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Author SHA1 Message Date
Gitea Actions
68aadcaa4e ci: Bump version to 0.1.2 [skip ci] 2025-12-25 01:41:06 +05:00
971d2c3fa7 add ai agent fallbacks
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2025-12-24 12:39:15 -08:00
10 changed files with 578 additions and 161 deletions

4
package-lock.json generated
View File

@@ -1,12 +1,12 @@
{
"name": "flyer-crawler",
"version": "0.1.1",
"version": "0.1.2",
"lockfileVersion": 3,
"requires": true,
"packages": {
"": {
"name": "flyer-crawler",
"version": "0.1.1",
"version": "0.1.2",
"dependencies": {
"@bull-board/api": "^6.14.2",
"@bull-board/express": "^6.14.2",

View File

@@ -1,7 +1,7 @@
{
"name": "flyer-crawler",
"private": true,
"version": "0.1.1",
"version": "0.1.2",
"type": "module",
"scripts": {
"dev": "concurrently \"npm:start:dev\" \"vite\"",

View File

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

View File

@@ -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(
new Response(JSON.stringify({ jobId: 'job-123' }), { status: 200 }),
);
mockedAiApiClient.getJobStatus.mockResolvedValue(
new Response(JSON.stringify({ state: 'active', progress: { message: 'Checking...' } })),
);
mockedAiApiClient.uploadAndProcessFlyer.mockResolvedValue({ jobId: 'job-123' });
mockedAiApiClient.getJobStatus.mockResolvedValue({
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(
new Response(JSON.stringify({ jobId: 'job-dnd' }), { status: 200 }),
);
mockedAiApiClient.getJobStatus.mockResolvedValue(
new Response(JSON.stringify({ state: 'active', progress: { message: 'Dropped...' } })),
);
mockedAiApiClient.uploadAndProcessFlyer.mockResolvedValue({ jobId: 'job-dnd' });
mockedAiApiClient.getJobStatus.mockResolvedValue({
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(
new Response(JSON.stringify({ jobId: 'job-123' }), { status: 200 }),
);
mockedAiApiClient.uploadAndProcessFlyer.mockResolvedValue({ jobId: 'job-123' });
mockedAiApiClient.getJobStatus
.mockResolvedValueOnce(
new Response(JSON.stringify({ state: 'active', progress: { message: 'Analyzing...' } })),
)
.mockResolvedValueOnce(
new Response(JSON.stringify({ state: 'completed', returnValue: { flyerId: 42 } })),
);
.mockResolvedValueOnce({ state: 'active', progress: { message: 'Analyzing...' } })
.mockResolvedValueOnce({ 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(
new Response(JSON.stringify({ jobId: 'job-fail' }), { status: 200 }),
);
mockedAiApiClient.getJobStatus.mockResolvedValue(
new Response(JSON.stringify({ state: 'failed', failedReason: 'AI model exploded' })),
);
mockedAiApiClient.uploadAndProcessFlyer.mockResolvedValue({ jobId: 'job-fail' });
mockedAiApiClient.getJobStatus.mockResolvedValue({
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(
new Response(JSON.stringify({ flyerId: 99, message: 'Duplicate' }), { status: 409 }),
);
// The API client now throws a structured error for non-2xx responses.
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(
new Response(JSON.stringify({ jobId: 'job-stop' }), { status: 200 }),
);
mockedAiApiClient.getJobStatus.mockResolvedValue(
new Response(JSON.stringify({ state: 'active', progress: { message: 'Analyzing...' } })),
);
mockedAiApiClient.uploadAndProcessFlyer.mockResolvedValue({ jobId: 'job-stop' });
mockedAiApiClient.getJobStatus.mockResolvedValue({
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(
new Error('Network Error During Upload'),
);
// Simulate a structured error from the API client
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(
new Response(JSON.stringify({ jobId: 'job-poll-fail' }), { status: 200 }),
);
mockedAiApiClient.uploadAndProcessFlyer.mockResolvedValue({ jobId: 'job-poll-fail' });
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(
new Response(JSON.stringify({ jobId: 'job-no-flyerid' }), { status: 200 }),
);
mockedAiApiClient.uploadAndProcessFlyer.mockResolvedValue({ jobId: 'job-no-flyerid' });
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);

View File

@@ -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);
console.debug(`[DEBUG] pollStatus(): API response status: ${statusResponse.status}`);
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);
const job = await getJobStatus(jobId); // Now returns parsed JSON directly
console.debug('[DEBUG] pollStatus(): Job status received:', job); // The rest of the logic remains the same
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);
console.debug(`[DEBUG] processFile(): Upload response status: ${startResponse.status}`);
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();
// The API client now returns parsed JSON on success or throws a structured error on failure.
const { jobId: newJobId } = await uploadAndProcessFlyer(file, checksum);
console.debug(`[DEBUG] processFile(): Upload successful. Received jobId: ${newJobId}`);
setJobId(newJobId);
setProcessingState('polling');
} catch (error) {
logger.error('An unexpected error occurred during file upload:', { error });
setErrorMessage(error instanceof Error ? error.message : 'An unexpected error occurred.');
} catch (error: any) {
// Handle the structured error thrown by the API client.
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');
}
}, []);

View File

@@ -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
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 };
return aiApiClient.searchWeb(query);
}
/**
@@ -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
.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 };
return aiApiClient.compareWatchedItemPrices(watchedItems);
}
/**
@@ -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;
}
/**

View File

@@ -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: ${file.name}`);
return apiFetch(
const response = await apiFetch(
'/ai/upload-and-process',
{
method: 'POST',
@@ -35,26 +41,79 @@ export const uploadAndProcessFlyer = async (
},
{ tokenOverride },
);
if (!response.ok) {
let errorBody;
try {
errorBody = await response.json();
} catch (e) {
errorBody = { message: await response.text() };
}
// Throw a structured error so the component can inspect the status and body
throw { status: response.status, body: errorBody };
}
return response.json();
};
// Define the expected shape of the job status response
export interface JobStatus {
id: string;
state: 'completed' | 'failed' | 'active' | 'waiting' | 'delayed' | 'paused';
progress: {
stages?: ProcessingStage[];
estimatedTimeRemaining?: number;
message?: string;
} | null;
returnValue: {
flyerId?: number;
} | null;
failedReason: string | null;
}
/**
* Fetches the status of a background processing job.
* This is the second step in the new background processing flow.
* @param jobId The ID of the job to check.
* @param tokenOverride Optional token for testing.
* @returns A promise that resolves to the API response with the job's status.
* @returns A promise that resolves to the parsed job status object.
* @throws An error if the network request fails or if the response is not valid JSON.
*/
export const getJobStatus = async (jobId: string, tokenOverride?: string): Promise<Response> => {
return apiFetch(`/ai/jobs/${jobId}/status`, {}, { tokenOverride });
export const getJobStatus = async (
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> => {
return apiFetch(
): Promise<{ text: string }> => {
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> => {
return apiFetch(
): Promise<{ text: string }> => {
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> => {
return apiFetch(
): Promise<GroundedResponse> => {
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();
};

View File

@@ -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 = `[

View File

@@ -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
// 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 });
return this._generateWithFallback(genAI, 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 {

View File

@@ -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) => {
// The processJob method creates its own job-specific logger internally.
return flyerProcessingService.processJob(job);
async (job) => {
try {
// 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,