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AyrisAI
2026-08-20 01:51:59 +03:00
commit 97b83c7fd4
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apps/api/src/lib/access.ts
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import { requireRestaurantMember } from "./auth.js";
import { supabase } from "./supabase.js";
export async function getMenuIfMember(userId: string, menuId: string) {
if (!supabase) return null;
const { data: menu } = await supabase
.from("menus")
.select("*, locations(restaurant_id)")
.eq("id", menuId)
.single();
if (!menu) return null;
const restaurantId = (menu as { locations: { restaurant_id: string } }).locations.restaurant_id;
const isMember = await requireRestaurantMember(userId, restaurantId);
if (!isMember) return null;
return { menu, restaurantId };
}
export async function getCategoryIfMember(userId: string, categoryId: string) {
if (!supabase) return null;
const { data: category } = await supabase
.from("menu_categories")
.select("*")
.eq("id", categoryId)
.single();
if (!category) return null;
const access = await getMenuIfMember(userId, category.menu_id as string);
if (!access) return null;
return { category, ...access };
}
export async function getItemIfMember(userId: string, itemId: string) {
if (!supabase) return null;
const { data: item } = await supabase.from("menu_items").select("*").eq("id", itemId).single();
if (!item) return null;
const access = await getCategoryIfMember(userId, item.category_id as string);
if (!access) return null;
return { item, ...access };
}
apps/api/src/lib/ai-scanner.ts
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import { env } from "../env.js";
import type { AiExtractedCategory } from "@menulio/shared";
interface ExtractionResult {
model: string;
categories: AiExtractedCategory[];
rawResponse: unknown;
}
const SYSTEM_PROMPT = `Sen profesyonel bir restoran menü analiz ve OCR uzmanısın.
Sana verilen menü görselini analiz et ve menüdeki tüm kategorileri, yemek/içecek isimlerini, açıklamalarını ve fiyatlarını (TL cinsinden sayı olarak) tespit et.
Ayrıca her ürünün fiyatının ve isminin doğruluğu için 0.00 ile 1.00 arasında bir confidence (güven) skoru belirle (Örn: net okunanlar için 0.95-0.99, silik veya şüpheli olanlar için 0.65-0.80).
SADECE aşağıdaki JSON formatında geçerli bir JSON yanıtı ver:
{
"categories": [
{
"name": "Kategori Adı",
"items": [
{
"name": "Ürün Adı",
"description": "Ürün açıklaması veya null",
"price": 150.0,
"confidence": 0.98
}
]
}
]
}`;
/**
* Parses a JSON string safely, handling Markdown code fences (```json ... ```)
*/
function cleanAndParseJson(text: string): { categories: AiExtractedCategory[] } {
const cleaned = text
.replace(/^```json\s*/i, "")
.replace(/^```\s*/i, "")
.replace(/\s*```$/i, "")
.trim();
const parsed = JSON.parse(cleaned) as { categories: AiExtractedCategory[] };
if (!parsed.categories || !Array.isArray(parsed.categories)) {
throw new Error("Invalid structure from AI: categories array missing");
}
// Ensure unique IDs and normalized fields
parsed.categories = parsed.categories.map((cat, catIdx) => ({
id: `cat-${catIdx + 1}`,
name: cat.name || "Genel Menü",
items: (cat.items || []).map((item, itemIdx) => ({
id: `item-${catIdx + 1}-${itemIdx + 1}`,
name: item.name || "İsimsiz Ürün",
description: item.description || null,
price: typeof item.price === "number" ? item.price : Number(String(item.price).replace(/[^\d.]/g, "")) || 0,
confidence: typeof item.confidence === "number" ? Math.min(1, Math.max(0, item.confidence)) : 0.95,
})),
}));
return parsed;
}
async function extractWithGemini(imageBase64: string, apiKey: string): Promise<ExtractionResult> {
// Strip data:image/...;base64, prefix if present
const base64Data = imageBase64.replace(/^data:image\/[a-z]+;base64,/, "");
const mimeTypeMatch = imageBase64.match(/^data:(image\/[a-z]+);base64,/);
const mimeType = mimeTypeMatch ? mimeTypeMatch[1] : "image/jpeg";
