c7317c4335
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>
86 lines
2.8 KiB
Go
86 lines
2.8 KiB
Go
package main
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import (
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"context"
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"github.com/food-ai/backend/internal/adapters/kafka"
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"github.com/food-ai/backend/internal/adapters/openai"
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"github.com/food-ai/backend/internal/domain/dish"
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"github.com/food-ai/backend/internal/domain/product"
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"github.com/food-ai/backend/internal/domain/recognition"
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"github.com/jackc/pgx/v5/pgxpool"
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"github.com/kelseyhightower/envconfig"
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)
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type workerConfig struct {
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DatabaseURL string `envconfig:"DATABASE_URL" required:"true"`
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OpenAIAPIKey string `envconfig:"OPENAI_API_KEY" required:"true"`
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KafkaBrokers []string `envconfig:"KAFKA_BROKERS" default:"kafka:9092"`
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WorkerPlan string `envconfig:"WORKER_PLAN" default:"free"` // "paid" | "free"
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}
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func loadConfig() (*workerConfig, error) {
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var workerCfg workerConfig
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if configError := envconfig.Process("", &workerCfg); configError != nil {
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return nil, configError
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}
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return &workerCfg, nil
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}
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// WorkerApp bundles background services that need lifecycle management.
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type WorkerApp struct {
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workerPool *recognition.WorkerPool
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productWorkerPool *recognition.ProductWorkerPool
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}
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// Start launches the dish and product worker pool goroutines.
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func (workerApp *WorkerApp) Start(applicationContext context.Context) {
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workerApp.workerPool.Start(applicationContext)
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workerApp.productWorkerPool.Start(applicationContext)
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}
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func initWorker(workerCfg *workerConfig, pool *pgxpool.Pool) (*WorkerApp, error) {
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openaiClient := openai.NewClient(workerCfg.OpenAIAPIKey)
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// Dish recognition worker.
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dishRepository := dish.NewRepository(pool)
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jobRepository := recognition.NewJobRepository(pool)
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dishTopic := recognition.TopicFree
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dishGroupID := "dish-recognition-free"
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if workerCfg.WorkerPlan == "paid" {
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dishTopic = recognition.TopicPaid
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dishGroupID = "dish-recognition-paid"
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}
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dishConsumer, dishConsumerError := kafka.NewConsumer(workerCfg.KafkaBrokers, dishGroupID, dishTopic)
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if dishConsumerError != nil {
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return nil, dishConsumerError
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}
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workerPool := recognition.NewWorkerPool(jobRepository, openaiClient, dishRepository, dishConsumer)
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// Product recognition worker.
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productRepository := product.NewRepository(pool)
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productJobRepository := recognition.NewProductJobRepository(pool)
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productTopic := recognition.ProductTopicFree
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productGroupID := "product-recognition-free"
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if workerCfg.WorkerPlan == "paid" {
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productTopic = recognition.ProductTopicPaid
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productGroupID = "product-recognition-paid"
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}
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productConsumer, productConsumerError := kafka.NewConsumer(workerCfg.KafkaBrokers, productGroupID, productTopic)
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if productConsumerError != nil {
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return nil, productConsumerError
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}
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productWorkerPool := recognition.NewProductWorkerPool(productJobRepository, openaiClient, productRepository, productConsumer)
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return &WorkerApp{
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workerPool: workerPool,
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productWorkerPool: productWorkerPool,
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}, nil
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}
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