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refactor: introduce adapter pattern for AI provider (OpenAI)

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- 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>
This commit is contained in:
dbastrikin
2026-03-15 21:27:04 +02:00
parent 19a985ad49
commit fee240da7d
8 changed files with 217 additions and 194 deletions
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80
backend/internal/adapters/openai/recognition.go
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@@ -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)
}