add ai agent fallbacks

src/App.test.tsx

@@ -243,9 +243,7 @@ describe('App Component', () => {
     mockedApiClient.fetchShoppingLists.mockImplementation(() =>
       Promise.resolve(new Response(JSON.stringify([]))),
     );
-    mockedAiApiClient.rescanImageArea.mockResolvedValue(
+    mockedAiApiClient.rescanImageArea.mockResolvedValue({ text: 'mocked text' }); // Mock for FlyerCorrectionTool
-      new Response(JSON.stringify({ text: 'mocked text' })),
-    ); // Mock for FlyerCorrectionTool
     console.log('[TEST DEBUG] beforeEach: Setup complete');
   });
 

src/features/flyer/FlyerUploader.test.tsx

@@ -73,12 +73,11 @@ describe('FlyerUploader', () => {
 
   it('should handle file upload and start polling', async () => {
     console.log('--- [TEST LOG] ---: 1. Setting up mocks for upload and polling.');
-    mockedAiApiClient.uploadAndProcessFlyer.mockResolvedValue(
+    mockedAiApiClient.uploadAndProcessFlyer.mockResolvedValue({ jobId: 'job-123' });
-      new Response(JSON.stringify({ jobId: 'job-123' }), { status: 200 }),
+    mockedAiApiClient.getJobStatus.mockResolvedValue({
-    );
+      state: 'active',
-    mockedAiApiClient.getJobStatus.mockResolvedValue(
+      progress: { message: 'Checking...' },
-      new Response(JSON.stringify({ state: 'active', progress: { message: 'Checking...' } })),
+    });
-    );
 
     console.log('--- [TEST LOG] ---: 2. Rendering component and preparing file.');
     renderComponent();
@@ -131,12 +130,11 @@ describe('FlyerUploader', () => {
 
   it('should handle file upload via drag and drop', async () => {
     console.log('--- [TEST LOG] ---: 1. Setting up mocks for drag and drop.');
-    mockedAiApiClient.uploadAndProcessFlyer.mockResolvedValue(
+    mockedAiApiClient.uploadAndProcessFlyer.mockResolvedValue({ jobId: 'job-dnd' });
-      new Response(JSON.stringify({ jobId: 'job-dnd' }), { status: 200 }),
+    mockedAiApiClient.getJobStatus.mockResolvedValue({
-    );
+      state: 'active',
-    mockedAiApiClient.getJobStatus.mockResolvedValue(
+      progress: { message: 'Dropped...' },
-      new Response(JSON.stringify({ state: 'active', progress: { message: 'Dropped...' } })),
+    });
-    );
 
     console.log('--- [TEST LOG] ---: 2. Rendering component and preparing file for drop.');
     renderComponent();
@@ -159,16 +157,10 @@ describe('FlyerUploader', () => {
   it('should poll for status, complete successfully, and redirect', async () => {
     const onProcessingComplete = vi.fn();
     console.log('--- [TEST LOG] ---: 1. Setting up mock sequence for polling.');
-    mockedAiApiClient.uploadAndProcessFlyer.mockResolvedValue(
+    mockedAiApiClient.uploadAndProcessFlyer.mockResolvedValue({ jobId: 'job-123' });
-      new Response(JSON.stringify({ jobId: 'job-123' }), { status: 200 }),
-    );
     mockedAiApiClient.getJobStatus
-      .mockResolvedValueOnce(
+      .mockResolvedValueOnce({ state: 'active', progress: { message: 'Analyzing...' } })
-        new Response(JSON.stringify({ state: 'active', progress: { message: 'Analyzing...' } })),
+      .mockResolvedValueOnce({ state: 'completed', returnValue: { flyerId: 42 } });
-      )
-      .mockResolvedValueOnce(
-        new Response(JSON.stringify({ state: 'completed', returnValue: { flyerId: 42 } })),
-      );
 
     console.log('--- [TEST LOG] ---: 2. Rendering component and uploading file.');
     renderComponent(onProcessingComplete);
@@ -229,12 +221,11 @@ describe('FlyerUploader', () => {
 
   it('should handle a failed job', async () => {
     console.log('--- [TEST LOG] ---: 1. Setting up mocks for a failed job.');
-    mockedAiApiClient.uploadAndProcessFlyer.mockResolvedValue(
+    mockedAiApiClient.uploadAndProcessFlyer.mockResolvedValue({ jobId: 'job-fail' });
-      new Response(JSON.stringify({ jobId: 'job-fail' }), { status: 200 }),
+    mockedAiApiClient.getJobStatus.mockResolvedValue({
-    );
+      state: 'failed',
-    mockedAiApiClient.getJobStatus.mockResolvedValue(
+      failedReason: 'AI model exploded',
-      new Response(JSON.stringify({ state: 'failed', failedReason: 'AI model exploded' })),
+    });
-    );
 
     console.log('--- [TEST LOG] ---: 2. Rendering and uploading.');
     renderComponent();
@@ -260,11 +251,82 @@ describe('FlyerUploader', () => {
     console.log('--- [TEST LOG] ---: 6. "Upload Another" button confirmed.');
   });
 
