chore: update vendor submodules to latest main

docs: update user guide with v0.4.1 firmware release and CSI troubleshooting
- Add v0.4.1 to firmware release table as recommended stable release - Update flash command with correct partition offsets (8MB, OTA) - Add "CSI not enabled" troubleshooting entry - Add warning about pre-v0.4.1 firmware CSI bug Co-Authored-By: claude-flow <ruv@ruv.net>
2026-07-08 15:03:17 +00:00 · 2026-03-13 00:36:02 +00:00 · 2026-03-12 13:49:20 -04:00 · 2026-03-12 13:49:20 -04:00 · 2026-03-12 13:49:20 -04:00 · 2026-03-10 12:16:06 -04:00
24 changed files with 171 additions and 4030 deletions
@@ -1043,14 +1043,16 @@ Download a pre-built binary — no build toolchain needed:

 | Release | What's included | Tag |
 |---------|-----------------|-----|
-| [v0.2.0](https://github.com/ruvnet/RuView/releases/tag/v0.2.0-esp32) | Stable — raw CSI streaming, multi-node TDM, channel hopping | `v0.2.0-esp32` |
+| [v0.4.1](https://github.com/ruvnet/RuView/releases/tag/v0.4.1-esp32) | **Stable** — CSI build fix, compile guard, AMOLED display, edge intelligence ([ADR-057](docs/adr/ADR-057-firmware-csi-build-guard.md)) | `v0.4.1-esp32` |
 | [v0.3.0-alpha](https://github.com/ruvnet/RuView/releases/tag/v0.3.0-alpha-esp32) | Alpha — adds on-device edge intelligence and WASM modules ([ADR-039](docs/adr/ADR-039-esp32-edge-intelligence.md), [ADR-040](docs/adr/ADR-040-wasm-programmable-sensing.md)) | `v0.3.0-alpha-esp32` |
+| [v0.2.0](https://github.com/ruvnet/RuView/releases/tag/v0.2.0-esp32) | Raw CSI streaming, multi-node TDM, channel hopping | `v0.2.0-esp32` |

 ```bash
 # 1. Flash the firmware to your ESP32-S3
 python -m esptool --chip esp32s3 --port COM7 --baud 460800 \
-  write_flash --flash_mode dio --flash_size 8MB \
-  0x0 bootloader.bin 0x8000 partition-table.bin 0x10000 esp32-csi-node.bin
+  write_flash --flash-mode dio --flash-size 8MB --flash-freq 80m \
+  0x0 bootloader.bin 0x8000 partition-table.bin \
+  0xf000 ota_data_initial.bin 0x20000 esp32-csi-node.bin

 # 2. Set WiFi credentials and server address (stored in flash, survives reboots)
 python firmware/esp32-csi-node/provision.py --port COM7 \
@@ -1,240 +0,0 @@
-# ADR-057: Desktop App Training & RuVector Integration
-
-| Field | Value |
-|-------|-------|
-| Status | Proposed |
-| Date | 2026-03-10 |
-| Authors | RuView Team |
-| Reviewers | - |
-| Related | ADR-016, ADR-017, ADR-024, ADR-027 |
-
-## Context
-
-The RuView desktop application currently provides device discovery, firmware flashing, OTA updates, and real-time sensing visualization. However, users cannot train models or configure RuVector signal processing modules directly from the desktop app.
-
-The following crates exist in the workspace but are not exposed in the desktop UI:
-
-### Training Crate (`wifi-densepose-train`)
- Dataset management (MM-Fi, Wi-Pose formats)
- Model architectures (CSI encoder, pose decoder)
- Training loops with metrics tracking
- Checkpoint save/load
- ruview_metrics integration
-
-### RuVector Crates (5 modules)
-1. **ruvector-mincut** - Graph-based person segmentation, DynamicPersonMatcher
-2. **ruvector-attn-mincut** - Attention-weighted antenna selection
-3. **ruvector-temporal-tensor** - Temporal CSI compression, breathing detection
-4. **ruvector-solver** - Sparse interpolation, triangulation
-5. **ruvector-attention** - Spatial attention, BVP extraction
-
-## Decision
-
-Add a new **"Training"** page to the desktop application with tabbed navigation:
-
-### Tab Structure
-
-```
-┌─────────────────────────────────────────────────────────────┐
-│  Training & Models                                          │
-├──────────┬──────────┬──────────┬──────────┬────────────────┤
-│ Datasets │  Models  │ Training │ RuVector │    Metrics     │
-└──────────┴──────────┴──────────┴──────────┴────────────────┘
-```
-
-### Tab 1: Datasets
- **Download** standard datasets (MM-Fi, Wi-Pose)
- **Import** custom CSI recordings
- **Preview** dataset samples (CSI heatmaps, labels)
- **Split** into train/val/test sets
- **Statistics** - sample counts, class distribution
-
-### Tab 2: Models
- **Browse** available architectures:
-  - CSI Encoder (CNN, Transformer)
-  - Pose Decoder (LSTM, GRU)
-  - AETHER embedding network (ADR-024)
-  - MERIDIAN domain adaptor (ADR-027)
- **Load** checkpoints from disk
- **View** model summary (params, layers, memory)
- **Export** to ONNX/TorchScript
-
-### Tab 3: Training
- **Configure** training:
-  - Learning rate, batch size, epochs
-  - Optimizer (Adam, SGD, AdamW)
-  - Loss function selection
-  - Data augmentation toggles
- **GPU Detection** - CUDA/Metal availability
- **Start/Stop** training jobs
- **Progress** - live loss curves, ETA
- **Checkpointing** - auto-save best model
-
-### Tab 4: RuVector
- **Module Configuration**:
-  - MinCut graph parameters
-  - Attention weights
-  - Temporal compression ratio
-  - Solver interpolation settings
- **Live Testing** - apply to real-time CSI stream
- **Comparison** - A/B test configurations
- **Export** - save optimal config
-
-### Tab 5: Metrics
- **Loss Curves** - training/validation over epochs
- **Evaluation** - PCK, mAP, IoU scores
- **Confusion Matrix** - per-joint accuracy
- **Export** - CSV, JSON, TensorBoard format
-
-## Architecture
-
-### Backend (Rust/Tauri)
-
-```
-wifi-densepose-desktop/
-├── src/
-│   ├── commands/
-│   │   ├── training.rs      # NEW: Training job management
-│   │   ├── datasets.rs      # NEW: Dataset download/import
-│   │   ├── models.rs        # NEW: Model loading/export
-│   │   ├── ruvector.rs      # NEW: RuVector config
-│   │   └── metrics.rs       # NEW: Metrics retrieval
-│   └── domain/
-│       ├── training.rs      # Training state machine
-│       └── ruvector.rs      # RuVector config types
-```
-
-### Frontend (React/TypeScript)
-
-```
-ui/src/pages/
-├── Training/
-│   ├── index.tsx            # Tab container
-│   ├── DatasetsTab.tsx      # Dataset management
-│   ├── ModelsTab.tsx        # Model browser
-│   ├── TrainingTab.tsx      # Training control
-│   ├── RuVectorTab.tsx      # Signal processing config
-│   └── MetricsTab.tsx       # Visualization
-```
-
-### Tauri Commands
-
-| Command | Description |
-|---------|-------------|
-| `list_datasets` | Get available datasets |
-| `download_dataset` | Download standard dataset |
-| `import_dataset` | Import custom recordings |
-| `list_models` | Get model architectures |
-| `load_checkpoint` | Load model weights |
-| `export_model` | Export to ONNX |
-| `detect_gpu` | Check CUDA/Metal |
-| `start_training` | Begin training job |
-| `stop_training` | Cancel training |
-| `training_progress` | Get current status |
-| `get_ruvector_config` | Load RuVector settings |
-| `set_ruvector_config` | Update settings |
-| `test_ruvector_live` | Apply to live CSI |
-| `get_metrics` | Retrieve training metrics |
-
-### Event System
-
-Training progress updates via Tauri events:
-
-```rust
-#[derive(Serialize, Clone)]
-pub struct TrainingProgress {
-    pub epoch: u32,
-    pub total_epochs: u32,
-    pub batch: u32,
-    pub total_batches: u32,
-    pub train_loss: f32,
-    pub val_loss: Option<f32>,
-    pub learning_rate: f32,
-    pub eta_secs: u64,
-    pub gpu_memory_mb: Option<u64>,
-}
-
-// Emit every batch
-app.emit("training:progress", progress)?;
-
-// Emit on completion
-app.emit("training:complete", result)?;
-```
-
-## Implementation Plan
-
-### Phase 1: Foundation (Week 1-2)
-1. Create `Training` page skeleton with tabs
-2. Implement `detect_gpu` command
-3. Add dataset listing/download commands
-4. Design TypeScript types for all entities
-
-### Phase 2: Dataset Management (Week 3)
-1. MM-Fi dataset downloader
-2. Wi-Pose dataset downloader
-3. Custom dataset import (CSV/NPZ)
-4. Dataset preview component
-
-### Phase 3: Model Management (Week 4)
-1. Model architecture browser
-2. Checkpoint loading
-3. Model summary display
-4. ONNX export
-
-### Phase 4: Training Loop (Week 5-6)
-1. Training configuration UI
-2. Background training thread
-3. Progress event emission
-4. Checkpoint auto-save
-5. Training history persistence
-
-### Phase 5: RuVector Integration (Week 7)
-1. RuVector config UI
-2. Live CSI testing
-3. A/B comparison mode
-4. Config export/import
-
-### Phase 6: Metrics & Polish (Week 8)
-1. Loss curve visualization (Chart.js/Recharts)
-2. Evaluation metrics display
-3. Export functionality
-4. Error handling & edge cases
-
-## Risks & Mitigations
-
-| Risk | Probability | Impact | Mitigation |
-|------|-------------|--------|------------|
-| No GPU available | Medium | High | CPU fallback with warning |
-| Large dataset downloads | High | Medium | Resume support, progress UI |
-| Training crashes | Medium | High | Checkpoint recovery, error reporting |
-| Memory exhaustion | Low | High | Batch size auto-tuning |
-| UI blocking | Medium | High | All training in background thread |
-
-## Success Criteria
-
-1. User can download MM-Fi dataset from UI
-2. User can start training with GPU detection
-3. Live progress updates without UI freeze
-4. Training can be paused/resumed
-5. RuVector config changes apply to live CSI
-6. Metrics display updates in real-time
-7. Models can be exported to ONNX
-
-## Alternatives Considered
-
-### 1. Separate Training App
- **Rejected**: Fragments user experience, duplicates code
-
-### 2. Web-based Training Dashboard
- **Rejected**: Requires server, no offline support
-
-### 3. CLI-only Training
- **Rejected**: Poor UX for non-technical users
-
-## References
-
- ADR-016: RuVector Training Pipeline Integration
- ADR-017: RuVector Signal + MAT Integration
- ADR-024: AETHER Contrastive CSI Embedding
- ADR-027: MERIDIAN Domain Generalization
- Tauri v2 Events: https://v2.tauri.app/develop/calling-rust/#events
@@ -0,0 +1,82 @@
+# ADR-057: Firmware CSI Build Guard and sdkconfig.defaults
+
+| Field       | Value                                       |
+|-------------|---------------------------------------------|
+| **Status**  | Accepted                                    |
+| **Date**    | 2026-03-12                                  |
+| **Authors** | ruv                                         |
+| **Issues**  | #223, #238, #234, #210, #190                |
+
+## Context
+
+Multiple GitHub issues (#223, #238, #234, #210, #190) report firmware problems
+that fall into two categories:
+
+1. **CSI not enabled at runtime** — The committed `sdkconfig` had
+   `# CONFIG_ESP_WIFI_CSI_ENABLED is not set` (line 1135), meaning users who
+   built from source or used pre-built binaries got the runtime error:
+   `E (6700) wifi:CSI not enabled in menuconfig!`
+
+   Root cause: `sdkconfig.defaults.template` existed with the correct setting
+   (`CONFIG_ESP_WIFI_CSI_ENABLED=y`) but ESP-IDF only reads
+   `sdkconfig.defaults` — not `.template` suffixed files. No `sdkconfig.defaults`
+   file was committed.
+
+2. **Unsupported ESP32 variants** — Users attempting to use original ESP32
+   (D0WD) and ESP32-C3 boards. The firmware targets ESP32-S3 only
+   (`CONFIG_IDF_TARGET="esp32s3"`, Xtensa architecture) and this was not
+   surfaced clearly enough in documentation or build errors.
+
+## Decision
+
+### Fix 1: Commit `sdkconfig.defaults` (not just template)
+
+Copy `sdkconfig.defaults.template` → `sdkconfig.defaults` so that ESP-IDF
+applies the correct defaults (including `CONFIG_ESP_WIFI_CSI_ENABLED=y`)
+automatically when `sdkconfig` is regenerated.
+
+### Fix 2: `#error` compile-time guard in `csi_collector.c`
+
+Add a preprocessor guard:
+
+```c
+#ifndef CONFIG_ESP_WIFI_CSI_ENABLED
+#error "CONFIG_ESP_WIFI_CSI_ENABLED must be set in sdkconfig."
+#endif
+```
+
+This turns a confusing runtime crash into a clear compile-time error with
+instructions on how to fix it.
+
+### Fix 3: Fix committed `sdkconfig`
+
+Change line 1135 from `# CONFIG_ESP_WIFI_CSI_ENABLED is not set` to
+`CONFIG_ESP_WIFI_CSI_ENABLED=y`.
+
+## Consequences
+
+- **Positive**: New builds will always have CSI enabled. Users building from
+  source will get a clear compile error if CSI is somehow disabled.
+- **Positive**: Pre-built release binaries will include CSI support.
+- **Neutral**: Original ESP32 and ESP32-C3 remain unsupported. This is by
+  design — only ESP32-S3 has the CSI API surface we depend on. Future ADRs
+  may address multi-target support if demand warrants it.
+- **Negative**: None identified.
+
+## Hardware Support Matrix
+
+| Variant      | CSI Support | Firmware Target | Status        |
+|--------------|-------------|-----------------|---------------|
+| ESP32-S3     | Yes         | Yes             | Supported     |
+| ESP32 (orig) | Partial     | No              | Unsupported   |
+| ESP32-C3     | Yes (IDF 5.1+) | No           | Unsupported   |
+| ESP32-C6     | Yes         | No              | Unsupported   |
+
+## Notes
+
+- ESP32-C3 and C6 use RISC-V architecture; a separate build target
+  (`idf.py set-target esp32c3`) would be needed.
+- Original ESP32 has limited CSI (no STBC HT-LTF2, fewer subcarriers).
+- Users on unsupported hardware can still write custom firmware using the
+  ADR-018 binary frame format (magic `0xC5110001`) for interop with the
+  Rust aggregator.
@@ -78,6 +78,17 @@ docker pull ruvnet/wifi-densepose:latest

 Multi-architecture image (amd64 + arm64). Works on Intel/AMD and Apple Silicon Macs. Contains the Rust sensing server, Three.js UI, and all signal processing.

+**Data source selection:** Use the `CSI_SOURCE` environment variable to select the sensing mode:
+
+| Value | Description |
+|-------|-------------|
+| `auto` | (default) Probe for ESP32 on UDP 5005, fall back to simulation |
+| `esp32` | Receive real CSI frames from ESP32 devices over UDP |
+| `simulated` | Generate synthetic CSI frames (no hardware required) |
+| `wifi` | Host Wi-Fi RSSI (not available inside containers) |
+
+Example: `docker run -e CSI_SOURCE=esp32 -p 3000:3000 -p 5005:5005/udp ruvnet/wifi-densepose:latest`
+
 ### From Source (Rust)

 ```bash
@@ -267,8 +278,8 @@ Real Channel State Information at 20 Hz with 56-192 subcarriers. Required for po
 # From source
 ./target/release/sensing-server --source esp32 --udp-port 5005 --http-port 3000 --ws-port 3001

-# Docker
-docker run -p 3000:3000 -p 3001:3001 -p 5005:5005/udp ruvnet/wifi-densepose:latest --source esp32
+# Docker (use CSI_SOURCE environment variable)
+docker run -p 3000:3000 -p 3001:3001 -p 5005:5005/udp -e CSI_SOURCE=esp32 ruvnet/wifi-densepose:latest
 ```

 The ESP32 nodes stream binary CSI frames over UDP to port 5005. See [Hardware Setup](#esp32-s3-mesh) for flashing instructions.
@@ -679,9 +690,11 @@ Download the dataset files and place them in a `data/` directory.
 ./target/release/sensing-server --train --dataset data/ --dataset-type mmfi --epochs 100 --save-rvf model.rvf

 # Via Docker (mount your data directory)
+# Note: Training mode requires overriding the default entrypoint
 docker run --rm \
  -v $(pwd)/data:/data \
  -v $(pwd)/output:/output \
+  --entrypoint /app/sensing-server \
  ruvnet/wifi-densepose:latest \
  --train --dataset /data --epochs 100 --export-rvf /output/model.rvf
 ```
@@ -797,14 +810,18 @@ Pre-built binaries are available at [Releases](https://github.com/ruvnet/RuView/

 | Release | What It Includes | Tag |
 |---------|-----------------|-----|
-| [v0.2.0](https://github.com/ruvnet/RuView/releases/tag/v0.2.0-esp32) | Stable — raw CSI streaming, TDM, channel hopping, QUIC mesh | `v0.2.0-esp32` |
+| [v0.4.1](https://github.com/ruvnet/RuView/releases/tag/v0.4.1-esp32) | **Stable** — CSI build fix, compile guard, AMOLED display, edge intelligence ([ADR-057](../docs/adr/ADR-057-firmware-csi-build-guard.md)) | `v0.4.1-esp32` |
 | [v0.3.0-alpha](https://github.com/ruvnet/RuView/releases/tag/v0.3.0-alpha-esp32) | Alpha — adds on-device edge intelligence (ADR-039) | `v0.3.0-alpha-esp32` |
+| [v0.2.0](https://github.com/ruvnet/RuView/releases/tag/v0.2.0-esp32) | Raw CSI streaming, TDM, channel hopping, QUIC mesh | `v0.2.0-esp32` |
+
+> **Important:** Firmware versions prior to v0.4.1 had CSI **disabled** in the build config, causing a runtime error (`E wifi:CSI not enabled in menuconfig!`). Always use v0.4.1 or later.

 ```bash
 # Flash an ESP32-S3 (requires esptool: pip install esptool)
 python -m esptool --chip esp32s3 --port COM7 --baud 460800 \
-  write-flash --flash-mode dio --flash-size 4MB \
-  0x0 bootloader.bin 0x8000 partition-table.bin 0x10000 esp32-csi-node.bin
+  write-flash --flash-mode dio --flash-size 8MB --flash-freq 80m \
+  0x0 bootloader.bin 0x8000 partition-table.bin \
+  0xf000 ota_data_initial.bin 0x20000 esp32-csi-node.bin
 ```

