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feat: async product/receipt recognition via Kafka

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Backend:
- Migration 002: product_recognition_jobs table with JSONB images column
  and job_type CHECK ('receipt' | 'products')
- New Kafka topics: ai.products.paid / ai.products.free
- ProductJob model, ProductJobRepository (mirrors dish job pattern)
- itemEnricher extracted from Handler — shared by HTTP handler and worker
- ProductSSEBroker: PG LISTEN on product_job_update channel
- ProductWorkerPool: 5 workers, branches on job_type to call
  RecognizeReceipt or RecognizeProducts per image in parallel
- Handler: RecognizeReceipt and RecognizeProducts now return 202 Accepted
  instead of blocking; 4 new endpoints: GET /ai/product-jobs,
  /product-jobs/history, /product-jobs/{id}, /product-jobs/{id}/stream
- cmd/worker: extended to run ProductWorkerPool alongside dish WorkerPool
- cmd/server: wires productJobRepository + productSSEBroker; both SSE
  brokers started in App.Start()

Flutter client:
- ProductJobCreated, ProductJobResult, ProductJobSummary, ProductJobEvent
  models + submitReceiptRecognition/submitProductsRecognition/stream methods
- Shared _openSseStream helper eliminates duplicate SSE parsing loop
- ScanScreen: replace blocking AI calls with async submit + navigate to
  ProductJobWatchScreen
- ProductJobWatchScreen: watches SSE stream, navigates to /scan/confirm
  when done, shows error on failure
- ProductsScreen: prepends _RecentScansSection (hidden when empty); compact
  horizontal list of recent scans with "See all" → history
- ProductJobHistoryScreen: full list of all product recognition jobs
- New routes: /scan/product-job-watch, /products/job-history
- L10n: 7 new keys in all 12 ARB files

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
This commit is contained in:
dbastrikin
2026-03-23 23:01:30 +02:00
parent bffeb05a43
commit c7317c4335
43 changed files with 2073 additions and 239 deletions
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248
client/lib/features/scan/recognition_service.dart
View File

@@ -1,7 +1,6 @@
import 'dart:async';
import 'dart:convert';
import 'package:dio/dio.dart';
import 'package:flutter_riverpod/flutter_riverpod.dart';
import 'package:http/http.dart' as http;
import 'package:image_picker/image_picker.dart';
@@ -142,7 +141,110 @@ class DishResult {
}
// ---------------------------------------------------------------------------
// Async job models
// Product job models
// ---------------------------------------------------------------------------
/// Result of a completed product or receipt recognition job.
class ProductJobResult {
final String jobType;
final List<RecognizedItem> items;
final List<UnrecognizedItem> unrecognized;
const ProductJobResult({
required this.jobType,
required this.items,
required this.unrecognized,
});
factory ProductJobResult.fromJson(Map<String, dynamic> json) {
return ProductJobResult(
jobType: json['job_type'] as String? ?? '',
items: (json['items'] as List<dynamic>? ?? [])
.map((element) => RecognizedItem.fromJson(element as Map<String, dynamic>))
.toList(),
unrecognized: (json['unrecognized'] as List<dynamic>? ?? [])
.map((element) => UnrecognizedItem.fromJson(element as Map<String, dynamic>))
.toList(),
);
}
}
/// The 202 response from POST /ai/recognize-receipt or /ai/recognize-products.
class ProductJobCreated {
final String jobId;
final int queuePosition;
final int estimatedSeconds;
const ProductJobCreated({
required this.jobId,
required this.queuePosition,
required this.estimatedSeconds,
});
factory ProductJobCreated.fromJson(Map<String, dynamic> json) {
return ProductJobCreated(
jobId: json['job_id'] as String,
queuePosition: json['queue_position'] as int? ?? 0,
estimatedSeconds: json['estimated_seconds'] as int? ?? 0,
);
}
}
/// A lightweight summary of a product recognition job for list endpoints.