+  it('should clear the polling timeout when a job fails', async () => {
+    const clearTimeoutSpy = vi.spyOn(global, 'clearTimeout');
+    console.log('--- [TEST LOG] ---: 1. Setting up mocks for failed job timeout clearance.');
+    mockedAiApiClient.uploadAndProcessFlyer.mockResolvedValue({ jobId: 'job-fail-timeout' });
+
+    // We need at least one 'active' response to establish a timeout loop so we have something to clear
+    mockedAiApiClient.getJobStatus
+      .mockResolvedValueOnce({ state: 'active', progress: { message: 'Working...' } })
+      .mockResolvedValueOnce({ state: 'failed', failedReason: 'Fatal Error' });
+
+    renderComponent();
+    const file = new File(['content'], 'flyer.pdf', { type: 'application/pdf' });
+    const input = screen.getByLabelText(/click to select a file/i);
+
+    fireEvent.change(input, { target: { files: [file] } });
+
+    // Wait for the first poll to complete and UI to update to "Working..."
+    await screen.findByText('Working...');
+
+    // Advance time to trigger the second poll
+    await act(async () => {
+      vi.advanceTimersByTime(3000);
+    });
+
+    // Wait for the failure UI
+    await screen.findByText(/Processing failed: Fatal Error/i);
+
+    // Verify clearTimeout was called
+    expect(clearTimeoutSpy).toHaveBeenCalled();
+
+    // Verify no further polling occurs
+    const callsBefore = mockedAiApiClient.getJobStatus.mock.calls.length;
+    await act(async () => {
+      vi.advanceTimersByTime(10000);
+    });
+    expect(mockedAiApiClient.getJobStatus).toHaveBeenCalledTimes(callsBefore);
+
+    clearTimeoutSpy.mockRestore();
+  });
+
+  it('should clear the polling timeout when the component unmounts', async () => {
+    const clearTimeoutSpy = vi.spyOn(global, 'clearTimeout');
+    console.log('--- [TEST LOG] ---: 1. Setting up mocks for unmount timeout clearance.');
+    mockedAiApiClient.uploadAndProcessFlyer.mockResolvedValue({ jobId: 'job-unmount' });
+    mockedAiApiClient.getJobStatus.mockResolvedValue({
+      state: 'active',
+      progress: { message: 'Polling...' },
+    });
+
+    const { unmount } = renderComponent();
+    const file = new File(['content'], 'flyer.pdf', { type: 'application/pdf' });
+    const input = screen.getByLabelText(/click to select a file/i);
+
+    fireEvent.change(input, { target: { files: [file] } });
+
+    // Wait for the first poll to complete and the UI to show the polling state
+    await screen.findByText('Polling...');
+
+    // Now that we are in a polling state (and a timeout is set), unmount the component
+    console.log('--- [TEST LOG] ---: 2. Unmounting component to trigger cleanup effect.');
+    unmount();
+
+    // Verify that the cleanup function in the useEffect hook was called
+    expect(clearTimeoutSpy).toHaveBeenCalled();
+    console.log('--- [TEST LOG] ---: 3. clearTimeout confirmed.');
+
+    clearTimeoutSpy.mockRestore();
+  });
+
   it('should handle a duplicate flyer error (409)', async () => {
     console.log('--- [TEST LOG] ---: 1. Setting up mock for 409 duplicate error.');
-    mockedAiApiClient.uploadAndProcessFlyer.mockResolvedValue(
+    // The API client now throws a structured error for non-2xx responses.
-      new Response(JSON.stringify({ flyerId: 99, message: 'Duplicate' }), { status: 409 }),
+    mockedAiApiClient.uploadAndProcessFlyer.mockRejectedValue({
-    );
+      status: 409,
+      body: { flyerId: 99, message: 'Duplicate' },
+  });
 
     console.log('--- [TEST LOG] ---: 2. Rendering and uploading.');
     renderComponent();
@@ -295,12 +357,11 @@ describe('FlyerUploader', () => {
 
   it('should allow the user to stop watching progress', async () => {
     console.log('--- [TEST LOG] ---: 1. Setting up mocks for infinite polling.');
-    mockedAiApiClient.uploadAndProcessFlyer.mockResolvedValue(
+    mockedAiApiClient.uploadAndProcessFlyer.mockResolvedValue({ jobId: 'job-stop' });
-      new Response(JSON.stringify({ jobId: 'job-stop' }), { status: 200 }),
+    mockedAiApiClient.getJobStatus.mockResolvedValue({
-    );
+      state: 'active',
-    mockedAiApiClient.getJobStatus.mockResolvedValue(
+      progress: { message: 'Analyzing...' },
-      new Response(JSON.stringify({ state: 'active', progress: { message: 'Analyzing...' } })),
+    } as any);
-    );
 
     console.log('--- [TEST LOG] ---: 2. Rendering and uploading.');
     renderComponent();
@@ -362,9 +423,11 @@ describe('FlyerUploader', () => {
 
     it('should handle a generic network error during upload', async () => {
       console.log('--- [TEST LOG] ---: 1. Setting up mock for generic upload error.');
-      mockedAiApiClient.uploadAndProcessFlyer.mockRejectedValue(
+      // Simulate a structured error from the API client
-        new Error('Network Error During Upload'),
+      mockedAiApiClient.uploadAndProcessFlyer.mockRejectedValue({
-      );
+        status: 500,
+        body: { message: 'Network Error During Upload' },
+      });
       renderComponent();
       const file = new File(['content'], 'flyer.pdf', { type: 'application/pdf' });
       const input = screen.getByLabelText(/click to select a file/i);
@@ -379,9 +442,7 @@ describe('FlyerUploader', () => {
 
     it('should handle a generic network error during polling', async () => {
       console.log('--- [TEST LOG] ---: 1. Setting up mock for polling error.');
-      mockedAiApiClient.uploadAndProcessFlyer.mockResolvedValue(
+      mockedAiApiClient.uploadAndProcessFlyer.mockResolvedValue({ jobId: 'job-poll-fail' });
-        new Response(JSON.stringify({ jobId: 'job-poll-fail' }), { status: 200 }),
-      );
       mockedAiApiClient.getJobStatus.mockRejectedValue(new Error('Polling Network Error'));
 
