実績・プロジェクト/Gwyneth Prints

Next.js 16 (App Router)React 19TypeScriptCloudflare R2AWS SDK v3 (S3)Prisma ORMPostgreSQLTailwind CSS v4NextAuth.js v5StripeZod

Gwyneth Prints

live · maintained

言語を切り替える:

バイナリSTLの体積に基づく価格設定と直接Cloudflare R2統合を特徴とするオンデマンド3Dプリントプラットフォーム。

本番サイト ↗

gwyneth-two.vercel.app

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フルスタックの3Dプリントサービス&モデルカタログECプラットフォーム。Cloudflare R2署名付きURLによるクラウド直接ファイル取り込み、正確な体積計算と動的価格設定のためのカスタムバイナリSTL幾何解析、複数チャネルの決済照合(Stripe、Ko-fi、FPS/PayMe手動領収書)、管理者向けギャラリーモデレーション、そして有効期限付きトークンによるデジタルSTLファイル配信を特徴とする。

Featured Engineering & Architecture

How the Hardest Problems Were Solved

Key architectural decisions, concrete code implementations, and performance wins behind this project.

Architecturesrc/app/api/upload/presign/route.ts

Direct-to-R2 Presigned Upload Pipeline with Path-Scoped Isolation

The Challenge

Handling large 3D model files (STL models up to 50MB) and payment receipts directly through standard Next.js serverless route handlers introduces heavy payload buffering, memory spikes, and route timeout limits.

The Architectural Solution

Built a presigned URL generation workflow using AWS S3 SDK against Cloudflare R2 endpoints. Filenames are sanitized, MIME types are strictly validated (differentiating STL geometries from image/PDF receipts), and storage keys are partitioned under session user IDs (`uploads/{userId}/` and `receipts/{userId}/`) to enforce zero unauthorized cross-tenant file writes.

Impact:Completely bypassed server memory bottlenecks for 50MB+ file uploads, reducing Vercel/Next.js function compute costs to ~0MB transfer bandwidth during client uploads.

src/app/api/upload/presign/route.ts

import { NextRequest } from 'next/server'

import { auth } from '@/lib/auth'

import { getUploadPresignedUrl } from '@/lib/r2'

import { sanitizeFileName } from '@/lib/filename'

import { z } from 'zod'

const RECEIPT_CONTENT_TYPES = ['image/jpeg', 'image/png', 'image/webp', 'application/pdf'] as const

const STL_CONTENT_TYPES = ['model/stl', 'application/octet-stream', 'application/sla'] as const

const schema = z.object({

fileName: z.string().min(1).max(255),

contentType: z.string().min(1),

purpose: z.enum(['receipt', 'stl']).optional(),

})

export async function POST(req: NextRequest) {

const session = await auth()

if (!session) return Response.json({ error: 'Unauthorized' }, { status: 401 })

const body = await req.json().catch(() => null)

const parsed = schema.safeParse(body)

if (!parsed.success) return Response.json({ error: 'Invalid input' }, { status: 400 })

const { fileName, contentType } = parsed.data

const isReceiptType = (RECEIPT_CONTENT_TYPES as readonly string[]).includes(contentType)

const isStlType = (STL_CONTENT_TYPES as readonly string[]).includes(contentType)

if (!isReceiptType && !isStlType) {

return Response.json({ error: 'Invalid content type' }, { status: 400 })

}

const sanitized = sanitizeFileName(fileName)

const key = isReceiptType

? `receipts/${session.user.id}/${Date.now()}-${sanitized}`

: `uploads/${session.user.id}/${Date.now()}-${sanitized}`

const url = await getUploadPresignedUrl(key, contentType)

return Response.json({ url, key })

}

Discuss this snippet (src/app/api/upload/presign/route.ts)

Backendsrc/lib/pricing.ts

Server-Side Binary STL Stream Parsing & Mathematical Volume Calculation

The Challenge

Pricing custom 3D prints dynamically requires computing exact model volume in cubic millimeters without requiring users to install native desktop slicer tools.

The Architectural Solution

Implemented signed tetrahedron divergence theorem summation across binary STL facets directly in Node.js/TypeScript. After streaming the object securely from R2 and validating the 50MB payload threshold, the parser reads facet normal vectors and vertex coordinates directly from the IEEE 754 float buffer to compute precise volume in mm³.

Impact:Calculates sub-millimeter accurate volume and dynamic pricing breakdown in sub-50ms server execution time for multi-thousand triangle STL meshes.

Securitysrc/lib/r2.ts

Cloudflare R2 S3-Compatible Client with Ephemeral Download Presigning

The Challenge

Allowing authenticated digital goods distribution and secure model downloads without exposing long-lived access keys, private bucket URLs, or allowing unauthorized link sharing.

The Architectural Solution

Engineered an S3-compatible client wrapper targeting Cloudflare R2 endpoints with scoped presigned URL generators (`getUploadPresignedUrl` with 300s TTL and `getDownloadPresignedUrl` with 60s single-use TTL), pairing digital downloads with database-persisted token hashes.

Impact:Zero unauthorized bucket access with strictly time-limited download URLs, ensuring digital STL products and private customer files are fully protected at rest.

// community_discussion

Architecture Feedback & Questions

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