refactor: introduce adapter pattern for AI provider (OpenAI)

- Add internal/adapters/ai/types.go with neutral shared types
  (Recipe, DayPlan, RecognizedItem, IngredientClassification, etc.)
- Remove types from internal/adapters/openai/ — adapter now uses ai.*
- Define Recognizer interface in recognition package
- Define MenuGenerator interface in menu package
- Define RecipeGenerator interface in recommendation package
- Handler structs now hold interfaces, not *openai.Client
- Add wire.Bind entries for the three new interface bindings

To swap OpenAI for another provider: implement the three interfaces
using ai.* types and change the wire.Bind lines in cmd/server/wire.go.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

backend/cmd/server/wire.go

@@ -13,6 +13,7 @@ import (
 	"github.com/food-ai/backend/internal/ingredient"
 	"github.com/food-ai/backend/internal/menu"
 	"github.com/food-ai/backend/internal/infra/middleware"
+	"github.com/food-ai/backend/internal/adapters/openai"
 	"github.com/food-ai/backend/internal/adapters/pexels"
 	"github.com/food-ai/backend/internal/product"
 	"github.com/food-ai/backend/internal/recipe"
@@ -105,6 +106,9 @@ func initRouter(appConfig *config.Config, pool *pgxpool.Pool) (http.Handler, err
 		wire.Bind(new(recommendation.UserLoader),        new(*user.Repository)),
 		wire.Bind(new(recommendation.ProductLister),     new(*product.Repository)),
 		wire.Bind(new(recognition.IngredientRepository),     new(*ingredient.Repository)),
+		wire.Bind(new(recognition.Recognizer),               new(*openai.Client)),
+		wire.Bind(new(menu.MenuGenerator),                   new(*openai.Client)),
+		wire.Bind(new(recommendation.RecipeGenerator),       new(*openai.Client)),
 		wire.Bind(new(middleware.AccessTokenValidator),       new(*jwtAdapter)),
 	)
 	return nil, nil

