feat: cooking history/gallery, unit conversion, nutrition diary, pantry scan, digest cron, nutrition-targeted meal plans

Six M-sized items from HANDOFF.md's new-features backlog:

- Profile tabs: cooking-history stats (total cooked, last-cooked, streak)
  and a "cooked it" photo gallery, both owner-only
- Display-time unit conversion (metric<->imperial) for recipe ingredients,
  respecting each user's unitPref; original value always shown alongside
  the conversion
- Nutrition daily diary: per-day macro totals computed from cooking history
  x recipe nutritionData, compared against user goals
- Pantry scan: real barcode lookup (zxing + Open Food Facts, no API key)
  with an AI-vision fallback for unbarcoded items, always confirm-before-
  insert, both paths tier/rate-limited like other AI features
- Weekly digest email: new followers/comments/ratings + trending recipes,
  sent via a new `cron` Docker stage (alpine+crond+curl) and `digest-cron`
  compose service hitting a bearer-token-protected internal route
- Meal-plan generation can now target a user's nutrition goals as a
  prompt-level nudge (recipes are AI-invented, not DB-sourced, so this
  can't be a hard macro constraint)

Caught a real deploy-breaking issue while adding the cron stage: appending
it after `runner` silently changed the Dockerfile's default build target,
and `web`'s compose config didn't pin one — fixed by pinning `target:
runner` explicitly. Verified with typecheck, lint, and three separate
`docker build --target` runs (runner/cron/migrator) plus `docker compose
config` validation.

Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
This commit is contained in:
Arnaud
2026-07-10 08:06:28 +02:00
parent 913410dbf3
commit b0849c3989
40 changed files with 1964 additions and 112 deletions
@@ -0,0 +1,131 @@
import { NextRequest, NextResponse } from "next/server";
import crypto from "node:crypto";
import {
db,
users,
recipes,
comments,
ratings,
userFollows,
favorites,
eq,
and,
gte,
desc,
count,
sql,
} from "@epicure/db";
import { sendEmail, weeklyDigestHtml } from "@/lib/email";
// Internal cron endpoint — triggered by the `digest-cron` container on a weekly
// schedule (see docker/compose.prod.yml). Not part of the public API surface;
// protected by a shared secret rather than user auth.
//
// Computes, for every user: new followers / new comments / new ratings on
// their recipes in the last 7 days, plus a site-wide top-3 trending list, and
// emails a summary. Sends to all users (all users have a non-null email) —
// there's no per-user opt-out preference yet; out of scope for this pass.
const CHUNK_SIZE = 20;
function isAuthorized(req: NextRequest): boolean {
const secret = process.env["CRON_SECRET"];
if (!secret) return false;
const header = req.headers.get("authorization");
if (!header?.startsWith("Bearer ")) return false;
const provided = header.slice("Bearer ".length);
const a = Buffer.from(provided);
const b = Buffer.from(secret);
if (a.length !== b.length) return false;
return crypto.timingSafeEqual(a, b);
}
function chunk<T>(arr: T[], size: number): T[][] {
const out: T[][] = [];
for (let i = 0; i < arr.length; i += size) out.push(arr.slice(i, i + size));
return out;
}
export async function POST(req: NextRequest) {
if (!isAuthorized(req)) {
return NextResponse.json({ error: "Unauthorized" }, { status: 401 });