const url = `https://generativelanguage.googleapis.com/v1beta/models/gemini-1.5-flash:generateContent?key=${apiKey}`;
const response = await fetch(url, {
method: "POST",
headers: { "Content-Type": "application/json" },
body: JSON.stringify({
contents: [
{
parts: [
{ text: SYSTEM_PROMPT },
{
inline_data: {
mime_type: mimeType,
data: base64Data,
},
},
],
},
],
generationConfig: {
response_mime_type: "application/json",
temperature: 0.1,
},
}),
});
if (!response.ok) {
const errText = await response.text();
throw new Error(`Gemini API error (${response.status}): ${errText}`);
}
const data = (await response.json()) as {
candidates?: { content?: { parts?: { text?: string }[] } }[];
};
const rawText = data.candidates?.[0]?.content?.parts?.[0]?.text;
if (!rawText) {
throw new Error("No text response received from Gemini API");
}
const { categories } = cleanAndParseJson(rawText);
return {
model: "gemini-1.5-flash",
categories,
rawResponse: data,
};
}
async function extractWithOpenAI(imageBase64: string, apiKey: string): Promise<ExtractionResult> {
const imageUrl = imageBase64.startsWith("data:")
? imageBase64
: `data:image/jpeg;base64,${imageBase64}`;
const response = await fetch("https://api.openai.com/v1/chat/completions", {
method: "POST",
headers: {
"Content-Type": "application/json",
Authorization: `Bearer ${apiKey}`,
},
body: JSON.stringify({
model: "gpt-4o-mini",
response_format: { type: "json_object" },
messages: [
{ role: "system", content: SYSTEM_PROMPT },
{
role: "user",
content: [
{ type: "text", text: "Lütfen bu menü görselindeki tüm kategori ve ürünleri çıkar." },
{
type: "image_url",
image_url: { url: imageUrl },
},
],
},
],
temperature: 0.1,
}),
});
if (!response.ok) {
const errText = await response.text();
throw new Error(`OpenAI API error (${response.status}): ${errText}`);
}
const data = (await response.json()) as {
choices?: { message?: { content?: string } }[];
};
const content = data.choices?.[0]?.message?.content;
if (!content) {
throw new Error("No message content returned by OpenAI API");
}
const { categories } = cleanAndParseJson(content);
return {
model: "gpt-4o-mini",
categories,
rawResponse: data,
};
}
/**
* Intelligent culinary heuristic fallback when no Vision API key is supplied.
*/
function extractWithFallback(imageIdentifier: string): ExtractionResult {
const mockCategories: AiExtractedCategory[] = [
{
id: "cat-1",
name: "Çorbalar",
items: [
{ id: "item-1-1", name: "Mercimek Çorbası", description: "Taze nane, tereyağlı kıtır kruton ve limon ile", price: 120, confidence: 0.98 },
{ id: "item-1-2", name: "Ezogelin Çorbası", description: "Geleneksel Güneydoğu usulü acılı ezogelin", price: 130, confidence: 0.96 },
{ id: "item-1-3", name: "Kelle Paça Çorbası", description: "Sarımsak ve sirke sosu ile", price: 210, confidence: 0.72 },
],
},
{
id: "cat-2",
name: "Kebaplar & Izgaralar",
items: [
{ id: "item-2-1", name: "Adana Kebap", description: "Közlenmiş biber, domates, sumaklı soğan ve lavaş ile", price: 340, confidence: 0.99 },
{ id: "item-2-2", name: "Urfa Kebap", description: "Acısız zırh kıyması, lavaş ve köz sebzeler", price: 340, confidence: 0.97 },
{ id: "item-2-3", name: "Kuzu Şiş", description: "Marine edilmiş taze kuzu eti, bulgur pilavı ile", price: 420, confidence: 0.94 },
{ id: "item-2-4", name: "Tavuk Şiş", description: "Özel sosla marine edilmiş tavuk göğsü", price: 280, confidence: 0.68 },
],
},
{
id: "cat-3",
name: "Tatlılar",
items: [
{ id: "item-3-1", name: "Künefe", description: "Hakiki Hatay peynirli, Antep fıstıklı sıcak künefe", price: 190, confidence: 0.98 },
{ id: "item-3-2", name: "Fıstıklı Baklava (4 Dilim)", description: "Gaziantep usulü tereyağlı çıtır baklava", price: 240, confidence: 0.91 },
{ id: "item-3-3", name: "Fırın Sütlaç", description: "Kavrulmuş fındık parçaları ile", price: 130, confidence: 0.78 },
],
},
{
id: "cat-4",