backend/internal/adapters/ai/types.go

@@ -0,0 +1,128 @@
+package ai
+
+// RecipeRequest contains parameters for recipe generation.
+type RecipeRequest struct {
+	UserGoal          string   // "lose" | "maintain" | "gain"
+	DailyCalories     int
+	Restrictions      []string // e.g. ["gluten_free", "vegetarian"]
+	CuisinePrefs      []string // e.g. ["russian", "asian"]
+	Count             int
+	AvailableProducts []string // human-readable list of products in user's pantry
+	Lang              string   // ISO 639-1 target language code, e.g. "en", "ru"
+}
+
+// Recipe is an AI-generated recipe.
+type Recipe struct {
+	Title       string        `json:"title"`
+	Description string        `json:"description"`
+	Cuisine     string        `json:"cuisine"`
+	Difficulty  string        `json:"difficulty"`
+	PrepTimeMin int           `json:"prep_time_min"`
+	CookTimeMin int           `json:"cook_time_min"`
+	Servings    int           `json:"servings"`
+	ImageQuery  string        `json:"image_query"`
+	ImageURL    string        `json:"image_url"`
+	Ingredients []Ingredient  `json:"ingredients"`
+	Steps       []Step        `json:"steps"`
+	Tags        []string      `json:"tags"`
+	Nutrition   NutritionInfo `json:"nutrition_per_serving"`
+}
+
+// Ingredient is a single ingredient in a recipe.
+type Ingredient struct {
+	Name   string  `json:"name"`
+	Amount float64 `json:"amount"`
+	Unit   string  `json:"unit"`
+}
+
+// Step is a single preparation step.
+type Step struct {
+	Number       int    `json:"number"`
+	Description  string `json:"description"`
+	TimerSeconds *int   `json:"timer_seconds"`
+}
+
+// NutritionInfo contains approximate nutritional information per serving.
+type NutritionInfo struct {
+	Calories    float64 `json:"calories"`
+	ProteinG    float64 `json:"protein_g"`
+	FatG        float64 `json:"fat_g"`
+	CarbsG      float64 `json:"carbs_g"`
+	Approximate bool    `json:"approximate"`
+}
+
+// MenuRequest contains parameters for weekly menu generation.
+type MenuRequest struct {
+	UserGoal          string
+	DailyCalories     int
+	Restrictions      []string
+	CuisinePrefs      []string
+	AvailableProducts []string
+	Lang              string // ISO 639-1 target language code, e.g. "en", "ru"
+}
+
+// DayPlan is the AI-generated plan for a single day.
+type DayPlan struct {
+	Day   int         `json:"day"`
+	Meals []MealEntry `json:"meals"`
+}
+
+// MealEntry is a single meal within a day plan.
+type MealEntry struct {
+	MealType string `json:"meal_type"` // breakfast | lunch | dinner
+	Recipe   Recipe `json:"recipe"`
+}
+
+// RecognizedItem is a food item identified in an image.
+type RecognizedItem struct {
+	Name       string  `json:"name"`
+	Quantity   float64 `json:"quantity"`
+	Unit       string  `json:"unit"`
+	Category   string  `json:"category"`
+	Confidence float64 `json:"confidence"`
+}
+
+// UnrecognizedItem is text from a receipt that could not be identified as food.
+type UnrecognizedItem struct {
+	RawText string  `json:"raw_text"`
+	Price   float64 `json:"price,omitempty"`
+}
+
+// ReceiptResult is the full result of receipt OCR.
+type ReceiptResult struct {
+	Items        []RecognizedItem   `json:"items"`
+	Unrecognized []UnrecognizedItem `json:"unrecognized"`
+}
+
+// DishResult is the result of dish recognition.
+type DishResult struct {
+	DishName      string   `json:"dish_name"`
+	WeightGrams   int      `json:"weight_grams"`
+	Calories      float64  `json:"calories"`
+	ProteinG      float64  `json:"protein_g"`
+	FatG          float64  `json:"fat_g"`
+	CarbsG        float64  `json:"carbs_g"`
+	Confidence    float64  `json:"confidence"`
+	SimilarDishes []string `json:"similar_dishes"`
+}
+
+// IngredientTranslation holds the localized name and aliases for one language.
+type IngredientTranslation struct {
+	Lang    string   `json:"lang"`
+	Name    string   `json:"name"`
+	Aliases []string `json:"aliases"`
+}
+
+// IngredientClassification is the AI-produced classification of an unknown food item.
+type IngredientClassification struct {
+	CanonicalName   string                  `json:"canonical_name"`
+	Aliases         []string                `json:"aliases"`      // English aliases
+	Translations    []IngredientTranslation `json:"translations"` // other languages
+	Category        string                  `json:"category"`
+	DefaultUnit     string                  `json:"default_unit"`
+	CaloriesPer100g *float64                `json:"calories_per_100g"`
+	ProteinPer100g  *float64                `json:"protein_per_100g"`
+	FatPer100g      *float64                `json:"fat_per_100g"`
+	CarbsPer100g    *float64                `json:"carbs_per_100g"`
+	StorageDays     int                     `json:"storage_days"`
+}

backend/internal/adapters/openai/menu.go

@@ -4,34 +4,14 @@ import (
 	"context"
 	"fmt"
 	"sync"
+
+	"github.com/food-ai/backend/internal/adapters/ai"
 )
 
-// MenuRequest contains parameters for weekly menu generation.
-type MenuRequest struct {
-	UserGoal          string
-	DailyCalories     int
-	Restrictions      []string
-	CuisinePrefs      []string
-	AvailableProducts []string
-	Lang              string // ISO 639-1 target language code, e.g. "en", "ru"
-}
-
-// DayPlan is the AI-generated plan for a single day.
-type DayPlan struct {
-	Day   int         `json:"day"`
-	Meals []MealEntry `json:"meals"`
-}
-
-// MealEntry is a single meal within a day plan.
-type MealEntry struct {
-	MealType string `json:"meal_type"` // breakfast | lunch | dinner
-	Recipe   Recipe `json:"recipe"`
-}
-
 // GenerateMenu produces a 7-day × 3-meal plan by issuing three parallel
 // GenerateRecipes calls (one per meal type). This avoids token-limit errors
 // that arise from requesting 21 full recipes in a single prompt.
-func (c *Client) GenerateMenu(ctx context.Context, req MenuRequest) ([]DayPlan, error) {
+func (c *Client) GenerateMenu(ctx context.Context, req ai.MenuRequest) ([]ai.DayPlan, error) {
 	type mealSlot struct {
 		mealType string
 		fraction float64 // share of daily calories
@@ -44,7 +24,7 @@ func (c *Client) GenerateMenu(ctx context.Context, req MenuRequest) ([]DayPlan,
 	}
 
 	type mealResult struct {
-		recipes []Recipe
+		recipes []ai.Recipe
 		err     error
 	}
 
