moving

packages/hive-mind-core/tests/mind/helpers/mock-embedder.ts

@@ -0,0 +1,50 @@
+import type { Embedder } from '../../../src/mind/embeddings.js';
+
+/**
+ * Deterministic mock embedder for testing.
+ * Generates embeddings based on word overlap so that semantically
+ * similar texts produce similar vectors.
+ */
+export class MockEmbedder implements Embedder {
+  dimensions = 1024;
+
+  async embed(text: string): Promise<Float32Array> {
+    return this.textToVector(text);
+  }
+
+  async embedBatch(texts: string[]): Promise<Float32Array[]> {
+    return texts.map(t => this.textToVector(t));
+  }
+
+  private textToVector(text: string): Float32Array {
+    const vec = new Float32Array(this.dimensions);
+    const words = text.toLowerCase().split(/\s+/);
+
+    for (const word of words) {
+      // Hash each word to a set of dimensions and add a value
+      const hash = this.simpleHash(word);
+      for (let i = 0; i < 8; i++) {
+        const idx = (hash + i * 127) % this.dimensions;
+        vec[idx] += 1.0;
+      }
+    }
+
+    // Normalize to unit vector
+    let norm = 0;
+    for (let i = 0; i < this.dimensions; i++) norm += vec[i] * vec[i];
+    norm = Math.sqrt(norm);
+    if (norm > 0) {
+      for (let i = 0; i < this.dimensions; i++) vec[i] /= norm;
+    }
+
+    return vec;
+  }
+
+  private simpleHash(str: string): number {
+    let hash = 0;
+    for (let i = 0; i < str.length; i++) {
+      hash = ((hash << 5) - hash + str.charCodeAt(i)) | 0;
+    }
+    return Math.abs(hash);
+  }
+}