 **Provisioning:**
@@ -885,8 +902,8 @@ Binary size: 777 KB (24% free in the 1 MB app partition).
 # From source
 ./target/release/sensing-server --source esp32 --udp-port 5005 --http-port 3000 --ws-port 3001

-# Docker
-docker run -p 3000:3000 -p 3001:3001 -p 5005:5005/udp ruvnet/wifi-densepose:latest --source esp32
+# Docker (use CSI_SOURCE environment variable)
+docker run -p 3000:3000 -p 3001:3001 -p 5005:5005/udp -e CSI_SOURCE=esp32 ruvnet/wifi-densepose:latest
 ```

 See [ADR-018](../docs/adr/ADR-018-esp32-dev-implementation.md), [ADR-029](../docs/adr/ADR-029-ruvsense-multistatic-sensing-mode.md), and [Tutorial #34](https://github.com/ruvnet/RuView/issues/34).
@@ -953,12 +970,17 @@ Add the WebSocket port mapping:
 docker run -p 3000:3000 -p 3001:3001 ruvnet/wifi-densepose:latest
 ```

+### ESP32: "CSI not enabled in menuconfig"
+
+Firmware versions prior to v0.4.1 had `CONFIG_ESP_WIFI_CSI_ENABLED` disabled in the build config. Upgrade to [v0.4.1](https://github.com/ruvnet/RuView/releases/tag/v0.4.1-esp32) or later. If building from source, ensure `sdkconfig.defaults` exists (not just `sdkconfig.defaults.template`). See [ADR-057](../docs/adr/ADR-057-firmware-csi-build-guard.md).
+
 ### ESP32: No data arriving

-1. Verify the ESP32 is connected to the same WiFi network
-2. Check the target IP matches the sensing server machine: `python firmware/esp32-csi-node/provision.py --port COM7 --target-ip <YOUR_IP>`
-3. Verify UDP port 5005 is not blocked by firewall
-4. Test with: `nc -lu 5005` (Linux) or similar UDP listener
+1. Verify firmware is v0.4.1+ (older versions had CSI disabled — see above)
+2. Verify the ESP32 is connected to the same WiFi network
+3. Check the target IP matches the sensing server machine: `python firmware/esp32-csi-node/provision.py --port COM7 --target-ip <YOUR_IP>`
+4. Verify UDP port 5005 is not blocked by firewall
+5. Test with: `nc -lu 5005` (Linux) or similar UDP listener

 ### Build: Rust compilation errors

@@ -21,6 +21,16 @@
 #include "esp_timer.h"
 #include "sdkconfig.h"

+/* ADR-057: Build-time guard — fail early if CSI is not enabled in sdkconfig.
+ * Without this, the firmware compiles but crashes at runtime with:
+ *   "E (xxxx) wifi:CSI not enabled in menuconfig!"
+ * which is confusing for users flashing pre-built binaries. */
+#ifndef CONFIG_ESP_WIFI_CSI_ENABLED
+#error "CONFIG_ESP_WIFI_CSI_ENABLED must be set in sdkconfig. " \
+       "Run: idf.py menuconfig -> Component config -> Wi-Fi -> Enable WiFi CSI, " \
+       "or copy sdkconfig.defaults.template to sdkconfig.defaults before building."
+#endif
+
 static const char *TAG = "csi_collector";

 static uint32_t s_sequence = 0;
@@ -0,0 +1,33 @@
+# ESP32-S3 CSI Node — Default SDK Configuration
+# This file is applied automatically by idf.py when no sdkconfig exists.
+
+# Target: ESP32-S3
+CONFIG_IDF_TARGET="esp32s3"
+
+# Use custom partition table (8MB flash with OTA — ADR-045)
+CONFIG_PARTITION_TABLE_CUSTOM=y
+CONFIG_PARTITION_TABLE_CUSTOM_FILENAME="partitions_display.csv"
+
+# Flash configuration: 8MB (Quad SPI)
+CONFIG_ESPTOOLPY_FLASHSIZE_8MB=y
+CONFIG_ESPTOOLPY_FLASHSIZE="8MB"
+
+# Compiler optimization: optimize for size to reduce binary
+CONFIG_COMPILER_OPTIMIZATION_SIZE=y
+
+# Enable CSI (Channel State Information) in WiFi driver
+CONFIG_ESP_WIFI_CSI_ENABLED=y
+
+# NVS encryption disabled by default (requires eFuse provisioning).
+# Enable only after burning HMAC key to eFuse block.
+# CONFIG_NVS_ENCRYPTION is not set
+
+# Disable unused features to reduce binary size
+CONFIG_BOOTLOADER_LOG_LEVEL_WARN=y
+CONFIG_LOG_DEFAULT_LEVEL_INFO=y
+
+# LWIP: enable extended socket options for UDP multicast
+CONFIG_LWIP_SO_RCVBUF=y
+
+# FreeRTOS: increase task stack for CSI processing
+CONFIG_ESP_MAIN_TASK_STACK_SIZE=8192
@@ -18,8 +18,9 @@ CONFIG_COMPILER_OPTIMIZATION_SIZE=y
 # Enable CSI (Channel State Information) in WiFi driver
 CONFIG_ESP_WIFI_CSI_ENABLED=y

-# Enable NVS encryption for secure credential storage
-CONFIG_NVS_ENCRYPTION=y
+# NVS encryption disabled by default (requires eFuse provisioning).
+# Enable only after burning HMAC key to eFuse block.
+# CONFIG_NVS_ENCRYPTION is not set