       renderComponent();
@@ -398,11 +459,9 @@ describe('FlyerUploader', () => {
 
     it('should handle a completed job with a missing flyerId', async () => {
       console.log('--- [TEST LOG] ---: 1. Setting up mock for malformed completion payload.');
-      mockedAiApiClient.uploadAndProcessFlyer.mockResolvedValue(
+      mockedAiApiClient.uploadAndProcessFlyer.mockResolvedValue({ jobId: 'job-no-flyerid' });
-        new Response(JSON.stringify({ jobId: 'job-no-flyerid' }), { status: 200 }),
-      );
       mockedAiApiClient.getJobStatus.mockResolvedValue(
-        new Response(JSON.stringify({ state: 'completed', returnValue: {} })), // No flyerId
+      { state: 'completed', returnValue: {} }, // No flyerId
       );
 
       renderComponent();
@@ -419,6 +478,27 @@ describe('FlyerUploader', () => {
       console.log('--- [TEST LOG] ---: 4. Assertions passed.');
     });
 
+    it('should handle a non-JSON response during polling', async () => {
+      console.log('--- [TEST LOG] ---: 1. Setting up mock for non-JSON response.');
+      // The actual function would throw, so we mock the rejection.
+      // The new getJobStatus would throw an error like "Failed to parse JSON..."
+      mockedAiApiClient.uploadAndProcessFlyer.mockResolvedValue({ jobId: 'job-bad-json' });
+      mockedAiApiClient.getJobStatus.mockRejectedValue(
+        new Error('Failed to parse JSON response from server. Body: <html>502 Bad Gateway</html>'),
+      );
+
+      renderComponent();
+      const file = new File(['content'], 'flyer.pdf', { type: 'application/pdf' });
+      const input = screen.getByLabelText(/click to select a file/i);
+
+      console.log('--- [TEST LOG] ---: 2. Firing file change event.');
+      fireEvent.change(input, { target: { files: [file] } });
+
+      console.log('--- [TEST LOG] ---: 3. Awaiting error message.');
+      expect(await screen.findByText(/Failed to parse JSON response from server/i)).toBeInTheDocument();
+      console.log('--- [TEST LOG] ---: 4. Assertions passed.');
+    });
+
     it('should do nothing if the file input is cancelled', () => {
       renderComponent();
       const input = screen.getByLabelText(/click to select a file/i);

src/features/flyer/FlyerUploader.tsx

@@ -60,14 +60,8 @@ export const FlyerUploader: React.FC<FlyerUploaderProps> = ({ onProcessingComple
     const pollStatus = async () => {
       console.debug(`[DEBUG] pollStatus(): Polling for jobId: ${jobId}`);
       try {
-        const statusResponse = await getJobStatus(jobId);
+        const job = await getJobStatus(jobId); // Now returns parsed JSON directly
-        console.debug(`[DEBUG] pollStatus(): API response status: ${statusResponse.status}`);
+        console.debug('[DEBUG] pollStatus(): Job status received:', job); // The rest of the logic remains the same
-        if (!statusResponse.ok) {
-          throw new Error(`Failed to get job status (HTTP ${statusResponse.status})`);
-        }
-
-        const job = await statusResponse.json();
-        console.debug('[DEBUG] pollStatus(): Job status received:', job);
 
         if (job.progress) {
           setProcessingStages(job.progress.stages || []);
@@ -97,7 +91,13 @@ export const FlyerUploader: React.FC<FlyerUploaderProps> = ({ onProcessingComple
             console.debug(
               `[DEBUG] pollStatus(): Job state is "failed". Reason: ${job.failedReason}`,
             );
+            // Explicitly clear any pending timeout to stop the polling loop immediately.
+            if (pollingTimeoutRef.current) {
+              clearTimeout(pollingTimeoutRef.current);
+            }
             setErrorMessage(`Processing failed: ${job.failedReason || 'Unknown error'}`);
+            // Clear any stale "in-progress" messages to avoid user confusion.
+            setStatusMessage(null);
             setProcessingState('error');
             break;
 
@@ -150,29 +150,24 @@ export const FlyerUploader: React.FC<FlyerUploaderProps> = ({ onProcessingComple
         `[DEBUG] processFile(): Checksum generated: ${checksum}. Calling uploadAndProcessFlyer.`,
       );
 
-      const startResponse = await uploadAndProcessFlyer(file, checksum);
+      // The API client now returns parsed JSON on success or throws a structured error on failure.
-      console.debug(`[DEBUG] processFile(): Upload response status: ${startResponse.status}`);
+      const { jobId: newJobId } = await uploadAndProcessFlyer(file, checksum);
-
-      if (!startResponse.ok) {
-        const errorData = await startResponse.json();
-        console.debug('[DEBUG] processFile(): Upload failed. Error data:', errorData);
-        if (startResponse.status === 409 && errorData.flyerId) {
-          setErrorMessage(`This flyer has already been processed. You can view it here:`);
-          setDuplicateFlyerId(errorData.flyerId);
-        } else {
-          setErrorMessage(errorData.message || `Upload failed with status ${startResponse.status}`);
-        }
-        setProcessingState('error');
-        return;
-      }
-
-      const { jobId: newJobId } = await startResponse.json();
       console.debug(`[DEBUG] processFile(): Upload successful. Received jobId: ${newJobId}`);
       setJobId(newJobId);
       setProcessingState('polling');
-    } catch (error) {
+    } catch (error: any) {
-      logger.error('An unexpected error occurred during file upload:', { error });
+      // Handle the structured error thrown by the API client.
-      setErrorMessage(error instanceof Error ? error.message : 'An unexpected error occurred.');
+      logger.error('An error occurred during file upload:', { error });
+      // Handle 409 Conflict for duplicate flyers
+      if (error?.status === 409 && error.body?.flyerId) {
+        setErrorMessage(`This flyer has already been processed. You can view it here:`);
+        setDuplicateFlyerId(error.body.flyerId);
+      } else {
+        // Handle other errors (e.g., validation, server errors)
+        const message =
+          error?.body?.message || error?.message || 'An unexpected error occurred during upload.';
+        setErrorMessage(message);
+      }
       setProcessingState('error');
     }
   }, []);