@@ -57,7 +37,7 @@ func (c *Client) GenerateMenu(ctx context.Context, req MenuRequest) ([]DayPlan,
 			defer wg.Done()
 			// Scale daily calories to what this meal should contribute.
 			mealCal := int(float64(req.DailyCalories) * fraction)
-			r, err := c.GenerateRecipes(ctx, RecipeRequest{
+			r, err := c.GenerateRecipes(ctx, ai.RecipeRequest{
 				UserGoal:          req.UserGoal,
 				DailyCalories:     mealCal * 3, // prompt divides by 3 internally
 				Restrictions:      req.Restrictions,
@@ -84,11 +64,11 @@ func (c *Client) GenerateMenu(ctx context.Context, req MenuRequest) ([]DayPlan,
 		}
 	}
 
-	days := make([]DayPlan, 7)
+	days := make([]ai.DayPlan, 7)
 	for day := range 7 {
-		days[day] = DayPlan{
+		days[day] = ai.DayPlan{
 			Day: day + 1,
-			Meals: []MealEntry{
+			Meals: []ai.MealEntry{
 				{MealType: slots[0].mealType, Recipe: results[0].recipes[day]},
 				{MealType: slots[1].mealType, Recipe: results[1].recipes[day]},
 				{MealType: slots[2].mealType, Recipe: results[2].recipes[day]},

backend/internal/adapters/openai/recipe.go

@@ -6,65 +6,10 @@ import (
 	"fmt"
 	"strings"
 
+	"github.com/food-ai/backend/internal/adapters/ai"
 	"github.com/food-ai/backend/internal/infra/locale"
 )
 
-// RecipeGenerator generates recipes using the Gemini AI.
-type RecipeGenerator interface {
-	GenerateRecipes(ctx context.Context, req RecipeRequest) ([]Recipe, error)
-}
-
-// RecipeRequest contains parameters for recipe generation.
-type RecipeRequest struct {
-	UserGoal          string   // "lose" | "maintain" | "gain"
-	DailyCalories     int
-	Restrictions      []string // e.g. ["gluten_free", "vegetarian"]
-	CuisinePrefs      []string // e.g. ["russian", "asian"]
-	Count             int
-	AvailableProducts []string // human-readable list of products in user's pantry
-	Lang              string   // ISO 639-1 target language code, e.g. "en", "ru"
-}
-
-// Recipe is a recipe returned by Gemini.
-type Recipe struct {
-	Title       string        `json:"title"`
-	Description string        `json:"description"`
-	Cuisine     string        `json:"cuisine"`
-	Difficulty  string        `json:"difficulty"`
-	PrepTimeMin int           `json:"prep_time_min"`
-	CookTimeMin int           `json:"cook_time_min"`
-	Servings    int           `json:"servings"`
-	ImageQuery  string        `json:"image_query"`
-	ImageURL    string        `json:"image_url"`
-	Ingredients []Ingredient  `json:"ingredients"`
-	Steps       []Step        `json:"steps"`
-	Tags        []string      `json:"tags"`
-	Nutrition   NutritionInfo `json:"nutrition_per_serving"`
-}
-
-// Ingredient is a single ingredient in a recipe.
-type Ingredient struct {
-	Name   string  `json:"name"`
-	Amount float64 `json:"amount"`
-	Unit   string  `json:"unit"`
-}
-
-// Step is a single preparation step.
-type Step struct {
-	Number       int    `json:"number"`
-	Description  string `json:"description"`
-	TimerSeconds *int   `json:"timer_seconds"`
-}
-
-// NutritionInfo contains approximate nutritional information per serving.
-type NutritionInfo struct {
-	Calories    float64 `json:"calories"`
-	ProteinG    float64 `json:"protein_g"`
-	FatG        float64 `json:"fat_g"`
-	CarbsG      float64 `json:"carbs_g"`
-	Approximate bool    `json:"approximate"`
-}
-
 // goalNames maps internal goal codes to English descriptions used in the prompt.
 var goalNames = map[string]string{
 	"lose":     "weight loss",
@@ -72,10 +17,10 @@ var goalNames = map[string]string{
 	"gain":     "muscle gain",
 }
 