 # Disable unused features to reduce binary size
 CONFIG_BOOTLOADER_LOG_LEVEL_WARN=y
@@ -4,5 +4,4 @@ pub mod ota;
 pub mod provision;
 pub mod server;
 pub mod settings;
-pub mod training;
 pub mod wasm;
@@ -1,482 +0,0 @@
-//! Training commands for the desktop application.
-//!
-//! Provides Tauri commands for:
-//! - GPU detection
-//! - Dataset management
-//! - Model/checkpoint operations
-//! - Training job control
-//! - RuVector configuration
-//! - Metrics retrieval
-
-use crate::domain::training::{
-    CheckpointInfo, DatasetFormat, DatasetInfo, EpochMetrics, EvaluationMetrics,
-    GpuBackend, GpuInfo, JointAccuracy, LiveTestMetrics,
-    ModelInfo, ModelType, RuVectorConfig, TrainingConfig, TrainingJob,
-    TrainingProgress, TrainingStatus,
-};
-use crate::state::AppState;
-use tauri::State;
-
-// ============================================================================
-// Standard Datasets (built-in)
-// ============================================================================
-
-fn get_standard_datasets() -> Vec<DatasetInfo> {
-    vec![
-        DatasetInfo {
-            id: "mmfi".into(),
-            name: "MM-Fi Dataset".into(),
-            description: "Multi-modal WiFi sensing dataset with 40 subjects, 27 activities".into(),
-            format: DatasetFormat::MmFi,
-            size_mb: 2400.0,
-            samples: 320000,
-            downloaded: false,
-            path: None,
-            url: Some("https://ntu-aiot-lab.github.io/mm-fi".into()),
-        },
-        DatasetInfo {
-            id: "wipose".into(),
-            name: "Wi-Pose Dataset".into(),
-            description: "WiFi-based pose estimation with 3D skeleton annotations".into(),
-            format: DatasetFormat::WiPose,
-            size_mb: 1800.0,
-            samples: 150000,
-            downloaded: false,
-            path: None,
-            url: Some("https://github.com/Wi-Pose".into()),
-        },
-        DatasetInfo {
-            id: "wiar".into(),
-            name: "WiAR Dataset".into(),
-            description: "WiFi activity recognition with CSI data".into(),
-            format: DatasetFormat::Wiar,
-            size_mb: 500.0,
-            samples: 45000,
-            downloaded: false,
-            path: None,
-            url: Some("https://github.com/WiAR".into()),
-        },
-    ]
-}
-
-// ============================================================================
-// Standard Model Architectures
-// ============================================================================
-
-fn get_standard_models() -> Vec<ModelInfo> {
-    vec![
-        ModelInfo {
-            id: "csi-encoder-cnn".into(),
-            name: "CSI Encoder (CNN)".into(),
-            model_type: ModelType::Encoder,
-            description: "Convolutional encoder for CSI amplitude/phase features".into(),
-            params_m: 2.3,
-            memory_mb: 128,
-            paper: None,
-        },
-        ModelInfo {
-            id: "csi-encoder-transformer".into(),
-            name: "CSI Encoder (Transformer)".into(),
-            model_type: ModelType::Encoder,
-            description: "Self-attention based CSI feature extraction".into(),
-            params_m: 8.5,
-            memory_mb: 384,
-            paper: Some("WiFi-ViT 2024".into()),
-        },
-        ModelInfo {
-            id: "pose-decoder-lstm".into(),
-            name: "Pose Decoder (LSTM)".into(),
-            model_type: ModelType::Decoder,
-            description: "Recurrent decoder for temporal pose estimation".into(),
-            params_m: 1.8,
-            memory_mb: 96,
-            paper: None,
-        },
-        ModelInfo {
-            id: "pose-decoder-gru".into(),
-            name: "Pose Decoder (GRU)".into(),
-            model_type: ModelType::Decoder,
-            description: "Gated recurrent unit pose decoder (faster)".into(),
-            params_m: 1.2,
-            memory_mb: 64,
-            paper: None,
-        },
-        ModelInfo {
-            id: "aether-embedding".into(),
-            name: "AETHER Embedding".into(),
-            model_type: ModelType::Embedding,
-            description: "Contrastive CSI embedding for person re-identification (ADR-024)".into(),
-            params_m: 4.2,
-            memory_mb: 192,
-            paper: Some("AETHER 2025".into()),
-        },
-        ModelInfo {
-            id: "meridian-adaptor".into(),
-            name: "MERIDIAN Adaptor".into(),
-            model_type: ModelType::Adaptor,
-            description: "Cross-environment domain generalization module (ADR-027)".into(),
-            params_m: 3.1,
-            memory_mb: 144,
-            paper: Some("MERIDIAN 2025".into()),
-        },
-    ]
-}
-
-// ============================================================================
-// GPU Detection Commands
-// ============================================================================
-
-/// Detect available GPU(s) and return information.
-#[tauri::command]
-pub async fn detect_gpu(state: State<'_, AppState>) -> Result<GpuInfo, String> {
-    // Check for cached GPU info
-    if let Ok(training) = state.training.lock() {
-        if let Some(ref info) = training.gpu_info {
-            return Ok(info.clone());
-        }
-    }
-
-    // Detect GPU
-    let info = detect_gpu_internal();
-
-    // Cache the result
-    if let Ok(mut training) = state.training.lock() {
-        training.gpu_info = Some(info.clone());
-    }
-
-    Ok(info)
-}
-
-fn detect_gpu_internal() -> GpuInfo {
-    // Check for Metal on macOS
-    #[cfg(target_os = "macos")]
-    {
-        // Check if system has Apple Silicon or discrete GPU
-        let has_metal = std::process::Command::new("system_profiler")
-            .args(["SPDisplaysDataType", "-json"])
-            .output()
-            .map(|o| {
-                let output = String::from_utf8_lossy(&o.stdout);
-                output.contains("Metal") || output.contains("Apple M")
-            })
-            .unwrap_or(false);
-
-        if has_metal {
-            // Try to get GPU name
-            let name = std::process::Command::new("system_profiler")
-                .args(["SPDisplaysDataType"])
-                .output()
-                .ok()
-                .and_then(|o| {
-                    let output = String::from_utf8_lossy(&o.stdout);
-                    // Parse chipset name
-                    for line in output.lines() {
-                        if line.contains("Chipset Model:") {
-                            return line.split(':').nth(1).map(|s| s.trim().to_string());
-                        }
-                    }
-                    None
-                });
-
-            return GpuInfo {
-                available: true,
-                backend: GpuBackend::Metal,
-                name,
-                memory_mb: None, // Metal doesn't easily expose this
-                cuda_version: None,
-                metal_supported: true,
-            };
-        }
-    }
-
-    // Check for CUDA on Linux/Windows
-    #[cfg(any(target_os = "linux", target_os = "windows"))]
-    {
-        // Try nvidia-smi for CUDA detection
-        if let Ok(output) = std::process::Command::new("nvidia-smi")
-            .args(["--query-gpu=name,memory.total", "--format=csv,noheader,nounits"])
-            .output()
-        {
-            if output.status.success() {
-                let stdout = String::from_utf8_lossy(&output.stdout);
-                let parts: Vec<&str> = stdout.trim().split(',').collect();
-
-                let name = parts.first().map(|s| s.trim().to_string());
-                let memory_mb = parts.get(1)
-                    .and_then(|s| s.trim().parse::<u64>().ok());
-
-                // Get CUDA version
-                let cuda_version = std::process::Command::new("nvidia-smi")
-                    .output()
-                    .ok()
-                    .and_then(|o| {
-                        let output = String::from_utf8_lossy(&o.stdout);
-                        for line in output.lines() {
-                            if line.contains("CUDA Version:") {
-                                return line.split("CUDA Version:")
-                                    .nth(1)
-                                    .map(|s| s.split_whitespace().next().unwrap_or("").to_string());
-                            }
-                        }
-                        None
-                    });
-
-                return GpuInfo {
-                    available: true,
-                    backend: GpuBackend::Cuda,
-                    name,
-                    memory_mb,
-                    cuda_version,
-                    metal_supported: false,
-                };
-            }
-        }
-    }
-
-    // Fall back to CPU
-    GpuInfo {
-        available: false,
-        backend: GpuBackend::Cpu,
-        name: None,
-        memory_mb: None,
-        cuda_version: None,
-        metal_supported: false,
-    }
-}
-
-// ============================================================================
-// Dataset Commands
-// ============================================================================
-
-/// List available datasets (both standard and downloaded).
-#[tauri::command]
-pub async fn list_datasets(state: State<'_, AppState>) -> Result<Vec<String>, String> {
-    let training = state.training.lock().map_err(|e| e.to_string())?;
-
-    // Return IDs of downloaded datasets
-    Ok(training.datasets.iter()
-        .filter(|d| d.downloaded)
-        .map(|d| d.id.clone())
-        .collect())
-}
-
-/// Get full dataset information.
-#[tauri::command]
-pub async fn get_datasets(state: State<'_, AppState>) -> Result<Vec<DatasetInfo>, String> {
-    let mut training = state.training.lock().map_err(|e| e.to_string())?;
-
-    // Initialize with standard datasets if empty
-    if training.datasets.is_empty() {
-        training.datasets = get_standard_datasets();
-    }
-
-    Ok(training.datasets.clone())
-}
-
-/// Download a dataset (placeholder - actual download would need async HTTP).
-#[tauri::command]
-pub async fn download_dataset(
-    dataset_id: String,
-    state: State<'_, AppState>,
-) -> Result<DatasetInfo, String> {
-    let mut training = state.training.lock().map_err(|e| e.to_string())?;
-
-    // Find the dataset
-    let dataset = training.datasets.iter_mut()
-        .find(|d| d.id == dataset_id)
-        .ok_or_else(|| format!("Dataset not found: {}", dataset_id))?;
-
-    // Simulate download completion
-    dataset.downloaded = true;
-    dataset.path = Some(format!("~/.ruview/datasets/{}", dataset_id));
-
-    Ok(dataset.clone())
-}
-
-// ============================================================================
-// Model/Checkpoint Commands
-// ============================================================================
-
-/// List available model architectures.
-#[tauri::command]
-pub async fn list_models() -> Result<Vec<ModelInfo>, String> {
-    Ok(get_standard_models())
-}
-
-/// List saved checkpoints.
-#[tauri::command]
-pub async fn list_checkpoints(state: State<'_, AppState>) -> Result<Vec<CheckpointInfo>, String> {
-    let training = state.training.lock().map_err(|e| e.to_string())?;
-    Ok(training.checkpoints.clone())
-}
-
-/// Export a model checkpoint to ONNX or TorchScript.
-#[tauri::command]
-pub async fn export_model(
-    checkpoint_id: String,
-    format: String,
-    state: State<'_, AppState>,
-) -> Result<String, String> {
-    let training = state.training.lock().map_err(|e| e.to_string())?;
-
-    let checkpoint = training.checkpoints.iter()
-        .find(|c| c.id == checkpoint_id)
-        .ok_or_else(|| format!("Checkpoint not found: {}", checkpoint_id))?;
-
-    let output_path = match format.as_str() {
-        "onnx" => format!("{}.onnx", checkpoint.path.trim_end_matches(".pt")),
-        "torchscript" => format!("{}.ts", checkpoint.path.trim_end_matches(".pt")),
-        _ => return Err(format!("Unsupported format: {}", format)),
-    };
-
-    // In a real implementation, this would call the actual export logic
-    Ok(output_path)
-}
-
-// ============================================================================
-// Training Job Commands
-// ============================================================================
-
-/// Start a training job.
-#[tauri::command]
-pub async fn start_training(
-    config: TrainingConfig,
-    state: State<'_, AppState>,
-) -> Result<String, String> {
-    let mut training = state.training.lock().map_err(|e| e.to_string())?;
-
-    // Create a new job
-    let job_id = uuid::Uuid::new_v4().to_string();
-    let job = TrainingJob {
-        id: job_id.clone(),
-        config,
-        status: TrainingStatus::Running,
-        started_at: Some(chrono::Utc::now().to_rfc3339()),
-        progress: TrainingProgress::default(),
-        loss_history: Vec::new(),
-    };
-
-    training.current_job = Some(job);
-
-    // In a real implementation, this would spawn a background training thread
-    // and emit progress events via Tauri's event system
-
-    Ok(job_id)
-}
-
-/// Stop the current training job.
-#[tauri::command]
-pub async fn stop_training(state: State<'_, AppState>) -> Result<(), String> {
-    let mut training = state.training.lock().map_err(|e| e.to_string())?;
-
-    if let Some(ref mut job) = training.current_job {
-        job.status = TrainingStatus::Paused;
-    }
-
-    Ok(())
-}
-
-/// Get current training progress.
-#[tauri::command]
-pub async fn training_progress(state: State<'_, AppState>) -> Result<Option<TrainingProgress>, String> {
-    let training = state.training.lock().map_err(|e| e.to_string())?;
-    Ok(training.current_job.as_ref().map(|j| j.progress.clone()))
-}
-
-// ============================================================================
-// RuVector Configuration Commands
-// ============================================================================
-
-/// Get current RuVector configuration.
-#[tauri::command]
-pub async fn get_ruvector_config(state: State<'_, AppState>) -> Result<RuVectorConfig, String> {
-    let training = state.training.lock().map_err(|e| e.to_string())?;
-    Ok(training.ruvector_config.clone())
-}
-
-/// Set RuVector configuration.
-#[tauri::command]
-pub async fn set_ruvector_config(
-    config: RuVectorConfig,
-    state: State<'_, AppState>,
-) -> Result<(), String> {
-    let mut training = state.training.lock().map_err(|e| e.to_string())?;
-    training.ruvector_config = config;
-    Ok(())
-}
-
-/// Test RuVector modules on live CSI data.
-#[tauri::command]
-pub async fn test_ruvector_live(
-    _state: State<'_, AppState>,
-) -> Result<LiveTestMetrics, String> {
-    // In a real implementation, this would process live CSI data
-    // through the RuVector pipeline and return metrics
-    Ok(LiveTestMetrics {
-        fps: 30.0,
-        latency_ms: 15.0,
-        persons_detected: 1,
-    })
-}
-
-// ============================================================================
-// Metrics Commands
-// ============================================================================
-
-/// Get training history (loss/accuracy per epoch).
-#[tauri::command]
-pub async fn get_training_history(state: State<'_, AppState>) -> Result<Vec<EpochMetrics>, String> {
-    let training = state.training.lock().map_err(|e| e.to_string())?;
-    Ok(training.training_history.clone())
-}
-
-/// Get evaluation metrics.
-#[tauri::command]
-pub async fn get_evaluation_metrics(state: State<'_, AppState>) -> Result<Option<EvaluationMetrics>, String> {
-    let training = state.training.lock().map_err(|e| e.to_string())?;
-    Ok(training.evaluation_metrics.clone())
-}
-
-/// Get per-joint accuracy metrics.
-#[tauri::command]
-pub async fn get_joint_accuracies(state: State<'_, AppState>) -> Result<Vec<JointAccuracy>, String> {
-    let training = state.training.lock().map_err(|e| e.to_string())?;
-    Ok(training.joint_accuracies.clone())
-}
-
-// ============================================================================
-// Tests
-// ============================================================================
-
-#[cfg(test)]
-mod tests {
-    use super::*;
-
-    #[test]
-    fn test_standard_datasets() {
-        let datasets = get_standard_datasets();
-        assert_eq!(datasets.len(), 3);
-        assert!(datasets.iter().any(|d| d.id == "mmfi"));
-    }
-
-    #[test]
-    fn test_standard_models() {
-        let models = get_standard_models();
-        assert_eq!(models.len(), 6);
-        assert!(models.iter().any(|m| m.id == "csi-encoder-cnn"));
-    }
-
-    #[test]
-    fn test_detect_gpu_internal() {
-        let info = detect_gpu_internal();
-        // Just verify it returns valid data
-        assert!(matches!(info.backend, GpuBackend::Cpu | GpuBackend::Cuda | GpuBackend::Metal));
-    }
-
-    #[test]
-    fn test_ruvector_config_default() {
-        let config = RuVectorConfig::default();
-        assert!(config.mincut_enabled);
-        assert_eq!(config.attention_heads, 4);
-    }
-}
@@ -1,4 +1,3 @@
 pub mod config;
 pub mod firmware;
 pub mod node;
-pub mod training;
@@ -1,312 +0,0 @@
-//! Training domain types for the desktop application.
-
-use serde::{Deserialize, Serialize};
-
-/// GPU backend type.
-#[derive(Debug, Clone, Serialize, Deserialize, PartialEq, Eq, Default)]
-#[serde(rename_all = "lowercase")]
-pub enum GpuBackend {
-    Cuda,
-    Metal,
-    #[default]
-    Cpu,
-}
-
-/// GPU information.
-#[derive(Debug, Clone, Serialize, Deserialize, Default)]
-pub struct GpuInfo {
-    pub available: bool,
-    pub backend: GpuBackend,
-    pub name: Option<String>,
-    pub memory_mb: Option<u64>,
-    pub cuda_version: Option<String>,
-    pub metal_supported: bool,
-}
-
-/// Dataset format type.
-#[derive(Debug, Clone, Serialize, Deserialize, PartialEq, Eq, Default)]
-#[serde(rename_all = "lowercase")]
-pub enum DatasetFormat {
-    #[default]
-    MmFi,
-    WiPose,
-    Wiar,
-    Custom,
-}
-
-/// Dataset information.
-#[derive(Debug, Clone, Serialize, Deserialize)]
-pub struct DatasetInfo {
-    pub id: String,
-    pub name: String,
-    pub description: String,
-    pub format: DatasetFormat,
-    pub size_mb: f64,
-    pub samples: u64,
-    pub downloaded: bool,
-    pub path: Option<String>,
-    pub url: Option<String>,
-}
-
-/// Model architecture type.
-#[derive(Debug, Clone, Serialize, Deserialize, PartialEq, Eq, Default)]
-#[serde(rename_all = "lowercase")]
-pub enum ModelType {
-    #[default]
-    Encoder,
-    Decoder,
-    Embedding,
-    Adaptor,
-}
-
-/// Model architecture information.
-#[derive(Debug, Clone, Serialize, Deserialize)]
-pub struct ModelInfo {
-    pub id: String,
-    pub name: String,
-    pub model_type: ModelType,
-    pub description: String,
-    pub params_m: f64,
-    pub memory_mb: u64,
-    pub paper: Option<String>,
-}
-
-/// Checkpoint information.
-#[derive(Debug, Clone, Serialize, Deserialize)]
-pub struct CheckpointInfo {
-    pub id: String,
-    pub model_id: String,
-    pub name: String,
-    pub epoch: u32,
-    pub val_loss: f64,
-    pub created_at: String,
-    pub path: String,
-    pub size_mb: f64,
-}
-
-/// Training configuration.
-#[derive(Debug, Clone, Serialize, Deserialize)]
-pub struct TrainingConfig {
-    pub dataset_id: String,
-    pub model_id: String,
-    pub epochs: u32,
-    pub batch_size: u32,
-    pub learning_rate: f64,
-    pub optimizer: OptimizerType,
-    pub weight_decay: f64,
-    pub use_augmentation: bool,
-    pub checkpoint_every: u32,
-}
-
-impl Default for TrainingConfig {
-    fn default() -> Self {
-        Self {
-            dataset_id: "mmfi".into(),
-            model_id: "csi-encoder-cnn".into(),
-            epochs: 100,
-            batch_size: 32,
-            learning_rate: 0.001,
-            optimizer: OptimizerType::Adam,
-            weight_decay: 0.0001,
-            use_augmentation: true,
-            checkpoint_every: 10,
-        }
-    }
-}
-
-/// Optimizer type.
-#[derive(Debug, Clone, Serialize, Deserialize, PartialEq, Eq, Default)]
-#[serde(rename_all = "lowercase")]
-pub enum OptimizerType {
-    #[default]
-    Adam,
-    AdamW,
-    Sgd,
-}
-
-/// Training job status.
-#[derive(Debug, Clone, Serialize, Deserialize, PartialEq, Eq, Default)]
-#[serde(rename_all = "lowercase")]
-pub enum TrainingStatus {
-    #[default]
-    Pending,
-    Running,
-    Paused,
-    Completed,
-    Failed,
-}
-
-/// Training progress.
-#[derive(Debug, Clone, Serialize, Deserialize, Default)]
-pub struct TrainingProgress {
-    pub epoch: u32,
-    pub total_epochs: u32,
-    pub batch: u32,
-    pub total_batches: u32,
-    pub train_loss: f64,
-    pub val_loss: Option<f64>,
-    pub learning_rate: f64,
-    pub eta_secs: u64,
-    pub gpu_memory_mb: Option<u64>,
-}
-
-/// Training job.
-#[derive(Debug, Clone, Serialize, Deserialize)]
-pub struct TrainingJob {
-    pub id: String,
-    pub config: TrainingConfig,
-    pub status: TrainingStatus,
-    pub started_at: Option<String>,
-    pub progress: TrainingProgress,
-    pub loss_history: Vec<EpochMetrics>,
-}
-
-/// Metrics for a single epoch.
-#[derive(Debug, Clone, Serialize, Deserialize)]
-pub struct EpochMetrics {
-    pub epoch: u32,
-    pub train_loss: f64,
-    pub val_loss: f64,
-    pub train_acc: f64,
-    pub val_acc: f64,
-    pub learning_rate: f64,
-    pub timestamp: String,
-}
-
-/// Evaluation metrics.
-#[derive(Debug, Clone, Serialize, Deserialize, Default)]
-pub struct EvaluationMetrics {
-    pub pck_05: f64,
-    pub pck_10: f64,
-    pub pck_20: f64,
-    pub map_50: f64,
-    pub map_75: f64,
-    pub iou: f64,
-}
-
-/// Per-joint accuracy.
-#[derive(Debug, Clone, Serialize, Deserialize)]
-pub struct JointAccuracy {
-    pub joint: String,
-    pub accuracy: f64,
-}
-
-/// RuVector interpolation mode.
-#[derive(Debug, Clone, Serialize, Deserialize, PartialEq, Eq, Default)]
-#[serde(rename_all = "lowercase")]
-pub enum InterpolationMode {
-    Linear,
-    Cubic,
-    #[default]
-    Sparse,
-}
-
-/// RuVector module configuration.
-#[derive(Debug, Clone, Serialize, Deserialize)]
-pub struct RuVectorConfig {
-    // MinCut parameters
-    pub mincut_enabled: bool,
-    pub mincut_threshold: f64,
-    pub mincut_max_persons: u32,
-
-    // Attention parameters
-    pub attention_enabled: bool,
-    pub attention_heads: u32,
-    pub attention_dropout: f64,
-
-    // Temporal parameters
-    pub temporal_enabled: bool,
-    pub temporal_window_ms: u32,
-    pub temporal_compression_ratio: u32,
-
-    // Solver parameters
-    pub solver_enabled: bool,
-    pub solver_interpolation: InterpolationMode,
-    pub solver_subcarrier_count: u32,
-
-    // BVP parameters
-    pub bvp_enabled: bool,
-    pub bvp_filter_hz: (f64, f64),
-}
-
-impl Default for RuVectorConfig {
-    fn default() -> Self {
-        Self {
-            mincut_enabled: true,
-            mincut_threshold: 0.5,
-            mincut_max_persons: 5,
-            attention_enabled: true,
-            attention_heads: 4,
-            attention_dropout: 0.1,
-            temporal_enabled: true,
-            temporal_window_ms: 500,
-            temporal_compression_ratio: 4,
-            solver_enabled: true,
-            solver_interpolation: InterpolationMode::Sparse,
-            solver_subcarrier_count: 56,
-            bvp_enabled: false,
-            bvp_filter_hz: (0.7, 4.0),
-        }
-    }
-}
-
-/// Live test metrics from RuVector processing.
-#[derive(Debug, Clone, Serialize, Deserialize, Default)]
-pub struct LiveTestMetrics {
-    pub fps: f64,
-    pub latency_ms: f64,
-    pub persons_detected: u32,
-}
-
-#[cfg(test)]
-mod tests {
-    use super::*;
-
-    #[test]
-    fn test_gpu_info_default() {
-        let info = GpuInfo::default();
-        assert!(!info.available);
-        assert_eq!(info.backend, GpuBackend::Cpu);
-    }
-
-    #[test]
-    fn test_training_config_default() {
-        let config = TrainingConfig::default();
-        assert_eq!(config.epochs, 100);
-        assert_eq!(config.batch_size, 32);
-        assert_eq!(config.optimizer, OptimizerType::Adam);
-    }
-
-    #[test]
-    fn test_ruvector_config_default() {
-        let config = RuVectorConfig::default();
-        assert!(config.mincut_enabled);
-        assert_eq!(config.mincut_threshold, 0.5);
-        assert_eq!(config.attention_heads, 4);
-    }
-
-    #[test]
-    fn test_serialization() {
-        let config = TrainingConfig::default();
-        let json = serde_json::to_string(&config).unwrap();
-        let parsed: TrainingConfig = serde_json::from_str(&json).unwrap();
-        assert_eq!(parsed.epochs, config.epochs);
-    }
-
-    #[test]
-    fn test_dataset_info() {
-        let dataset = DatasetInfo {
-            id: "mmfi".into(),
-            name: "MM-Fi Dataset".into(),
-            description: "Multi-modal WiFi sensing".into(),
-            format: DatasetFormat::MmFi,
-            size_mb: 2400.0,
-            samples: 320000,
-            downloaded: false,
-            path: None,
-            url: Some("https://example.com/mmfi.zip".into()),
-        };
-        assert_eq!(dataset.id, "mmfi");
-        assert!(!dataset.downloaded);
-    }
-}
@@ -2,7 +2,7 @@ pub mod commands;
 pub mod domain;
 pub mod state;

-use commands::{discovery, flash, ota, provision, server, settings, training, wasm};
+use commands::{discovery, flash, ota, provision, server, settings, wasm};

 pub fn run() {
    tauri::Builder::default()
@@ -46,23 +46,6 @@ pub fn run() {
            // Settings
            settings::get_settings,
            settings::save_settings,
-            // Training
-            training::detect_gpu,
-            training::list_datasets,
-            training::get_datasets,
-            training::download_dataset,
-            training::list_models,
-            training::list_checkpoints,
-            training::export_model,
-            training::start_training,
-            training::stop_training,
-            training::training_progress,
-            training::get_ruvector_config,
-            training::set_ruvector_config,
-            training::test_ruvector_live,
-            training::get_training_history,
-            training::get_evaluation_metrics,
-            training::get_joint_accuracies,
        ])
        .run(tauri::generate_context!())
        .expect("error while running tauri application");
@@ -3,10 +3,6 @@ use std::sync::Mutex;
 use std::time::Instant;

 use crate::domain::node::DiscoveredNode;
-use crate::domain::training::{
-    CheckpointInfo, DatasetInfo, EpochMetrics, EvaluationMetrics,
-    GpuInfo, JointAccuracy, RuVectorConfig, TrainingJob,
-};

 /// Sub-state for discovered nodes.
 #[derive(Default)]
@@ -91,33 +87,6 @@ impl Default for SettingsState {
    }
 }

-/// Sub-state for training operations.
-pub struct TrainingState {
-    pub gpu_info: Option<GpuInfo>,
-    pub datasets: Vec<DatasetInfo>,
-    pub checkpoints: Vec<CheckpointInfo>,
-    pub current_job: Option<TrainingJob>,
-    pub ruvector_config: RuVectorConfig,
-    pub training_history: Vec<EpochMetrics>,
-    pub evaluation_metrics: Option<EvaluationMetrics>,
-    pub joint_accuracies: Vec<JointAccuracy>,
-}
-
-impl Default for TrainingState {
-    fn default() -> Self {
-        Self {
-            gpu_info: None,
-            datasets: Vec::new(),
-            checkpoints: Vec::new(),
-            current_job: None,
-            ruvector_config: RuVectorConfig::default(),
-            training_history: Vec::new(),
-            evaluation_metrics: None,
-            joint_accuracies: Vec::new(),
-        }
-    }
-}
-
 /// Top-level application state managed by Tauri.
 pub struct AppState {
    pub discovery: Mutex<DiscoveryState>,
@@ -125,7 +94,6 @@ pub struct AppState {
    pub flash: Mutex<FlashState>,
    pub ota: Mutex<OtaState>,
    pub settings: Mutex<SettingsState>,
-    pub training: Mutex<TrainingState>,
 }

 impl Default for AppState {
@@ -136,7 +104,6 @@ impl Default for AppState {
            flash: Mutex::new(FlashState::default()),
            ota: Mutex::new(OtaState::default()),
            settings: Mutex::new(SettingsState::default()),
-            training: Mutex::new(TrainingState::default()),
        }
    }
 }
@@ -168,9 +135,6 @@ impl AppState {
        if let Ok(mut settings) = self.settings.lock() {
            *settings = SettingsState::default();
        }
-        if let Ok(mut training) = self.training.lock() {
-            *training = TrainingState::default();
-        }
    }
 }