src/services/aiAnalysisService.ts

@@ -1,15 +1,8 @@
 // src/services/aiAnalysisService.ts
-import { Flyer, FlyerItem, MasterGroceryItem, GroundedResponse, Source } from '../types';
+import { Flyer, FlyerItem, MasterGroceryItem, GroundedResponse } from '../types';
 import * as aiApiClient from './aiApiClient';
 import { logger } from './logger.client';
 
-interface RawSource {
-  web?: {
-    uri?: string;
-    title?: string;
-  };
-}
-
 /**
  * A service class to encapsulate all AI analysis API calls and related business logic.
  * This decouples the React components and hooks from the data fetching implementation.
@@ -22,7 +15,8 @@ export class AiAnalysisService {
    */
   async getQuickInsights(items: FlyerItem[]): Promise<string> {
     logger.info('[AiAnalysisService] getQuickInsights called.');
-    return aiApiClient.getQuickInsights(items).then((res) => res.json());
+    const result = await aiApiClient.getQuickInsights(items);
+    return result.text;
   }
 
   /**
@@ -32,7 +26,8 @@ export class AiAnalysisService {
    */
   async getDeepDiveAnalysis(items: FlyerItem[]): Promise<string> {
     logger.info('[AiAnalysisService] getDeepDiveAnalysis called.');
-    return aiApiClient.getDeepDiveAnalysis(items).then((res) => res.json());
+    const result = await aiApiClient.getDeepDiveAnalysis(items);
+    return result.text;
   }
 
   /**
@@ -44,18 +39,7 @@ export class AiAnalysisService {
     logger.info('[AiAnalysisService] searchWeb called.');
     // Construct a query string from the item names.
     const query = items.map((item) => item.item).join(', ');
-    // The API client returns a specific shape that we need to await the JSON from
+    return aiApiClient.searchWeb(query);
-    const response: { text: string; sources: RawSource[] } = await aiApiClient
-      .searchWeb(query)
-      .then((res) => res.json());
-    // Normalize sources to a consistent format.
-    const mappedSources = (response.sources || []).map(
-      (s: RawSource) =>
-        (s.web
-          ? { uri: s.web.uri || '', title: s.web.title || 'Untitled' }
-          : { uri: '', title: 'Untitled' }) as Source,
-    );
-    return { ...response, sources: mappedSources };
   }
 
   /**
@@ -68,7 +52,7 @@ export class AiAnalysisService {
     logger.info('[AiAnalysisService] planTripWithMaps called.');
     // Encapsulate geolocation logic within the service.
     const userLocation = await this.getCurrentLocation();
-    return aiApiClient.planTripWithMaps(items, store, userLocation).then((res) => res.json());
+    return aiApiClient.planTripWithMaps(items, store, userLocation);
   }
 
   /**
@@ -78,17 +62,7 @@ export class AiAnalysisService {
    */
   async compareWatchedItemPrices(watchedItems: MasterGroceryItem[]): Promise<GroundedResponse> {
     logger.info('[AiAnalysisService] compareWatchedItemPrices called.');
-    const response: { text: string; sources: RawSource[] } = await aiApiClient
+    return aiApiClient.compareWatchedItemPrices(watchedItems);
-      .compareWatchedItemPrices(watchedItems)
-      .then((res) => res.json());
-    // Normalize sources to a consistent format.
-    const mappedSources = (response.sources || []).map(
-      (s: RawSource) =>
-        (s.web
-          ? { uri: s.web.uri || '', title: s.web.title || 'Untitled' }
-          : { uri: '', title: 'Untitled' }) as Source,
-    );
-    return { ...response, sources: mappedSources };
   }
 
   /**
@@ -98,7 +72,8 @@ export class AiAnalysisService {
    */
   async generateImageFromText(prompt: string): Promise<string> {
     logger.info('[AiAnalysisService] generateImageFromText called.');
-    return aiApiClient.generateImageFromText(prompt).then((res) => res.json());
+    const result = await aiApiClient.generateImageFromText(prompt);
+    return result.imageUrl;
   }
 
   /**

src/services/aiApiClient.ts

@@ -4,7 +4,13 @@
  * It communicates with the application's own backend endpoints, which then securely
  * call the Google AI services. This ensures no API keys are exposed on the client.
  */
-import type { FlyerItem, Store, MasterGroceryItem } from '../types';
+import type {
+  FlyerItem,
+  Store,
+  MasterGroceryItem,
+  ProcessingStage,
+  GroundedResponse,
+} from '../types';
 import { logger } from './logger.client';
 import { apiFetch } from './apiClient';
 
