d803bfe2b1
git-subtree-dir: vendor/ruvector git-subtree-split: b64c21726f2bb37286d9ee36a7869fef60cc6900
56 lines
1.3 KiB
Markdown
56 lines
1.3 KiB
Markdown
# ADR-CE-019: Memory as Nodes
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**Status**: Accepted
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**Date**: 2026-01-22
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**Parent**: ADR-014 Coherence Engine Architecture
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## Context
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RuvLLM has three memory types:
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- `AgenticMemory`: Long-term patterns
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- `WorkingMemory`: Current context
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- `EpisodicMemory`: Conversation history
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These memories can contradict each other. Currently no systematic way to detect.
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## Decision
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**AgenticMemory, WorkingMemory, EpisodicMemory become sheaf nodes.**
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Integration:
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```rust
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pub struct MemoryCoherenceLayer {
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agentic: AgenticMemory,
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working: WorkingMemory,
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episodic: EpisodicMemory,
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graph: SheafGraph,
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}
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```
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When memory is added:
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1. Create sheaf node with memory embedding
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2. Add edges to related memories
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3. Compute coherence energy
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4. Alert if incoherent memory detected
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Edge types:
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- Temporal: Episode N should be consistent with N-1
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- Semantic: Related facts should agree
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- Hierarchical: Specific facts consistent with general patterns
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## Consequences
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### Benefits
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- Detect contradictory memories before they cause problems
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- Unified coherence across all memory types
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- Can query "is my context self-consistent?"
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### Risks
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- Overhead for every memory write
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- Edge creation requires semantic analysis
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## References
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- ADR-014: Coherence Engine Architecture, "RuvLLM Integration"
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- ruvllm/src/context/
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