Add comprehensive caching layer for the Agent Memory System:
- HotMemoryCache: LRU cache for frequently accessed memories
- Python 3.12 type parameter syntax
- Thread-safe operations with RLock
- TTL-based expiration
- Access count tracking for hot memory identification
- Scoped invalidation by type, scope, or pattern
- EmbeddingCache: Cache embeddings by content hash
- Content-hash based deduplication
- Optional Redis backing for persistence
- LRU eviction with configurable max size
- CachedEmbeddingGenerator wrapper for transparent caching
- CacheManager: Unified cache management
- Coordinates hot cache, embedding cache, and retrieval cache
- Centralized invalidation across all caches
- Aggregated statistics and hit rate tracking
- Automatic cleanup scheduling
- Cache warmup support
Performance targets:
- Cache hit rate > 80% for hot memories
- Cache operations < 1ms (memory), < 5ms (Redis)
83 new tests with comprehensive coverage.
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Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
Add MCP-compatible tools that expose memory operations to agents:
Tools implemented:
- remember: Store data in working, episodic, semantic, or procedural memory
- recall: Retrieve memories by query across multiple memory types
- forget: Delete specific keys or bulk delete by pattern
- reflect: Analyze patterns in recent episodes (success/failure factors)
- get_memory_stats: Return usage statistics and breakdowns
- search_procedures: Find procedures matching trigger patterns
- record_outcome: Record task outcomes and update procedure success rates
Key components:
- tools.py: Pydantic schemas for tool argument validation with comprehensive
field constraints (importance 0-1, TTL limits, limit ranges)
- service.py: MemoryToolService coordinating memory type operations with
proper scoping via ToolContext (project_id, agent_instance_id, session_id)
- Lazy initialization of memory services (WorkingMemory, EpisodicMemory,
SemanticMemory, ProceduralMemory)
Test coverage:
- 60 tests covering tool definitions, argument validation, and service
execution paths
- Mock-based tests for all memory type interactions
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Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
- Add MemoryConsolidationService with Working→Episodic→Semantic/Procedural transfer
- Add Celery tasks for session and nightly consolidation
- Implement memory pruning with importance-based retention
- Add comprehensive test suite (32 tests)
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Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
Add comprehensive indexing and retrieval system for memory search:
- VectorIndex for semantic similarity search using cosine similarity
- TemporalIndex for time-based queries with range and recency support
- EntityIndex for entity-based lookups with multi-entity intersection
- OutcomeIndex for success/failure filtering on episodes
- MemoryIndexer as unified interface for all index types
- RetrievalEngine with hybrid search combining all indices
- RelevanceScorer for multi-signal relevance scoring
- RetrievalCache for LRU caching of search results
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Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
Add scope management system for hierarchical memory access:
- ScopeManager with hierarchy: Global → Project → Agent Type → Agent Instance → Session
- ScopePolicy for access control (read, write, inherit permissions)
- ScopeResolver for resolving queries across scope hierarchies with inheritance
- ScopeFilter for filtering scopes by type, project, or agent
- Access control enforcement with parent scope visibility
- Deduplication support during resolution across scopes
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Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
Implements procedural memory for learned skills and procedures:
Core functionality:
- ProceduralMemory class for procedure storage/retrieval
- record_procedure with duplicate detection and step merging
- find_matching for context-based procedure search
- record_outcome for success/failure tracking
- get_best_procedure for finding highest success rate
- update_steps for procedure refinement
Supporting modules:
- ProcedureMatcher: Keyword-based procedure matching
- MatchResult/MatchContext: Matching result types
- Success rate weighting in match scoring
Test coverage:
- 43 unit tests covering all modules
- matching.py: 97% coverage
- memory.py: 86% coverage
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Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
Implements the episodic memory service for storing and retrieving
agent task execution experiences. This enables learning from past
successes and failures.
Components:
- EpisodicMemory: Main service class combining recording and retrieval
- EpisodeRecorder: Handles episode creation, importance scoring
- EpisodeRetriever: Multiple retrieval strategies (recency, semantic,
outcome, importance, task type)
Key features:
- Records task completions with context, actions, outcomes
- Calculates importance scores based on outcome, duration, lessons
- Semantic search with fallback to recency when embeddings unavailable
- Full CRUD operations with statistics and summarization
- Comprehensive unit tests (50 tests, all passing)
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Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
Implements session-scoped ephemeral memory with:
Storage Backends:
- InMemoryStorage: Thread-safe fallback with TTL support and capacity limits
- RedisStorage: Primary storage with connection pooling and JSON serialization
- Auto-fallback from Redis to in-memory when unavailable
WorkingMemory Class:
- Key-value storage with TTL and reserved key protection
- Task state tracking with progress updates
- Scratchpad for reasoning steps with timestamps
- Checkpoint/snapshot support for recovery
- Factory methods for auto-configured storage
Tests:
- 55 unit tests covering all functionality
- Tests for basic ops, TTL, capacity, concurrency
- Tests for task state, scratchpad, checkpoints
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Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
Implements Sub-Issue #87 of Issue #62 (Agent Memory System).
Core infrastructure:
- memory/types.py: Type definitions for all memory types (Working, Episodic,
Semantic, Procedural) with enums for MemoryType, ScopeLevel, Outcome
- memory/config.py: MemorySettings with MEM_ env prefix, thread-safe singleton
- memory/exceptions.py: Comprehensive exception hierarchy for memory operations
- memory/manager.py: MemoryManager facade with placeholder methods
Directory structure:
- working/: Working memory (Redis/in-memory) - to be implemented in #89
- episodic/: Episodic memory (experiences) - to be implemented in #90
- semantic/: Semantic memory (facts) - to be implemented in #91
- procedural/: Procedural memory (skills) - to be implemented in #92
- scoping/: Scope management - to be implemented in #93
- indexing/: Vector indexing - to be implemented in #94
- consolidation/: Memory consolidation - to be implemented in #95
Tests: 71 unit tests for config, types, and exceptions
Docs: Comprehensive implementation plan at docs/architecture/memory-system-plan.md
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Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