-// GenerateRecipes generates recipes using the Gemini AI.
+// GenerateRecipes generates recipes using the OpenAI API.
 // Retries up to maxRetries times only when the response is not valid JSON.
 // API-level errors (rate limits, auth, etc.) are returned immediately.
-func (c *Client) GenerateRecipes(ctx context.Context, req RecipeRequest) ([]Recipe, error) {
+func (c *Client) GenerateRecipes(ctx context.Context, req ai.RecipeRequest) ([]ai.Recipe, error) {
 	prompt := buildRecipePrompt(req)
 
 	messages := []map[string]string{
@@ -111,7 +56,7 @@ func (c *Client) GenerateRecipes(ctx context.Context, req RecipeRequest) ([]Reci
 	return nil, fmt.Errorf("failed to parse valid JSON after %d attempts: %w", maxRetries, lastErr)
 }
 
-func buildRecipePrompt(req RecipeRequest) string {
+func buildRecipePrompt(req ai.RecipeRequest) string {
 	lang := req.Lang
 	if lang == "" {
 		lang = "en"
@@ -189,7 +134,7 @@ Return ONLY a valid JSON array without markdown or extra text:
 }]`, count, langName, goal, req.DailyCalories, restrictions, cuisines, productsSection, perMealCalories, langName)
 }
 
-func parseRecipesJSON(text string) ([]Recipe, error) {
+func parseRecipesJSON(text string) ([]ai.Recipe, error) {
 	text = strings.TrimSpace(text)
 	if strings.HasPrefix(text, "```") {
 		text = strings.TrimPrefix(text, "```json")
@@ -198,7 +143,7 @@ func parseRecipesJSON(text string) ([]Recipe, error) {
 		text = strings.TrimSpace(text)
 	}
 
-	var recipes []Recipe
+	var recipes []ai.Recipe
 	if err := json.Unmarshal([]byte(text), &recipes); err != nil {
 		return nil, err
 	}

backend/internal/adapters/openai/recognition.go

@@ -1,68 +1,16 @@
 package openai
 
 import (
+	"context"
 	"encoding/json"
 	"fmt"
 	"strings"
-	"context"
+
+	"github.com/food-ai/backend/internal/adapters/ai"
 )
 
-// RecognizedItem is a food item identified in an image.
-type RecognizedItem struct {
-	Name       string  `json:"name"`
-	Quantity   float64 `json:"quantity"`
-	Unit       string  `json:"unit"`
-	Category   string  `json:"category"`
-	Confidence float64 `json:"confidence"`
-}
-
-// UnrecognizedItem is text from a receipt that could not be identified as food.
-type UnrecognizedItem struct {
-	RawText string  `json:"raw_text"`
-	Price   float64 `json:"price,omitempty"`
-}
-
-// ReceiptResult is the full result of receipt OCR.
-type ReceiptResult struct {
-	Items        []RecognizedItem   `json:"items"`
-	Unrecognized []UnrecognizedItem `json:"unrecognized"`
-}
-
-// DishResult is the result of dish recognition.
-type DishResult struct {
-	DishName      string   `json:"dish_name"`
-	WeightGrams   int      `json:"weight_grams"`
-	Calories      float64  `json:"calories"`
-	ProteinG      float64  `json:"protein_g"`
-	FatG          float64  `json:"fat_g"`
-	CarbsG        float64  `json:"carbs_g"`
-	Confidence    float64  `json:"confidence"`
-	SimilarDishes []string `json:"similar_dishes"`
-}
-
-// IngredientTranslation holds the localized name and aliases for one language.
-type IngredientTranslation struct {
-	Lang    string   `json:"lang"`
-	Name    string   `json:"name"`
-	Aliases []string `json:"aliases"`
-}
-
-// IngredientClassification is the AI-produced classification of an unknown food item.
-type IngredientClassification struct {
-	CanonicalName   string                  `json:"canonical_name"`
-	Aliases         []string                `json:"aliases"`      // English aliases
-	Translations    []IngredientTranslation `json:"translations"` // other languages
-	Category        string                  `json:"category"`
-	DefaultUnit     string                  `json:"default_unit"`
-	CaloriesPer100g *float64                `json:"calories_per_100g"`
-	ProteinPer100g  *float64                `json:"protein_per_100g"`
-	FatPer100g      *float64                `json:"fat_per_100g"`
-	CarbsPer100g    *float64                `json:"carbs_per_100g"`
-	StorageDays     int                     `json:"storage_days"`
-}
-
 // RecognizeReceipt uses the vision model to extract food items from a receipt photo.
-func (c *Client) RecognizeReceipt(ctx context.Context, imageBase64, mimeType string) (*ReceiptResult, error) {
+func (c *Client) RecognizeReceipt(ctx context.Context, imageBase64, mimeType string) (*ai.ReceiptResult, error) {
 	prompt := `Ты — OCR-система для чеков из продуктовых магазинов.
 