class ProductJobSummary {
final String id;
final String jobType;
final String status;
final ProductJobResult? result;
final String? error;
final DateTime createdAt;
const ProductJobSummary({
required this.id,
required this.jobType,
required this.status,
this.result,
this.error,
required this.createdAt,
});
factory ProductJobSummary.fromJson(Map<String, dynamic> json) {
return ProductJobSummary(
id: json['id'] as String,
jobType: json['job_type'] as String? ?? '',
status: json['status'] as String? ?? '',
result: json['result'] != null
? ProductJobResult.fromJson(json['result'] as Map<String, dynamic>)
: null,
error: json['error'] as String?,
createdAt: DateTime.parse(json['created_at'] as String),
);
}
}
/// Events emitted by the SSE stream for a product recognition job.
sealed class ProductJobEvent {}
class ProductJobQueued extends ProductJobEvent {
final int position;
final int estimatedSeconds;
ProductJobQueued({required this.position, required this.estimatedSeconds});
}
class ProductJobProcessing extends ProductJobEvent {}
class ProductJobDone extends ProductJobEvent {
final ProductJobResult result;
ProductJobDone(this.result);
}
class ProductJobFailed extends ProductJobEvent {
final String error;
ProductJobFailed(this.error);
}
// ---------------------------------------------------------------------------
// Dish job models
// ---------------------------------------------------------------------------
/// A lightweight summary of a dish recognition job (no image payload).
@@ -239,32 +341,71 @@ class RecognitionService {
final AppConfig _appConfig;
final String Function() _languageGetter;
/// Recognizes food items from a receipt photo.
Future<ReceiptResult> recognizeReceipt(XFile image) async {
/// Submits a receipt image for async recognition.
/// Returns immediately with a [ProductJobCreated] containing the job ID.
Future<ProductJobCreated> submitReceiptRecognition(XFile image) async {
final payload = await _buildImagePayload(image);
final data = await _client.post('/ai/recognize-receipt', data: payload);
return ReceiptResult(
items: (data['items'] as List<dynamic>? ?? [])
.map((element) => RecognizedItem.fromJson(element as Map<String, dynamic>))
.toList(),
unrecognized: (data['unrecognized'] as List<dynamic>? ?? [])
.map((element) => UnrecognizedItem.fromJson(element as Map<String, dynamic>))
.toList(),
);
return ProductJobCreated.fromJson(data);
}
/// Recognizes food items from 1–3 product photos.
Future<List<RecognizedItem>> recognizeProducts(List<XFile> images) async {
/// Submits 1–3 product images for async recognition.
/// Returns immediately with a [ProductJobCreated] containing the job ID.
Future<ProductJobCreated> submitProductsRecognition(List<XFile> images) async {
final imageList = await Future.wait(images.map(_buildImagePayload));
final data = await _client.post(
'/ai/recognize-products',
data: {'images': imageList},
);
return (data['items'] as List<dynamic>? ?? [])
.map((element) => RecognizedItem.fromJson(element as Map<String, dynamic>))
return ProductJobCreated.fromJson(data);
}
/// Returns product recognition jobs from the last 7 days.
Future<List<ProductJobSummary>> listRecentProductJobs() async {
final data = await _client.getList('/ai/product-jobs');
return data
.map((element) =>
ProductJobSummary.fromJson(element as Map<String, dynamic>))
.toList();
}
/// Returns all product recognition jobs for the current user, newest first.
Future<List<ProductJobSummary>> listAllProductJobs() async {
final data = await _client.getList('/ai/product-jobs/history');
return data
.map((element) =>
ProductJobSummary.fromJson(element as Map<String, dynamic>))
.toList();
}
/// Opens an SSE stream for product job [jobId] and emits [ProductJobEvent]s
/// until the job reaches a terminal state or the stream is cancelled.
Stream<ProductJobEvent> streamProductJobEvents(String jobId) async* {
final streamUri = Uri.parse('${_appConfig.apiBaseUrl}/ai/product-jobs/$jobId/stream');
await for (final parsed in _openSseStream(streamUri)) {
final eventName = parsed.$1;
final json = parsed.$2;
ProductJobEvent? event;
switch (eventName) {
case 'queued':
event = ProductJobQueued(
position: json['position'] as int? ?? 0,
estimatedSeconds: json['estimated_seconds'] as int? ?? 0,
);
case 'processing':
event = ProductJobProcessing();
case 'done':
event = ProductJobDone(ProductJobResult.fromJson(json));
case 'failed':
event = ProductJobFailed(json['error'] as String? ?? 'Recognition failed');
}
if (event != null) {
yield event;
if (event is ProductJobDone || event is ProductJobFailed) return;
}
}
}
/// Submits a dish image for async recognition.