@@ -20,14 +26,14 @@ export const uploadAndProcessFlyer = async (
   file: File,
   checksum: string,
   tokenOverride?: string,
-): Promise<Response> => {
+): Promise<{ jobId: string }> => {
   const formData = new FormData();
   formData.append('flyerFile', file);
   formData.append('checksum', checksum);
 
   logger.info(`[aiApiClient] Starting background processing for file: ${file.name}`);
 
-  return apiFetch(
+  const response = await apiFetch(
     '/ai/upload-and-process',
     {
       method: 'POST',
@@ -35,26 +41,79 @@ export const uploadAndProcessFlyer = async (
     },
     { tokenOverride },
   );
+
+  if (!response.ok) {
+    let errorBody;
+    try {
+      errorBody = await response.json();
+    } catch (e) {
+      errorBody = { message: await response.text() };
+    }
+    // Throw a structured error so the component can inspect the status and body
+    throw { status: response.status, body: errorBody };
+  }
+
+  return response.json();
 };
 
+// Define the expected shape of the job status response
+export interface JobStatus {
+  id: string;
+  state: 'completed' | 'failed' | 'active' | 'waiting' | 'delayed' | 'paused';
+  progress: {
+    stages?: ProcessingStage[];
+    estimatedTimeRemaining?: number;
+    message?: string;
+  } | null;
+  returnValue: {
+    flyerId?: number;
+  } | null;
+  failedReason: string | null;
+}
+
 /**
  * Fetches the status of a background processing job.
  * This is the second step in the new background processing flow.
  * @param jobId The ID of the job to check.
  * @param tokenOverride Optional token for testing.
- * @returns A promise that resolves to the API response with the job's status.
+ * @returns A promise that resolves to the parsed job status object.
+ * @throws An error if the network request fails or if the response is not valid JSON.
  */
-export const getJobStatus = async (jobId: string, tokenOverride?: string): Promise<Response> => {
+export const getJobStatus = async (
-  return apiFetch(`/ai/jobs/${jobId}/status`, {}, { tokenOverride });
+  jobId: string,
+  tokenOverride?: string,
+): Promise<JobStatus> => {
+  const response = await apiFetch(`/ai/jobs/${jobId}/status`, {}, { tokenOverride });
+
+  if (!response.ok) {
+    let errorText = `API Error: ${response.status} ${response.statusText}`;
+    try {
+      const errorBody = await response.text();
+      if (errorBody) errorText = `API Error ${response.status}: ${errorBody}`;
+    } catch (e) {
+      // ignore if reading body fails
+    }
+    throw new Error(errorText);
+  }
+
+  try {
+    return await response.json();
+  } catch (error) {
+    const rawText = await response.text();
+    throw new Error(`Failed to parse JSON response from server. Body: ${rawText}`);
+  }
 };
 
-export const isImageAFlyer = async (imageFile: File, tokenOverride?: string): Promise<Response> => {
+export const isImageAFlyer = async (
+  imageFile: File,
+  tokenOverride?: string,
+): Promise<{ is_flyer: boolean }> => {
   const formData = new FormData();
   formData.append('image', imageFile);
 
   // Use apiFetchWithAuth for FormData to let the browser set the correct Content-Type.
   // The URL must be relative, as the helper constructs the full path.
-  return apiFetch(
+  const response = await apiFetch(
     '/ai/check-flyer',
     {
       method: 'POST',
@@ -62,16 +121,28 @@ export const isImageAFlyer = async (imageFile: File, tokenOverride?: string): Pr
     },
     { tokenOverride },
   );
+
+  if (!response.ok) {
+    let errorBody;
+    try {
+      errorBody = await response.json();
+    } catch (e) {
+      errorBody = { message: await response.text() };
+    }
+    throw { status: response.status, body: errorBody };
+  }
+
+  return response.json();
 };
 
 export const extractAddressFromImage = async (
   imageFile: File,
   tokenOverride?: string,
-): Promise<Response> => {
+): Promise<{ address: string }> => {
   const formData = new FormData();
   formData.append('image', imageFile);
 
-  return apiFetch(
+  const response = await apiFetch(
     '/ai/extract-address',
     {
       method: 'POST',
@@ -79,18 +150,30 @@ export const extractAddressFromImage = async (
     },
     { tokenOverride },
   );
+
+  if (!response.ok) {
+    let errorBody;
+    try {
+      errorBody = await response.json();
+    } catch (e) {
+      errorBody = { message: await response.text() };
+    }
+    throw { status: response.status, body: errorBody };
+  }
+
+  return response.json();
 };
 
 export const extractLogoFromImage = async (
   imageFiles: File[],
   tokenOverride?: string,
-): Promise<Response> => {
+): Promise<{ store_logo_base_64: string | null }> => {
   const formData = new FormData();
   imageFiles.forEach((file) => {
     formData.append('images', file);
   });
 
