Felipe Cardoso
c9d8c0835c
Add SQLAlchemy models for the Agent Memory System: - WorkingMemory: Key-value storage with TTL for active sessions - Episode: Experiential memories from task executions - Fact: Semantic knowledge triples with confidence scores - Procedure: Learned skills and procedures with success tracking - MemoryConsolidationLog: Tracks consolidation jobs between memory tiers Create enums for memory system: - ScopeType: global, project, agent_type, agent_instance, session - EpisodeOutcome: success, failure, partial - ConsolidationType: working_to_episodic, episodic_to_semantic, etc. - ConsolidationStatus: pending, running, completed, failed Add Alembic migration (0005) for all memory tables with: - Foreign key relationships to projects, agent_instances, agent_types - Comprehensive indexes for query patterns - Unique constraints for key lookups and triple uniqueness - Vector embedding column placeholders (Text fallback until pgvector enabled) Fix timezone-naive datetime.now() in types.py TaskState (review feedback) Includes 30 unit tests for models and enums. Closes #88 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
74 lines
1.8 KiB
Python
74 lines
1.8 KiB
Python
# app/models/memory/enums.py
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"""
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Enums for Memory System database models.
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These enums define the database-level constraints for memory types
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and scoping levels.
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"""
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from enum import Enum as PyEnum
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class ScopeType(str, PyEnum):
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"""
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Memory scope levels matching the memory service types.
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GLOBAL: System-wide memories accessible by all
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PROJECT: Project-scoped memories
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AGENT_TYPE: Type-specific memories (shared by instances of same type)
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AGENT_INSTANCE: Instance-specific memories
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SESSION: Session-scoped ephemeral memories
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"""
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GLOBAL = "global"
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PROJECT = "project"
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AGENT_TYPE = "agent_type"
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AGENT_INSTANCE = "agent_instance"
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SESSION = "session"
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class EpisodeOutcome(str, PyEnum):
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"""
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Outcome of an episode (task execution).
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SUCCESS: Task completed successfully
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FAILURE: Task failed
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PARTIAL: Task partially completed
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"""
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SUCCESS = "success"
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FAILURE = "failure"
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PARTIAL = "partial"
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class ConsolidationType(str, PyEnum):
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"""
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Types of memory consolidation operations.
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WORKING_TO_EPISODIC: Transfer session state to episodic
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EPISODIC_TO_SEMANTIC: Extract facts from episodes
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EPISODIC_TO_PROCEDURAL: Extract procedures from episodes
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PRUNING: Remove low-value memories
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"""
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WORKING_TO_EPISODIC = "working_to_episodic"
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EPISODIC_TO_SEMANTIC = "episodic_to_semantic"
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EPISODIC_TO_PROCEDURAL = "episodic_to_procedural"
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PRUNING = "pruning"
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class ConsolidationStatus(str, PyEnum):
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"""
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Status of a consolidation job.
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PENDING: Job is queued
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RUNNING: Job is currently executing
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COMPLETED: Job finished successfully
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FAILED: Job failed with errors
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"""
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PENDING = "pending"
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RUNNING = "running"
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COMPLETED = "completed"
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FAILED = "failed"
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