feat: add SelVA LoRA Evaluator node

Generates audio samples from a list of adapters against a fixed reference
clip, collects spectral metrics for each, and outputs a comparison bar
chart + eval_summary.json. Useful for comparing sweep candidates before
committing to a next round of training.

JSON format: name, data_dir, output_dir, steps, seed, adapters[{id, path}].
Empty path = baseline (no LoRA).

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

nodes/__init__.py

@@ -10,6 +10,7 @@ _NODES = {
     "SelvaLoraScheduler":    (".selva_lora_scheduler",    "SelvaLoraScheduler",    "SelVA LoRA Scheduler"),
     "SelvaDatasetBrowser":   (".selva_dataset_browser",   "SelvaDatasetBrowser",   "SelVA Dataset Browser"),
     "SelvaSkipExperiment":   (".selva_skip_experiment",   "SelvaSkipExperiment",   "SelVA Skip Experiment"),
+    "SelvaLoraEvaluator":    (".selva_lora_evaluator",    "SelvaLoraEvaluator",    "SelVA LoRA Evaluator"),
 }
 
 for key, (module_path, class_name, display_name) in _NODES.items():