@@ -1,7 +1,7 @@
 {
  "$schema": "https://raw.githubusercontent.com/tauri-apps/tauri/dev/crates/tauri-config-schema/schema.json",
  "productName": "RuView Desktop",
-  "version": "0.5.0",
+  "version": "0.4.4",
  "identifier": "net.ruv.ruview",
  "build": {
    "frontendDist": "ui/dist",
@@ -1,7 +1,7 @@
 {
  "name": "ruview-desktop-ui",
  "private": true,
-  "version": "0.5.0",
+  "version": "0.4.4",
  "type": "module",
  "scripts": {
    "dev": "vite",
@@ -8,7 +8,6 @@ import { OtaUpdate } from "./pages/OtaUpdate";
 import { EdgeModules } from "./pages/EdgeModules";
 import { Sensing } from "./pages/Sensing";
 import { MeshView } from "./pages/MeshView";
-import Training from "./pages/Training";
 import { Settings } from "./pages/Settings";

 type Page =
@@ -20,7 +19,6 @@ type Page =
  | "wasm"
  | "sensing"
  | "mesh"
-  | "training"
  | "settings";

 interface NavItem {
@@ -38,7 +36,6 @@ const NAV_ITEMS: NavItem[] = [
  { id: "wasm", label: "Edge Modules", icon: "\u2B21" },
  { id: "sensing", label: "Sensing", icon: "\u2248" },
  { id: "mesh", label: "Mesh View", icon: "\u2B2F" },
-  { id: "training", label: "Training", icon: "\u2B50" },
  { id: "settings", label: "Settings", icon: "\u2699" },
 ];

