release(tiny-dancer): 0.1.21 — expose trainRouter to JS (types + bump)

Adds trainRouter/DracoRowJs/TrainRouterOptions/TrainRouterResult to the
hand-written index.d.ts and bumps to 0.1.21 (8 optionalDependencies lock-stepped)
so the native train_router export ships typed across all environments.

Co-Authored-By: claude-flow <ruv@ruv.net>

Author: ruvnet

npm/packages/tiny-dancer/index.d.ts

@@ -136,3 +136,58 @@ export function version(): string;
  * Test function to verify bindings are working
  */
 export function hello(): string;
+
+/**
+ * One DRACO training row: a query embedding and the quality each model achieved
+ * on it. Matches the `{ embedding, scores }` shape `@metaharness/router` consumes.
+ */
+export interface DracoRowJs {
+  /** Query embedding (used directly as the model's input features). */
+  embedding: number[];
+  /** model id → quality achieved on this query (0..1). */
+  scores: Record<string, number>;
+}
+
+/** Options for {@link trainRouter}. */
+export interface TrainRouterOptions {
+  /** Where to write the trained `.safetensors` model. */
+  outputPath: string;
+  /** Input feature dimension (must equal the embedding length). */
+  inputDim: number;
+  /** Hidden dimension (default 12). */
+  hiddenDim?: number;
+  /** Training epochs (default 40). */
+  epochs?: number;
+  /** Learning rate (default 0.05). */
+  learningRate?: number;
+  /** DRACO label tolerance: cheap model is "good enough" within this of the best (default 0.05). */
+  tolerance?: number;
+}
+
+/** Result of {@link trainRouter}. */
+export interface TrainRouterResult {
+  epochsRun: number;
+  trainLoss: number;
+  trainAccuracy: number;
+  valAccuracy: number;
+  modelPath: string;
+  modelBytes: number;
+}
+
+/**
+ * Train a FastGRNN router from a DRACO dataset and write it to a `.safetensors`
+ * file consumable by `new Router({ modelPath })`.
+ *
+ * @example
+ * ```javascript
+ * const res = await trainRouter(rows, { haiku: 1, opus: 15 }, {
+ *   outputPath: './router.safetensors', inputDim: 8, epochs: 40,
+ * });
+ * const router = new Router({ modelPath: res.modelPath });
+ * ```
+ */
+export function trainRouter(
+  rows: DracoRowJs[],
+  prices: Record<string, number>,
+  options: TrainRouterOptions
+): Promise<TrainRouterResult>;

npm/packages/tiny-dancer/package.json

@@ -1,6 +1,6 @@
 {
   "name": "@ruvector/tiny-dancer",
-  "version": "0.1.20",
+  "version": "0.1.21",
   "description": "Neural router for AI agent orchestration - FastGRNN-based intelligent routing with circuit breaker, uncertainty estimation, and hot-reload",
   "main": "index.js",
   "types": "index.d.ts",
@@ -31,14 +31,14 @@
     "@napi-rs/cli": "^2.18.0"
   },
   "optionalDependencies": {
-    "@ruvector/tiny-dancer-linux-x64-gnu": "0.1.20",
-    "@ruvector/tiny-dancer-linux-x64-musl": "0.1.20",
-    "@ruvector/tiny-dancer-linux-arm64-gnu": "0.1.20",
-    "@ruvector/tiny-dancer-linux-arm64-musl": "0.1.20",
-    "@ruvector/tiny-dancer-darwin-x64": "0.1.20",
-    "@ruvector/tiny-dancer-darwin-arm64": "0.1.20",
-    "@ruvector/tiny-dancer-win32-x64-msvc": "0.1.20",
-    "@ruvector/tiny-dancer-win32-arm64-msvc": "0.1.20"
+    "@ruvector/tiny-dancer-linux-x64-gnu": "0.1.21",
+    "@ruvector/tiny-dancer-linux-x64-musl": "0.1.21",
+    "@ruvector/tiny-dancer-linux-arm64-gnu": "0.1.21",
+    "@ruvector/tiny-dancer-linux-arm64-musl": "0.1.21",
+    "@ruvector/tiny-dancer-darwin-x64": "0.1.21",
+    "@ruvector/tiny-dancer-darwin-arm64": "0.1.21",
+    "@ruvector/tiny-dancer-win32-x64-msvc": "0.1.21",
+    "@ruvector/tiny-dancer-win32-arm64-msvc": "0.1.21"
   },
   "publishConfig": {
     "access": "public"