feat(desktop): v0.5.0 - Training & RuVector Integration (ADR-057)#225
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feat(desktop): v0.5.0 - Training & RuVector Integration (ADR-057)#225
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Proposes a new Training page in the desktop app with tabs: - Datasets: Download/manage training datasets (MM-Fi, Wi-Pose) - Models: Browse architectures, load checkpoints, export ONNX - Training: Configure and run training jobs with GPU support - RuVector: Configure signal processing modules, live testing - Metrics: View loss curves, evaluation results Integrates wifi-densepose-train crate and 5 RuVector crates into the Tauri desktop application. Co-Authored-By: claude-flow <ruv@ruv.net>
Implements the Training & Models page with tabbed navigation: - Datasets tab: Download/import datasets, preview samples - Models tab: Browse architectures, manage checkpoints, export ONNX - Training tab: Configure training, GPU detection, live progress - RuVector tab: Module config (MinCut, Attention, Temporal, Solver) - Metrics tab: Loss curves, evaluation metrics, per-joint accuracy Features: - GPU detection status display (CUDA/Metal) - Live training progress with Tauri events - RuVector module enable/disable and parameter tuning - Training presets (Low Latency, High Accuracy, Balanced) - Export metrics to CSV/JSON/TensorBoard - Mock data for demonstration when backend not implemented Ref: ADR-057 Co-Authored-By: claude-flow <ruv@ruv.net>
Implements full Rust backend for Training page (ADR-057): Training Domain Types (domain/training.rs): - GpuInfo, GpuBackend (Cpu, Cuda, Metal) - DatasetInfo, DatasetFormat (MmFi, WiPose, Wiar, Custom) - ModelInfo, ModelType (Encoder, Decoder, Embedding, Adaptor) - CheckpointInfo, TrainingJob, TrainingConfig, TrainingProgress - RuVectorConfig with MinCut, Attention, Temporal, Solver params - EvaluationMetrics, JointAccuracy, EpochMetrics Training Commands (commands/training.rs): - detect_gpu - Auto-detect CUDA/Metal/CPU with caching - list_datasets, get_datasets, download_dataset - list_models, list_checkpoints, export_model (ONNX/TorchScript) - start_training, stop_training, training_progress - get_ruvector_config, set_ruvector_config, test_ruvector_live - get_training_history, get_evaluation_metrics, get_joint_accuracies State Management (state.rs): - Added TrainingState to AppState - GPU info caching, datasets, checkpoints, current job - RuVector config persistence Tests: 48 passed (27 unit + 21 integration) Ref: ADR-057 Co-Authored-By: claude-flow <ruv@ruv.net>
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Summary
Implements the Training & Models page for RuView Desktop with full Rust backend integration:
Changes
Frontend (React/TypeScript)
Training/index.tsx- Main page with 5-tab navigation + GPU statusTraining/DatasetsTab.tsx- Dataset download/import/previewTraining/ModelsTab.tsx- Model browser, checkpoint management, ONNX exportTraining/TrainingTab.tsx- Training config form, live progress trackingTraining/RuVectorTab.tsx- 5 RuVector module configs with presetsTraining/MetricsTab.tsx- Loss curves, evaluation metrics, per-joint accuracyBackend (Rust)
domain/training.rs- 15 domain types (GpuInfo, DatasetInfo, TrainingJob, etc.)commands/training.rs- 16 Tauri commands with testsstate.rs- TrainingState added to AppStateTauri Commands
detect_gpulist_datasetsget_datasetsdownload_datasetlist_modelslist_checkpointsexport_modelstart_trainingstop_trainingtraining_progressget_ruvector_configset_ruvector_configtest_ruvector_liveget_training_historyget_evaluation_metricsget_joint_accuraciesTest plan
Architecture Decision
Ref: ADR-057
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