tfm_ainventory/frontend/tests/hooks/useAIExtraction.test.ts

import { renderHook, act } from '@testing-library/react';
import { describe, it, expect, vi, beforeEach, afterEach } from 'vitest';
import { useAIExtraction } from '@/hooks/useAIExtraction';
import * as api from '@/lib/api';
import { toast } from 'react-hot-toast';

vi.mock('@/lib/api');
vi.mock('react-hot-toast');

describe('useAIExtraction', () => {
  const mockInventory = [
    { id: 1, name: 'Item 1', type: 'Type A', box_label: 'Box 1' },
    { id: 2, name: 'Item 2', type: 'Type B', box_label: 'Box 2' }
  ];

  const mockOnComplete = vi.fn();

  beforeEach(() => {
    vi.clearAllMocks();
    vi.mocked(api.inventoryApi.analyzeLabel).mockResolvedValue({
      items: [
        {
          name: 'Test Item',
          Item: 'Test Item',
          category: 'Electronics',
          Category: 'Electronics',
          type: 'Resistor',
          Type: 'Resistor',
          part_number: 'R-001',
          PartNr: 'R-001',
          image_processing: {
            crop_bounds: { x: 10, y: 20, width: 100, height: 100 },
            rotation_degrees: 0,
            confidence: 0.95
          }
        }
      ]
    });
  });

  describe('extractedImageBlob state', () => {
    it('should initialize extractedImageBlob as null', () => {
      const { result } = renderHook(() =>
        useAIExtraction(mockInventory, mockOnComplete)
      );

      expect(result.current.extractedImageBlob).toBeNull();
    });

    it('should store blob after processImage fetches from data URL', async () => {
      const { result } = renderHook(() =>
        useAIExtraction(mockInventory, mockOnComplete)
      );

      const mockBlob = new Blob(['fake image data'], { type: 'image/jpeg' });
      const dataURL = 'data:image/jpeg;base64,abc123';

      global.fetch = vi.fn().mockResolvedValue({
        blob: vi.fn().mockResolvedValue(mockBlob)
      });

      act(() => {
        result.current.setImage(dataURL);
      });

      await act(async () => {
        await result.current.processImage();
      });

      expect(result.current.extractedImageBlob).toBe(mockBlob);
    });

    it('should allow manual setExtractedImageBlob', () => {
      const { result } = renderHook(() =>
        useAIExtraction(mockInventory, mockOnComplete)
      );

      const testBlob = new Blob(['test data'], { type: 'image/jpeg' });

      act(() => {
        result.current.setExtractedImageBlob(testBlob);
      });

      expect(result.current.extractedImageBlob).toBe(testBlob);
    });

    it('should allow clearing extractedImageBlob by setting to null', async () => {
      const { result } = renderHook(() =>
        useAIExtraction(mockInventory, mockOnComplete)
      );

      const mockBlob = new Blob(['test'], { type: 'image/jpeg' });

      act(() => {
        result.current.setExtractedImageBlob(mockBlob);
      });

      expect(result.current.extractedImageBlob).toBe(mockBlob);

      act(() => {
        result.current.setExtractedImageBlob(null);
      });

      expect(result.current.extractedImageBlob).toBeNull();
    });
  });

  describe('extractedItems with image_processing metadata', () => {
    it('should store extractedItems with image_processing from AI response', async () => {
      const { result } = renderHook(() =>
        useAIExtraction(mockInventory, mockOnComplete)
      );

      const mockBlob = new Blob(['image'], { type: 'image/jpeg' });
      const dataURL = 'data:image/jpeg;base64,abc123';

      global.fetch = vi.fn().mockResolvedValue({
        blob: vi.fn().mockResolvedValue(mockBlob)
      });

      act(() => {
        result.current.setImage(dataURL);
      });

      await act(async () => {
        await result.current.processImage();
      });

      expect(result.current.extractedItems).toHaveLength(1);
      expect(result.current.extractedItems[0]).toMatchObject({
        name: 'Test Item',
        category: 'Electronics',
        type: 'Resistor',
        part_number: 'R-001',
        image_processing: {
          crop_bounds: { x: 10, y: 20, width: 100, height: 100 },
          rotation_degrees: 0,
          confidence: 0.95
        }
      });
    });

    it('should preserve image_processing when handling wrapped AI responses', () => {
      const { result } = renderHook(() =>
        useAIExtraction(mockInventory, mockOnComplete)
      );