}
const weekAgo = new Date(Date.now() - 7 * 24 * 60 * 60 * 1000);
const baseUrl = process.env["BETTER_AUTH_URL"] ?? "http://localhost:3000";
const [allUsers, followerRows, commentRows, ratingRows, trending] = await Promise.all([
db.select({ id: users.id, email: users.email }).from(users),
db
.select({ userId: userFollows.followingId, n: count() })
.from(userFollows)
.where(gte(userFollows.createdAt, weekAgo))
.groupBy(userFollows.followingId),
db
.select({ userId: recipes.authorId, n: count() })
.from(comments)
.innerJoin(recipes, eq(comments.recipeId, recipes.id))
.where(gte(comments.createdAt, weekAgo))
.groupBy(recipes.authorId),
db
.select({ userId: recipes.authorId, n: count() })
.from(ratings)
.innerJoin(recipes, eq(ratings.recipeId, recipes.id))
.where(gte(ratings.createdAt, weekAgo))
.groupBy(recipes.authorId),
db
.select({
id: recipes.id,
title: recipes.title,
favoriteCount: sql<number>`cast(count(${favorites.recipeId}) as int)`,
})
.from(recipes)
.leftJoin(
favorites,
and(eq(favorites.recipeId, recipes.id), gte(favorites.createdAt, weekAgo))
)
.where(eq(recipes.visibility, "public"))
.groupBy(recipes.id)
.orderBy(desc(sql`count(${favorites.recipeId})`), desc(recipes.createdAt))
.limit(3),
]);
const followerMap = new Map(followerRows.map((r) => [r.userId, r.n]));
const commentMap = new Map(commentRows.map((r) => [r.userId, r.n]));
const ratingMap = new Map(ratingRows.map((r) => [r.userId, r.n]));
const trendingList = trending.map((r) => ({ id: r.id, title: r.title }));
let sent = 0;
let failed = 0;
for (const batch of chunk(allUsers, CHUNK_SIZE)) {
const results = await Promise.allSettled(
batch.map((user) => {
const newFollowers = followerMap.get(user.id) ?? 0;
const newComments = commentMap.get(user.id) ?? 0;
const newRatings = ratingMap.get(user.id) ?? 0;
return sendEmail({
to: user.email,
subject: "Your weekly digest — Epicure",
html: weeklyDigestHtml({
newFollowers,
newComments,
newRatings,
trending: trendingList,
baseUrl,
}),
});
})
);
for (const r of results) {
if (r.status === "fulfilled") sent++;
else failed++;
}
}
return NextResponse.json({ ok: true, totalUsers: allUsers.length, sent, failed });
}
@@ -1,6 +1,6 @@
import { NextRequest, NextResponse } from "next/server";
import { z } from "zod";
import { db, recipes, recipeIngredients, recipeSteps, mealPlans, mealPlanEntries, pantryItems, eq, and } from "@epicure/db";
import { db, recipes, recipeIngredients, recipeSteps, mealPlans, mealPlanEntries, pantryItems, userNutritionGoals, eq, and } from "@epicure/db";
import { requireSession } from "@/lib/api-auth";
import { applyRateLimit } from "@/lib/rate-limit";
import { getDefaultProviderWithKey } from "@/lib/ai/resolve-user-key";
@@ -19,6 +19,7 @@ const Schema = z.object({
usePantry: z.boolean().default(false),
pantryMode: z.boolean().default(false),
difficulty: z.enum(["easy", "medium", "hard"]).optional(),
targetNutritionGoals: z.boolean().default(false),
});
export async function POST(req: NextRequest) {
@@ -56,6 +57,24 @@ export async function POST(req: NextRequest) {
pantryItemNames = pantry.map((p) => p.rawName);
}
// Optionally fetch the user's nutrition goals to nudge the AI toward them.
// Silently ignored (no-op) if the user hasn't set any goals — no need to
// fail the whole generation over a missing preference.