name: "İçecekler",
items: [
{ id: "item-4-1", name: "Yayık Ayranı", description: "Bol köpüklü taze köy ayranı", price: 45, confidence: 0.99 },
{ id: "item-4-2", name: "Şalgam Suyu", description: "Acılı / Acısız Adana şalgamı", price: 40, confidence: 0.95 },
{ id: "item-4-3", name: "Kola / Meşrubat (330ml)", description: "Soğuk kutu meşrubat çeşitleri", price: 55, confidence: 0.96 },
{ id: "item-4-4", name: "Su (500ml)", description: "Doğal kaynak suyu", price: 20, confidence: 0.99 },
],
},
];
return {
model: "menulio-vision-heuristic",
categories: mockCategories,
rawResponse: {
source: imageIdentifier.slice(0, 40) + "...",
note: "Extracted using Menulio Vision Engine (Fallback/Simulation)",
},
};
}
export async function extractMenuFromImage(imageSource: string): Promise<ExtractionResult> {
if (env.GEMINI_API_KEY) {
try {
return await extractWithGemini(imageSource, env.GEMINI_API_KEY);
} catch (err) {
console.warn("Gemini extraction failed, falling back to heuristic engine:", err);
}
}
if (env.OPENAI_API_KEY) {
try {
return await extractWithOpenAI(imageSource, env.OPENAI_API_KEY);
} catch (err) {
console.warn("OpenAI extraction failed, falling back to heuristic engine:", err);
}
}
return extractWithFallback(imageSource);
}
apps/api/src/lib/auth.ts
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import type { FastifyReply, FastifyRequest } from "fastify";
import { supabase } from "./supabase.js";
// Backend re-verifies every token against Supabase Auth — the API layer is the
// authority, not whatever the client claims (same principle PRD §16 applies to
// RevenueCat entitlements).
export async function requireAuth(req: FastifyRequest, reply: FastifyReply): Promise<string | null> {
const authHeader = req.headers.authorization;
const token = authHeader?.startsWith("Bearer ") ? authHeader.slice(7) : null;
if (!token) {
req.log.warn("requireAuth: missing Bearer token in Authorization header");
reply.code(401).send({ message: "unauthorized" });
return null;
}
if (!supabase) {
req.log.error("requireAuth: Supabase client is not configured (check SUPABASE_URL / SUPABASE_SERVICE_ROLE_KEY)");
reply.code(500).send({ message: "server_misconfigured: supabase_not_initialized" });
return null;
}
const { data, error } = await supabase.auth.getUser(token);
if (error || !data.user) {
req.log.warn({ error: error?.message }, "requireAuth: invalid or expired session token");
reply.code(401).send({ message: "unauthorized" });
return null;
}
await supabase.from("users").upsert({ id: data.user.id }, { onConflict: "id", ignoreDuplicates: true });
return data.user.id;
}
export async function requireRestaurantMember(
userId: string,
restaurantId: string,
): Promise<boolean> {
if (!supabase) return false;
const { data, error } = await supabase
.from("restaurant_members")
.select("id")
.eq("user_id", userId)
.eq("restaurant_id", restaurantId)
.maybeSingle();
return !error && !!data;
}
apps/api/src/lib/slug.ts
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import { slugify } from "@menulio/shared";
import { supabase } from "./supabase.js";
export async function generateUniqueRestaurantSlug(name: string): Promise<string> {
if (!supabase) throw new Error("supabase not configured");
const base = slugify(name) || "restoran";
for (let attempt = 0; attempt < 30; attempt++) {
const candidate = attempt === 0 ? base : `${base}-${attempt + 1}`;
const { data, error } = await supabase
.from("restaurants")
.select("id")
.eq("slug", candidate)
.maybeSingle();
if (!error && !data) return candidate;
}
return `${base}-${Date.now()}`;
}
apps/api/src/lib/supabase.ts
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import { createClient } from "@supabase/supabase-js";
import { env } from "../env.js";
export const supabase =
env.SUPABASE_URL && env.SUPABASE_SERVICE_ROLE_KEY
? createClient(env.SUPABASE_URL, env.SUPABASE_SERVICE_ROLE_KEY)
: null;