feat: Complete Rust port of WiFi-DensePose with modular crates
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
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# Self-Healing Workflows
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## Purpose
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Automatically detect and recover from errors without interrupting your flow.
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## Self-Healing Features
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### 1. Error Detection
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Monitors for:
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- Failed commands
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- Syntax errors
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- Missing dependencies
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- Broken tests
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### 2. Automatic Recovery
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**Missing Dependencies:**
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```
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Error: Cannot find module 'express'
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→ Automatically runs: npm install express
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→ Retries original command
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```
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**Syntax Errors:**
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```
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Error: Unexpected token
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→ Analyzes error location
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→ Suggests fix through analyzer agent
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→ Applies fix with confirmation
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```
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**Test Failures:**
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```
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Test failed: "user authentication"
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→ Spawns debugger agent
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→ Analyzes failure cause
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→ Implements fix
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→ Re-runs tests
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```
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### 3. Learning from Failures
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Each recovery improves future prevention:
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- Patterns saved to knowledge base
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- Similar errors prevented proactively
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- Recovery strategies optimized
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**Pattern Storage:**
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```javascript
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// Store error patterns
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mcp__claude-flow__memory_usage({
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"action": "store",
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"key": "error-pattern-" + Date.now(),
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"value": JSON.stringify(errorData),
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"namespace": "error-patterns",
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"ttl": 2592000 // 30 days
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})
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// Analyze patterns
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mcp__claude-flow__neural_patterns({
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"action": "analyze",
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"operation": "error-recovery",
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"outcome": "success"
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})
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```
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## Self-Healing Integration
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### MCP Tool Coordination
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```javascript
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// Initialize self-healing swarm
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mcp__claude-flow__swarm_init({
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"topology": "star",
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"maxAgents": 4,
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"strategy": "adaptive"
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})
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// Spawn recovery agents
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mcp__claude-flow__agent_spawn({
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"type": "monitor",
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"name": "Error Monitor",
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"capabilities": ["error-detection", "recovery"]
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})
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// Orchestrate recovery
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mcp__claude-flow__task_orchestrate({
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"task": "recover from error",
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"strategy": "sequential",
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"priority": "critical"
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})
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```
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### Fallback Hook Configuration
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```json
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{
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"PostToolUse": [{
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"matcher": "^Bash$",
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"command": "npx claude-flow hook post-bash --exit-code '${tool.result.exitCode}' --auto-recover"
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}]
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}
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```
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## Benefits
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- 🛡️ Resilient workflows
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- 🔄 Automatic recovery
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- 📚 Learns from errors
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- ⏱️ Saves debugging time
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