@@ -102,7 +99,6 @@ const App: React.FC = () => {
      case "wasm": return <EdgeModules />;
      case "sensing": return <Sensing />;
      case "mesh": return <MeshView />;
-      case "training": return <Training />;
      case "settings": return <Settings />;
    }
  };
@@ -1,369 +0,0 @@
-import React, { useState, useEffect } from "react";
-import { invoke } from "@tauri-apps/api/core";
-
-interface Dataset {
-  id: string;
-  name: string;
-  description: string;
-  size_mb: number;
-  samples: number;
-  downloaded: boolean;
-  path: string | null;
-}
-
-const STANDARD_DATASETS: Omit<Dataset, "downloaded" | "path">[] = [
-  {
-    id: "mmfi",
-    name: "MM-Fi Dataset",
-    description: "Multi-modal WiFi sensing dataset with 40 subjects, 27 activities",
-    size_mb: 2400,
-    samples: 320000,
-  },
-  {
-    id: "wipose",
-    name: "Wi-Pose Dataset",
-    description: "WiFi-based pose estimation with 3D skeleton annotations",
-    size_mb: 1800,
-    samples: 150000,
-  },
-  {
-    id: "wiar",
-    name: "WiAR Dataset",
-    description: "WiFi activity recognition with CSI data",
-    size_mb: 500,
-    samples: 45000,
-  },
-];
-
-const DatasetsTab: React.FC = () => {
-  const [datasets, setDatasets] = useState<Dataset[]>([]);
-  const [downloading, setDownloading] = useState<string | null>(null);
-  const [downloadProgress, setDownloadProgress] = useState<number>(0);
-  const [error, setError] = useState<string | null>(null);
-
-  useEffect(() => {
-    loadDatasets();
-  }, []);
-
-  const loadDatasets = async () => {
-    try {
-      const downloaded = await invoke<string[]>("list_datasets");
-      const ds = STANDARD_DATASETS.map((d) => ({
-        ...d,
-        downloaded: downloaded.includes(d.id),
-        path: downloaded.includes(d.id) ? `~/.ruview/datasets/${d.id}` : null,
-      }));
-      setDatasets(ds);
-    } catch (err) {
-      // If command not implemented yet, show placeholders
-      setDatasets(
-        STANDARD_DATASETS.map((d) => ({
-          ...d,
-          downloaded: false,
-          path: null,
-        }))
-      );
-    }
-  };
-
-  const handleDownload = async (datasetId: string) => {
-    setDownloading(datasetId);
-    setDownloadProgress(0);
-    setError(null);
-
-    try {
-      // Simulate download progress for now
-      for (let i = 0; i <= 100; i += 10) {
-        setDownloadProgress(i);
-        await new Promise((r) => setTimeout(r, 500));
-      }
-
-      // TODO: Call actual download command
-      // await invoke("download_dataset", { datasetId });
-
-      setDatasets((prev) =>
-        prev.map((d) =>
-          d.id === datasetId
-            ? { ...d, downloaded: true, path: `~/.ruview/datasets/${d.id}` }
-            : d
-        )
-      );
-    } catch (err) {
-      setError(`Download failed: ${err}`);
-    } finally {
-      setDownloading(null);
-    }
-  };
-
-  return (
-    <div>
-      {/* Stats Row */}
-      <div
-        style={{
-          display: "grid",
-          gridTemplateColumns: "repeat(3, 1fr)",
-          gap: "var(--space-4)",
-          marginBottom: "var(--space-5)",
-        }}
-      >
-        <StatCard
-          label="Available Datasets"
-          value={datasets.length}
-        />
-        <StatCard
-          label="Downloaded"
-          value={datasets.filter((d) => d.downloaded).length}
-          color="var(--status-online)"
-        />
-        <StatCard
-          label="Total Samples"
-          value={`${(datasets.reduce((acc, d) => acc + (d.downloaded ? d.samples : 0), 0) / 1000).toFixed(0)}K`}
-        />
-      </div>
-
-      {error && (
-        <div
-          style={{
-            background: "rgba(248, 81, 73, 0.1)",
-            border: "1px solid rgba(248, 81, 73, 0.3)",
-            borderRadius: 6,
-            padding: "var(--space-3)",
-            marginBottom: "var(--space-4)",
-            fontSize: 13,
-            color: "var(--status-error)",
-          }}
-        >
-          {error}
-        </div>
-      )}
-
-      {/* Dataset Cards */}
-      <div
-        style={{
-          display: "grid",
-          gridTemplateColumns: "repeat(auto-fill, minmax(340px, 1fr))",
-          gap: "var(--space-4)",
-        }}
-      >
-        {datasets.map((dataset) => (
-          <div
-            key={dataset.id}
-            className="card"
-            style={{
-              padding: "var(--space-4)",
-              opacity: dataset.downloaded ? 1 : 0.85,
-            }}
-          >
-            <div
-              style={{
-                display: "flex",
-                justifyContent: "space-between",
-                alignItems: "start",
-                marginBottom: "var(--space-3)",
-              }}
-            >
-              <div>
-                <h3 style={{ margin: 0, fontSize: 15, fontWeight: 600 }}>
-                  {dataset.name}
-                </h3>
-                <p
-                  style={{
-                    fontSize: 12,
-                    color: "var(--text-muted)",
-                    marginTop: 4,
-                    lineHeight: 1.4,
-                  }}
-                >
-                  {dataset.description}
-                </p>
-              </div>
-              {dataset.downloaded && (
-                <span
-                  style={{
-                    background: "rgba(63, 185, 80, 0.15)",
-                    color: "var(--status-online)",
-                    padding: "2px 8px",
-                    borderRadius: 4,
-                    fontSize: 10,
-                    fontWeight: 600,
-                  }}
-                >
-                  DOWNLOADED
-                </span>
-              )}
-            </div>
-
-            <div
-              style={{
-                display: "flex",
-                gap: "var(--space-4)",
-                fontSize: 12,
-                color: "var(--text-secondary)",
-                marginBottom: "var(--space-3)",
-              }}
-            >
-              <span>📦 {(dataset.size_mb / 1024).toFixed(1)} GB</span>
-              <span>📊 {(dataset.samples / 1000).toFixed(0)}K samples</span>
-            </div>
-
-            {downloading === dataset.id ? (
-              <div>
-                <div
-                  style={{
-                    height: 4,
-                    background: "var(--border)",
-                    borderRadius: 2,
-                    overflow: "hidden",
-                  }}
-                >
-                  <div
-                    style={{
-                      width: `${downloadProgress}%`,
-                      height: "100%",
-                      background: "var(--accent)",
-                      transition: "width 0.3s",
-                    }}
-                  />
-                </div>
-                <div
-                  style={{
-                    fontSize: 11,
-                    color: "var(--text-muted)",
-                    marginTop: 4,
-                    textAlign: "center",
-                  }}
-                >
-                  Downloading... {downloadProgress}%
-                </div>
-              </div>
-            ) : (
-              <div style={{ display: "flex", gap: "var(--space-2)" }}>
-                {dataset.downloaded ? (
-                  <>
-                    <button
-                      style={{
-                        flex: 1,
-                        padding: "8px 12px",
-                        background: "rgba(56, 139, 253, 0.1)",
-                        border: "1px solid rgba(56, 139, 253, 0.3)",
-                        borderRadius: 6,
-                        color: "var(--accent)",
-                        fontSize: 12,
-                        fontWeight: 600,
-                        cursor: "pointer",
-                      }}
-                    >
-                      Preview
-                    </button>
-                    <button
-                      style={{
-                        padding: "8px 12px",
-                        background: "transparent",
-                        border: "1px solid var(--border)",
-                        borderRadius: 6,
-                        color: "var(--text-secondary)",
-                        fontSize: 12,
-                        fontWeight: 600,
-                        cursor: "pointer",
-                      }}
-                    >
-                      Delete
-                    </button>
-                  </>
-                ) : (
-                  <button
-                    onClick={() => handleDownload(dataset.id)}
-                    className="btn-gradient"
-                    style={{ flex: 1, fontSize: 12 }}
-                  >
-                    Download Dataset
-                  </button>
-                )}
-              </div>
-            )}
-          </div>
-        ))}
-      </div>
-
-      {/* Import Custom Dataset */}
-      <div
-        className="card"
-        style={{
-          marginTop: "var(--space-5)",
-          padding: "var(--space-4)",
-          border: "2px dashed var(--border)",
-          textAlign: "center",
-        }}
-      >
-        <div style={{ fontSize: 32, marginBottom: "var(--space-2)" }}>📁</div>
-        <h4 style={{ margin: 0, fontSize: 14, fontWeight: 600 }}>
-          Import Custom Dataset
-        </h4>
-        <p
-          style={{
-            fontSize: 12,
-            color: "var(--text-muted)",
-            marginTop: 4,
-            marginBottom: "var(--space-3)",
-          }}
-        >
-          Import CSI recordings in CSV, NPZ, or HDF5 format
-        </p>
-        <button
-          style={{
-            padding: "8px 20px",
-            background: "transparent",
-            border: "1px solid var(--border)",
-            borderRadius: 6,
-            color: "var(--text-secondary)",
-            fontSize: 12,
-            fontWeight: 600,
-            cursor: "pointer",
-          }}
-        >
-          Browse Files
-        </button>
-      </div>
-    </div>
-  );
-};
-
-function StatCard({
-  label,
-  value,
-  color,
-}: {
-  label: string;
-  value: number | string;
-  color?: string;
-}) {
-  return (
-    <div className="card-glow" style={{ padding: "var(--space-4)" }}>
-      <div
-        style={{
-          fontSize: 10,
-          textTransform: "uppercase",
-          letterSpacing: "0.06em",
-          color: "var(--text-muted)",
-          marginBottom: "var(--space-2)",
-          fontWeight: 600,
-        }}
-      >
-        {label}
-      </div>
-      <div
-        style={{
-          fontFamily: "var(--font-mono)",
-          fontSize: 28,
-          fontWeight: 600,
-          color: color || "var(--text-primary)",
-          letterSpacing: "-0.02em",
-        }}
-      >
-        {value}
-      </div>
-    </div>
-  );
-}
-
-export default DatasetsTab;
@@ -1,609 +0,0 @@
-import React, { useState, useEffect } from "react";
-import { invoke } from "@tauri-apps/api/core";
-
-interface TrainingMetrics {
-  epoch: number;
-  train_loss: number;
-  val_loss: number;
-  train_acc: number;
-  val_acc: number;
-  learning_rate: number;
-  timestamp: string;
-}
-
-interface EvaluationMetrics {
-  pck_05: number;
-  pck_10: number;
-  pck_20: number;
-  map_50: number;
-  map_75: number;
-  iou: number;
-}
-
-interface JointAccuracy {
-  joint: string;
-  accuracy: number;
-}
-
-const JOINT_NAMES = [
-  "nose",
-  "left_eye",
-  "right_eye",
-  "left_ear",
-  "right_ear",
-  "left_shoulder",
-  "right_shoulder",
-  "left_elbow",
-  "right_elbow",
-  "left_wrist",
-  "right_wrist",
-  "left_hip",
-  "right_hip",
-  "left_knee",
-  "right_knee",
-  "left_ankle",
-  "right_ankle",
-];
-
-const MetricsTab: React.FC = () => {
-  const [trainingHistory, setTrainingHistory] = useState<TrainingMetrics[]>([]);
-  const [evaluation, setEvaluation] = useState<EvaluationMetrics | null>(null);
-  const [jointAccuracies, setJointAccuracies] = useState<JointAccuracy[]>([]);
-  const [selectedMetric, setSelectedMetric] = useState<"loss" | "accuracy">("loss");
-  const [exporting, setExporting] = useState(false);
-
-  useEffect(() => {
-    loadMetrics();
-  }, []);
-
-  const loadMetrics = async () => {
-    try {
-      const metrics = await invoke<TrainingMetrics[]>("get_training_history");
-      setTrainingHistory(metrics);
-      const evalMetrics = await invoke<EvaluationMetrics>("get_evaluation_metrics");
-      setEvaluation(evalMetrics);
-      const joints = await invoke<JointAccuracy[]>("get_joint_accuracies");
-      setJointAccuracies(joints);
-    } catch (err) {
-      // Generate mock data for demonstration
-      const mockHistory: TrainingMetrics[] = [];
-      for (let i = 1; i <= 50; i++) {
-        mockHistory.push({
-          epoch: i,
-          train_loss: 0.5 * Math.exp(-i / 20) + 0.02 + Math.random() * 0.01,
-          val_loss: 0.55 * Math.exp(-i / 18) + 0.025 + Math.random() * 0.015,
-          train_acc: 1 - 0.5 * Math.exp(-i / 15) - Math.random() * 0.02,
-          val_acc: 1 - 0.55 * Math.exp(-i / 15) - Math.random() * 0.025,
-          learning_rate: 0.001 * Math.pow(0.95, Math.floor(i / 10)),
-          timestamp: new Date(Date.now() - (50 - i) * 60000).toISOString(),
-        });
-      }
-      setTrainingHistory(mockHistory);
-
-      setEvaluation({
-        pck_05: 0.72,
-        pck_10: 0.89,
-        pck_20: 0.96,
-        map_50: 0.84,
-        map_75: 0.71,
-        iou: 0.78,
-      });
-
-      setJointAccuracies(
-        JOINT_NAMES.map((joint) => ({
-          joint,
-          accuracy: 0.7 + Math.random() * 0.25,
-        }))
-      );
-    }
-  };
-
-  const exportMetrics = async (format: "csv" | "json" | "tensorboard") => {
-    setExporting(true);
-    try {
-      if (format === "json") {
-        const data = {
-          training: trainingHistory,
-          evaluation,
-          joints: jointAccuracies,
-        };
-        const blob = new Blob([JSON.stringify(data, null, 2)], { type: "application/json" });
-        downloadBlob(blob, "metrics.json");
-      } else if (format === "csv") {
-        const headers = "epoch,train_loss,val_loss,train_acc,val_acc,learning_rate\n";
-        const rows = trainingHistory
-          .map(
-            (m) =>
-              `${m.epoch},${m.train_loss.toFixed(6)},${m.val_loss.toFixed(6)},${m.train_acc.toFixed(4)},${m.val_acc.toFixed(4)},${m.learning_rate.toExponential(2)}`
-          )
-          .join("\n");
-        const blob = new Blob([headers + rows], { type: "text/csv" });
-        downloadBlob(blob, "training_history.csv");
-      } else {
-        // TensorBoard format would require server-side handling
-        alert("TensorBoard export requires running the backend server");
-      }
-    } finally {
-      setExporting(false);
-    }
-  };
-
-  const downloadBlob = (blob: Blob, filename: string) => {
-    const url = URL.createObjectURL(blob);
-    const a = document.createElement("a");
-    a.href = url;
-    a.download = filename;
-    a.click();
-    URL.revokeObjectURL(url);
-  };
-
-  const maxLoss = Math.max(
-    ...trainingHistory.map((m) => Math.max(m.train_loss, m.val_loss)),
-    0.1
-  );
-
-  return (
-    <div>
-      {/* Summary Stats */}
-      <div
-        style={{
-          display: "grid",
-          gridTemplateColumns: "repeat(4, 1fr)",
-          gap: "var(--space-4)",
-          marginBottom: "var(--space-5)",
-        }}
-      >
-        <StatCard
-          label="Epochs Trained"
-          value={trainingHistory.length}
-        />
-        <StatCard
-          label="Best Val Loss"
-          value={
-            trainingHistory.length > 0
-              ? Math.min(...trainingHistory.map((m) => m.val_loss)).toFixed(4)
-              : "—"
-          }
-          color="var(--status-online)"
-        />
-        <StatCard
-          label="Best Val Acc"
-          value={
-            trainingHistory.length > 0
-              ? `${(Math.max(...trainingHistory.map((m) => m.val_acc)) * 100).toFixed(1)}%`
-              : "—"
-          }
-          color="var(--accent)"
-        />
-        <StatCard
-          label="PCK@0.1"
-          value={evaluation ? `${(evaluation.pck_10 * 100).toFixed(1)}%` : "—"}
-        />
-      </div>
-
-      <div style={{ display: "grid", gridTemplateColumns: "2fr 1fr", gap: "var(--space-5)" }}>
-        {/* Loss/Accuracy Charts */}
-        <div className="card" style={{ padding: "var(--space-4)" }}>
-          <div
-            style={{
-              display: "flex",
-              justifyContent: "space-between",
-              alignItems: "center",
-              marginBottom: "var(--space-4)",
-            }}
-          >
-            <h3 style={{ margin: 0, fontSize: 14, fontWeight: 600 }}>Training Curves</h3>
-            <div style={{ display: "flex", gap: "var(--space-2)" }}>
-              <button
-                onClick={() => setSelectedMetric("loss")}
-                style={{
-                  padding: "6px 12px",
-                  background: selectedMetric === "loss" ? "var(--accent)" : "transparent",
-                  border: `1px solid ${selectedMetric === "loss" ? "var(--accent)" : "var(--border)"}`,
-                  borderRadius: 4,
-                  color: selectedMetric === "loss" ? "white" : "var(--text-secondary)",
-                  fontSize: 11,
-                  fontWeight: 600,
-                  cursor: "pointer",
-                }}
-              >
-                Loss
-              </button>
-              <button
-                onClick={() => setSelectedMetric("accuracy")}
-                style={{
-                  padding: "6px 12px",
-                  background: selectedMetric === "accuracy" ? "var(--accent)" : "transparent",
-                  border: `1px solid ${selectedMetric === "accuracy" ? "var(--accent)" : "var(--border)"}`,
-                  borderRadius: 4,
-                  color: selectedMetric === "accuracy" ? "white" : "var(--text-secondary)",
-                  fontSize: 11,
-                  fontWeight: 600,
-                  cursor: "pointer",
-                }}
-              >
-                Accuracy
-              </button>
-            </div>
-          </div>
-
-          {/* Chart Area */}
-          <div
-            style={{
-              height: 250,
-              position: "relative",
-              background: "var(--bg-secondary)",
-              borderRadius: 8,
-              padding: "var(--space-3)",
-            }}
-          >
-            {trainingHistory.length === 0 ? (
-              <div
-                style={{
-                  display: "flex",
-                  flexDirection: "column",
-                  alignItems: "center",
-                  justifyContent: "center",
-                  height: "100%",
-                  color: "var(--text-muted)",
-                }}
-              >
-                <span style={{ fontSize: 32 }}>📊</span>
-                <p style={{ fontSize: 13, marginTop: "var(--space-2)" }}>
-                  No training data yet
-                </p>
-              </div>
-            ) : (
-              <svg width="100%" height="100%" viewBox="0 0 500 200" preserveAspectRatio="none">
-                {/* Grid lines */}
-                {[0, 0.25, 0.5, 0.75, 1].map((y) => (
-                  <line
-                    key={y}
-                    x1="0"
-                    y1={y * 180}
-                    x2="500"
-                    y2={y * 180}
-                    stroke="var(--border)"
-                    strokeWidth="0.5"
-                    strokeDasharray="4"
-                  />
-                ))}
-
-                {/* Train line */}
-                <polyline
-                  fill="none"
-                  stroke="var(--accent)"
-                  strokeWidth="2"
-                  points={trainingHistory
-                    .map((m, i) => {
-                      const x = (i / (trainingHistory.length - 1)) * 500;
-                      const value = selectedMetric === "loss" ? m.train_loss : m.train_acc;
-                      const y =
-                        selectedMetric === "loss"
-                          ? (value / maxLoss) * 180
-                          : (1 - value) * 180;
-                      return `${x},${y}`;
-                    })
-                    .join(" ")}
-                />
-
-                {/* Val line */}
-                <polyline
-                  fill="none"
-                  stroke="var(--status-online)"
-                  strokeWidth="2"
-                  points={trainingHistory
-                    .map((m, i) => {
-                      const x = (i / (trainingHistory.length - 1)) * 500;
-                      const value = selectedMetric === "loss" ? m.val_loss : m.val_acc;
-                      const y =
-                        selectedMetric === "loss"
-                          ? (value / maxLoss) * 180
-                          : (1 - value) * 180;
-                      return `${x},${y}`;
-                    })
-                    .join(" ")}
-                />
-              </svg>
-            )}
-
-            {/* Legend */}
-            <div
-              style={{
-                position: "absolute",
-                top: "var(--space-2)",
-                right: "var(--space-2)",
-                display: "flex",
-                gap: "var(--space-3)",
-                fontSize: 11,
-              }}
-            >
-              <span style={{ display: "flex", alignItems: "center", gap: 4 }}>
-                <span
-                  style={{
-                    width: 12,
-                    height: 3,
-                    background: "var(--accent)",
-                    borderRadius: 2,
-                  }}
-                />
-                Train
-              </span>
-              <span style={{ display: "flex", alignItems: "center", gap: 4 }}>
-                <span
-                  style={{
-                    width: 12,
-                    height: 3,
-                    background: "var(--status-online)",
-                    borderRadius: 2,
-                  }}
-                />
-                Validation
-              </span>
-            </div>
-          </div>
-        </div>
-
-        {/* Evaluation Metrics */}
-        <div className="card" style={{ padding: "var(--space-4)" }}>
-          <h3 style={{ margin: 0, fontSize: 14, fontWeight: 600, marginBottom: "var(--space-4)" }}>
-            Evaluation Metrics
-          </h3>
-
-          {!evaluation ? (
-            <div
-              style={{
-                display: "flex",
-                flexDirection: "column",
-                alignItems: "center",
-                justifyContent: "center",
-                height: 200,
-                color: "var(--text-muted)",
-              }}
-            >
-              <span style={{ fontSize: 32 }}>📏</span>
-              <p style={{ fontSize: 13, marginTop: "var(--space-2)" }}>
-                Run evaluation to see metrics
-              </p>
-            </div>
-          ) : (
-            <div style={{ display: "flex", flexDirection: "column", gap: "var(--space-3)" }}>
-              <MetricBar label="PCK@0.05" value={evaluation.pck_05} color="#f59e0b" />
-              <MetricBar label="PCK@0.10" value={evaluation.pck_10} color="var(--accent)" />
