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Implements a complete Compress-Sense-Expand architecture as standalone example: - **Compress Layer**: Binary tensor storage with 4 compression strategies - None (1x), Float16 (2x), Int8 (4x), Binary (32x) - **Sense Layer**: Policy network for COMPRESS/EXPAND routing decisions - ThresholdPolicy (~2μs), LinearPolicy (~5μs), MLPPolicy (~15μs) - **Expand Layer**: Dimension projection with LLM registry - Supports LLaMA, GPT-4, Claude, Mistral, Phi-3 - **RefragStore**: Hybrid search returning mixed tensor/text results This example demonstrates REFRAG concepts (arXiv:2509.01092) without modifying ruvector-core, serving as proof-of-concept for Issue #10. Includes: - 25 passing unit tests - Interactive demo (cargo run --bin refrag-demo) - Performance benchmarks (cargo run --bin refrag-benchmark) - Criterion benchmarks for CI integration Refs: #10, #22 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com> |
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| .. | ||
| benchmark.rs | ||
| compress.rs | ||
| expand.rs | ||
| lib.rs | ||
| main.rs | ||
| sense.rs | ||
| store.rs | ||
| types.rs | ||