Files
Epicure/apps/web/lib/ai/features/import-photo.ts
T
Arnaud 4a90ad910c feat(deploy): dockerize web app for portainer git-stack deploy behind external traefik
Add root Dockerfile (standalone Next output, multi-stage pnpm build), drop
in-stack caddy in favor of publishing web's port for an external traefik
LXC (file-provider dynamic config included), and document the portainer
deploy flow.

Also fixes issues that blocked any production build: a bad auth-client
type cast, the ai SDK's mimeType->mediaType rename, an implicit-any
callback param, and push.ts eagerly calling webpush.setVapidDetails at
module import time (which crashed page-data collection whenever VAPID
env vars weren't present at build) — now lazily configured on first send.

Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
2026-07-01 16:20:34 +02:00

61 lines
1.8 KiB
TypeScript

import { generateObject } from "ai";
import { z } from "zod";
import { resolveModel, type AiConfig } from "../factory";
const ImportedRecipeSchema = z.object({
title: z.string(),
description: z.string().optional(),
baseServings: z.number().int().min(1).optional(),
prepMins: z.number().int().min(0).optional(),
cookMins: z.number().int().min(0).optional(),
difficulty: z.enum(["easy", "medium", "hard"]).optional(),
dietaryTags: z.object({
vegan: z.boolean().optional(),
vegetarian: z.boolean().optional(),
glutenFree: z.boolean().optional(),
dairyFree: z.boolean().optional(),
nutFree: z.boolean().optional(),
halal: z.boolean().optional(),
kosher: z.boolean().optional(),
}).optional(),
ingredients: z.array(z.object({
rawName: z.string(),
quantity: z.string().optional(),
unit: z.string().optional(),
note: z.string().optional(),
})),
steps: z.array(z.object({
instruction: z.string(),
timerSeconds: z.number().int().optional(),
})),
});
export type ImportedRecipe = z.infer<typeof ImportedRecipeSchema>;
export async function importFromPhoto(
imageBase64: string,
mimeType: "image/jpeg" | "image/png" | "image/webp",
config?: AiConfig,
_locale?: string,
): Promise<ImportedRecipe> {
const model = resolveModel(config);
const { object } = await generateObject({
model,
schema: ImportedRecipeSchema,
system:
"You are a recipe extraction specialist. Extract the complete recipe from the provided image. Be precise with ingredient quantities and cooking instructions.",
messages: [
{
role: "user",
content: [
{ type: "image", image: imageBase64, mediaType: mimeType },
{ type: "text", text: "Extract the complete recipe from this image." },
],
},
],
});
return object;
}