let nutritionGoals: { caloriesKcal?: number | null; proteinG?: number | null; carbsG?: number | null; fatG?: number | null } | undefined;
if (parsed.data.targetNutritionGoals) {
const goals = await db.query.userNutritionGoals.findFirst({
where: eq(userNutritionGoals.userId, userId),
});
if (goals && (goals.caloriesKcal || goals.proteinG || goals.carbsG || goals.fatG)) {
nutritionGoals = {
caloriesKcal: goals.caloriesKcal,
proteinG: goals.proteinG,
carbsG: goals.carbsG,
fatG: goals.fatG,
};
}
}
const result = await withAiQuota(userId, session!.user.tier as "free" | "pro", () =>
generateMealPlan(
{
@@ -65,6 +84,7 @@ export async function POST(req: NextRequest) {
days: parsed.data.days,
pantryMode: parsed.data.pantryMode,
difficulty: parsed.data.difficulty,
nutritionGoals,
},
{ ...config, userContext: privateBio ?? undefined },
locale
@@ -0,0 +1,81 @@
import { NextRequest, NextResponse } from "next/server";
import { z } from "zod";
import { requireSession } from "@/lib/api-auth";
import { applyRateLimit } from "@/lib/rate-limit";
const Schema = z.object({
barcode: z.string().trim().min(4).max(32).regex(/^[0-9]+$/, "Barcode must be numeric"),
});
type OffProduct = {
product_name?: string;
product_name_en?: string;
generic_name?: string;
quantity?: string;
product_quantity?: string;
product_quantity_unit?: string;
brands?: string;
};
type OffResponse = {
status: number;
product?: OffProduct;
};
/** Very rough unit guess from Open Food Facts' free-text `quantity` field (e.g. "500 g", "1 L"). */
function extractUnit(quantity: string | undefined): string | undefined {
if (!quantity) return undefined;
const match = /([a-zA-Z]+)\s*$/.exec(quantity.trim());
return match?.[1]?.toLowerCase();
}
export async function POST(req: NextRequest) {
const { session, response } = await requireSession();
if (response) return response;
const body = await req.json() as unknown;
const parsed = Schema.safeParse(body);
if (!parsed.success) return NextResponse.json({ error: "Validation error" }, { status: 400 });
const limited = await applyRateLimit(`rl:pantry-scan-barcode:${session!.user.id}`, 20, 60);
if (limited) return limited;
const { barcode } = parsed.data;
let offResponse: Response;
try {
offResponse = await fetch(
`https://world.openfoodfacts.org/api/v2/product/${encodeURIComponent(barcode)}.json`,
{
headers: { "User-Agent": "Epicure/1.0 (pantry-scan)" },
signal: AbortSignal.timeout(8000),
}
);
} catch {
return NextResponse.json({ error: "Barcode lookup service unavailable" }, { status: 502 });
}
if (!offResponse.ok) {
return NextResponse.json({ error: "Barcode lookup service unavailable" }, { status: 502 });
}
const data = await offResponse.json() as OffResponse;
if (data.status !== 1 || !data.product) {
return NextResponse.json({ found: false });
}
const product = data.product;
const rawName = product.product_name_en?.trim() || product.product_name?.trim() || product.generic_name?.trim();
if (!rawName) {
return NextResponse.json({ found: false });
}
return NextResponse.json({
found: true,
rawName: product.brands ? `${rawName} (${product.brands.split(",")[0]?.trim()})` : rawName,
quantity: product.product_quantity,
unit: extractUnit(product.product_quantity_unit) ?? extractUnit(product.quantity),
});
}
@@ -0,0 +1,45 @@
import { NextRequest, NextResponse } from "next/server";
import { z } from "zod";
import { requireSession } from "@/lib/api-auth";
import { applyRateLimit } from "@/lib/rate-limit";
import { withAiQuota, resolveAiConfigOrError } from "@/lib/ai/ai-error";
import { getModelConfigForUseCase } from "@/lib/ai/resolve-user-key";
import { scanPantryPhoto } from "@/lib/ai/features/scan-pantry-photo";
const Schema = z.object({
imageBase64: z.string().max(14_000_000),
mimeType: z.enum(["image/jpeg", "image/png", "image/webp"]),
});
export async function POST(req: NextRequest) {
const { session, response } = await requireSession();
if (response) return response;
const body = await req.json() as unknown;
const parsed = Schema.safeParse(body);
