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292 lines
12 KiB
TypeScript
292 lines
12 KiB
TypeScript
// src/services/flyerProcessingService.server.ts
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import type { Job, Queue } from 'bullmq';
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import { UnrecoverableError } from 'bullmq';
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import type { Logger } from 'pino';
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import type { FlyerFileHandler, IFileSystem, ICommandExecutor } from './flyerFileHandler.server';
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import type { FlyerAiProcessor } from './flyerAiProcessor.server';
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import type * as Db from './db/index.db';
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import type { AdminRepository } from './db/admin.db';
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import { FlyerDataTransformer } from './flyerDataTransformer';
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import type { FlyerJobData, CleanupJobData } from '../types/job-data';
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import {
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FlyerProcessingError,
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PdfConversionError,
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AiDataValidationError,
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UnsupportedFileTypeError,
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} from './processingErrors';
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import { createFlyerAndItems } from './db/flyer.db';
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import { logger as globalLogger } from './logger.server';
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// Define ProcessingStage locally as it's not exported from the types file.
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export type ProcessingStage = {
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name: string;
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status: 'pending' | 'in-progress' | 'completed' | 'failed' | 'skipped';
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critical: boolean;
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detail?: string;
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};
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/**
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* This service orchestrates the entire flyer processing workflow. It's responsible for
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* coordinating various sub-services (file handling, AI processing, data transformation,
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* and database operations) to process a flyer from upload to completion.
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*/
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export class FlyerProcessingService {
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constructor(
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private fileHandler: FlyerFileHandler,
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private aiProcessor: FlyerAiProcessor,
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// This service only needs the `logActivity` method from the `adminRepo`.
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// By using `Pick`, we create a more focused and testable dependency.
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private db: { adminRepo: Pick<AdminRepository, 'logActivity'> },
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private fs: IFileSystem,
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// By depending on `Pick<Queue, 'add'>`, we specify that this service only needs
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// an object with an `add` method that matches the Queue's `add` method signature.
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// This decouples the service from the full BullMQ Queue implementation, making it more modular and easier to test.
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private cleanupQueue: Pick<Queue<CleanupJobData>, 'add'>,
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private transformer: FlyerDataTransformer,
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) {}
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/**
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* Orchestrates the processing of a flyer job.
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* @param job The BullMQ job containing flyer data.
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* @returns An object containing the ID of the newly created flyer.
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*/
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async processJob(job: Job<FlyerJobData>): Promise<{ flyerId: number }> {
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// Create a logger instance with job-specific context for better traceability.
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const logger = globalLogger.child({ jobId: job.id, jobName: job.name, ...job.data });
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logger.info('Picked up flyer processing job.');
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const stages: ProcessingStage[] = [
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{ name: 'Preparing Inputs', status: 'pending', critical: true, detail: 'Validating and preparing file...' },
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{ name: 'Extracting Data with AI', status: 'pending', critical: true, detail: 'Communicating with AI model...' },
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{ name: 'Transforming AI Data', status: 'pending', critical: true },
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{ name: 'Saving to Database', status: 'pending', critical: true },
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];
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// Keep track of all created file paths for eventual cleanup.
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const allFilePaths: string[] = [job.data.filePath];
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try {
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// Stage 1: Prepare Inputs (e.g., convert PDF to images)
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stages[0].status = 'in-progress';
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await job.updateProgress({ stages });
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const { imagePaths, createdImagePaths } = await this.fileHandler.prepareImageInputs(
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job.data.filePath,
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job,
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logger,
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);
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allFilePaths.push(...createdImagePaths);
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stages[0].status = 'completed';
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stages[0].detail = `${imagePaths.length} page(s) ready for AI.`;
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await job.updateProgress({ stages });
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// Stage 2: Extract Data with AI
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stages[1].status = 'in-progress';
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await job.updateProgress({ stages });
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const aiResult = await this.aiProcessor.extractAndValidateData(imagePaths, job.data, logger);
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stages[1].status = 'completed';
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await job.updateProgress({ stages });
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// Stage 3: Transform AI Data into DB format
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stages[2].status = 'in-progress';
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await job.updateProgress({ stages });
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const { flyerData, itemsForDb } = await this.transformer.transform(
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aiResult,
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imagePaths,
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job.data.originalFileName,
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job.data.checksum,
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job.data.userId,
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logger,
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);
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stages[2].status = 'completed';
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await job.updateProgress({ stages });
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// Stage 4: Save to Database
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stages[3].status = 'in-progress';
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await job.updateProgress({ stages });
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const { flyer } = await createFlyerAndItems(flyerData, itemsForDb, logger);
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stages[3].status = 'completed';
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await job.updateProgress({ stages });
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// Stage 5: Log Activity
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await this.db.adminRepo.logActivity(
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{
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action: 'flyer_processed',
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displayText: `Processed flyer for ${flyerData.store_name}`,
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details: { flyer_id: flyer.flyer_id, store_name: flyerData.store_name },
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userId: job.data.userId,
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},
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logger,
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);
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// Enqueue a job to clean up the original and any generated files.