      // Test that the hook properly handles items with image_processing metadata
      const itemWithMetadata = {
        Item: 'Test Item',
        name: 'Test Item',
        image_processing: {
          crop_bounds: { x: 5, y: 15, width: 200, height: 150 },
          rotation_degrees: 90,
          confidence: 0.87
        }
      };

      act(() => {
        result.current.setExtractedItems([itemWithMetadata]);
      });

      expect(result.current.extractedItems[0].image_processing).toEqual({
        crop_bounds: { x: 5, y: 15, width: 200, height: 150 },
        rotation_degrees: 90,
        confidence: 0.87
      });
    });

    it('should handle multiple items each with independent image_processing', async () => {
      (api.inventoryApi.analyzeLabel as any).mockResolvedValue({
        items: [
          {
            name: 'Item 1',
            Item: 'Item 1',
            image_processing: {
              crop_bounds: { x: 0, y: 0, width: 100, height: 100 },
              rotation_degrees: 0,
              confidence: 0.9
            }
          },
          {
            name: 'Item 2',
            Item: 'Item 2',
            image_processing: {
              crop_bounds: { x: 110, y: 0, width: 100, height: 100 },
              rotation_degrees: 45,
              confidence: 0.85
            }
          }
        ]
      });

      const { result } = renderHook(() =>
        useAIExtraction(mockInventory, mockOnComplete)
      );

      const mockBlob = new Blob(['image'], { type: 'image/jpeg' });
      const dataURL = 'data:image/jpeg;base64,multi123';

      global.fetch = vi.fn().mockResolvedValue({
        blob: vi.fn().mockResolvedValue(mockBlob)
      });

      act(() => {
        result.current.setImage(dataURL);
      });

      await act(async () => {
        await result.current.processImage();
      });

      expect(result.current.extractedItems).toHaveLength(2);
      expect(result.current.extractedItems[0].image_processing.crop_bounds).toEqual({
        x: 0,
        y: 0,
        width: 100,
        height: 100
      });
      expect(result.current.extractedItems[1].image_processing.crop_bounds).toEqual({
        x: 110,
        y: 0,
        width: 100,
        height: 100
      });
    });
  });

  describe('blob and metadata together', () => {
    it('should store both blob and image_processing for use in photo upload', async () => {
      const { result } = renderHook(() =>
        useAIExtraction(mockInventory, mockOnComplete)
      );

      const mockBlob = new Blob(['image data'], { type: 'image/jpeg' });
      const dataURL = 'data:image/jpeg;base64,together123';

      global.fetch = vi.fn().mockResolvedValue({
        blob: vi.fn().mockResolvedValue(mockBlob)
      });

      act(() => {
        result.current.setImage(dataURL);
      });

      await act(async () => {
        await result.current.processImage();
      });

      // Both blob and metadata should be available
      expect(result.current.extractedImageBlob).toBe(mockBlob);
      expect(result.current.extractedItems).toHaveLength(1);

      const item = result.current.extractedItems[0];
      expect(item.image_processing).toBeDefined();
      expect(item.image_processing.crop_bounds).toBeDefined();
    });

    it('should maintain blob when extractedItems are updated', async () => {
      const { result } = renderHook(() =>
        useAIExtraction(mockInventory, mockOnComplete)
      );

      const mockBlob = new Blob(['image'], { type: 'image/jpeg' });
      const dataURL = 'data:image/jpeg;base64,maintain123';

      global.fetch = vi.fn().mockResolvedValue({
        blob: vi.fn().mockResolvedValue(mockBlob)
      });

      act(() => {
        result.current.setImage(dataURL);
      });

      await act(async () => {
        await result.current.processImage();
      });

      const originalBlob = result.current.extractedImageBlob;

      act(() => {
        result.current.updateEditingItem({ name: 'Updated Name' });
      });

      expect(result.current.extractedImageBlob).toBe(originalBlob);
    });
  });

  describe('cleanup and reset', () => {
    it('should clear extractedImageBlob when resetting extracted items', async () => {
      const { result } = renderHook(() =>
        useAIExtraction(mockInventory, mockOnComplete)
      );

      const mockBlob = new Blob(['image'], { type: 'image/jpeg' });
      const dataURL = 'data:image/jpeg;base64,reset123';