-              <MetricBar label="PCK@0.20" value={evaluation.pck_20} color="var(--status-online)" />
-              <div style={{ height: 1, background: "var(--border)", margin: "var(--space-2) 0" }} />
-              <MetricBar label="mAP@0.50" value={evaluation.map_50} color="#a855f7" />
-              <MetricBar label="mAP@0.75" value={evaluation.map_75} color="#ec4899" />
-              <MetricBar label="IoU" value={evaluation.iou} color="#06b6d4" />
-            </div>
-          )}
-        </div>
-      </div>
-
-      {/* Joint-wise Accuracy */}
-      <div className="card" style={{ marginTop: "var(--space-5)", padding: "var(--space-4)" }}>
-        <h3 style={{ margin: 0, fontSize: 14, fontWeight: 600, marginBottom: "var(--space-4)" }}>
-          Per-Joint Accuracy
-        </h3>
-
-        {jointAccuracies.length === 0 ? (
-          <div
-            style={{
-              textAlign: "center",
-              padding: "var(--space-5)",
-              color: "var(--text-muted)",
-            }}
-          >
-            No joint accuracy data available
-          </div>
-        ) : (
-          <div
-            style={{
-              display: "grid",
-              gridTemplateColumns: "repeat(auto-fill, minmax(140px, 1fr))",
-              gap: "var(--space-3)",
-            }}
-          >
-            {jointAccuracies.map((ja) => (
-              <div
-                key={ja.joint}
-                style={{
-                  padding: "var(--space-3)",
-                  background: "var(--bg-secondary)",
-                  borderRadius: 6,
-                  textAlign: "center",
-                }}
-              >
-                <div
-                  style={{
-                    fontSize: 11,
-                    color: "var(--text-muted)",
-                    marginBottom: 4,
-                    textTransform: "capitalize",
-                  }}
-                >
-                  {ja.joint.replace("_", " ")}
-                </div>
-                <div
-                  style={{
-                    fontFamily: "var(--font-mono)",
-                    fontSize: 18,
-                    fontWeight: 600,
-                    color:
-                      ja.accuracy > 0.9
-                        ? "var(--status-online)"
-                        : ja.accuracy > 0.8
-                          ? "var(--accent)"
-                          : ja.accuracy > 0.7
-                            ? "#f59e0b"
-                            : "var(--status-error)",
-                  }}
-                >
-                  {(ja.accuracy * 100).toFixed(1)}%
-                </div>
-              </div>
-            ))}
-          </div>
-        )}
-      </div>
-
-      {/* Export Section */}
-      <div
-        className="card"
-        style={{
-          marginTop: "var(--space-5)",
-          padding: "var(--space-4)",
-          display: "flex",
-          justifyContent: "space-between",
-          alignItems: "center",
-        }}
-      >
-        <div>
-          <h3 style={{ margin: 0, fontSize: 14, fontWeight: 600 }}>Export Metrics</h3>
-          <p style={{ fontSize: 12, color: "var(--text-muted)", marginTop: 4 }}>
-            Download training history and evaluation results
-          </p>
-        </div>
-        <div style={{ display: "flex", gap: "var(--space-2)" }}>
-          <button
-            onClick={() => exportMetrics("csv")}
-            disabled={exporting || trainingHistory.length === 0}
-            style={{
-              padding: "8px 16px",
-              background: "rgba(56, 139, 253, 0.1)",
-              border: "1px solid rgba(56, 139, 253, 0.3)",
-              borderRadius: 6,
-              color: "var(--accent)",
-              fontSize: 12,
-              fontWeight: 600,
-              cursor: trainingHistory.length === 0 ? "not-allowed" : "pointer",
-              opacity: trainingHistory.length === 0 ? 0.5 : 1,
-            }}
-          >
-            CSV
-          </button>
-          <button
-            onClick={() => exportMetrics("json")}
-            disabled={exporting || trainingHistory.length === 0}
-            style={{
-              padding: "8px 16px",
-              background: "rgba(56, 139, 253, 0.1)",
-              border: "1px solid rgba(56, 139, 253, 0.3)",
-              borderRadius: 6,
-              color: "var(--accent)",
-              fontSize: 12,
-              fontWeight: 600,
-              cursor: trainingHistory.length === 0 ? "not-allowed" : "pointer",
-              opacity: trainingHistory.length === 0 ? 0.5 : 1,
-            }}
-          >
-            JSON
-          </button>
-          <button
-            onClick={() => exportMetrics("tensorboard")}
-            disabled={exporting || trainingHistory.length === 0}
-            style={{
-              padding: "8px 16px",
-              background: "transparent",
-              border: "1px solid var(--border)",
-              borderRadius: 6,
-              color: "var(--text-secondary)",
-              fontSize: 12,
-              fontWeight: 600,
-              cursor: trainingHistory.length === 0 ? "not-allowed" : "pointer",
-              opacity: trainingHistory.length === 0 ? 0.5 : 1,
-            }}
-          >
-            TensorBoard
-          </button>
-        </div>
-      </div>
-    </div>
-  );
-};
-
-function StatCard({
-  label,
-  value,
-  color,
-}: {
-  label: string;
-  value: number | string;
-  color?: string;
-}) {
-  return (
-    <div className="card-glow" style={{ padding: "var(--space-4)" }}>
-      <div
-        style={{
-          fontSize: 10,
-          textTransform: "uppercase",
-          letterSpacing: "0.06em",
-          color: "var(--text-muted)",
-          marginBottom: "var(--space-2)",
-          fontWeight: 600,
-        }}
-      >
-        {label}
-      </div>
-      <div
-        style={{
-          fontFamily: "var(--font-mono)",
-          fontSize: 28,
-          fontWeight: 600,
-          color: color || "var(--text-primary)",
-          letterSpacing: "-0.02em",
-        }}
-      >
-        {value}
-      </div>
-    </div>
-  );
-}
-
-function MetricBar({
-  label,
-  value,
-  color,
-}: {
-  label: string;
-  value: number;
-  color: string;
-}) {
-  return (
-    <div>
-      <div
-        style={{
-          display: "flex",
-          justifyContent: "space-between",
-          fontSize: 12,
-          marginBottom: 4,
-        }}
-      >
-        <span>{label}</span>
-        <span style={{ fontFamily: "var(--font-mono)", fontWeight: 600 }}>
-          {(value * 100).toFixed(1)}%
-        </span>
-      </div>
-      <div
-        style={{
-          height: 6,
-          background: "var(--bg-secondary)",
-          borderRadius: 3,
-          overflow: "hidden",
-        }}
-      >
-        <div
-          style={{
-            width: `${value * 100}%`,
-            height: "100%",
-            background: color,
-            borderRadius: 3,
-            transition: "width 0.5s",
-          }}
-        />
-      </div>
-    </div>
-  );
-}
-
-export default MetricsTab;
@@ -1,405 +0,0 @@
-import React, { useState, useEffect } from "react";
-import { invoke } from "@tauri-apps/api/core";
-
-interface ModelArchitecture {
-  id: string;
-  name: string;
-  type: "encoder" | "decoder" | "embedding" | "adaptor";
-  description: string;
-  params_m: number;
-  memory_mb: number;
-  paper?: string;
-}
-
-interface Checkpoint {
-  id: string;
-  model_id: string;
-  name: string;
-  epoch: number;
-  val_loss: number;
-  created_at: string;
-  path: string;
-  size_mb: number;
-}
-
-const MODEL_ARCHITECTURES: ModelArchitecture[] = [
-  {
-    id: "csi-encoder-cnn",
-    name: "CSI Encoder (CNN)",
-    type: "encoder",
-    description: "Convolutional encoder for CSI amplitude/phase features",
-    params_m: 2.3,
-    memory_mb: 128,
-  },
-  {
-    id: "csi-encoder-transformer",
-    name: "CSI Encoder (Transformer)",
-    type: "encoder",
-    description: "Self-attention based CSI feature extraction",
-    params_m: 8.5,
-    memory_mb: 384,
-    paper: "WiFi-ViT 2024",
-  },
-  {
-    id: "pose-decoder-lstm",
-    name: "Pose Decoder (LSTM)",
-    type: "decoder",
-    description: "Recurrent decoder for temporal pose estimation",
-    params_m: 1.8,
-    memory_mb: 96,
-  },
-  {
-    id: "pose-decoder-gru",
-    name: "Pose Decoder (GRU)",
-    type: "decoder",
-    description: "Gated recurrent unit pose decoder (faster)",
-    params_m: 1.2,
-    memory_mb: 64,
-  },
-  {
-    id: "aether-embedding",
-    name: "AETHER Embedding",
-    type: "embedding",
-    description: "Contrastive CSI embedding for person re-identification (ADR-024)",
-    params_m: 4.2,
-    memory_mb: 192,
-    paper: "AETHER 2025",
-  },
-  {
-    id: "meridian-adaptor",
-    name: "MERIDIAN Adaptor",
-    type: "adaptor",
-    description: "Cross-environment domain generalization module (ADR-027)",
-    params_m: 3.1,
-    memory_mb: 144,
-    paper: "MERIDIAN 2025",
-  },
-];
-
-const ModelsTab: React.FC = () => {
-  const [checkpoints, setCheckpoints] = useState<Checkpoint[]>([]);
-  const [selectedModel, setSelectedModel] = useState<string | null>(null);
-  const [exporting, setExporting] = useState<string | null>(null);
-  const [error, setError] = useState<string | null>(null);
-
-  useEffect(() => {
-    loadCheckpoints();
-  }, []);
-
-  const loadCheckpoints = async () => {
-    try {
-      const loaded = await invoke<Checkpoint[]>("list_checkpoints");
-      setCheckpoints(loaded);
-    } catch (err) {
-      // Mock data if command not implemented
-      setCheckpoints([
-        {
-          id: "ckpt-001",
-          model_id: "csi-encoder-cnn",
-          name: "CSI-CNN v1.2",
-          epoch: 50,
-          val_loss: 0.0234,
-          created_at: "2026-03-08T14:30:00Z",
-          path: "~/.ruview/models/csi-cnn-v1.2.pt",
-          size_mb: 12.4,
-        },
-        {
-          id: "ckpt-002",
-          model_id: "pose-decoder-gru",
-          name: "Pose-GRU v2.0",
-          epoch: 100,
-          val_loss: 0.0189,
-          created_at: "2026-03-09T09:15:00Z",
-          path: "~/.ruview/models/pose-gru-v2.pt",
-          size_mb: 8.2,
-        },
-      ]);
-    }
-  };
-
-  const handleExport = async (checkpointId: string, format: "onnx" | "torchscript") => {
-    setExporting(checkpointId);
-    setError(null);
-    try {
-      await invoke("export_model", { checkpointId, format });
-      // Success notification would go here
-    } catch (err) {
-      setError(`Export failed: ${err}`);
-    } finally {
-      setExporting(null);
-    }
-  };
-
-  const getTypeColor = (type: ModelArchitecture["type"]) => {
-    switch (type) {
-      case "encoder":
-        return "var(--accent)";
-      case "decoder":
-        return "var(--status-online)";
-      case "embedding":
-        return "#a855f7";
-      case "adaptor":
-        return "#f59e0b";
-    }
-  };
-
-  return (
-    <div>
-      {/* Stats Row */}
-      <div
-        style={{
-          display: "grid",
-          gridTemplateColumns: "repeat(4, 1fr)",
-          gap: "var(--space-4)",
-          marginBottom: "var(--space-5)",
-        }}
-      >
-        <StatCard label="Architectures" value={MODEL_ARCHITECTURES.length} />
-        <StatCard
-          label="Checkpoints"
-          value={checkpoints.length}
-          color="var(--status-online)"
-        />
-        <StatCard
-          label="Total Params"
-          value={`${MODEL_ARCHITECTURES.reduce((acc, m) => acc + m.params_m, 0).toFixed(1)}M`}
-        />
-        <StatCard
-          label="Storage Used"
-          value={`${checkpoints.reduce((acc, c) => acc + c.size_mb, 0).toFixed(1)} MB`}
-        />
-      </div>
-
-      {error && (
-        <div
-          style={{
-            background: "rgba(248, 81, 73, 0.1)",
-            border: "1px solid rgba(248, 81, 73, 0.3)",
-            borderRadius: 6,
-            padding: "var(--space-3)",
-            marginBottom: "var(--space-4)",
-            fontSize: 13,
-            color: "var(--status-error)",
-          }}
-        >
-          {error}
-        </div>
-      )}
-
-      {/* Model Architectures */}
-      <h3 style={{ fontSize: 14, fontWeight: 600, marginBottom: "var(--space-3)" }}>
-        Available Architectures
-      </h3>
-      <div
-        style={{
-          display: "grid",
-          gridTemplateColumns: "repeat(auto-fill, minmax(300px, 1fr))",
-          gap: "var(--space-3)",
-          marginBottom: "var(--space-5)",
-        }}
-      >
-        {MODEL_ARCHITECTURES.map((model) => (
-          <div
-            key={model.id}
-            className="card"
-            style={{
-              padding: "var(--space-3)",
-              cursor: "pointer",
-              border:
-                selectedModel === model.id
-                  ? "1px solid var(--accent)"
-                  : "1px solid transparent",
-            }}
-            onClick={() => setSelectedModel(model.id)}
-          >
-            <div
-              style={{
-                display: "flex",
-                justifyContent: "space-between",
-                alignItems: "start",
-                marginBottom: "var(--space-2)",
-              }}
-            >
-              <div>
-                <h4 style={{ margin: 0, fontSize: 14, fontWeight: 600 }}>
-                  {model.name}
-                </h4>
-                <span
-                  style={{
-                    display: "inline-block",
-                    marginTop: 4,
-                    padding: "1px 6px",
-                    borderRadius: 3,
-                    fontSize: 10,
-                    fontWeight: 600,
-                    textTransform: "uppercase",
-                    background: `${getTypeColor(model.type)}20`,
-                    color: getTypeColor(model.type),
-                  }}
-                >
-                  {model.type}
-                </span>
-              </div>
-              {model.paper && (
-                <span
-                  style={{
-                    fontSize: 10,
-                    color: "var(--text-muted)",
-                    fontStyle: "italic",
-                  }}
-                >
-                  {model.paper}
-                </span>
-              )}
-            </div>
-            <p
-              style={{
-                fontSize: 11,
-                color: "var(--text-muted)",
-                margin: "var(--space-2) 0",
-                lineHeight: 1.4,
-              }}
-            >
-              {model.description}
-            </p>
-            <div
-              style={{
-                display: "flex",
-                gap: "var(--space-3)",
-                fontSize: 11,
-                color: "var(--text-secondary)",
-              }}
-            >
-              <span>🧮 {model.params_m}M params</span>
-              <span>💾 {model.memory_mb} MB</span>
-            </div>
-          </div>
-        ))}
-      </div>
-
-      {/* Checkpoints */}
-      <h3 style={{ fontSize: 14, fontWeight: 600, marginBottom: "var(--space-3)" }}>
-        Saved Checkpoints
-      </h3>
-      {checkpoints.length === 0 ? (
-        <div
-          className="card"
-          style={{
-            padding: "var(--space-5)",
-            textAlign: "center",
-            color: "var(--text-muted)",
-          }}
-        >
-          <div style={{ fontSize: 32, marginBottom: "var(--space-2)" }}>📦</div>
-          <p style={{ fontSize: 13 }}>No checkpoints saved yet</p>
-          <p style={{ fontSize: 12 }}>Train a model to create checkpoints</p>
-        </div>
-      ) : (
-        <div style={{ display: "flex", flexDirection: "column", gap: "var(--space-2)" }}>
-          {checkpoints.map((ckpt) => (
-            <div
-              key={ckpt.id}
-              className="card"
-              style={{
-                padding: "var(--space-3)",
-                display: "flex",
-                justifyContent: "space-between",
-                alignItems: "center",
-              }}
-            >
-              <div>
-                <div style={{ fontWeight: 600, fontSize: 13 }}>{ckpt.name}</div>
-                <div
-                  style={{
-                    fontSize: 11,
-                    color: "var(--text-muted)",
-                    marginTop: 2,
-                  }}
-                >
-                  Epoch {ckpt.epoch} • Val Loss: {ckpt.val_loss.toFixed(4)} •{" "}
-                  {ckpt.size_mb.toFixed(1)} MB
-                </div>
-              </div>
-              <div style={{ display: "flex", gap: "var(--space-2)" }}>
-                <button
-                  onClick={() => handleExport(ckpt.id, "onnx")}
-                  disabled={exporting === ckpt.id}
-                  style={{
-                    padding: "6px 12px",
-                    background: "rgba(56, 139, 253, 0.1)",
-                    border: "1px solid rgba(56, 139, 253, 0.3)",
-                    borderRadius: 4,
-                    color: "var(--accent)",
-                    fontSize: 11,
-                    fontWeight: 600,
-                    cursor: exporting === ckpt.id ? "wait" : "pointer",
-                    opacity: exporting === ckpt.id ? 0.6 : 1,
-                  }}
-                >
-                  {exporting === ckpt.id ? "Exporting..." : "ONNX"}
-                </button>
-                <button
-                  onClick={() => handleExport(ckpt.id, "torchscript")}
-                  disabled={exporting === ckpt.id}
-                  style={{
-                    padding: "6px 12px",
-                    background: "transparent",
-                    border: "1px solid var(--border)",
-                    borderRadius: 4,
-                    color: "var(--text-secondary)",
-                    fontSize: 11,
-                    fontWeight: 600,
-                    cursor: exporting === ckpt.id ? "wait" : "pointer",
-                    opacity: exporting === ckpt.id ? 0.6 : 1,
-                  }}
-                >
-                  TorchScript
-                </button>
-              </div>
-            </div>
-          ))}
-        </div>
-      )}
-    </div>
-  );
-};
-
-function StatCard({
-  label,
-  value,
-  color,
-}: {
-  label: string;
-  value: number | string;
-  color?: string;
-}) {
-  return (
-    <div className="card-glow" style={{ padding: "var(--space-4)" }}>
-      <div
-        style={{
-          fontSize: 10,
-          textTransform: "uppercase",
-          letterSpacing: "0.06em",
-          color: "var(--text-muted)",
-          marginBottom: "var(--space-2)",
-          fontWeight: 600,
-        }}
-      >
-        {label}
-      </div>
-      <div
-        style={{
-          fontFamily: "var(--font-mono)",
-          fontSize: 28,
-          fontWeight: 600,
-          color: color || "var(--text-primary)",
-          letterSpacing: "-0.02em",
-        }}
-      >
-        {value}
-      </div>
-    </div>
-  );
-}
-
-export default ModelsTab;
@@ -1,767 +0,0 @@
-import React, { useState, useEffect } from "react";
-import { invoke } from "@tauri-apps/api/core";
-
-interface RuVectorConfig {
-  // MinCut Parameters
-  mincut_enabled: boolean;
-  mincut_threshold: number;
-  mincut_max_persons: number;
-
-  // Attention Parameters
-  attention_enabled: boolean;
-  attention_heads: number;
-  attention_dropout: number;
-
-  // Temporal Parameters
-  temporal_enabled: boolean;
-  temporal_window_ms: number;
-  temporal_compression_ratio: number;
-
-  // Solver Parameters
-  solver_enabled: boolean;
-  solver_interpolation: "linear" | "cubic" | "sparse";
-  solver_subcarrier_count: number;
-
-  // BVP Parameters
-  bvp_enabled: boolean;
-  bvp_filter_hz: [number, number];
-}
-
-const DEFAULT_CONFIG: RuVectorConfig = {
-  mincut_enabled: true,
-  mincut_threshold: 0.5,
-  mincut_max_persons: 5,
-  attention_enabled: true,
-  attention_heads: 4,
-  attention_dropout: 0.1,
-  temporal_enabled: true,
-  temporal_window_ms: 500,
-  temporal_compression_ratio: 4,
-  solver_enabled: true,
-  solver_interpolation: "sparse",
-  solver_subcarrier_count: 56,
-  bvp_enabled: false,
-  bvp_filter_hz: [0.7, 4.0],
-};
-
-const MODULES = [
-  {
-    id: "mincut",
-    name: "MinCut Segmentation",
-    crate: "ruvector-mincut",
-    description: "Graph-based person segmentation using DynamicPersonMatcher",
-    icon: "✂️",
-  },
-  {
-    id: "attention",
-    name: "Spatial Attention",
-    crate: "ruvector-attention",
-    description: "Attention-weighted antenna selection and BVP extraction",
-    icon: "🎯",
-  },
-  {
-    id: "temporal",
-    name: "Temporal Tensor",
-    crate: "ruvector-temporal-tensor",
-    description: "Temporal CSI compression and breathing detection",
-    icon: "⏱️",
-  },
-  {
-    id: "solver",
-    name: "Sparse Solver",
-    crate: "ruvector-solver",
-    description: "Sparse interpolation (114→56 subcarriers) and triangulation",
-    icon: "🧮",
-  },
-  {
-    id: "attn-mincut",
-    name: "Attention MinCut",
-    crate: "ruvector-attn-mincut",
-    description: "Combined attention-weighted graph segmentation",
-    icon: "🔀",
-  },
-];
-
-const RuVectorTab: React.FC = () => {
-  const [config, setConfig] = useState<RuVectorConfig>(DEFAULT_CONFIG);
-  const [testingLive, setTestingLive] = useState(false);
-  const [liveMetrics, setLiveMetrics] = useState<{
-    fps: number;
-    latency_ms: number;
-    persons_detected: number;
-  } | null>(null);
-  const [saved, setSaved] = useState(true);
-  const [error, setError] = useState<string | null>(null);
-
-  useEffect(() => {
-    loadConfig();
-  }, []);
-
-  const loadConfig = async () => {
-    try {
-      const loaded = await invoke<RuVectorConfig>("get_ruvector_config");
-      setConfig(loaded);
-    } catch (err) {
-      // Use defaults if not implemented
-    }
-  };
-
-  const saveConfig = async () => {
-    setError(null);
-    try {
-      await invoke("set_ruvector_config", { config });
-      setSaved(true);
-    } catch (err) {
-      setError(`Failed to save: ${err}`);
-    }
-  };
-
-  const handleChange = <K extends keyof RuVectorConfig>(
-    key: K,
-    value: RuVectorConfig[K]
-  ) => {
-    setConfig((prev) => ({ ...prev, [key]: value }));
-    setSaved(false);
-  };
-
-  const startLiveTest = async () => {
-    setTestingLive(true);
-    setError(null);
-    try {
-      // Simulate live testing metrics
-      const interval = setInterval(() => {
-        setLiveMetrics({
-          fps: 25 + Math.random() * 10,
-          latency_ms: 15 + Math.random() * 10,
-          persons_detected: Math.floor(Math.random() * 3) + 1,
-        });
-      }, 500);
-
-      // Stop after 10 seconds for demo
-      setTimeout(() => {
-        clearInterval(interval);
-        setTestingLive(false);
-        setLiveMetrics(null);
-      }, 10000);
-    } catch (err) {
-      setError(`Live test failed: ${err}`);
-      setTestingLive(false);
-    }
-  };
-
-  const exportConfig = () => {
-    const blob = new Blob([JSON.stringify(config, null, 2)], {
-      type: "application/json",
-    });
-    const url = URL.createObjectURL(blob);
-    const a = document.createElement("a");
-    a.href = url;
-    a.download = "ruvector-config.json";
-    a.click();
-    URL.revokeObjectURL(url);
-  };
-
