$ show ruvnet/RuView
This is a large polyglot monorepo for WiFi-based human sensing (WiFi-DensePose) that turns commodity WiFi routers into spatial intelligence systems. It captures Channel State Information (CSI) from ESP32 nodes to detect presence, estimate 17-keypoint body pose, measure breathing and heart rate, and track movement through walls without cameras or wearables. The system integrates deeply with Home Assistant via MQTT and Matter, provides a HomeKit bridge, and exposes multiple surfaces: a Rust backend workspace (v2/crates) with 50+ crates for signal processing, privacy shielding (VEIL/BFLD), pose physics, and home automation; Python bindings (PyO3) for ML training and inference; TypeScript CLI and MCP tools for AI agent integration; ESP32-C6/S3 firmware with adaptive sensing; React Native mobile app; Lit-based dashboard; and Tauri desktop app. The architecture is event-driven with a streaming engine, coherence-gated privacy layers, and deterministic verification via SHA-256 golden files. The codebase is heavily ADR-driven with extensive test coverage including cross-language parity gates. While primarily an application, it also contains substantial research code (benchmarks, physics simulations, SOTA surveys) and is best described as a research-informed production platform.
The LLM identified 7 files worth highlighting for reuse:
Defines the PluginRuntime trait with two implementations: InProcessRuntime (native Rust) and feature-gated WasmtimeRuntime (WASM). The trait provides load, unload, list, and shutdown operations, returning a LoadedPlugin handle. The registry is runtime-agnostic, allowing plugins to be swapped without changing the host. This is a clean, reusable abstraction for any system needing extensible plugin execution with multiple backend options.
Implements a CoherenceGate with configurable hysteresis and debounce for privacy-preserving event gating. It uses a state machine (Idle, Active, Cooldown) with clock-skew resilience via saturating arithmetic. The gate can downgrade to PredictOnly mode for AlwaysMatch scenarios. This pattern is reusable for any system needing to suppress transient signals while maintaining privacy guarantees.
Provides energy-conserving Givens rotation transforms for privacy shielding. The implementation is pure computation with no external dependencies, using deterministic SplitMix64 PRNG. It includes compliance audit functions and proof bundle generation. This is a self-contained, reusable module for any application requiring orthogonal, energy-preserving data transformations.
Defines a JSON-over-linear-memory ABI for WASM plugins with zero external imports. It provides encode/decode functions for tool calls and results, using a simple string-based protocol. The kernel is platform-agnostic and can be used in any JavaScript/TypeScript project needing a lightweight WASM plugin system.
Implements a flywheel self-improvement loop: propose changes, evaluate against benchmarks, gate promotion based on evidence, and replay results. It uses a genome configuration and fixture-based testing. This pattern is reusable for any system wanting automated, evidence-gated self-improvement cycles.
A UI component that displays a banner indicating whether data is live, simulated, or synthetic. It uses CSS classes and DOM manipulation to show provenance information. This is a reusable pattern for any application that needs to clearly distinguish real from synthetic data sources.
Demonstrates a golden-file parity testing pattern between Python bindings and native Rust. It computes SHA-256 over concatenated little-endian f32 outputs and compares against a committed hash. This pattern is reusable for any project needing bit-exact cross-language correctness guarantees.