Implement full CRV (Coordinate Remote Viewing) signal-line protocol mapping to WiFi CSI sensing via ruvector-crv: - Stage I: CsiGestaltClassifier (6 gestalt types from amplitude/phase) - Stage II: CsiSensoryEncoder (texture/color/temperature/sound/luminosity/dimension) - Stage III: Mesh topology encoding (AP nodes/links → GNN graph) - Stage IV: Coherence gate → AOL detection (signal vs noise separation) - Stage V: Pose interrogation via differentiable search - Stage VI: Person partitioning via MinCut clustering - Cross-session convergence for cross-room identity New files: - crv/mod.rs: 1,430 lines, 43 tests - crv_bench.rs: 8 criterion benchmarks (gestalt, sensory, pipeline, convergence) - ADR-033: 740-line architecture decision with 30+ acceptance criteria - patches/ruvector-crv: Fix ruvector-gnn 2.0.5 API mismatch Dependencies: ruvector-crv 0.1.1, ruvector-gnn 2.0.5 Co-Authored-By: claude-flow <ruv@ruv.net>
24 lines
699 B
TOML
24 lines
699 B
TOML
[package]
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name = "ruvector-crv"
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version = "0.1.1"
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edition = "2021"
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authors = ["ruvector contributors"]
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description = "CRV (Coordinate Remote Viewing) protocol integration for ruvector - maps 6-stage signal line methodology to vector database subsystems"
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license = "MIT OR Apache-2.0"
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repository = "https://github.com/ruvnet/ruvector"
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[lib]
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name = "ruvector_crv"
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path = "src/lib.rs"
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[dependencies]
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ruvector-attention = "0.1.31"
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ruvector-gnn = { version = "2.0", default-features = false }
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ruvector-mincut = { version = "2.0", default-features = false, features = ["exact"] }
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serde = { version = "1.0", features = ["derive"] }
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serde_json = "1.0"
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thiserror = "1.0"
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[dev-dependencies]
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approx = "0.5"
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