-  return apiFetch(
+  const response = await apiFetch(
     '/ai/extract-logo',
     {
       method: 'POST',
@@ -98,14 +181,26 @@ export const extractLogoFromImage = async (
     },
     { tokenOverride },
   );
+
+  if (!response.ok) {
+    let errorBody;
+    try {
+      errorBody = await response.json();
+    } catch (e) {
+      errorBody = { message: await response.text() };
+    }
+    throw { status: response.status, body: errorBody };
+  }
+
+  return response.json();
 };
 
 export const getQuickInsights = async (
   items: Partial<FlyerItem>[],
   signal?: AbortSignal,
   tokenOverride?: string,
-): Promise<Response> => {
+): Promise<{ text: string }> => {
-  return apiFetch(
+  const response = await apiFetch(
     '/ai/quick-insights',
     {
       method: 'POST',
@@ -115,14 +210,26 @@ export const getQuickInsights = async (
     },
     { tokenOverride, signal },
   );
+
+  if (!response.ok) {
+    let errorBody;
+    try {
+      errorBody = await response.json();
+    } catch (e) {
+      errorBody = { message: await response.text() };
+    }
+    throw { status: response.status, body: errorBody };
+  }
+
+  return response.json();
 };
 
 export const getDeepDiveAnalysis = async (
   items: Partial<FlyerItem>[],
   signal?: AbortSignal,
   tokenOverride?: string,
-): Promise<Response> => {
+): Promise<{ text: string }> => {
-  return apiFetch(
+  const response = await apiFetch(
     '/ai/deep-dive',
     {
       method: 'POST',
@@ -132,14 +239,26 @@ export const getDeepDiveAnalysis = async (
     },
     { tokenOverride, signal },
   );
+
+  if (!response.ok) {
+    let errorBody;
+    try {
+      errorBody = await response.json();
+    } catch (e) {
+      errorBody = { message: await response.text() };
+    }
+    throw { status: response.status, body: errorBody };
+  }
+
+  return response.json();
 };
 
 export const searchWeb = async (
   query: string,
   signal?: AbortSignal,
   tokenOverride?: string,
-): Promise<Response> => {
+): Promise<GroundedResponse> => {
-  return apiFetch(
+  const response = await apiFetch(
     '/ai/search-web',
     {
       method: 'POST',
@@ -149,6 +268,18 @@ export const searchWeb = async (
     },
     { tokenOverride, signal },
   );
+
+  if (!response.ok) {
+    let errorBody;
+    try {
+      errorBody = await response.json();
+    } catch (e) {
+      errorBody = { message: await response.text() };
+    }
+    throw { status: response.status, body: errorBody };
+  }
+
+  return response.json();
 };
 
 // ============================================================================
@@ -161,9 +292,9 @@ export const planTripWithMaps = async (
   userLocation: GeolocationCoordinates,
   signal?: AbortSignal,
   tokenOverride?: string,
-): Promise<Response> => {
+): Promise<GroundedResponse> => {
   logger.debug('Stub: planTripWithMaps called with location:', { userLocation });
-  return apiFetch(
+  const response = await apiFetch(
     '/ai/plan-trip',
     {
       method: 'POST',
@@ -172,6 +303,18 @@ export const planTripWithMaps = async (
     },
     { signal, tokenOverride },
   );
+
+  if (!response.ok) {
+    let errorBody;
+    try {
+      errorBody = await response.json();
+    } catch (e) {
+      errorBody = { message: await response.text() };
+    }
+    throw { status: response.status, body: errorBody };
+  }
+
+  return response.json();
 };
 
 /**
@@ -183,9 +326,9 @@ export const generateImageFromText = async (
   prompt: string,
   signal?: AbortSignal,
   tokenOverride?: string,
-): Promise<Response> => {
+): Promise<{ imageUrl: string }> => {
   logger.debug('Stub: generateImageFromText called with prompt:', { prompt });
-  return apiFetch(
+  const response = await apiFetch(
     '/ai/generate-image',
     {
       method: 'POST',
@@ -195,6 +338,18 @@ export const generateImageFromText = async (
     },
     { tokenOverride, signal },
   );
+
+  if (!response.ok) {
+    let errorBody;
+    try {
+      errorBody = await response.json();
+    } catch (e) {
+      errorBody = { message: await response.text() };
+    }
+    throw { status: response.status, body: errorBody };
+  }
+
+  return response.json();
 };
 
 /**
@@ -206,9 +361,9 @@ export const generateSpeechFromText = async (
   text: string,
   signal?: AbortSignal,
   tokenOverride?: string,
-): Promise<Response> => {
+): Promise<{ audioUrl: string }> => {
   logger.debug('Stub: generateSpeechFromText called with text:', { text });
-  return apiFetch(
+  const response = await apiFetch(
     '/ai/generate-speech',
     {
       method: 'POST',
@@ -218,6 +373,18 @@ export const generateSpeechFromText = async (
     },
     { tokenOverride, signal },
   );
+
+  if (!response.ok) {
+    let errorBody;
+    try {
+      errorBody = await response.json();
+    } catch (e) {
+      errorBody = { message: await response.text() };
+    }
+    throw { status: response.status, body: errorBody };
+  }
+
+  return response.json();
 };
 
 /**
@@ -264,13 +431,29 @@ export const rescanImageArea = async (
   cropArea: { x: number; y: number; width: number; height: number },
   extractionType: 'store_name' | 'dates' | 'item_details',
   tokenOverride?: string,
-): Promise<Response> => {
+): Promise<{ text: string | undefined }> => {
   const formData = new FormData();
   formData.append('image', imageFile);
   formData.append('cropArea', JSON.stringify(cropArea));
   formData.append('extractionType', extractionType);
 
-  return apiFetch('/ai/rescan-area', { method: 'POST', body: formData }, { tokenOverride });
+  const response = await apiFetch(
+    '/ai/rescan-area',
+    { method: 'POST', body: formData },
+    { tokenOverride },
+  );
+
+  if (!response.ok) {
+    let errorBody;
+    try {
+      errorBody = await response.json();
+    } catch (e) {
+      errorBody = { message: await response.text() };
+    }
+    throw { status: response.status, body: errorBody };
+  }
+
+  return response.json();
 };
 