 Проанализируй фото чека и извлеки список продуктов питания.
@@ -91,21 +39,21 @@ func (c *Client) RecognizeReceipt(ctx context.Context, imageBase64, mimeType str
 		return nil, fmt.Errorf("recognize receipt: %w", err)
 	}
 
-	var result ReceiptResult
+	var result ai.ReceiptResult
 	if err := parseJSON(text, &result); err != nil {
 		return nil, fmt.Errorf("parse receipt result: %w", err)
 	}
 	if result.Items == nil {
-		result.Items = []RecognizedItem{}
+		result.Items = []ai.RecognizedItem{}
 	}
 	if result.Unrecognized == nil {
-		result.Unrecognized = []UnrecognizedItem{}
+		result.Unrecognized = []ai.UnrecognizedItem{}
 	}
 	return &result, nil
 }
 
 // RecognizeProducts uses the vision model to identify food items in a photo (fridge, shelf, etc.).
-func (c *Client) RecognizeProducts(ctx context.Context, imageBase64, mimeType string) ([]RecognizedItem, error) {
+func (c *Client) RecognizeProducts(ctx context.Context, imageBase64, mimeType string) ([]ai.RecognizedItem, error) {
 	prompt := `Ты — система распознавания продуктов питания.
 
 Посмотри на фото и определи все видимые продукты питания.
@@ -131,19 +79,19 @@ func (c *Client) RecognizeProducts(ctx context.Context, imageBase64, mimeType st
 	}
 
 	var result struct {
-		Items []RecognizedItem `json:"items"`
+		Items []ai.RecognizedItem `json:"items"`
 	}
 	if err := parseJSON(text, &result); err != nil {
 		return nil, fmt.Errorf("parse products result: %w", err)
 	}
 	if result.Items == nil {
-		return []RecognizedItem{}, nil
+		return []ai.RecognizedItem{}, nil
 	}
 	return result.Items, nil
 }
 
 // RecognizeDish uses the vision model to identify a dish and estimate its nutritional content.
-func (c *Client) RecognizeDish(ctx context.Context, imageBase64, mimeType string) (*DishResult, error) {
+func (c *Client) RecognizeDish(ctx context.Context, imageBase64, mimeType string) (*ai.DishResult, error) {
 	prompt := `Ты — диетолог и кулинарный эксперт.
 
 Посмотри на фото блюда и определи:
@@ -171,7 +119,7 @@ func (c *Client) RecognizeDish(ctx context.Context, imageBase64, mimeType string
 		return nil, fmt.Errorf("recognize dish: %w", err)
 	}
 
-	var result DishResult
+	var result ai.DishResult
 	if err := parseJSON(text, &result); err != nil {
 		return nil, fmt.Errorf("parse dish result: %w", err)
 	}
@@ -183,7 +131,7 @@ func (c *Client) RecognizeDish(ctx context.Context, imageBase64, mimeType string
 
 // ClassifyIngredient uses the text model to classify an unknown food item
 // and build an ingredient_mappings record for it.
-func (c *Client) ClassifyIngredient(ctx context.Context, name string) (*IngredientClassification, error) {
+func (c *Client) ClassifyIngredient(ctx context.Context, name string) (*ai.IngredientClassification, error) {
 	prompt := fmt.Sprintf(`Classify the food product: "%s".
 Return ONLY valid JSON without markdown:
 {
@@ -209,7 +157,7 @@ Return ONLY valid JSON without markdown:
 		return nil, fmt.Errorf("classify ingredient: %w", err)
 	}
 
-	var result IngredientClassification
+	var result ai.IngredientClassification
 	if err := parseJSON(text, &result); err != nil {
 		return nil, fmt.Errorf("parse classification: %w", err)
 	}

backend/internal/menu/handler.go

@@ -10,8 +10,8 @@ import (
 	"sync"
 	"time"
 
