mirror of
https://github.com/basicmachines-co/basic-memory
synced 2026-06-21 13:47:35 +00:00
phernandez
109 lines
2.9 KiB
Python
109 lines
2.9 KiB
Python
"""Request schemas for interacting with the knowledge graph."""
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from typing import List, Optional, Annotated, Dict, Any
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from annotated_types import MaxLen, MinLen
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from pydantic import BaseModel
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from basic_memory.schemas.base import (
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Observation,
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Entity,
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Relation,
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PathId,
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ObservationCategory,
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EntityType,
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)
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class ObservationCreate(BaseModel):
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"""A single observation with category, content, and optional context."""
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category: ObservationCategory = ObservationCategory.NOTE
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content: Observation
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class AddObservationsRequest(BaseModel):
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"""Add new observations to an existing entity.
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Observations are atomic pieces of information about the entity.
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Each observation should be a single fact or note that adds value
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to our understanding of the entity.
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"""
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permalink: PathId
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context: Optional[str] = None
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observations: List[ObservationCreate]
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class CreateEntityRequest(BaseModel):
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"""Create one or more new entities in the knowledge graph.
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Entities represent nodes in the knowledge graph. They can be created
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with initial observations and optional descriptions. Entity IDs are
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automatically generated from the type and name.
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Observations will be assigned the default category of 'note'.
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"""
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entities: Annotated[List[Entity], MinLen(1)]
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class SearchNodesRequest(BaseModel):
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"""Search for entities in the knowledge graph.
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The search looks across multiple fields:
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- Entity title
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- Entity types
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- summary
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- file content
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- Observations
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Features:
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- Case-insensitive matching
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- Partial word matches
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- Returns full entity objects with relations
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- Includes all matching entities
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- If a category is specified, only entities with that category are returned
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Example Queries:
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- "memory" - Find entities related to memory systems
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- "SQLite" - Find database-related components
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- "test" - Find test-related entities
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- "implementation" - Find concrete implementations
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- "service" - Find service components
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Note: Currently uses SQL ILIKE for matching. Wildcard (*) searches
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and full-text search capabilities are planned for future versions.
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"""
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query: Annotated[str, MinLen(1), MaxLen(200)]
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category: Optional[ObservationCategory] = None
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class OpenNodesRequest(BaseModel):
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"""Retrieve specific entities by their IDs.
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Used to load complete entity details including all observations
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and relations. Particularly useful for following relations
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discovered through search.
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"""
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permalinks: Annotated[List[PathId], MinLen(1)]
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class CreateRelationsRequest(BaseModel):
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relations: List[Relation]
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## update
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class UpdateEntityRequest(BaseModel):
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"""Request to update an existing entity."""
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title: Optional[str] = None
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entity_type: Optional[EntityType] = None
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summary: Optional[str] = None
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content: Optional[str] = None
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entity_metadata: Optional[Dict[str, Any]] = None
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