feat(ai): Vercel AI SDK provider factory with BYOK and per-use-case model prefs
Provider factory (OpenAI/Anthropic/OpenRouter/Ollama). generateObject for all outputs. Features: recipe generation, photo-to-recipe vision, variations, drink/meal pairings, ingredient substitution, recipe adaptation, nutrition analysis, URL import, meal plan gen. User BYOK keys (AES-256-GCM). Per-use-case model preferences (text/vision/mealPlan). Site-level key override via admin settings.
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import { NextRequest, NextResponse } from "next/server";
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import { z } from "zod";
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import { db, recipes, recipeIngredients, recipeSteps } from "@epicure/db";
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import { requireSession } from "@/lib/api-auth";
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import { applyRateLimit } from "@/lib/rate-limit";
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import { checkTierLimit, incrementUsage } from "@/lib/tiers";
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import { importFromPhoto } from "@/lib/ai/features/import-photo";
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import { getModelConfigForUseCase } from "@/lib/ai/resolve-user-key";
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const Schema = z.object({
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imageBase64: z.string().max(14_000_000),
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mimeType: z.enum(["image/jpeg", "image/png", "image/webp"]),
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});
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export async function POST(req: NextRequest) {
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const { session, response } = await requireSession();
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if (response) return response;
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const body = await req.json() as unknown;
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const parsed = Schema.safeParse(body);
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if (!parsed.success) {
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return NextResponse.json({ error: "Validation error", issues: parsed.error.issues }, { status: 400 });
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}
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const limited = await applyRateLimit(`rl:ai:${session!.user.id}`, 5, 60);
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if (limited) return limited;
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try {
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await checkTierLimit(session!.user.id, session!.user.tier as "free" | "pro", "aiCall");
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} catch (err: unknown) {
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const msg = err instanceof Error ? err.message : "Tier limit reached";
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return NextResponse.json({ error: msg }, { status: 403 });
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}
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const userId = session!.user.id;
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const locale = (session!.user as { locale?: string }).locale ?? "en";
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const aiConfig = await getModelConfigForUseCase(userId, "vision");
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// Fall back to vision-capable defaults if no explicit model configured
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if (!aiConfig.model) {
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if (aiConfig.provider === "openai") aiConfig.model = "gpt-4o";
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else if (aiConfig.provider === "anthropic") aiConfig.model = "claude-sonnet-4-6";
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}
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let recipe;
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try {
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recipe = await importFromPhoto(parsed.data.imageBase64, parsed.data.mimeType, aiConfig, locale);
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} catch (err: unknown) {
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const msg = err instanceof Error ? err.message : "AI analysis failed";
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return NextResponse.json({ error: msg }, { status: 502 });
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}
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await incrementUsage(userId, "aiCall");
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const newRecipeId = crypto.randomUUID();
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const now = new Date();
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await db.transaction(async (tx) => {
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await tx.insert(recipes).values({
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id: newRecipeId,
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authorId: userId,
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title: recipe.title,
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description: recipe.description,
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baseServings: recipe.baseServings ?? 4,
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visibility: "private",
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difficulty: recipe.difficulty,
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prepMins: recipe.prepMins,
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cookMins: recipe.cookMins,
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dietaryTags: recipe.dietaryTags ?? {},
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aiGenerated: true,
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createdAt: now,
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updatedAt: now,
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});
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if (recipe.ingredients.length > 0) {
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await tx.insert(recipeIngredients).values(
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recipe.ingredients.map((ing, i) => ({
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id: crypto.randomUUID(),
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recipeId: newRecipeId,
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rawName: ing.rawName,
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quantity: ing.quantity !== undefined ? String(ing.quantity) : undefined,
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unit: ing.unit,
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note: ing.note,
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order: i,
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}))
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);
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}
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if (recipe.steps.length > 0) {
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await tx.insert(recipeSteps).values(
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recipe.steps.map((step, i) => ({
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id: crypto.randomUUID(),
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recipeId: newRecipeId,
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instruction: step.instruction,
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timerSeconds: step.timerSeconds,
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order: i,
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}))
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);
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}
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});
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return NextResponse.json({ id: newRecipeId });
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}
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