+	"github.com/food-ai/backend/internal/adapters/ai"
 	"github.com/food-ai/backend/internal/dish"
-	"github.com/food-ai/backend/internal/adapters/openai"
 	"github.com/food-ai/backend/internal/infra/locale"
 	"github.com/food-ai/backend/internal/infra/middleware"
 	"github.com/food-ai/backend/internal/user"
@@ -38,10 +38,15 @@ type RecipeSaver interface {
 	Create(ctx context.Context, req dish.CreateRequest) (string, error)
 }
 
+// MenuGenerator generates a 7-day meal plan via an AI provider.
+type MenuGenerator interface {
+	GenerateMenu(ctx context.Context, req ai.MenuRequest) ([]ai.DayPlan, error)
+}
+
 // Handler handles menu and shopping-list endpoints.
 type Handler struct {
 	repo          *Repository
-	openaiClient  *openai.Client
+	menuGenerator MenuGenerator
 	pexels        PhotoSearcher
 	userLoader    UserLoader
 	productLister ProductLister
@@ -51,7 +56,7 @@ type Handler struct {
 // NewHandler creates a new Handler.
 func NewHandler(
 	repo *Repository,
-	openaiClient *openai.Client,
+	menuGenerator MenuGenerator,
 	pexels PhotoSearcher,
 	userLoader UserLoader,
 	productLister ProductLister,
@@ -59,7 +64,7 @@ func NewHandler(
 ) *Handler {
 	return &Handler{
 		repo:          repo,
-		openaiClient:  openaiClient,
+		menuGenerator: menuGenerator,
 		pexels:        pexels,
 		userLoader:    userLoader,
 		productLister: productLister,
@@ -137,7 +142,7 @@ func (h *Handler) GenerateMenu(w http.ResponseWriter, r *http.Request) {
 	}
 
 	// Generate 7-day plan via Gemini.
-	days, err := h.openaiClient.GenerateMenu(r.Context(), menuReq)
+	days, err := h.menuGenerator.GenerateMenu(r.Context(), menuReq)
 	if err != nil {
 		slog.Error("generate menu", "user_id", userID, "err", err)
 		writeError(w, http.StatusServiceUnavailable, "menu generation failed, please try again")
@@ -449,8 +454,8 @@ type userPreferences struct {
 	Restrictions []string `json:"restrictions"`
 }
 
-func buildMenuRequest(u *user.User, lang string) openai.MenuRequest {
+func buildMenuRequest(u *user.User, lang string) ai.MenuRequest {
-	req := openai.MenuRequest{DailyCalories: 2000, Lang: lang}
+	req := ai.MenuRequest{DailyCalories: 2000, Lang: lang}
 	if u.Goal != nil {
 		req.UserGoal = *u.Goal
 	}
@@ -468,7 +473,7 @@ func buildMenuRequest(u *user.User, lang string) openai.MenuRequest {
 }
 
 // recipeToCreateRequest converts a Gemini recipe to a dish.CreateRequest.
-func recipeToCreateRequest(r openai.Recipe) dish.CreateRequest {
+func recipeToCreateRequest(r ai.Recipe) dish.CreateRequest {
 	cr := dish.CreateRequest{
 		Name:        r.Title,
 		Description: r.Description,

backend/internal/recognition/handler.go

@@ -8,7 +8,7 @@ import (
 	"strings"
 	"sync"
 
-	"github.com/food-ai/backend/internal/adapters/openai"
+	"github.com/food-ai/backend/internal/adapters/ai"
 	"github.com/food-ai/backend/internal/infra/middleware"
 	"github.com/food-ai/backend/internal/ingredient"
 )
@@ -21,15 +21,23 @@ type IngredientRepository interface {
 	UpsertAliases(ctx context.Context, id, lang string, aliases []string) error
 }
 
+// Recognizer is the AI provider interface for image-based food recognition.
+type Recognizer interface {
+	RecognizeReceipt(ctx context.Context, imageBase64, mimeType string) (*ai.ReceiptResult, error)
+	RecognizeProducts(ctx context.Context, imageBase64, mimeType string) ([]ai.RecognizedItem, error)
+	RecognizeDish(ctx context.Context, imageBase64, mimeType string) (*ai.DishResult, error)
+	ClassifyIngredient(ctx context.Context, name string) (*ai.IngredientClassification, error)
+}
+
 // Handler handles POST /ai/* recognition endpoints.
 type Handler struct {
-	openaiClient   *openai.Client
+	recognizer     Recognizer
 	ingredientRepo IngredientRepository
 }
 
