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Claude 6ed69a3d48 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

2026-01-13 03:11:16 +00:00

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Cross-Session Memory

Purpose

Maintain context and learnings across Claude Code sessions for continuous improvement.

Memory Features

1. Automatic State Persistence

At session end, automatically saves:

Active agents and specializations
Task history and patterns
Performance metrics
Neural network weights
Knowledge base updates

2. Session Restoration

// Using MCP tools for memory operations
mcp__claude-flow__memory_usage({
  "action": "retrieve",
  "key": "session-state",
  "namespace": "sessions"
})

// Restore swarm state
mcp__claude-flow__context_restore({
  "snapshotId": "sess-123"
})

Fallback with npx:

npx claude-flow hook session-restore --session-id "sess-123"

3. Memory Types

Project Memory:

File relationships
Common edit patterns
Testing approaches
Build configurations

Agent Memory:

Specialization levels
Task success rates
Optimization strategies
Error patterns

Performance Memory:

Bottleneck history
Optimization results
Token usage patterns
Efficiency trends

4. Privacy & Control

// List memory contents
mcp__claude-flow__memory_usage({
  "action": "list",
  "namespace": "sessions"
})

// Delete specific memory
mcp__claude-flow__memory_usage({
  "action": "delete",
  "key": "session-123",
  "namespace": "sessions"
})

// Backup memory
mcp__claude-flow__memory_backup({
  "path": "./backups/memory-backup.json"
})

Manual control:

# View stored memory
ls .claude-flow/memory/

# Disable memory
export CLAUDE_FLOW_MEMORY_PERSIST=false

Benefits

🧠 Contextual awareness
📈 Cumulative learning
⚡ Faster task completion
🎯 Personalized optimization

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