one lazy ai

src/routes/ai.test.ts

@@ -58,48 +58,6 @@ describe('AI Routes (/api/ai)', () => {
       });
   });
 
-  describe('POST /process-flyer', () => {
-    it('should process an uploaded flyer image and return extracted data', async () => {
-      // Arrange:
-      // 1. Define the mock data the AI service will "extract".
-      const mockExtractedData = {
-        store_name: 'Test Store',
-        items: [{ item: 'Test Item', price_display: '$1.99' }],
-      } as Awaited<ReturnType<typeof aiService.extractCoreDataFromFlyerImage>>;
-      mockedAiService.extractCoreDataFromFlyerImage.mockResolvedValue(mockExtractedData);
-
-      // 2. Define the other form fields that are sent along with the file.
-      const mockMasterItems = [{ master_item_id: 1, item_name: 'Milk' }];
-
-      // 3. Define the path to a dummy file to upload.
-      // The path is resolved from the current file's directory (`src/routes`) to the assets directory.
-      const imagePath = path.resolve(__dirname, '../tests/assets/test-flyer-image.jpg');
-
-      // Act:
-      // Use supertest to build the multipart/form-data request.
-      const response = await supertest(app)
-        .post('/api/ai/process-flyer')
-        .field('masterItems', JSON.stringify(mockMasterItems)) // Attach regular form fields
-        .attach('flyerImages', imagePath); // Attach the file for upload
-
-      // Assert:
-      // 1. Check for a successful HTTP status.
-      expect(response.status).toBe(200);
-
-      // 2. Verify the AI service was called correctly by the route handler.
-      // Multer adds properties like 'path' to the file object. We check that the service
-      // received an array of files with these properties.
-      expect(mockedAiService.extractCoreDataFromFlyerImage).toHaveBeenCalledTimes(1);
-      expect(mockedAiService.extractCoreDataFromFlyerImage).toHaveBeenCalledWith(
-        expect.arrayContaining([expect.objectContaining({ mimetype: 'image/jpeg' })]),
-        mockMasterItems
-      );
-
-      // 3. Ensure the response body contains the data we mocked.
-      expect(response.body.data).toEqual(mockExtractedData);
-    });
-  });
-
   describe('POST /flyers/process', () => {
     const imagePath = path.resolve(__dirname, '../tests/assets/test-flyer-image.jpg');
     const mockDataPayload = {

src/routes/ai.ts

@@ -127,47 +127,7 @@ router.get('/jobs/:jobId/status', async (req, res) => {
     res.json({ id: job.id, state, progress, returnValue, failedReason });
 });
 
-/**
- * This endpoint processes a flyer using AI. It uses `optionalAuth` middleware to allow
- * both authenticated and anonymous users to upload flyers.
- */
-router.post('/process-flyer', optionalAuth, uploadToDisk.array('flyerImages'), async (req: Request, res: Response, next: NextFunction) => {
-    try {
-        const files = req.files as Express.Multer.File[];
-        const totalSize = files ? files.reduce((acc, file) => acc + file.size, 0) : 0;
-        const totalSizeMB = (totalSize / (1024 * 1024)).toFixed(2);
 
-        // --- AI ROUTE DEBUG LOGGING ---
-        logger.debug('[API /ai/process-flyer] Request received.');
-        logger.debug(`[API /ai/process-flyer] Files received: ${files ? files.length : 0}. Total size: ${totalSizeMB} MB.`);
-        // --- END DEBUG LOGGING ---
-
-        if (!req.files || !Array.isArray(req.files) || req.files.length === 0) {
-            return res.status(400).json({ message: 'Flyer image files are required.' });
-        }
-
-        const masterItems = JSON.parse(req.body.masterItems);
-        const imagePaths = (req.files as Express.Multer.File[]).map(file => ({
-            path: file.path,
-            mimetype: file.mimetype
-        }));
-
-        logger.debug(`[API /ai/process-flyer] Processing image paths:`, { imagePaths });
-
-        const user = req.user as UserProfile | undefined;
-        const logIdentifier = user ? `user ID: ${user.user_id}` : 'anonymous user';
-
-        logger.info(`Starting AI flyer data extraction for ${imagePaths.length} image(s) for ${logIdentifier}.`);
-
-        const extractedData = await aiService.extractCoreDataFromFlyerImage(imagePaths, masterItems);
-        logger.info(`Completed AI flyer data extraction. Found ${extractedData.items.length} items.`);
-
-        res.status(200).json({ data: extractedData });
-    } catch (error) {
-        logger.error('Error in /api/ai/process-flyer endpoint:', { error });
-        next(error);
-    }
-});
 
 /**
  * This endpoint saves the processed flyer data to the database. It is the final step