 // NewHandler creates a new Handler.
-func NewHandler(openaiClient *openai.Client, repo IngredientRepository) *Handler {
+func NewHandler(recognizer Recognizer, repo IngredientRepository) *Handler {
-	return &Handler{openaiClient: openaiClient, ingredientRepo: repo}
+	return &Handler{recognizer: recognizer, ingredientRepo: repo}
 }
 
 // ---------------------------------------------------------------------------
@@ -61,11 +69,11 @@ type EnrichedItem struct {
 // ReceiptResponse is the response for POST /ai/recognize-receipt.
 type ReceiptResponse struct {
 	Items        []EnrichedItem            `json:"items"`
-	Unrecognized []openai.UnrecognizedItem `json:"unrecognized"`
+	Unrecognized []ai.UnrecognizedItem `json:"unrecognized"`
 }
 
 // DishResponse is the response for POST /ai/recognize-dish.
-type DishResponse = openai.DishResult
+type DishResponse = ai.DishResult
 
 // ---------------------------------------------------------------------------
 // Handlers
@@ -83,7 +91,7 @@ func (h *Handler) RecognizeReceipt(w http.ResponseWriter, r *http.Request) {
 		return
 	}
 
-	result, err := h.openaiClient.RecognizeReceipt(r.Context(), req.ImageBase64, req.MimeType)
+	result, err := h.recognizer.RecognizeReceipt(r.Context(), req.ImageBase64, req.MimeType)
 	if err != nil {
 		slog.Error("recognize receipt", "err", err)
 		writeErrorJSON(w, http.StatusServiceUnavailable, "recognition failed, please try again")
@@ -110,13 +118,13 @@ func (h *Handler) RecognizeProducts(w http.ResponseWriter, r *http.Request) {
 	}
 
 	// Process each image in parallel.
-	allItems := make([][]openai.RecognizedItem, len(req.Images))
+	allItems := make([][]ai.RecognizedItem, len(req.Images))
 	var wg sync.WaitGroup
 	for i, img := range req.Images {
 		wg.Add(1)
 		go func(i int, img imageRequest) {
 			defer wg.Done()
-			items, err := h.openaiClient.RecognizeProducts(r.Context(), img.ImageBase64, img.MimeType)
+			items, err := h.recognizer.RecognizeProducts(r.Context(), img.ImageBase64, img.MimeType)
 			if err != nil {
 				slog.Warn("recognize products from image", "index", i, "err", err)
 				return
@@ -140,7 +148,7 @@ func (h *Handler) RecognizeDish(w http.ResponseWriter, r *http.Request) {
 		return
 	}
 
-	result, err := h.openaiClient.RecognizeDish(r.Context(), req.ImageBase64, req.MimeType)
+	result, err := h.recognizer.RecognizeDish(r.Context(), req.ImageBase64, req.MimeType)
 	if err != nil {
 		slog.Error("recognize dish", "err", err)
 		writeErrorJSON(w, http.StatusServiceUnavailable, "recognition failed, please try again")
@@ -156,7 +164,7 @@ func (h *Handler) RecognizeDish(w http.ResponseWriter, r *http.Request) {
 
 // enrichItems matches each recognized item against ingredient_mappings.
 // Items without a match trigger a Gemini classification call and upsert into the DB.
-func (h *Handler) enrichItems(ctx context.Context, items []openai.RecognizedItem) []EnrichedItem {
+func (h *Handler) enrichItems(ctx context.Context, items []ai.RecognizedItem) []EnrichedItem {
 	result := make([]EnrichedItem, 0, len(items))
 	for _, item := range items {
 		enriched := EnrichedItem{
@@ -188,7 +196,7 @@ func (h *Handler) enrichItems(ctx context.Context, items []openai.RecognizedItem
 			}
 		} else {
 			// No mapping — ask AI to classify and save for future reuse.
-			classification, err := h.openaiClient.ClassifyIngredient(ctx, item.Name)
+			classification, err := h.recognizer.ClassifyIngredient(ctx, item.Name)
 			if err != nil {
 				slog.Warn("classify unknown ingredient", "name", item.Name, "err", err)
 			} else {
@@ -208,7 +216,7 @@ func (h *Handler) enrichItems(ctx context.Context, items []openai.RecognizedItem
 }
 