      global.fetch = vi.fn().mockResolvedValue({
        blob: vi.fn().mockResolvedValue(mockBlob)
      });

      act(() => {
        result.current.setImage(dataURL);
      });

      await act(async () => {
        await result.current.processImage();
      });

      expect(result.current.extractedImageBlob).toBe(mockBlob);

      act(() => {
        result.current.setExtractedItems([]);
        result.current.setExtractedImageBlob(null);
      });

      expect(result.current.extractedItems).toHaveLength(0);
      expect(result.current.extractedImageBlob).toBeNull();
    });

    it('should allow resetting image without affecting blob storage', () => {
      const { result } = renderHook(() =>
        useAIExtraction(mockInventory, mockOnComplete)
      );

      const mockBlob = new Blob(['image'], { type: 'image/jpeg' });

      act(() => {
        result.current.setExtractedImageBlob(mockBlob);
        result.current.setImage('data:image/jpeg;base64,somedata');
      });

      expect(result.current.extractedImageBlob).toBe(mockBlob);
      expect(result.current.image).toBe('data:image/jpeg;base64,somedata');

      act(() => {
        result.current.setImage(null);
      });

      expect(result.current.extractedImageBlob).toBe(mockBlob);
      expect(result.current.image).toBeNull();
    });
  });

  describe('error handling', () => {
    it('should not set extractedImageBlob if fetch fails', async () => {
      const { result } = renderHook(() =>
        useAIExtraction(mockInventory, mockOnComplete)
      );

      const dataURL = 'data:image/jpeg;base64,error123';
      global.fetch = vi.fn().mockRejectedValue(new Error('Fetch failed'));

      act(() => {
        result.current.setImage(dataURL);
      });

      await act(async () => {
        await result.current.processImage();
      });

      expect(result.current.extractedImageBlob).toBeNull();
    });

    it('should not set extractedImageBlob if blob conversion fails', async () => {
      const { result } = renderHook(() =>
        useAIExtraction(mockInventory, mockOnComplete)
      );

      const dataURL = 'data:image/jpeg;base64,blobfail123';
      global.fetch = vi.fn().mockResolvedValue({
        blob: vi.fn().mockRejectedValue(new Error('Blob conversion failed'))
      });

      act(() => {
        result.current.setImage(dataURL);
      });

      await act(async () => {
        await result.current.processImage();
      });

      expect(result.current.extractedImageBlob).toBeNull();
    });
  });

  describe('accessibility for photo upload', () => {
    it('should provide extractedImageBlob as FormData-ready Blob for later photo upload', async () => {
      const { result } = renderHook(() =>
        useAIExtraction(mockInventory, mockOnComplete)
      );

      const mockBlob = new Blob(['fake jpeg data'], { type: 'image/jpeg' });
      const dataURL = 'data:image/jpeg;base64,formdata123';

      global.fetch = vi.fn().mockResolvedValue({
        blob: vi.fn().mockResolvedValue(mockBlob)
      });

      act(() => {
        result.current.setImage(dataURL);
      });

      await act(async () => {
        await result.current.processImage();
      });

      // Blob should be usable in FormData
      const formData = new FormData();
      formData.append('file', result.current.extractedImageBlob!, 'photo.jpg');

      // FormData converts Blob to File, but content should be accessible
      const fileEntry = formData.get('file');
      expect(fileEntry).toBeTruthy();
      expect(fileEntry instanceof Blob || fileEntry instanceof File).toBe(true);
    });

    it('should preserve blob size and type for upload validation', async () => {
      const { result } = renderHook(() =>
        useAIExtraction(mockInventory, mockOnComplete)
      );

      const blobData = new Uint8Array(5000); // 5KB blob
      const mockBlob = new Blob([blobData], { type: 'image/jpeg' });
      const dataURL = 'data:image/jpeg;base64,size123';

      global.fetch = vi.fn().mockResolvedValue({
        blob: vi.fn().mockResolvedValue(mockBlob)
      });

      act(() => {
        result.current.setImage(dataURL);
      });

      await act(async () => {
        await result.current.processImage();
      });

      expect(result.current.extractedImageBlob?.size).toBe(5000);
      expect(result.current.extractedImageBlob?.type).toBe('image/jpeg');
    });
  });
});