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')
  })
})