 // saveClassification upserts an AI-produced ingredient classification into the DB.
-func (h *Handler) saveClassification(ctx context.Context, c *openai.IngredientClassification) *ingredient.IngredientMapping {
+func (h *Handler) saveClassification(ctx context.Context, c *ai.IngredientClassification) *ingredient.IngredientMapping {
 	if c == nil || c.CanonicalName == "" {
 		return nil
 	}
@@ -252,8 +260,8 @@ func (h *Handler) saveClassification(ctx context.Context, c *openai.IngredientCl
 
 // mergeAndDeduplicate combines results from multiple images.
 // Items sharing the same name (case-insensitive) have their quantities summed.
-func mergeAndDeduplicate(batches [][]openai.RecognizedItem) []openai.RecognizedItem {
+func mergeAndDeduplicate(batches [][]ai.RecognizedItem) []ai.RecognizedItem {
-	seen := make(map[string]*openai.RecognizedItem)
+	seen := make(map[string]*ai.RecognizedItem)
 	var order []string
 
 	for _, batch := range batches {
@@ -273,7 +281,7 @@ func mergeAndDeduplicate(batches [][]openai.RecognizedItem) []openai.RecognizedI
 		}
 	}
 
-	result := make([]openai.RecognizedItem, 0, len(order))
+	result := make([]ai.RecognizedItem, 0, len(order))
 	for _, key := range order {
 		result = append(result, *seen[key])
 	}

backend/internal/recommendation/handler.go

@@ -8,7 +8,7 @@ import (
 	"strconv"
 	"sync"
 
-	"github.com/food-ai/backend/internal/adapters/openai"
+	"github.com/food-ai/backend/internal/adapters/ai"
 	"github.com/food-ai/backend/internal/infra/locale"
 	"github.com/food-ai/backend/internal/infra/middleware"
 	"github.com/food-ai/backend/internal/user"
@@ -35,18 +35,23 @@ type userPreferences struct {
 	Restrictions []string `json:"restrictions"`
 }
 
+// RecipeGenerator generates recipe recommendations via an AI provider.
+type RecipeGenerator interface {
+	GenerateRecipes(ctx context.Context, req ai.RecipeRequest) ([]ai.Recipe, error)
+}
+
 // Handler handles GET /recommendations.
 type Handler struct {
-	openaiClient  *openai.Client
+	recipeGenerator RecipeGenerator
 	pexels          PhotoSearcher
 	userLoader      UserLoader
 	productLister   ProductLister
 }
 
 // NewHandler creates a new Handler.
-func NewHandler(openaiClient *openai.Client, pexels PhotoSearcher, userLoader UserLoader, productLister ProductLister) *Handler {
+func NewHandler(recipeGenerator RecipeGenerator, pexels PhotoSearcher, userLoader UserLoader, productLister ProductLister) *Handler {
 	return &Handler{
-		openaiClient:  openaiClient,
+		recipeGenerator: recipeGenerator,
 		pexels:          pexels,
 		userLoader:      userLoader,
 		productLister:   productLister,
@@ -84,7 +89,7 @@ func (h *Handler) GetRecommendations(w http.ResponseWriter, r *http.Request) {
 		slog.Warn("load products for recommendations", "user_id", userID, "err", err)
 	}
 
-	recipes, err := h.openaiClient.GenerateRecipes(r.Context(), req)
+	recipes, err := h.recipeGenerator.GenerateRecipes(r.Context(), req)
 	if err != nil {
 		slog.Error("generate recipes", "user_id", userID, "err", err)
 		writeErrorJSON(w, http.StatusServiceUnavailable, "recipe generation failed, please try again")
@@ -109,8 +114,8 @@ func (h *Handler) GetRecommendations(w http.ResponseWriter, r *http.Request) {
 	writeJSON(w, http.StatusOK, recipes)
 }
 
-func buildRecipeRequest(u *user.User, count int, lang string) openai.RecipeRequest {
+func buildRecipeRequest(u *user.User, count int, lang string) ai.RecipeRequest {
-	req := openai.RecipeRequest{
+	req := ai.RecipeRequest{
 		Count:         count,
 		DailyCalories: 2000, // sensible default
 		Lang:          lang,