 /**
@@ -281,10 +464,10 @@ export const rescanImageArea = async (
 export const compareWatchedItemPrices = async (
   watchedItems: MasterGroceryItem[],
   signal?: AbortSignal,
-): Promise<Response> => {
+): Promise<GroundedResponse> => {
   // Use the apiFetch wrapper for consistency with other API calls in this file.
   // This centralizes token handling and base URL logic.
-  return apiFetch(
+  const response = await apiFetch(
     '/ai/compare-prices',
     {
       method: 'POST',
@@ -293,4 +476,16 @@ export const compareWatchedItemPrices = async (
     },
     { signal },
   );
+
+  if (!response.ok) {
+    let errorBody;
+    try {
+      errorBody = await response.json();
+    } catch (e) {
+      errorBody = { message: await response.text() };
+    }
+    throw { status: response.status, body: errorBody };
+  }
+
+  return response.json();
 };

src/services/aiService.server.test.ts

@@ -166,6 +166,127 @@ describe('AI Service (Server)', () => {
     });
   });
 
+  describe('Model Fallback Logic', () => {
+    const originalEnv = process.env;
+
+    beforeEach(() => {
+      vi.unstubAllEnvs();
+      process.env = { ...originalEnv, GEMINI_API_KEY: 'test-key' };
+      vi.resetModules(); // Re-import to use the new env var and re-instantiate the service
+    });
+
+    afterEach(() => {
+      process.env = originalEnv;
+      vi.unstubAllEnvs();
+    });
+
+    it('should try the next model if the first one fails with a quota error', async () => {
+      // Arrange
+      const { AIService } = await import('./aiService.server');
+      const { logger } = await import('./logger.server');
+      const serviceWithFallback = new AIService(logger);
+
+      const quotaError = new Error('User rate limit exceeded due to quota');
+      const successResponse = { text: 'Success from fallback model', candidates: [] };
+
+      // Mock the generateContent function to fail on the first call and succeed on the second
+      mockGenerateContent.mockRejectedValueOnce(quotaError).mockResolvedValueOnce(successResponse);
+
+      const request = { contents: [{ parts: [{ text: 'test prompt' }] }] };
+
+      // Act
+      const result = await (serviceWithFallback as any).aiClient.generateContent(request);
+
+      // Assert
+      expect(result).toEqual(successResponse);
+      expect(mockGenerateContent).toHaveBeenCalledTimes(2);
+
+      // Check first call
+      expect(mockGenerateContent).toHaveBeenNthCalledWith(1, {
+        model: 'gemini-2.5-flash',
+        ...request,
+      });
+
+      // Check second call
+      expect(mockGenerateContent).toHaveBeenNthCalledWith(2, {
+        model: 'gemini-3-flash',
+        ...request,
+      });
+
+      // Check that a warning was logged
+      expect(logger.warn).toHaveBeenCalledWith(
+        expect.stringContaining(
+          "Model 'gemini-2.5-flash' failed due to quota/rate limit. Trying next model.",
+        ),
+      );
+    });
+
+    it('should throw immediately for non-retriable errors', async () => {
+      // Arrange
+      const { AIService } = await import('./aiService.server');
+      const { logger } = await import('./logger.server');
+      const serviceWithFallback = new AIService(logger);
+
+      const nonRetriableError = new Error('Invalid API Key');
+      mockGenerateContent.mockRejectedValueOnce(nonRetriableError);
+
+      const request = { contents: [{ parts: [{ text: 'test prompt' }] }] };
+
+      // Act & Assert
+      await expect((serviceWithFallback as any).aiClient.generateContent(request)).rejects.toThrow(
+        'Invalid API Key',
+      );
+
+      expect(mockGenerateContent).toHaveBeenCalledTimes(1);
+      expect(logger.error).toHaveBeenCalledWith(
+        `[AIService Adapter] Model 'gemini-2.5-flash' failed with a non-retriable error.`,
+        { error: nonRetriableError },
+      );
+    });
+
+    it('should throw the last error if all models fail', async () => {
+      // Arrange
+      const { AIService } = await import('./aiService.server');
+      const { logger } = await import('./logger.server');
+      const serviceWithFallback = new AIService(logger);
+
+      const quotaError1 = new Error('Quota exhausted for model 1');
+      const quotaError2 = new Error('429 Too Many Requests for model 2');
+      const quotaError3 = new Error('RESOURCE_EXHAUSTED for model 3');
+
+      mockGenerateContent
+        .mockRejectedValueOnce(quotaError1)
+        .mockRejectedValueOnce(quotaError2)
+        .mockRejectedValueOnce(quotaError3);
+
+      const request = { contents: [{ parts: [{ text: 'test prompt' }] }] };
+
+      // Act & Assert
+      await expect((serviceWithFallback as any).aiClient.generateContent(request)).rejects.toThrow(
+        quotaError3,
+      );
+
+      expect(mockGenerateContent).toHaveBeenCalledTimes(3);
+      expect(mockGenerateContent).toHaveBeenNthCalledWith(1, {
+        model: 'gemini-2.5-flash',
+        ...request,
+      });
+      expect(mockGenerateContent).toHaveBeenNthCalledWith(2, {
+        model: 'gemini-3-flash',
+        ...request,
+      });
+      expect(mockGenerateContent).toHaveBeenNthCalledWith(3, {
+        model: 'gemini-2.5-flash-lite',
+        ...request,
+      });
+
+      expect(logger.error).toHaveBeenCalledWith(
+        '[AIService Adapter] All AI models failed. Throwing last known error.',
+        { lastError: quotaError3 },
+      );
+    });
+  });
+
   describe('extractItemsFromReceiptImage', () => {
     it('should extract items from a valid AI response', async () => {
       const mockAiResponseText = `[

src/services/aiService.server.ts

@@ -72,6 +72,7 @@ export class AIService {
   private fs: IFileSystem;
   private rateLimiter: <T>(fn: () => Promise<T>) => Promise<T>;
   private logger: Logger;
+  private readonly models = ['gemini-2.5-flash', 'gemini-3-flash', 'gemini-2.5-flash-lite'];
 
   constructor(logger: Logger, aiClient?: IAiClient, fs?: IFileSystem) {
     this.logger = logger;
@@ -121,17 +122,11 @@ export class AIService {
         );
       }
 