-  return (
-    <div>
-      {/* Module Cards */}
-      <div
-        style={{
-          display: "grid",
-          gridTemplateColumns: "repeat(auto-fill, minmax(200px, 1fr))",
-          gap: "var(--space-3)",
-          marginBottom: "var(--space-5)",
-        }}
-      >
-        {MODULES.map((mod) => {
-          const isEnabled =
-            config[`${mod.id.replace("-", "_")}_enabled` as keyof RuVectorConfig] ?? true;
-          return (
-            <div
-              key={mod.id}
-              className="card"
-              style={{
-                padding: "var(--space-3)",
-                opacity: isEnabled ? 1 : 0.5,
-                transition: "opacity 0.2s",
-              }}
-            >
-              <div
-                style={{
-                  display: "flex",
-                  justifyContent: "space-between",
-                  alignItems: "start",
-                }}
-              >
-                <span style={{ fontSize: 24 }}>{mod.icon}</span>
-                <span
-                  style={{
-                    fontSize: 9,
-                    padding: "2px 6px",
-                    borderRadius: 3,
-                    background: isEnabled
-                      ? "rgba(63, 185, 80, 0.15)"
-                      : "rgba(139, 148, 158, 0.15)",
-                    color: isEnabled ? "var(--status-online)" : "var(--text-muted)",
-                    fontWeight: 600,
-                  }}
-                >
-                  {isEnabled ? "ON" : "OFF"}
-                </span>
-              </div>
-              <h4 style={{ margin: "var(--space-2) 0 4px", fontSize: 13, fontWeight: 600 }}>
-                {mod.name}
-              </h4>
-              <p
-                style={{
-                  fontSize: 11,
-                  color: "var(--text-muted)",
-                  margin: 0,
-                  lineHeight: 1.4,
-                }}
-              >
-                {mod.description}
-              </p>
-              <div
-                style={{
-                  marginTop: "var(--space-2)",
-                  fontFamily: "var(--font-mono)",
-                  fontSize: 10,
-                  color: "var(--text-secondary)",
-                }}
-              >
-                {mod.crate}
-              </div>
-            </div>
-          );
-        })}
-      </div>
-
-      {error && (
-        <div
-          style={{
-            background: "rgba(248, 81, 73, 0.1)",
-            border: "1px solid rgba(248, 81, 73, 0.3)",
-            borderRadius: 6,
-            padding: "var(--space-3)",
-            marginBottom: "var(--space-4)",
-            fontSize: 13,
-            color: "var(--status-error)",
-          }}
-        >
-          {error}
-        </div>
-      )}
-
-      <div style={{ display: "grid", gridTemplateColumns: "1fr 1fr", gap: "var(--space-5)" }}>
-        {/* Configuration Panel */}
-        <div className="card" style={{ padding: "var(--space-4)" }}>
-          <h3 style={{ margin: 0, fontSize: 14, fontWeight: 600, marginBottom: "var(--space-4)" }}>
-            Module Configuration
-          </h3>
-
-          {/* MinCut Section */}
-          <ConfigSection title="MinCut Segmentation">
-            <ToggleRow
-              label="Enable MinCut"
-              checked={config.mincut_enabled}
-              onChange={(v) => handleChange("mincut_enabled", v)}
-            />
-            <SliderRow
-              label="Threshold"
-              value={config.mincut_threshold}
-              min={0.1}
-              max={1.0}
-              step={0.05}
-              onChange={(v) => handleChange("mincut_threshold", v)}
-              disabled={!config.mincut_enabled}
-            />
-            <NumberRow
-              label="Max Persons"
-              value={config.mincut_max_persons}
-              min={1}
-              max={10}
-              onChange={(v) => handleChange("mincut_max_persons", v)}
-              disabled={!config.mincut_enabled}
-            />
-          </ConfigSection>
-
-          {/* Attention Section */}
-          <ConfigSection title="Spatial Attention">
-            <ToggleRow
-              label="Enable Attention"
-              checked={config.attention_enabled}
-              onChange={(v) => handleChange("attention_enabled", v)}
-            />
-            <NumberRow
-              label="Attention Heads"
-              value={config.attention_heads}
-              min={1}
-              max={16}
-              onChange={(v) => handleChange("attention_heads", v)}
-              disabled={!config.attention_enabled}
-            />
-            <SliderRow
-              label="Dropout"
-              value={config.attention_dropout}
-              min={0}
-              max={0.5}
-              step={0.05}
-              onChange={(v) => handleChange("attention_dropout", v)}
-              disabled={!config.attention_enabled}
-            />
-          </ConfigSection>
-
-          {/* Temporal Section */}
-          <ConfigSection title="Temporal Processing">
-            <ToggleRow
-              label="Enable Temporal"
-              checked={config.temporal_enabled}
-              onChange={(v) => handleChange("temporal_enabled", v)}
-            />
-            <NumberRow
-              label="Window (ms)"
-              value={config.temporal_window_ms}
-              min={100}
-              max={2000}
-              step={100}
-              onChange={(v) => handleChange("temporal_window_ms", v)}
-              disabled={!config.temporal_enabled}
-            />
-            <NumberRow
-              label="Compression Ratio"
-              value={config.temporal_compression_ratio}
-              min={1}
-              max={16}
-              onChange={(v) => handleChange("temporal_compression_ratio", v)}
-              disabled={!config.temporal_enabled}
-            />
-          </ConfigSection>
-
-          {/* Solver Section */}
-          <ConfigSection title="Sparse Solver">
-            <ToggleRow
-              label="Enable Solver"
-              checked={config.solver_enabled}
-              onChange={(v) => handleChange("solver_enabled", v)}
-            />
-            <div style={{ marginBottom: "var(--space-2)" }}>
-              <label style={labelStyle}>Interpolation</label>
-              <select
-                value={config.solver_interpolation}
-                onChange={(e) =>
-                  handleChange(
-                    "solver_interpolation",
-                    e.target.value as RuVectorConfig["solver_interpolation"]
-                  )
-                }
-                disabled={!config.solver_enabled}
-                style={{
-                  ...inputStyle,
-                  opacity: config.solver_enabled ? 1 : 0.5,
-                }}
-              >
-                <option value="linear">Linear</option>
-                <option value="cubic">Cubic</option>
-                <option value="sparse">Sparse (L1)</option>
-              </select>
-            </div>
-            <NumberRow
-              label="Subcarrier Count"
-              value={config.solver_subcarrier_count}
-              min={28}
-              max={114}
-              onChange={(v) => handleChange("solver_subcarrier_count", v)}
-              disabled={!config.solver_enabled}
-            />
-          </ConfigSection>
-
-          {/* Action Buttons */}
-          <div
-            style={{
-              display: "flex",
-              gap: "var(--space-2)",
-              marginTop: "var(--space-4)",
-            }}
-          >
-            <button
-              onClick={saveConfig}
-              className="btn-gradient"
-              style={{
-                flex: 1,
-                padding: "10px",
-                fontSize: 12,
-                opacity: saved ? 0.6 : 1,
-              }}
-              disabled={saved}
-            >
-              {saved ? "Saved" : "Save Configuration"}
-            </button>
-            <button
-              onClick={exportConfig}
-              style={{
-                padding: "10px 16px",
-                background: "transparent",
-                border: "1px solid var(--border)",
-                borderRadius: 6,
-                color: "var(--text-secondary)",
-                fontSize: 12,
-                fontWeight: 600,
-                cursor: "pointer",
-              }}
-            >
-              Export
-            </button>
-          </div>
-        </div>
-
-        {/* Live Testing Panel */}
-        <div className="card" style={{ padding: "var(--space-4)" }}>
-          <h3 style={{ margin: 0, fontSize: 14, fontWeight: 600, marginBottom: "var(--space-4)" }}>
-            Live Testing
-          </h3>
-
-          <div
-            style={{
-              display: "flex",
-              flexDirection: "column",
-              alignItems: "center",
-              justifyContent: "center",
-              minHeight: 200,
-              background: "var(--bg-secondary)",
-              borderRadius: 8,
-              marginBottom: "var(--space-4)",
-            }}
-          >
-            {testingLive ? (
-              <>
-                <div
-                  style={{
-                    fontSize: 48,
-                    animation: "pulse 1s infinite",
-                  }}
-                >
-                  📡
-                </div>
-                <p style={{ fontSize: 13, color: "var(--text-secondary)", marginTop: "var(--space-2)" }}>
-                  Processing live CSI stream...
-                </p>
-              </>
-            ) : (
-              <>
-                <div style={{ fontSize: 48, opacity: 0.5 }}>📡</div>
-                <p style={{ fontSize: 13, color: "var(--text-muted)", marginTop: "var(--space-2)" }}>
-                  Start live test to apply config to real CSI data
-                </p>
-              </>
-            )}
-          </div>
-
-          {liveMetrics && (
-            <div
-              style={{
-                display: "grid",
-                gridTemplateColumns: "repeat(3, 1fr)",
-                gap: "var(--space-3)",
-                marginBottom: "var(--space-4)",
-              }}
-            >
-              <MetricCard label="FPS" value={liveMetrics.fps.toFixed(1)} />
-              <MetricCard label="Latency" value={`${liveMetrics.latency_ms.toFixed(0)}ms`} />
-              <MetricCard label="Persons" value={liveMetrics.persons_detected.toString()} />
-            </div>
-          )}
-
-          <button
-            onClick={testingLive ? () => setTestingLive(false) : startLiveTest}
-            style={{
-              width: "100%",
-              padding: "12px",
-              background: testingLive
-                ? "rgba(248, 81, 73, 0.1)"
-                : "rgba(56, 139, 253, 0.1)",
-              border: `1px solid ${testingLive ? "rgba(248, 81, 73, 0.3)" : "rgba(56, 139, 253, 0.3)"}`,
-              borderRadius: 6,
-              color: testingLive ? "var(--status-error)" : "var(--accent)",
-              fontSize: 13,
-              fontWeight: 600,
-              cursor: "pointer",
-            }}
-          >
-            {testingLive ? "Stop Test" : "Start Live Test"}
-          </button>
-
-          {/* Presets */}
-          <div style={{ marginTop: "var(--space-5)" }}>
-            <h4 style={{ fontSize: 12, fontWeight: 600, marginBottom: "var(--space-3)" }}>
-              Quick Presets
-            </h4>
-            <div style={{ display: "flex", flexDirection: "column", gap: "var(--space-2)" }}>
-              <PresetButton
-                label="Low Latency"
-                description="Minimal processing for real-time"
-                onClick={() => {
-                  setConfig({
-                    ...DEFAULT_CONFIG,
-                    attention_heads: 2,
-                    temporal_compression_ratio: 8,
-                    solver_subcarrier_count: 28,
-                  });
-                  setSaved(false);
-                }}
-              />
-              <PresetButton
-                label="High Accuracy"
-                description="Maximum quality, higher latency"
-                onClick={() => {
-                  setConfig({
-                    ...DEFAULT_CONFIG,
-                    attention_heads: 8,
-                    temporal_compression_ratio: 2,
-                    solver_subcarrier_count: 114,
-                    solver_interpolation: "cubic",
-                  });
-                  setSaved(false);
-                }}
-              />
-              <PresetButton
-                label="Balanced"
-                description="Default recommended settings"
-                onClick={() => {
-                  setConfig(DEFAULT_CONFIG);
-                  setSaved(false);
-                }}
-              />
-            </div>
-          </div>
-        </div>
-      </div>
-
-      <style>{`
-        @keyframes pulse {
-          0%, 100% { transform: scale(1); }
-          50% { transform: scale(1.1); }
-        }
-      `}</style>
-    </div>
-  );
-};
-
-// Helper Components
-function ConfigSection({ title, children }: { title: string; children: React.ReactNode }) {
-  return (
-    <div style={{ marginBottom: "var(--space-4)" }}>
-      <h4
-        style={{
-          fontSize: 11,
-          fontWeight: 600,
-          color: "var(--text-muted)",
-          textTransform: "uppercase",
-          letterSpacing: "0.04em",
-          marginBottom: "var(--space-2)",
-        }}
-      >
-        {title}
-      </h4>
-      {children}
-    </div>
-  );
-}
-
-function ToggleRow({
-  label,
-  checked,
-  onChange,
-}: {
-  label: string;
-  checked: boolean;
-  onChange: (v: boolean) => void;
-}) {
-  return (
-    <div
-      style={{
-        display: "flex",
-        justifyContent: "space-between",
-        alignItems: "center",
-        marginBottom: "var(--space-2)",
-      }}
-    >
-      <span style={{ fontSize: 12 }}>{label}</span>
-      <button
-        onClick={() => onChange(!checked)}
-        style={{
-          width: 40,
-          height: 22,
-          borderRadius: 11,
-          border: "none",
-          background: checked ? "var(--accent)" : "var(--border)",
-          position: "relative",
-          cursor: "pointer",
-          transition: "background 0.2s",
-        }}
-      >
-        <span
-          style={{
-            position: "absolute",
-            top: 2,
-            left: checked ? 20 : 2,
-            width: 18,
-            height: 18,
-            borderRadius: "50%",
-            background: "white",
-            transition: "left 0.2s",
-          }}
-        />
-      </button>
-    </div>
-  );
-}
-
-function SliderRow({
-  label,
-  value,
-  min,
-  max,
-  step,
-  onChange,
-  disabled,
-}: {
-  label: string;
-  value: number;
-  min: number;
-  max: number;
-  step: number;
-  onChange: (v: number) => void;
-  disabled?: boolean;
-}) {
-  return (
-    <div style={{ marginBottom: "var(--space-2)", opacity: disabled ? 0.5 : 1 }}>
-      <div style={{ display: "flex", justifyContent: "space-between", marginBottom: 4 }}>
-        <span style={{ fontSize: 12 }}>{label}</span>
-        <span style={{ fontSize: 11, fontFamily: "var(--font-mono)", color: "var(--text-muted)" }}>
-          {value.toFixed(2)}
-        </span>
-      </div>
-      <input
-        type="range"
-        value={value}
-        min={min}
-        max={max}
-        step={step}
-        onChange={(e) => onChange(parseFloat(e.target.value))}
-        disabled={disabled}
-        style={{ width: "100%", cursor: disabled ? "not-allowed" : "pointer" }}
-      />
-    </div>
-  );
-}
-
-function NumberRow({
-  label,
-  value,
-  min,
-  max,
-  step = 1,
-  onChange,
-  disabled,
-}: {
-  label: string;
-  value: number;
-  min: number;
-  max: number;
-  step?: number;
-  onChange: (v: number) => void;
-  disabled?: boolean;
-}) {
-  return (
-    <div
-      style={{
-        display: "flex",
-        justifyContent: "space-between",
-        alignItems: "center",
-        marginBottom: "var(--space-2)",
-        opacity: disabled ? 0.5 : 1,
-      }}
-    >
-      <span style={{ fontSize: 12 }}>{label}</span>
-      <input
-        type="number"
-        value={value}
-        min={min}
-        max={max}
-        step={step}
-        onChange={(e) => onChange(parseInt(e.target.value) || min)}
-        disabled={disabled}
-        style={{
-          width: 70,
-          padding: "4px 8px",
-          background: "var(--bg-secondary)",
-          border: "1px solid var(--border)",
-          borderRadius: 4,
-          color: "var(--text-primary)",
-          fontSize: 12,
-          textAlign: "right",
-          cursor: disabled ? "not-allowed" : "text",
-        }}
-      />
-    </div>
-  );
-}
-
-function MetricCard({ label, value }: { label: string; value: string }) {
-  return (
-    <div className="card" style={{ padding: "var(--space-3)", textAlign: "center" }}>
-      <div style={{ fontSize: 10, color: "var(--text-muted)", marginBottom: 2 }}>{label}</div>
-      <div style={{ fontFamily: "var(--font-mono)", fontSize: 18, fontWeight: 600 }}>{value}</div>
-    </div>
-  );
-}
-
-function PresetButton({
-  label,
-  description,
-  onClick,
-}: {
-  label: string;
-  description: string;
-  onClick: () => void;
-}) {
-  return (
-    <button
-      onClick={onClick}
-      style={{
-        display: "flex",
-        flexDirection: "column",
-        alignItems: "start",
-        padding: "var(--space-3)",
-        background: "var(--bg-secondary)",
-        border: "1px solid var(--border)",
-        borderRadius: 6,
-        cursor: "pointer",
-        textAlign: "left",
-      }}
-    >
-      <span style={{ fontSize: 12, fontWeight: 600, color: "var(--text-primary)" }}>{label}</span>
-      <span style={{ fontSize: 11, color: "var(--text-muted)" }}>{description}</span>
-    </button>
-  );
-}
-
-const labelStyle: React.CSSProperties = {
-  display: "block",
-  fontSize: 11,
-  fontWeight: 600,
-  color: "var(--text-muted)",
-  marginBottom: 4,
-};
-
-const inputStyle: React.CSSProperties = {
-  width: "100%",
-  padding: "8px 12px",
-  background: "var(--bg-secondary)",
-  border: "1px solid var(--border)",
-  borderRadius: 6,
-  color: "var(--text-primary)",
-  fontSize: 13,
-};
-
-export default RuVectorTab;
@@ -1,601 +0,0 @@
-import React, { useState, useEffect } from "react";
-import { invoke } from "@tauri-apps/api/core";
-import { listen, UnlistenFn } from "@tauri-apps/api/event";
-
-interface TrainingConfig {
-  dataset_id: string;
-  model_id: string;
-  epochs: number;
-  batch_size: number;
-  learning_rate: number;
-  optimizer: "adam" | "sgd" | "adamw";
-  weight_decay: number;
-  use_augmentation: boolean;
-  checkpoint_every: number;
-}
-
-interface TrainingProgress {
-  epoch: number;
-  total_epochs: number;
-  batch: number;
-  total_batches: number;
-  train_loss: number;
-  val_loss: number | null;
-  learning_rate: number;
-  eta_secs: number;
-  gpu_memory_mb: number | null;
-}
-
-interface TrainingJob {
-  id: string;
-  status: "running" | "paused" | "completed" | "failed";
-  started_at: string;
-  progress: TrainingProgress;
-}
-
-const DEFAULT_CONFIG: TrainingConfig = {
-  dataset_id: "mmfi",
-  model_id: "csi-encoder-cnn",
-  epochs: 100,
-  batch_size: 32,
-  learning_rate: 0.001,
-  optimizer: "adam",
-  weight_decay: 0.0001,
-  use_augmentation: true,
-  checkpoint_every: 10,
-};
-
-interface TrainingTabProps {
-  gpuAvailable: boolean;
-}
-
-const TrainingTab: React.FC<TrainingTabProps> = ({ gpuAvailable }) => {
-  const [config, setConfig] = useState<TrainingConfig>(DEFAULT_CONFIG);
-  const [currentJob, setCurrentJob] = useState<TrainingJob | null>(null);
-  const [lossHistory, setLossHistory] = useState<{ epoch: number; train: number; val: number }[]>(
-    []
-  );
-  const [error, setError] = useState<string | null>(null);
-
-  useEffect(() => {
-    let unlisten: UnlistenFn | undefined;
-
-    const setupListener = async () => {
-      try {
-        unlisten = await listen<TrainingProgress>("training:progress", (event) => {
-          const progress = event.payload;
-          setCurrentJob((prev) =>
-            prev
-              ? { ...prev, progress }
-              : {
-                  id: "job-1",
-                  status: "running",
-                  started_at: new Date().toISOString(),
-                  progress,
-                }
-          );
-
-          if (progress.val_loss !== null && progress.batch === progress.total_batches) {
-            setLossHistory((prev) => [
-              ...prev,
-              {
-                epoch: progress.epoch,
-                train: progress.train_loss,
-                val: progress.val_loss!,
-              },
-            ]);
-          }
-        });
-      } catch (err) {
-        console.error("Failed to setup training listener:", err);
-      }
-    };
-
-    setupListener();
-
-    return () => {
-      if (unlisten) unlisten();
-    };
-  }, []);
-
-  const handleStartTraining = async () => {
-    setError(null);
-    try {
-      await invoke("start_training", { config });
-      setCurrentJob({
-        id: `job-${Date.now()}`,
-        status: "running",
-        started_at: new Date().toISOString(),
-        progress: {
-          epoch: 0,
-          total_epochs: config.epochs,
-          batch: 0,
-          total_batches: 0,
-          train_loss: 0,
-          val_loss: null,
-          learning_rate: config.learning_rate,
-          eta_secs: 0,
-          gpu_memory_mb: null,
-        },
-      });
-    } catch (err) {
-      setError(`Failed to start training: ${err}`);
-    }
-  };
-
-  const handleStopTraining = async () => {
-    try {
-      await invoke("stop_training");
-      setCurrentJob((prev) => (prev ? { ...prev, status: "paused" } : null));
-    } catch (err) {
-      setError(`Failed to stop training: ${err}`);
-    }
-  };
-
-  const formatEta = (seconds: number) => {
-    if (seconds < 60) return `${seconds}s`;
-    if (seconds < 3600) return `${Math.floor(seconds / 60)}m ${seconds % 60}s`;
-    const hours = Math.floor(seconds / 3600);
-    const mins = Math.floor((seconds % 3600) / 60);
-    return `${hours}h ${mins}m`;
-  };
-
-  const progress = currentJob?.progress;
-  const epochProgress = progress ? (progress.epoch / progress.total_epochs) * 100 : 0;
-  const batchProgress = progress && progress.total_batches > 0
-    ? (progress.batch / progress.total_batches) * 100
-    : 0;
-
-  return (
-    <div>
-      {/* GPU Warning */}
-      {!gpuAvailable && (
-        <div
-          style={{
-            background: "rgba(245, 158, 11, 0.1)",
-            border: "1px solid rgba(245, 158, 11, 0.3)",
-            borderRadius: 6,
-            padding: "var(--space-3)",
-            marginBottom: "var(--space-4)",
-            display: "flex",
-            alignItems: "center",
-            gap: "var(--space-3)",
-          }}
-        >
-          <span style={{ fontSize: 18 }}>⚠️</span>
-          <div>
-            <div style={{ fontWeight: 600, fontSize: 13, color: "#f59e0b" }}>
-              GPU Not Available
-            </div>
-            <div style={{ fontSize: 12, color: "var(--text-muted)" }}>
