mirror of
https://github.com/basicmachines-co/basic-memory
synced 2026-06-21 13:47:35 +00:00
168 lines
5.8 KiB
Python
168 lines
5.8 KiB
Python
"""Knowledge graph models."""
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from datetime import datetime
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from typing import Optional
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from sqlalchemy import (
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Integer,
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String,
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Text,
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ForeignKey,
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UniqueConstraint,
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DateTime,
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Index,
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JSON,
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)
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from sqlalchemy.orm import Mapped, mapped_column, relationship
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from basic_memory.models.base import Base
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from basic_memory.utils import generate_permalink
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class Entity(Base):
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"""Core entity in the knowledge graph.
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Entities represent semantic nodes maintained by the AI layer. Each entity:
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- Has a unique numeric ID (database-generated)
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- Maps to a file on disk
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- Maintains a checksum for change detection
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- Tracks both source file and semantic properties
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"""
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__tablename__ = "entity"
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__table_args__ = (
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UniqueConstraint("permalink", name="uix_entity_permalink"), # Make permalink unique
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Index("ix_entity_type", "entity_type"),
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Index("ix_entity_title", "title"),
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Index("ix_entity_created_at", "created_at"), # For timeline queries
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Index("ix_entity_updated_at", "updated_at"), # For timeline queries
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)
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# Core identity
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id: Mapped[int] = mapped_column(Integer, primary_key=True)
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title: Mapped[str] = mapped_column(String)
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entity_type: Mapped[str] = mapped_column(String)
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entity_metadata: Mapped[Optional[dict]] = mapped_column(JSON, nullable=True)
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content_type: Mapped[str] = mapped_column(String)
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# Normalized path for URIs
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permalink: Mapped[str] = mapped_column(String, unique=True, index=True)
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# Actual filesystem relative path
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file_path: Mapped[str] = mapped_column(String, unique=True, index=True)
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# checksum of file
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checksum: Mapped[Optional[str]] = mapped_column(String, nullable=True)
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# Metadata and tracking
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created_at: Mapped[datetime] = mapped_column(DateTime)
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updated_at: Mapped[datetime] = mapped_column(DateTime)
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# Relationships
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observations = relationship(
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"Observation", back_populates="entity", cascade="all, delete-orphan"
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)
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outgoing_relations = relationship(
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"Relation",
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back_populates="from_entity",
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foreign_keys="[Relation.from_id]",
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cascade="all, delete-orphan",
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)
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incoming_relations = relationship(
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"Relation",
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back_populates="to_entity",
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foreign_keys="[Relation.to_id]",
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cascade="all, delete-orphan",
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)
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@property
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def relations(self):
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"""Get all relations (incoming and outgoing) for this entity."""
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return self.incoming_relations + self.outgoing_relations
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def __repr__(self) -> str:
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return f"Entity(id={self.id}, name='{self.title}', type='{self.entity_type}'"
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class Observation(Base):
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"""An observation about an entity.
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Observations are atomic facts or notes about an entity.
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"""
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__tablename__ = "observation"
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__table_args__ = (
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Index("ix_observation_entity_id", "entity_id"), # Add FK index
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Index("ix_observation_category", "category"), # Add category index
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)
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id: Mapped[int] = mapped_column(Integer, primary_key=True)
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entity_id: Mapped[int] = mapped_column(Integer, ForeignKey("entity.id", ondelete="CASCADE"))
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content: Mapped[str] = mapped_column(Text)
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category: Mapped[str] = mapped_column(String, nullable=False, default="note")
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context: Mapped[Optional[str]] = mapped_column(Text, nullable=True)
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tags: Mapped[Optional[list[str]]] = mapped_column(
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JSON, nullable=True, default=list, server_default="[]"
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)
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# Relationships
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entity = relationship("Entity", back_populates="observations")
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@property
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def permalink(self) -> str:
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"""Create synthetic permalink for the observation.
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We can construct these because observations are always defined in
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and owned by a single entity.
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"""
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return generate_permalink(
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f"{self.entity.permalink}/observations/{self.category}/{self.content}"
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)
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def __repr__(self) -> str: # pragma: no cover
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return f"Observation(id={self.id}, entity_id={self.entity_id}, content='{self.content}')"
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class Relation(Base):
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"""A directed relation between two entities."""
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__tablename__ = "relation"
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__table_args__ = (
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UniqueConstraint("from_id", "to_id", "relation_type", name="uix_relation"),
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Index("ix_relation_type", "relation_type"),
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Index("ix_relation_from_id", "from_id"), # Add FK indexes
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Index("ix_relation_to_id", "to_id"),
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)
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id: Mapped[int] = mapped_column(Integer, primary_key=True)
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from_id: Mapped[int] = mapped_column(Integer, ForeignKey("entity.id", ondelete="CASCADE"))
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to_id: Mapped[Optional[int]] = mapped_column(
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Integer, ForeignKey("entity.id", ondelete="CASCADE"), nullable=True
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)
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to_name: Mapped[str] = mapped_column(String)
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relation_type: Mapped[str] = mapped_column(String)
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context: Mapped[Optional[str]] = mapped_column(Text, nullable=True)
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# Relationships
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from_entity = relationship(
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"Entity", foreign_keys=[from_id], back_populates="outgoing_relations"
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)
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to_entity = relationship("Entity", foreign_keys=[to_id], back_populates="incoming_relations")
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@property
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def permalink(self) -> str:
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"""Create relation permalink showing the semantic connection.
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Format: source/relation_type/target
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Example: "specs/search/implements/features/search-ui"
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"""
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if self.to_entity:
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return generate_permalink(
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f"{self.from_entity.permalink}/{self.relation_type}/{self.to_entity.permalink}"
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)
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return generate_permalink(
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f"{self.from_entity.permalink}/{self.relation_type}/{self.to_name}"
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)
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def __repr__(self) -> str:
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return f"Relation(id={self.id}, from_id={self.from_id}, to_id={self.to_id}, to_name={self.to_name}, type='{self.relation_type}')"
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