**test(tests): add comprehensive test suite for Brainy functionality**

- **New Tests Added**:
  - Introduced multiple test suites covering core functionalities (`core.test.ts`), vector operations (`vector-operations.test.ts`), Node.js environment (`environment.node.test.ts`), browser setup (`environment.browser.test.ts`), and TensorFlow.js-specific behaviors (`tensorflow-patch.test.ts`).
  - Added performance, scalability, and error-handling tests to ensure robust validation of vector addition, search, and text embedding functionalities.
  - Introduced setup utilities (`tests/setup.ts`) and standardized test utilities for creating predictable test cases.

- **Configuration**:
  - Created `vitest.config.ts` for custom test configurations, including support for modern test environments (`jsdom`, `happy-dom`) and extended timeouts for asynchronous operations.

- **Validation**:
  - Includes compatibility checks for TensorFlow.js imports and ensures proper handling of `TextEncoder`/`TextDecoder` in Node.js environments.

This commit significantly enhances the testing coverage and structure, ensuring Brainy functionality is robust, cross-platform, and aligned with evolving reliability standards.

tests/vector-operations.test.ts

@@ -0,0 +1,98 @@
+import { describe, it, expect } from 'vitest'
+
+describe('Vector Operations', () => {
+  it('should load brainy library successfully', async () => {
+    const brainy = await import('../dist/unified.js')
+    
+    expect(brainy).toBeDefined()
+    expect(typeof brainy.BrainyData).toBe('function')
+    expect(brainy.environment).toBeDefined()
+  })
+
+  it('should create and initialize BrainyData instance', async () => {
+    const brainy = await import('../dist/unified.js')
+    
+    const db = new brainy.BrainyData({
+      dimensions: 3,
+      metric: 'euclidean'
+    })
+    
+    expect(db).toBeDefined()
+    expect(db.dimensions).toBe(3)
+    
+    await db.init()
+    // If we get here without throwing, initialization was successful
+    expect(true).toBe(true)
+  })
+
+  it('should perform basic vector operations without TensorFlow', async () => {
+    const brainy = await import('../dist/unified.js')
+    
+    const db = new brainy.BrainyData({
+      dimensions: 3,
+      metric: 'euclidean'
+    })
+    
+    await db.init()
+    
+    // Add test vectors
+    await db.add([1, 0, 0], { id: 'x-axis', label: 'X axis vector' })
+    await db.add([0, 1, 0], { id: 'y-axis', label: 'Y axis vector' })
+    await db.add([0, 0, 1], { id: 'z-axis', label: 'Z axis vector' })
+    
+    // Search for similar vector
+    const results = await db.search([1, 0, 0], 1)
+    
+    expect(results).toBeDefined()
+    expect(results.length).toBeGreaterThan(0)
+    expect(results[0].metadata.id).toBe('x-axis')
+  })
+
+  it('should handle simple 2D vector operations', async () => {
+    const brainy = await import('../dist/unified.js')
+    
+    const db = new brainy.BrainyData({
+      dimensions: 2,
+      metric: 'euclidean'
+    })
+    
+    await db.init()
+    
+    // Add a simple vector
+    await db.add([1, 2], { id: 'test' })
+    
+    // Search for the same vector
+    const results = await db.search([1, 2], 1)
+    
+    expect(results).toBeDefined()
+    expect(results.length).toBeGreaterThan(0)
+    expect(results[0].metadata.id).toBe('test')
+  })
+
+  it('should handle multiple vector searches correctly', async () => {
+    const brainy = await import('../dist/unified.js')
+    
+    const db = new brainy.BrainyData({
+      dimensions: 3,
+      metric: 'euclidean'
+    })
+    
+    await db.init()
+    
+    // Add multiple vectors
+    await db.add([1, 0, 0], { id: 'vec1', type: 'unit' })
+    await db.add([0, 1, 0], { id: 'vec2', type: 'unit' })
+    await db.add([0, 0, 1], { id: 'vec3', type: 'unit' })
+    await db.add([0.5, 0.5, 0], { id: 'vec4', type: 'mixed' })
+    
+    // Search for multiple results
+    const results = await db.search([1, 0, 0], 3)
+    
+    expect(results).toBeDefined()
+    expect(results.length).toBeGreaterThanOrEqual(1)
+    expect(results.length).toBeLessThanOrEqual(3)
+    
+    // The closest should be the exact match
+    expect(results[0].metadata.id).toBe('vec1')
+  })
+})