Move heavy deps to optional extras: sentence-transformers, torch,
numpy, pillow, datasets, accelerate out of core. Remove unused deps
entirely (semantic-router, protobuf, sentencepiece).
New extras: [ml] for Kompress, [image] for image compression,
[langchain] for LangChain integration. Guard memory/image imports
so core install works without numpy/torch.
Core (tiktoken, pydantic, litellm, click, rich) gives full
compression: SmartCrusher, ContentRouter, CCR, TOIN, CLI.
Remove unnecessary module-level patches for AutoTokenizer and
AutoModelForSequenceClassification since models are now loaded via
MLModelRegistry. The _load_models mock is sufficient for this test.
Implement comprehensive memory system supporting:
- Local backend (SQLite + FTS5 + HNSW) for zero-dependency operation
- Mem0 backends (Neo4j + Qdrant) for production graph memory
- DirectMem0Adapter for optimized pre-extracted data (bypasses LLM)
- Memory extraction with facts, entities, and relationships
- Proxy integration with --memory flag for automatic memory injection
Key components:
- headroom/memory/backends/: LocalBackend, Mem0Backend, DirectMem0Adapter
- headroom/memory/system.py: MemorySystem with tool-based interface
- headroom/memory/extraction.py: Entity and relationship extraction
- headroom/proxy/memory_handler.py: Proxy integration layer
- headroom/prediction/feature_extractor.py: Content analysis features
Testing:
- 217 new memory system tests covering all backends
- LoCoMo evaluation framework for memory quality assessment
- Integration tests for proxy memory functionality
Also removes deprecated example files in favor of focused test coverage.
