/事实/时间和事实")
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reflection_model_id = Column(String, nullable=True, comment="反思模型ID")
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memory_verify = Column(Boolean, default=True, comment="记忆验证")
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quality_assessment = Column(Boolean, default=True, comment="质量评估")
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# 遗忘引擎配置
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statement_granularity = Column(Integer, default=2, comment="陈述提取颗粒度，挡位 1/2/3")
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include_dialogue_context = Column(Boolean, default=False, comment="是否包含对话上下文")
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max_context = Column(Integer, default=1000, comment="对话语境中包含字符的最大数量")
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lambda_time = Column("lambda_time", Float, default=0.5, comment="最低保持度，0-1 小数")
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lambda_mem = Column("lambda_mem", Float, default=0.5, comment="遗忘率，0-1 小数")
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offset = Column("offset", Float, default=0.0, comment="偏移度，0-1 小数")
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# ACT-R 遗忘引擎配置
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decay_constant = Column(Float, default=0.5, comment="ACT-R衰减常数d，默认0.5")
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forgetting_threshold = Column(Float, default=0.3, comment="遗忘阈值，默认0.3")
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forgetting_interval_hours = Column(Integer, default=24, comment="遗忘周期间隔（小时），默认24")
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enable_llm_summary = Column(Boolean, default=True, comment="是否使用LLM生成摘要，默认True")
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max_merge_batch_size = Column(Integer, default=100, comment="单次最大融合节点对数，默认100")
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max_history_length = Column(Integer, default=100, comment="访问历史最大长度，默认100")
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min_days_since_access = Column(Integer, default=30, comment="最小未访问天数，默认30")
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# 情绪引擎配置
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emotion_enabled = Column(Boolean, default=True, comment="是否启用情绪提取")
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emotion_model_id = Column(String, nullable=True, comment="情绪分析专用模型ID")
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emotion_extract_keywords = Column(Boolean, default=True, comment="是否提取情绪关键词")
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emotion_min_intensity = Column(Float, default=0.1, comment="最小情绪强度阈值")
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emotion_enable_subject = Column(Boolean, default=True, comment="是否启用主体分类")
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# 时间戳
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created_at = Column(DateTime, default=datetime.datetime.now, comment="创建时间")
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updated_at = Column(DateTime, default=datetime.datetime.now, onupdate=datetime.datetime.now, comment="更新时间")
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def __repr__(self):
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return f"<MemoryConfig(config_id={self.config_id}, config_name={self.config_name})>"
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