/// Returns a [DishJobCreated] with the job ID and queue position.
Future<DishJobCreated> submitDishRecognition(
@@ -298,21 +439,45 @@ class RecognitionService {
.toList();
}
/// Opens an SSE stream for job [jobId] and emits [DishJobEvent]s until the
/// job reaches a terminal state (done or failed) or the stream is cancelled.
/// Opens an SSE stream for dish job [jobId] and emits [DishJobEvent]s until
/// the job reaches a terminal state (done or failed) or the stream is cancelled.
Stream<DishJobEvent> streamJobEvents(String jobId) async* {
final streamUri = Uri.parse('${_appConfig.apiBaseUrl}/ai/jobs/$jobId/stream');
await for (final parsed in _openSseStream(streamUri)) {
final eventName = parsed.$1;
final json = parsed.$2;
DishJobEvent? event;
switch (eventName) {
case 'queued':
event = DishJobQueued(
position: json['position'] as int? ?? 0,
estimatedSeconds: json['estimated_seconds'] as int? ?? 0,
);
case 'processing':
event = DishJobProcessing();
case 'done':
event = DishJobDone(DishResult.fromJson(json));
case 'failed':
event = DishJobFailed(json['error'] as String? ?? 'Recognition failed');
}
if (event != null) {
yield event;
if (event is DishJobDone || event is DishJobFailed) return;
}
}
}
/// Opens a raw SSE connection and emits (eventName, jsonData) pairs.
///
/// Uses [http.Client] instead of Dio because on Flutter Web Dio relies on
/// XHR which does not support SSE streaming. [http.BrowserClient] reads the
/// response via XHR onProgress events and delivers chunks before the
/// connection is closed.
Stream<DishJobEvent> streamJobEvents(String jobId) async* {
/// XHR which does not support SSE streaming.
Stream<(String, Map<String, dynamic>)> _openSseStream(Uri streamUri) async* {
final token = await _storage.getAccessToken();
final language = _languageGetter();
final uri = Uri.parse('${_appConfig.apiBaseUrl}/ai/jobs/$jobId/stream');
final httpClient = http.Client();
try {
final request = http.Request('GET', uri)
final request = http.Request('GET', streamUri)
..headers['Authorization'] = token != null ? 'Bearer $token' : ''
..headers['Accept'] = 'text/event-stream'
..headers['Accept-Language'] = language
@@ -329,7 +494,6 @@ class RecognitionService {
buffer.write(chunk);
final text = buffer.toString();
// Process complete SSE messages (terminated by \n\n).
int doubleNewlineIndex;
var remaining = text;
while ((doubleNewlineIndex = remaining.indexOf('\n\n')) != -1) {
@@ -341,10 +505,13 @@ class RecognitionService {
currentEventName = line.substring(6).trim();
} else if (line.startsWith('data:')) {
final dataPayload = line.substring(5).trim();
final event = _parseSseEvent(currentEventName, dataPayload);
if (event != null) {
yield event;
if (event is DishJobDone || event is DishJobFailed) return;
try {
final jsonData = jsonDecode(dataPayload) as Map<String, dynamic>;
if (currentEventName != null) {
yield (currentEventName, jsonData);
}
} catch (_) {
// Malformed JSON — skip this message.
}
currentEventName = null;
}
@@ -360,29 +527,6 @@ class RecognitionService {
}
}
DishJobEvent? _parseSseEvent(String? eventName, String dataPayload) {
try {
final json = jsonDecode(dataPayload) as Map<String, dynamic>;
switch (eventName) {
case 'queued':
return DishJobQueued(
position: json['position'] as int? ?? 0,
estimatedSeconds: json['estimated_seconds'] as int? ?? 0,
);
case 'processing':
return DishJobProcessing();
case 'done':
return DishJobDone(DishResult.fromJson(json));
case 'failed':
return DishJobFailed(json['error'] as String? ?? 'Recognition failed');
default:
return null;
}
} catch (_) {
return null;
}
}
Future<Map<String, String>> _buildImagePayload(XFile image) async {
final bytes = await image.readAsBytes();
final base64Data = base64Encode(bytes);