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Add detailed implementation, optimization, and benchmarking plans for: 1. Self-Learning / ReasoningBank - Trajectory tracking, verdict judgment, memory distillation - Adaptive search parameter optimization 2. Attention Mechanisms (39 types) - Core: Scaled dot-product, multi-head, Flash v2, linear - Graph: GAT, GATv2, sparse patterns - Specialized: MoE, cross-attention, sliding window - Hyperbolic: Poincaré, Lorentz attention 3. GNN Layers - GCN, GraphSAGE, GAT, GIN layers - Message passing framework - PostgreSQL graph storage integration 4. Hyperbolic Embeddings - Poincaré ball and Lorentz models - Möbius operations, exp/log maps - Hyperbolic HNSW index 5. Sparse Vectors - COO/CSR formats, SPLADE support - Inverted index, WAND algorithm - Hybrid dense+sparse search 6. Graph Operations & Cypher - Full Cypher query language support - Property graph storage - Vector-enhanced traversals - Graph algorithms (PageRank, community detection) 7. Tiny Dancer Routing - FastGRNN neural inference - Semantic route matching - Cost/latency optimization - Agent registry and pool management 8. Optimization Strategy - SIMD dispatch (AVX-512/AVX2/NEON) - Zero-copy operations, memory pools - Query plan caching, parallel execution - PostgreSQL-specific tuning 9. Benchmarking Plan - Micro-benchmarks for all operations - Competitor comparison methodology - Stress testing and recall analysis - CI/CD integration 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com> |
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| .. | ||
| guides | ||
| implementation | ||
| integration-plans | ||
| API.md | ||
| ARCHITECTURE.md | ||
| BUILD.md | ||
| BUILD_QUICK_START.md | ||
| IMPLEMENTATION_SUMMARY.md | ||
| INSTALLATION.md | ||
| ivfflat_access_method.md | ||
| MIGRATION.md | ||
| NATIVE_TYPE_IO.md | ||
| NEON_COMPATIBILITY.md | ||
| QUANTIZED_TYPES.md | ||
| QUICK_REFERENCE_IVFFLAT.md | ||
| SIMD_OPTIMIZATION.md | ||
| TEST_SUMMARY.md | ||
| TESTING.md | ||
| TYPE_IO_IMPLEMENTATION_SUMMARY.md | ||