feat(TRUEREF-0007): implement pluggable embedding generation and vector storage

Add EmbeddingProvider interface with OpenAI-compatible, local (optional
@xenova/transformers via dynamic import), and Noop (FTS5-only fallback)
implementations. EmbeddingService batches requests and persists Float32Array
blobs to snippet_embeddings. GET/PUT /api/v1/settings/embedding endpoints
read and write embedding config from the settings table.

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

src/lib/server/embeddings/local.provider.ts

@@ -0,0 +1,61 @@
+/**
+ * LocalEmbeddingProvider — uses @xenova/transformers (optional dependency).
+ *
+ * @xenova/transformers is NOT installed by default. This provider uses a
+ * dynamic import so the module is only required at runtime when the local
+ * provider is actually configured. If the package is absent, isAvailable()
+ * returns false and embed() throws a clear error.
+ */
+
+import { EmbeddingError, type EmbeddingProvider, type EmbeddingVector } from './provider.js';
+
+export class LocalEmbeddingProvider implements EmbeddingProvider {
+	readonly name = 'local';
+	readonly model = 'Xenova/all-MiniLM-L6-v2';
+	readonly dimensions = 384;
+
+	// eslint-disable-next-line @typescript-eslint/no-explicit-any
+	private pipeline: ((text: string, options: Record<string, unknown>) => Promise<any>) | null =
+		null;
+
+	async embed(texts: string[]): Promise<EmbeddingVector[]> {
+		if (!this.pipeline) {
+			let transformers: { pipeline: Function };
+			try {
+				// Dynamic import — only succeeds when @xenova/transformers is installed.
+				// eslint-disable-next-line @typescript-eslint/no-explicit-any
+				transformers = (await import('@xenova/transformers' as any)) as {
+					pipeline: Function;
+				};
+			} catch {
+				throw new EmbeddingError(
+					'@xenova/transformers is not installed. Install it to use the local embedding provider.'
+				);
+			}
+			this.pipeline = await transformers.pipeline('feature-extraction', this.model);
+		}
+
+		const results: EmbeddingVector[] = [];
+		for (const text of texts) {
+			const output = await this.pipeline!(text, {
+				pooling: 'mean',
+				normalize: true
+			});
+			results.push({
+				values: new Float32Array(output.data),
+				dimensions: this.dimensions,
+				model: this.model
+			});
+		}
+		return results;
+	}
+
+	async isAvailable(): Promise<boolean> {
+		try {
+			await import('@xenova/transformers' as never);
+			return true;
+		} catch {
+			return false;
+		}
+	}
+}