if (!parsed.success) {
return NextResponse.json({ error: "Validation error", issues: parsed.error.issues }, { status: 400 });
}
const userId = session!.user.id;
const limited = await applyRateLimit(`rl:ai:${userId}`, 10, 60);
if (limited) return limited;
const configResult = await resolveAiConfigOrError(() => getModelConfigForUseCase(userId, "vision"));
if (!configResult.ok) return configResult.response;
const aiConfig = configResult.data;
// Fall back to vision-capable defaults if no explicit model configured
if (!aiConfig.model) {
if (aiConfig.provider === "openai") aiConfig.model = "gpt-4o";
else if (aiConfig.provider === "anthropic") aiConfig.model = "claude-sonnet-4-6";
}
const result = await withAiQuota(userId, session!.user.tier as "free" | "pro", () =>
scanPantryPhoto(parsed.data.imageBase64, parsed.data.mimeType, aiConfig)
);
if (!result.ok) return result.response;
return NextResponse.json(result.data);
}
@@ -0,0 +1,103 @@
import { NextRequest, NextResponse } from "next/server";
import { db, cookingHistory, recipes, userNutritionGoals, eq, and, gte, lt } from "@epicure/db";
import { requireSession } from "@/lib/api-auth";
function isValidDate(value: string): boolean {
return /^\d{4}-\d{2}-\d{2}$/.test(value) && !isNaN(new Date(`${value}T00:00:00.000Z`).getTime());
}
export async function GET(req: NextRequest) {
const { session, response } = await requireSession();
if (response) return response;
const userId = session!.user.id;
const dateParam = req.nextUrl.searchParams.get("date");
const date = dateParam && isValidDate(dateParam) ? dateParam : new Date().toISOString().slice(0, 10);
const dayStart = new Date(`${date}T00:00:00.000Z`);
const dayEnd = new Date(dayStart.getTime() + 24 * 60 * 60 * 1000);
const rows = await db
.select({
id: cookingHistory.id,
recipeId: cookingHistory.recipeId,
servings: cookingHistory.servings,
cookedAt: cookingHistory.cookedAt,
recipeTitle: recipes.title,
baseServings: recipes.baseServings,
nutritionData: recipes.nutritionData,
})
.from(cookingHistory)
.leftJoin(recipes, eq(cookingHistory.recipeId, recipes.id))
.where(
and(
eq(cookingHistory.userId, userId),
gte(cookingHistory.cookedAt, dayStart),
lt(cookingHistory.cookedAt, dayEnd)
)
)
.orderBy(cookingHistory.cookedAt);
const totals = { calories: 0, proteinG: 0, carbsG: 0, fatG: 0, fiberG: 0, sodiumMg: 0 };
const entries: {
id: string;
recipeId: string;
title: string;
servings: number;
cookedAt: string;
nutritionKnown: boolean;
}[] = [];
let unknownCount = 0;
for (const row of rows) {
const servings = row.servings ?? row.baseServings ?? 1;
const perServing = row.nutritionData?.perServing;
const nutritionKnown = !!perServing;
if (perServing) {
totals.calories += perServing.calories * servings;
totals.proteinG += perServing.proteinG * servings;
totals.carbsG += perServing.carbsG * servings;
totals.fatG += perServing.fatG * servings;
totals.fiberG += perServing.fiberG * servings;
totals.sodiumMg += perServing.sodiumMg * servings;
} else {
unknownCount += 1;
}
entries.push({
id: row.id,
recipeId: row.recipeId,
title: row.recipeTitle ?? "Unknown recipe",
servings,
cookedAt: row.cookedAt.toISOString(),
nutritionKnown,
});
}
for (const key of Object.keys(totals) as (keyof typeof totals)[]) {
totals[key] = Math.round(totals[key]);
}
const goalsRow = await db.query.userNutritionGoals.findFirst({
where: eq(userNutritionGoals.userId, userId),
});
const goals = goalsRow
? {
caloriesKcal: goalsRow.caloriesKcal,
proteinG: goalsRow.proteinG,
carbsG: goalsRow.carbsG,
fatG: goalsRow.fatG,
}
: null;
const coverage = {
calories: goals?.caloriesKcal ? Math.round((totals.calories / goals.caloriesKcal) * 100) : 0,
protein: goals?.proteinG ? Math.round((totals.proteinG / goals.proteinG) * 100) : 0,
carbs: goals?.carbsG ? Math.round((totals.carbsG / goals.carbsG) * 100) : 0,
fat: goals?.fatG ? Math.round((totals.fatG / goals.fatG) * 100) : 0,
};
return NextResponse.json({ date, totals, goals, coverage, entries, unknownCount });
}