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
115 lines
4.4 KiB
Markdown
115 lines
4.4 KiB
Markdown
# WiFi-DensePose Rust Port - 15-Agent Swarm Configuration
|
|
|
|
## Mission Statement
|
|
Port the WiFi-DensePose Python system to Rust using ruvnet/ruvector patterns, with modular crates, WASM support, and comprehensive documentation following ADR/DDD principles.
|
|
|
|
## Agent Swarm Architecture
|
|
|
|
### Tier 1: Orchestration (1 Agent)
|
|
1. **Orchestrator Agent** - Coordinates all agents, manages dependencies, tracks progress
|
|
|
|
### Tier 2: Architecture & Documentation (3 Agents)
|
|
2. **ADR Agent** - Creates Architecture Decision Records for all major decisions
|
|
3. **DDD Agent** - Designs Domain-Driven Design models and bounded contexts
|
|
4. **Documentation Agent** - Maintains comprehensive documentation, README, API docs
|
|
|
|
### Tier 3: Core Implementation (5 Agents)
|
|
5. **Signal Processing Agent** - Ports CSI processing, phase sanitization, FFT algorithms
|
|
6. **Neural Network Agent** - Ports DensePose head, modality translation using tch-rs/onnx
|
|
7. **API Agent** - Implements Axum/Actix REST API and WebSocket handlers
|
|
8. **Database Agent** - Implements SQLx PostgreSQL/SQLite with migrations
|
|
9. **Config Agent** - Implements configuration management, environment handling
|
|
|
|
### Tier 4: Platform & Integration (3 Agents)
|
|
10. **WASM Agent** - Implements wasm-bindgen, browser compatibility, wasm-pack builds
|
|
11. **Hardware Agent** - Ports CSI extraction, router interfaces, hardware abstraction
|
|
12. **Integration Agent** - Integrates ruvector crates, vector search, GNN layers
|
|
|
|
### Tier 5: Quality Assurance (3 Agents)
|
|
13. **Test Agent** - Writes unit, integration, and benchmark tests
|
|
14. **Validation Agent** - Validates against Python implementation, accuracy checks
|
|
15. **Optimization Agent** - Profiles, benchmarks, and optimizes hot paths
|
|
|
|
## Crate Workspace Structure
|
|
|
|
```
|
|
wifi-densepose-rs/
|
|
├── Cargo.toml # Workspace root
|
|
├── crates/
|
|
│ ├── wifi-densepose-core/ # Core types, traits, errors
|
|
│ ├── wifi-densepose-signal/ # Signal processing (CSI, phase, FFT)
|
|
│ ├── wifi-densepose-nn/ # Neural networks (DensePose, translation)
|
|
│ ├── wifi-densepose-api/ # REST/WebSocket API (Axum)
|
|
│ ├── wifi-densepose-db/ # Database layer (SQLx)
|
|
│ ├── wifi-densepose-config/ # Configuration management
|
|
│ ├── wifi-densepose-hardware/ # Hardware abstraction
|
|
│ ├── wifi-densepose-wasm/ # WASM bindings
|
|
│ └── wifi-densepose-cli/ # CLI application
|
|
├── docs/
|
|
│ ├── adr/ # Architecture Decision Records
|
|
│ ├── ddd/ # Domain-Driven Design docs
|
|
│ └── api/ # API documentation
|
|
├── benches/ # Benchmarks
|
|
└── tests/ # Integration tests
|
|
```
|
|
|
|
## Domain Model (DDD)
|
|
|
|
### Bounded Contexts
|
|
1. **Signal Domain** - CSI data, phase processing, feature extraction
|
|
2. **Pose Domain** - DensePose inference, keypoints, segmentation
|
|
3. **Streaming Domain** - WebSocket, real-time updates, connection management
|
|
4. **Storage Domain** - Persistence, caching, retrieval
|
|
5. **Hardware Domain** - Router interfaces, device management
|
|
|
|
### Core Aggregates
|
|
- `CsiFrame` - Raw CSI data aggregate
|
|
- `ProcessedSignal` - Cleaned and extracted features
|
|
- `PoseEstimate` - DensePose inference result
|
|
- `Session` - Client session with history
|
|
- `Device` - Hardware device state
|
|
|
|
## ADR Topics to Document
|
|
- ADR-001: Rust Workspace Structure
|
|
- ADR-002: Signal Processing Library Selection
|
|
- ADR-003: Neural Network Inference Strategy
|
|
- ADR-004: API Framework Selection (Axum vs Actix)
|
|
- ADR-005: Database Layer Strategy (SQLx)
|
|
- ADR-006: WASM Compilation Strategy
|
|
- ADR-007: Error Handling Approach
|
|
- ADR-008: Async Runtime Selection (Tokio)
|
|
- ADR-009: ruvector Integration Strategy
|
|
- ADR-010: Configuration Management
|
|
|
|
## Phase Execution Plan
|
|
|
|
### Phase 1: Foundation
|
|
- Set up Cargo workspace
|
|
- Create all crate scaffolding
|
|
- Write ADR-001 through ADR-005
|
|
- Define core traits and types
|
|
|
|
### Phase 2: Core Implementation
|
|
- Port signal processing algorithms
|
|
- Implement neural network inference
|
|
- Build API layer
|
|
- Database integration
|
|
|
|
### Phase 3: Platform
|
|
- WASM compilation
|
|
- Hardware abstraction
|
|
- ruvector integration
|
|
|
|
### Phase 4: Quality
|
|
- Comprehensive testing
|
|
- Python validation
|
|
- Benchmarking
|
|
- Optimization
|
|
|
|
## Success Metrics
|
|
- Feature parity with Python implementation
|
|
- < 10ms latency improvement over Python
|
|
- WASM bundle < 5MB
|
|
- 100% test coverage
|
|
- All ADRs documented
|