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await this.cleanupQueue.add(
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'cleanup-flyer-files',
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{ flyerId: flyer.flyer_id, paths: allFilePaths },
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{ removeOnComplete: true },
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);
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logger.info(`Successfully processed job and enqueued cleanup for flyer ID: ${flyer.flyer_id}`);
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return { flyerId: flyer.flyer_id };
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} catch (error) {
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logger.warn('Job failed. Temporary files will NOT be cleaned up to allow for manual inspection.');
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// This private method handles error reporting and re-throwing.
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await this._reportErrorAndThrow(error, job, logger, stages);
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// This line is technically unreachable because the above method always throws,
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// but it's required to satisfy TypeScript's control flow analysis.
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throw error;
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}
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}
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/**
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* Processes a job to clean up temporary files associated with a flyer.
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* @param job The BullMQ job containing cleanup data.
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* @returns An object indicating the status of the cleanup operation.
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*/
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async processCleanupJob(job: Job<CleanupJobData>): Promise<{ status: string; deletedCount?: number; reason?: string }> {
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const logger = globalLogger.child({ jobId: job.id, jobName: job.name, ...job.data });
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logger.info('Picked up file cleanup job.');
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const { paths } = job.data;
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if (!paths || paths.length === 0) {
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logger.warn('Job received no paths to clean. Skipping.');
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return { status: 'skipped', reason: 'no paths' };
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}
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const results = await Promise.allSettled(
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paths.map(async (filePath) => {
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try {
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await this.fs.unlink(filePath);
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logger.info(`Successfully deleted temporary file: ${filePath}`);
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} catch (error) {
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const nodeError = error as NodeJS.ErrnoException;
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if (nodeError.code === 'ENOENT') {
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// This is not a critical error; the file might have been deleted already.
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logger.warn(`File not found during cleanup (already deleted?): ${filePath}`);
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} else {
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logger.error({ err: nodeError, path: filePath }, 'Failed to delete temporary file.');
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throw error; // Re-throw to mark this specific deletion as failed.
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}
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}
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}),
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);
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const failedDeletions = results.filter((r) => r.status === 'rejected');
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if (failedDeletions.length > 0) {
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const failedPaths = paths.filter((_, i) => results[i].status === 'rejected');
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throw new Error(`Failed to delete ${failedDeletions.length} file(s): ${failedPaths.join(', ')}`);
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}
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logger.info(`Successfully deleted all ${paths.length} temporary files.`);
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return { status: 'success', deletedCount: paths.length };
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}
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/**
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* A private helper to normalize errors, update job progress with an error state,
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* and re-throw the error to be handled by BullMQ.
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* @param error The error that was caught.
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* @param job The BullMQ job instance.
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* @param logger The logger instance.