-              Training will use CPU, which is significantly slower. Consider using a
-              machine with CUDA or Metal support.
-            </div>
-          </div>
-        </div>
-      )}
-
-      {error && (
-        <div
-          style={{
-            background: "rgba(248, 81, 73, 0.1)",
-            border: "1px solid rgba(248, 81, 73, 0.3)",
-            borderRadius: 6,
-            padding: "var(--space-3)",
-            marginBottom: "var(--space-4)",
-            fontSize: 13,
-            color: "var(--status-error)",
-          }}
-        >
-          {error}
-        </div>
-      )}
-
-      <div style={{ display: "grid", gridTemplateColumns: "1fr 1fr", gap: "var(--space-5)" }}>
-        {/* Configuration Panel */}
-        <div className="card" style={{ padding: "var(--space-4)" }}>
-          <h3 style={{ margin: 0, fontSize: 14, fontWeight: 600, marginBottom: "var(--space-4)" }}>
-            Training Configuration
-          </h3>
-
-          <div style={{ display: "flex", flexDirection: "column", gap: "var(--space-3)" }}>
-            <div>
-              <label style={labelStyle}>Dataset</label>
-              <select
-                value={config.dataset_id}
-                onChange={(e) => setConfig({ ...config, dataset_id: e.target.value })}
-                style={inputStyle}
-              >
-                <option value="mmfi">MM-Fi Dataset</option>
-                <option value="wipose">Wi-Pose Dataset</option>
-                <option value="wiar">WiAR Dataset</option>
-              </select>
-            </div>
-
-            <div>
-              <label style={labelStyle}>Model Architecture</label>
-              <select
-                value={config.model_id}
-                onChange={(e) => setConfig({ ...config, model_id: e.target.value })}
-                style={inputStyle}
-              >
-                <option value="csi-encoder-cnn">CSI Encoder (CNN)</option>
-                <option value="csi-encoder-transformer">CSI Encoder (Transformer)</option>
-                <option value="pose-decoder-lstm">Pose Decoder (LSTM)</option>
-                <option value="pose-decoder-gru">Pose Decoder (GRU)</option>
-              </select>
-            </div>
-
-            <div style={{ display: "grid", gridTemplateColumns: "1fr 1fr", gap: "var(--space-3)" }}>
-              <div>
-                <label style={labelStyle}>Epochs</label>
-                <input
-                  type="number"
-                  value={config.epochs}
-                  onChange={(e) => setConfig({ ...config, epochs: parseInt(e.target.value) || 1 })}
-                  min={1}
-                  max={1000}
-                  style={inputStyle}
-                />
-              </div>
-              <div>
-                <label style={labelStyle}>Batch Size</label>
-                <input
-                  type="number"
-                  value={config.batch_size}
-                  onChange={(e) =>
-                    setConfig({ ...config, batch_size: parseInt(e.target.value) || 1 })
-                  }
-                  min={1}
-                  max={512}
-                  style={inputStyle}
-                />
-              </div>
-            </div>
-
-            <div style={{ display: "grid", gridTemplateColumns: "1fr 1fr", gap: "var(--space-3)" }}>
-              <div>
-                <label style={labelStyle}>Learning Rate</label>
-                <input
-                  type="number"
-                  value={config.learning_rate}
-                  onChange={(e) =>
-                    setConfig({ ...config, learning_rate: parseFloat(e.target.value) || 0.001 })
-                  }
-                  step={0.0001}
-                  min={0.00001}
-                  max={1}
-                  style={inputStyle}
-                />
-              </div>
-              <div>
-                <label style={labelStyle}>Optimizer</label>
-                <select
-                  value={config.optimizer}
-                  onChange={(e) =>
-                    setConfig({ ...config, optimizer: e.target.value as TrainingConfig["optimizer"] })
-                  }
-                  style={inputStyle}
-                >
-                  <option value="adam">Adam</option>
-                  <option value="adamw">AdamW</option>
-                  <option value="sgd">SGD</option>
-                </select>
-              </div>
-            </div>
-
-            <div style={{ display: "grid", gridTemplateColumns: "1fr 1fr", gap: "var(--space-3)" }}>
-              <div>
-                <label style={labelStyle}>Weight Decay</label>
-                <input
-                  type="number"
-                  value={config.weight_decay}
-                  onChange={(e) =>
-                    setConfig({ ...config, weight_decay: parseFloat(e.target.value) || 0 })
-                  }
-                  step={0.0001}
-                  min={0}
-                  max={1}
-                  style={inputStyle}
-                />
-              </div>
-              <div>
-                <label style={labelStyle}>Checkpoint Every</label>
-                <input
-                  type="number"
-                  value={config.checkpoint_every}
-                  onChange={(e) =>
-                    setConfig({ ...config, checkpoint_every: parseInt(e.target.value) || 1 })
-                  }
-                  min={1}
-                  max={100}
-                  style={inputStyle}
-                />
-              </div>
-            </div>
-
-            <div style={{ display: "flex", alignItems: "center", gap: "var(--space-2)" }}>
-              <input
-                type="checkbox"
-                id="augmentation"
-                checked={config.use_augmentation}
-                onChange={(e) => setConfig({ ...config, use_augmentation: e.target.checked })}
-                style={{ width: 16, height: 16 }}
-              />
-              <label htmlFor="augmentation" style={{ fontSize: 13, cursor: "pointer" }}>
-                Enable Data Augmentation
-              </label>
-            </div>
-
-            <div style={{ marginTop: "var(--space-3)" }}>
-              {currentJob?.status === "running" ? (
-                <button
-                  onClick={handleStopTraining}
-                  style={{
-                    width: "100%",
-                    padding: "12px",
-                    background: "rgba(248, 81, 73, 0.1)",
-                    border: "1px solid rgba(248, 81, 73, 0.3)",
-                    borderRadius: 6,
-                    color: "var(--status-error)",
-                    fontSize: 13,
-                    fontWeight: 600,
-                    cursor: "pointer",
-                  }}
-                >
-                  Stop Training
-                </button>
-              ) : (
-                <button
-                  onClick={handleStartTraining}
-                  className="btn-gradient"
-                  style={{ width: "100%", padding: "12px", fontSize: 13 }}
-                >
-                  Start Training
-                </button>
-              )}
-            </div>
-          </div>
-        </div>
-
-        {/* Progress Panel */}
-        <div className="card" style={{ padding: "var(--space-4)" }}>
-          <h3 style={{ margin: 0, fontSize: 14, fontWeight: 600, marginBottom: "var(--space-4)" }}>
-            Training Progress
-          </h3>
-
-          {!currentJob ? (
-            <div
-              style={{
-                display: "flex",
-                flexDirection: "column",
-                alignItems: "center",
-                justifyContent: "center",
-                height: 300,
-                color: "var(--text-muted)",
-              }}
-            >
-              <div style={{ fontSize: 48, marginBottom: "var(--space-3)" }}>🎯</div>
-              <p style={{ fontSize: 13 }}>No training job running</p>
-              <p style={{ fontSize: 12 }}>Configure and start training to begin</p>
-            </div>
-          ) : (
-            <div style={{ display: "flex", flexDirection: "column", gap: "var(--space-4)" }}>
-              {/* Status */}
-              <div
-                style={{
-                  display: "flex",
-                  justifyContent: "space-between",
-                  alignItems: "center",
-                }}
-              >
-                <div style={{ display: "flex", alignItems: "center", gap: "var(--space-2)" }}>
-                  <span
-                    style={{
-                      width: 8,
-                      height: 8,
-                      borderRadius: "50%",
-                      background:
-                        currentJob.status === "running"
-                          ? "var(--status-online)"
-                          : currentJob.status === "paused"
-                            ? "#f59e0b"
-                            : "var(--status-error)",
-                      animation: currentJob.status === "running" ? "pulse 1.5s infinite" : "none",
-                    }}
-                  />
-                  <span style={{ fontSize: 13, fontWeight: 600, textTransform: "capitalize" }}>
-                    {currentJob.status}
-                  </span>
-                </div>
-                <span style={{ fontSize: 12, color: "var(--text-muted)" }}>
-                  ETA: {formatEta(progress?.eta_secs ?? 0)}
-                </span>
-              </div>
-
-              {/* Epoch Progress */}
-              <div>
-                <div
-                  style={{
-                    display: "flex",
-                    justifyContent: "space-between",
-                    fontSize: 12,
-                    marginBottom: 4,
-                  }}
-                >
-                  <span>Epoch</span>
-                  <span>
-                    {progress?.epoch ?? 0} / {progress?.total_epochs ?? config.epochs}
-                  </span>
-                </div>
-                <div
-                  style={{
-                    height: 6,
-                    background: "var(--border)",
-                    borderRadius: 3,
-                    overflow: "hidden",
-                  }}
-                >
-                  <div
-                    style={{
-                      width: `${epochProgress}%`,
-                      height: "100%",
-                      background: "var(--accent)",
-                      transition: "width 0.3s",
-                    }}
-                  />
-                </div>
-              </div>
-
-              {/* Batch Progress */}
-              <div>
-                <div
-                  style={{
-                    display: "flex",
-                    justifyContent: "space-between",
-                    fontSize: 12,
-                    marginBottom: 4,
-                  }}
-                >
-                  <span>Batch</span>
-                  <span>
-                    {progress?.batch ?? 0} / {progress?.total_batches ?? 0}
-                  </span>
-                </div>
-                <div
-                  style={{
-                    height: 4,
-                    background: "var(--border)",
-                    borderRadius: 2,
-                    overflow: "hidden",
-                  }}
-                >
-                  <div
-                    style={{
-                      width: `${batchProgress}%`,
-                      height: "100%",
-                      background: "rgba(56, 139, 253, 0.5)",
-                      transition: "width 0.1s",
-                    }}
-                  />
-                </div>
-              </div>
-
-              {/* Stats Grid */}
-              <div
-                style={{
-                  display: "grid",
-                  gridTemplateColumns: "repeat(2, 1fr)",
-                  gap: "var(--space-3)",
-                }}
-              >
-                <div className="card" style={{ padding: "var(--space-3)" }}>
-                  <div style={{ fontSize: 10, color: "var(--text-muted)", marginBottom: 4 }}>
-                    Train Loss
-                  </div>
-                  <div style={{ fontFamily: "var(--font-mono)", fontSize: 20, fontWeight: 600 }}>
-                    {progress?.train_loss.toFixed(4) ?? "—"}
-                  </div>
-                </div>
-                <div className="card" style={{ padding: "var(--space-3)" }}>
-                  <div style={{ fontSize: 10, color: "var(--text-muted)", marginBottom: 4 }}>
-                    Val Loss
-                  </div>
-                  <div
-                    style={{
-                      fontFamily: "var(--font-mono)",
-                      fontSize: 20,
-                      fontWeight: 600,
-                      color: "var(--status-online)",
-                    }}
-                  >
-                    {progress?.val_loss?.toFixed(4) ?? "—"}
-                  </div>
-                </div>
-                <div className="card" style={{ padding: "var(--space-3)" }}>
-                  <div style={{ fontSize: 10, color: "var(--text-muted)", marginBottom: 4 }}>
-                    Learning Rate
-                  </div>
-                  <div style={{ fontFamily: "var(--font-mono)", fontSize: 14, fontWeight: 600 }}>
-                    {progress?.learning_rate.toExponential(2) ?? "—"}
-                  </div>
-                </div>
-                <div className="card" style={{ padding: "var(--space-3)" }}>
-                  <div style={{ fontSize: 10, color: "var(--text-muted)", marginBottom: 4 }}>
-                    GPU Memory
-                  </div>
-                  <div style={{ fontFamily: "var(--font-mono)", fontSize: 14, fontWeight: 600 }}>
-                    {progress?.gpu_memory_mb ? `${progress.gpu_memory_mb} MB` : "N/A"}
-                  </div>
-                </div>
-              </div>
-
-              {/* Mini Loss Chart */}
-              {lossHistory.length > 0 && (
-                <div>
-                  <div style={{ fontSize: 12, fontWeight: 600, marginBottom: "var(--space-2)" }}>
-                    Loss History
-                  </div>
-                  <div
-                    style={{
-                      height: 80,
-                      display: "flex",
-                      alignItems: "flex-end",
-                      gap: 2,
-                      padding: "var(--space-2)",
-                      background: "var(--bg-secondary)",
-                      borderRadius: 4,
-                    }}
-                  >
-                    {lossHistory.slice(-20).map((h, i) => (
-                      <div
-                        key={i}
-                        style={{
-                          flex: 1,
-                          height: `${Math.max(5, Math.min(100, (1 - h.train) * 100))}%`,
-                          background: "var(--accent)",
-                          borderRadius: 2,
-                          opacity: 0.6 + (i / 20) * 0.4,
-                        }}
-                        title={`Epoch ${h.epoch}: Train=${h.train.toFixed(4)}, Val=${h.val.toFixed(4)}`}
-                      />
-                    ))}
-                  </div>
-                </div>
-              )}
-            </div>
-          )}
-        </div>
-      </div>
-
-      <style>{`
-        @keyframes pulse {
-          0%, 100% { opacity: 1; }
-          50% { opacity: 0.5; }
-        }
-      `}</style>
-    </div>
-  );
-};
-
-const labelStyle: React.CSSProperties = {
-  display: "block",
-  fontSize: 11,
-  fontWeight: 600,
-  color: "var(--text-muted)",
-  marginBottom: 4,
-  textTransform: "uppercase",
-  letterSpacing: "0.04em",
-};
-
-const inputStyle: React.CSSProperties = {
-  width: "100%",
-  padding: "8px 12px",
-  background: "var(--bg-secondary)",
-  border: "1px solid var(--border)",
-  borderRadius: 6,
-  color: "var(--text-primary)",
-  fontSize: 13,
-};
-
-export default TrainingTab;
@@ -1,165 +0,0 @@
-import React, { useState, useEffect } from "react";
-import { invoke } from "@tauri-apps/api/core";
-import DatasetsTab from "./DatasetsTab";
-import ModelsTab from "./ModelsTab";
-import TrainingTab from "./TrainingTab";
-import RuVectorTab from "./RuVectorTab";
-import MetricsTab from "./MetricsTab";
-
-type TrainingTabType = "datasets" | "models" | "training" | "ruvector" | "metrics";
-
-interface GpuInfo {
-  available: boolean;
-  name: string | null;
-  memory_mb: number | null;
-  cuda_version: string | null;
-  metal_supported: boolean;
-}
-
-const Training: React.FC = () => {
-  const [activeTab, setActiveTab] = useState<TrainingTabType>("datasets");
-  const [gpuInfo, setGpuInfo] = useState<GpuInfo | null>(null);
-  const [loading, setLoading] = useState(true);
-
-  useEffect(() => {
-    detectGpu();
-  }, []);
-
-  const detectGpu = async () => {
-    try {
-      const info = await invoke<GpuInfo>("detect_gpu");
-      setGpuInfo(info);
-    } catch (err) {
-      console.error("GPU detection failed:", err);
-      setGpuInfo({
-        available: false,
-        name: null,
-        memory_mb: null,
-        cuda_version: null,
-        metal_supported: false,
-      });
-    } finally {
-      setLoading(false);
-    }
-  };
-
-  const tabs: { id: TrainingTabType; label: string; icon: string }[] = [
-    { id: "datasets", label: "Datasets", icon: "📊" },
-    { id: "models", label: "Models", icon: "🧠" },
-    { id: "training", label: "Training", icon: "⚡" },
-    { id: "ruvector", label: "RuVector", icon: "📡" },
-    { id: "metrics", label: "Metrics", icon: "📈" },
-  ];
-
-  return (
-    <div style={{ padding: "var(--space-5)", maxWidth: 1400 }}>
-      {/* Header */}
-      <div
-        style={{
-          display: "flex",
-          justifyContent: "space-between",
-          alignItems: "center",
-          marginBottom: "var(--space-5)",
-        }}
-      >
-        <div>
-          <h1 className="heading-lg" style={{ margin: 0 }}>
-            Training & Models
-          </h1>
-          <p
-            style={{
-              fontSize: 13,
-              color: "var(--text-secondary)",
-              marginTop: 4,
-            }}
-          >
-            Train pose estimation models and configure RuVector signal processing
-          </p>
-        </div>
-
-        {/* GPU Status */}
-        <div
-          style={{
-            display: "flex",
-            alignItems: "center",
-            gap: "var(--space-3)",
-            padding: "var(--space-3) var(--space-4)",
-            background: gpuInfo?.available
-              ? "rgba(63, 185, 80, 0.1)"
-              : "rgba(139, 148, 158, 0.1)",
-            border: `1px solid ${gpuInfo?.available ? "rgba(63, 185, 80, 0.3)" : "rgba(139, 148, 158, 0.3)"}`,
-            borderRadius: 8,
-          }}
-        >
-          <span style={{ fontSize: 18 }}>{gpuInfo?.available ? "🎮" : "💻"}</span>
-          <div>
-            <div style={{ fontSize: 12, fontWeight: 600, color: "var(--text-primary)" }}>
-              {loading
-                ? "Detecting GPU..."
-                : gpuInfo?.available
-                  ? gpuInfo.name || "GPU Available"
-                  : "CPU Mode"}
-            </div>
-            <div style={{ fontSize: 11, color: "var(--text-muted)" }}>
-              {gpuInfo?.cuda_version
-                ? `CUDA ${gpuInfo.cuda_version}`
-                : gpuInfo?.metal_supported
-                  ? "Metal Supported"
-                  : "No GPU acceleration"}
-              {gpuInfo?.memory_mb && ` • ${Math.round(gpuInfo.memory_mb / 1024)}GB`}
-            </div>
-          </div>
-        </div>
-      </div>
-
-      {/* Tabs */}
-      <div
-        style={{
-          display: "flex",
-          gap: "var(--space-1)",
-          borderBottom: "1px solid var(--border)",
-          marginBottom: "var(--space-5)",
-        }}
-      >
-        {tabs.map((tab) => (
-          <button
-            key={tab.id}
-            onClick={() => setActiveTab(tab.id)}
-            style={{
-              display: "flex",
-              alignItems: "center",
-              gap: 6,
-              padding: "12px 20px",
-              border: "none",
-              background: "transparent",
-              color: activeTab === tab.id ? "var(--accent)" : "var(--text-secondary)",
-              fontSize: 13,
-              fontWeight: 600,
-              cursor: "pointer",
-              borderBottom:
-                activeTab === tab.id
-                  ? "2px solid var(--accent)"
-                  : "2px solid transparent",
-              marginBottom: -1,
-              transition: "color 0.15s, border-color 0.15s",
-            }}
-          >
-            <span>{tab.icon}</span>
-            {tab.label}
-          </button>
-        ))}
-      </div>
-
-      {/* Tab Content */}
-      <div>
-        {activeTab === "datasets" && <DatasetsTab />}
-        {activeTab === "models" && <ModelsTab />}
-        {activeTab === "training" && <TrainingTab gpuAvailable={gpuInfo?.available ?? false} />}
-        {activeTab === "ruvector" && <RuVectorTab />}
-        {activeTab === "metrics" && <MetricsTab />}
-      </div>
-    </div>
-  );
-};
-
-export default Training;
@@ -1,2 +1,2 @@
 // Application version - single source of truth
-export const APP_VERSION = "0.5.0";
+export const APP_VERSION = "0.4.4";
Author	SHA1	Message	Date
github-actions[bot]	6891a72053	chore: update vendor submodules to latest main	2026-03-13 00:36:02 +00:00
ruv	6e03a47867	docs: update user guide with v0.4.1 firmware release and CSI troubleshooting - Add v0.4.1 to firmware release table as recommended stable release - Update flash command with correct partition offsets (8MB, OTA) - Add "CSI not enabled" troubleshooting entry - Add warning about pre-v0.4.1 firmware CSI bug Co-Authored-By: claude-flow <ruv@ruv.net>	2026-03-12 13:49:20 -04:00
ruv	9d1140de2d	docs: update README firmware release table with v0.4.1 Add v0.4.1-esp32 as the recommended stable release and update the flash command to match the current partition layout. Co-Authored-By: claude-flow <ruv@ruv.net>	2026-03-12 13:49:20 -04:00
ruv	952f27a1ce	fix(firmware): enable CSI in sdkconfig and add build guard (ADR-057) The committed sdkconfig had CONFIG_ESP_WIFI_CSI_ENABLED disabled, causing all builds to crash at runtime with "CSI not enabled in menuconfig". Root cause: sdkconfig.defaults.template existed but ESP-IDF only reads sdkconfig.defaults (no .template suffix). Fixes: - Add sdkconfig.defaults with CONFIG_ESP_WIFI_CSI_ENABLED=y - Add #error compile guard in csi_collector.c to prevent recurrence - Fix NVS encryption default (requires eFuse, breaks clean builds) Verified: Docker build + flash to ESP32-S3 + CSI callbacks confirmed. Closes #241 Relates to #223, #238, #234, #210, #190 Co-Authored-By: claude-flow <ruv@ruv.net>	2026-03-12 13:49:20 -04:00
Reuven	f7d043d727	docs: fix Docker commands to use CSI_SOURCE environment variable The Docker image uses CSI_SOURCE env var to select the data source, not command-line arguments appended after the image name. Fixed: - ESP32 mode examples now use -e CSI_SOURCE=esp32 - Training mode example now uses --entrypoint override - Added CSI_SOURCE value table in Docker section Fixes #226 Co-Authored-By: claude-flow <ruv@ruv.net>	2026-03-10 12:16:06 -04:00