-      // do not change "gemini-2.5-flash" - this is correct
-      const modelName = 'gemini-2.5-flash';
-
       // We create a shim/adapter that matches the old structure but uses the new SDK call pattern.
       // This preserves the dependency injection pattern used throughout the class.
       this.aiClient = genAI
         ? {
             generateContent: async (request) => {
-              // The model name is now injected here, into every call, as the new SDK requires.
-              // Architectural guard clause: All requests from this service must have content.
-              // This prevents sending invalid requests to the API and satisfies TypeScript's strictness.
               if (!request.contents || request.contents.length === 0) {
                 this.logger.error(
                   { request },
@@ -140,14 +135,7 @@ export class AIService {
                 throw new Error('AIService.generateContent requires at least one content element.');
               }
 
-              // Architectural Fix: After the guard clause, assign the guaranteed-to-exist element
+              return this._generateWithFallback(genAI, request);
-              // to a new constant. This provides a definitive type-safe variable for the compiler.
-              const firstContent = request.contents[0];
-              this.logger.debug(
-                { modelName, requestParts: firstContent.parts?.length ?? 0 },
-                '[AIService] Calling actual generateContent via adapter.',
-              );
-              return genAI.models.generateContent({ model: modelName, ...request });
             },
           }
         : {
@@ -182,6 +170,54 @@ export class AIService {
     this.logger.info('---------------- [AIService] Constructor End ----------------');
   }
 
+  private async _generateWithFallback(
+    genAI: GoogleGenAI,
+    request: { contents: Content[]; tools?: Tool[] },
+  ): Promise<GenerateContentResponse> {
+    let lastError: Error | null = null;
+
+    for (const modelName of this.models) {
+      try {
+        this.logger.info(
+          `[AIService Adapter] Attempting to generate content with model: ${modelName}`,
+        );
+        const result = await genAI.models.generateContent({ model: modelName, ...request });
+        // If the call succeeds, return the result immediately.
+        return result;
+      } catch (error: unknown) {
+        lastError = error instanceof Error ? error : new Error(String(error));
+        const errorMessage = lastError.message || '';
+
+        // Check for specific error messages indicating quota issues or model unavailability.
+        if (
+          errorMessage.includes('quota') ||
+          errorMessage.includes('429') || // HTTP 429 Too Many Requests
+          errorMessage.includes('RESOURCE_EXHAUSTED') ||
+          errorMessage.includes('model is overloaded')
+        ) {
+          this.logger.warn(
+            `[AIService Adapter] Model '${modelName}' failed due to quota/rate limit. Trying next model. Error: ${errorMessage}`,
+          );
+          continue; // Try the next model in the list.
+        } else {
+          // For other errors (e.g., invalid input, safety settings), fail immediately.
+          this.logger.error(
+            { error: lastError },
+            `[AIService Adapter] Model '${modelName}' failed with a non-retriable error.`,
+          );
+          throw lastError;
+        }
+      }
+    }
+
+    // If all models in the list have failed, throw the last error encountered.
+    this.logger.error(
+      { lastError },
+      '[AIService Adapter] All AI models failed. Throwing last known error.',
+    );
+    throw lastError || new Error('All AI models failed to generate content.');
+  }
+
   private async serverFileToGenerativePart(path: string, mimeType: string) {
     const fileData = await this.fs.readFile(path);
     return {

src/services/queueService.server.ts

@@ -1,5 +1,5 @@
 // src/services/queueService.server.ts
-import { Queue, Worker, Job } from 'bullmq';
+import { Queue, Worker, Job, UnrecoverableError } from 'bullmq';
 import IORedis from 'ioredis'; // Correctly imported
 import fsPromises from 'node:fs/promises';
 import { exec } from 'child_process';
@@ -185,9 +185,26 @@ const attachWorkerEventListeners = (worker: Worker) => {
 
 export const flyerWorker = new Worker<FlyerJobData>(
   'flyer-processing', // Must match the queue name
-  (job) => {
+  async (job) => {
-    // The processJob method creates its own job-specific logger internally.
+    try {
-    return flyerProcessingService.processJob(job);
+      // The processJob method creates its own job-specific logger internally.
+      return await flyerProcessingService.processJob(job);
+    } catch (error: any) {
+      // Check for quota errors or other unrecoverable errors from the AI service
+      const errorMessage = error?.message || '';
+      if (
+        errorMessage.includes('quota') ||
+        errorMessage.includes('429') ||
+        errorMessage.includes('RESOURCE_EXHAUSTED')
+      ) {
+        logger.error(
+          { err: error, jobId: job.id },
+          '[FlyerWorker] Unrecoverable quota error detected. Failing job immediately.',
+        );
+        throw new UnrecoverableError(errorMessage);
+      }
+      throw error;
+    }
   },
   {
     connection,