6ed69a3d48
Major changes: - Organized Python v1 implementation into v1/ subdirectory - Created Rust workspace with 9 modular crates: - wifi-densepose-core: Core types, traits, errors - wifi-densepose-signal: CSI processing, phase sanitization, FFT - wifi-densepose-nn: Neural network inference (ONNX/Candle/tch) - wifi-densepose-api: Axum-based REST/WebSocket API - wifi-densepose-db: SQLx database layer - wifi-densepose-config: Configuration management - wifi-densepose-hardware: Hardware abstraction - wifi-densepose-wasm: WebAssembly bindings - wifi-densepose-cli: Command-line interface Documentation: - ADR-001: Workspace structure - ADR-002: Signal processing library selection - ADR-003: Neural network inference strategy - DDD domain model with bounded contexts Testing: - 69 tests passing across all crates - Signal processing: 45 tests - Neural networks: 21 tests - Core: 3 doc tests Performance targets: - 10x faster CSI processing (~0.5ms vs ~5ms) - 5x lower memory usage (~100MB vs ~500MB) - WASM support for browser deployment
29 lines
437 B
YAML
29 lines
437 B
YAML
# Claude Flow V3 Runtime Configuration
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# Generated: 2026-01-13T02:28:22.177Z
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version: "3.0.0"
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swarm:
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topology: hierarchical-mesh
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maxAgents: 15
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autoScale: true
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coordinationStrategy: consensus
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memory:
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backend: hybrid
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enableHNSW: true
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persistPath: .claude-flow/data
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cacheSize: 100
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neural:
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enabled: true
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modelPath: .claude-flow/neural
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hooks:
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enabled: true
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autoExecute: true
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mcp:
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autoStart: false
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port: 3000
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