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*/
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private async _reportErrorAndThrow(
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error: unknown,
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job: Job,
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logger: Logger,
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initialStages: ProcessingStage[],
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): Promise<never> {
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const normalizedError = error instanceof Error ? error : new Error(String(error));
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let errorPayload: { errorCode: string; message: string; [key: string]: any };
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let stagesToReport: ProcessingStage[] = [...initialStages]; // Create a mutable copy
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if (normalizedError instanceof FlyerProcessingError) {
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errorPayload = normalizedError.toErrorPayload();
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} else {
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const message = normalizedError.message || 'An unknown error occurred.';
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errorPayload = { errorCode: 'UNKNOWN_ERROR', message };
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}
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// Determine which stage failed
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let errorStageIndex = -1;
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// 1. Try to map specific error codes/messages to stages
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if (errorPayload.errorCode === 'PDF_CONVERSION_FAILED' || errorPayload.errorCode === 'UNSUPPORTED_FILE_TYPE') {
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errorStageIndex = stagesToReport.findIndex(s => s.name === 'Preparing Inputs');
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} else if (errorPayload.errorCode === 'AI_VALIDATION_FAILED') {
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errorStageIndex = stagesToReport.findIndex(s => s.name === 'Extracting Data with AI');
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} else if (errorPayload.message.includes('Icon generation failed')) {
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errorStageIndex = stagesToReport.findIndex(s => s.name === 'Transforming AI Data');
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} else if (errorPayload.message.includes('Database transaction failed')) {
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errorStageIndex = stagesToReport.findIndex(s => s.name === 'Saving to Database');
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}
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// 2. If not mapped, find the currently running stage
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if (errorStageIndex === -1) {
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errorStageIndex = stagesToReport.findIndex(s => s.status === 'in-progress');
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}
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// 3. Fallback to the last stage
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if (errorStageIndex === -1 && stagesToReport.length > 0) {
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errorStageIndex = stagesToReport.length - 1;
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}
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// Update stages
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if (errorStageIndex !== -1) {
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stagesToReport[errorStageIndex] = {
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...stagesToReport[errorStageIndex],
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status: 'failed',
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detail: errorPayload.message, // Use the user-friendly message as detail
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};
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// Mark subsequent critical stages as skipped
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for (let i = errorStageIndex + 1; i < stagesToReport.length; i++) {
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if (stagesToReport[i].critical) {
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// When a stage is skipped, we don't need its previous 'detail' property.
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// This creates a clean 'skipped' state object by removing `detail` and keeping the rest.
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const { detail, ...restOfStage } = stagesToReport[i];
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stagesToReport[i] = { ...restOfStage, status: 'skipped' };
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}
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}
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}
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errorPayload.stages = stagesToReport;
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// Logging logic
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if (normalizedError instanceof FlyerProcessingError) {
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const logDetails: Record<string, any> = { err: normalizedError };
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if (normalizedError instanceof AiDataValidationError) {
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logDetails.validationErrors = normalizedError.validationErrors;
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logDetails.rawData = normalizedError.rawData;
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}
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// Also include stderr for PdfConversionError in logs
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if (normalizedError instanceof PdfConversionError) {
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logDetails.stderr = normalizedError.stderr;
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}
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// Include the errorPayload details in the log, but avoid duplicating err, validationErrors, rawData
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Object.assign(logDetails, errorPayload);
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// Remove the duplicated err property if it was assigned by Object.assign
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if ('err' in logDetails && logDetails.err === normalizedError) {
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// This check prevents accidental deletion if 'err' was a legitimate property of errorPayload
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delete logDetails.err;
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}
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// Ensure the original error object is always passed as 'err' for consistency in logging
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logDetails.err = normalizedError;
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logger.error(logDetails, `A known processing error occurred: ${normalizedError.name}`);
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} else {
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logger.error({ err: normalizedError, ...errorPayload }, `An unknown error occurred: ${errorPayload.message}`);
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}
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// Check for specific error messages that indicate a non-retriable failure, like quota exhaustion.
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if (errorPayload.message.toLowerCase().includes('quota') || errorPayload.message.toLowerCase().includes('resource_exhausted')) {
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const unrecoverablePayload = { errorCode: 'QUOTA_EXCEEDED', message: 'An AI quota has been exceeded. Please try again later.', stages: errorPayload.stages };
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await job.updateProgress(unrecoverablePayload);
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throw new UnrecoverableError(unrecoverablePayload.message);
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}
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await job.updateProgress(errorPayload);
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throw normalizedError;
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}
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}
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