惯性聚合 高效追踪和阅读你感兴趣的博客、新闻、科技资讯
阅读原文 在惯性聚合中打开

推荐订阅源

Apple Machine Learning Research
Apple Machine Learning Research
Y
Y Combinator Blog
博客园 - 【当耐特】
V
Visual Studio Blog
GbyAI
GbyAI
V
V2EX
P
Proofpoint News Feed
Microsoft Azure Blog
Microsoft Azure Blog
Microsoft Security Blog
Microsoft Security Blog
D
DataBreaches.Net
Hugging Face - Blog
Hugging Face - Blog
A
About on SuperTechFans
The Cloudflare Blog
阮一峰的网络日志
阮一峰的网络日志
Cyber Security Advisories - MS-ISAC
Cyber Security Advisories - MS-ISAC
N
Netflix TechBlog - Medium
aimingoo的专栏
aimingoo的专栏
B
Blog RSS Feed
量子位
MongoDB | Blog
MongoDB | Blog
有赞技术团队
有赞技术团队
人人都是产品经理
人人都是产品经理
Stack Overflow Blog
Stack Overflow Blog
小众软件
小众软件

DEV Community

Authentication Security Deep Dive: From Brute Force to Salted Hashing (With Java Examples) Why AI Systems Don’t Fail — They Drift Spilling beans for how i learn for exam😁"Reinforcement Learning Cheat Sheet" I Replaced Chrome with Safari for AI Browser Automation. Here's What Broke (and What Finally Worked) How Python Borrows Other People's Work The $40 Architecture: Processing 1 Billion API Requests with 99.99% Uptime Vibe Coding: A Workflow Guide (From Zero to SaaS) Most webhook security guides protect the wrong side. The scary part is delivery. Headless CMS for TanStack Start: Build a Blog with Cosmic EU Age Verification App "Hacked in 2 Minutes" — What Actually Happened Comfy Cloud’s delete function does not actually remove files Running AI Models on GPU Cloud Servers: A Beginner Guide Event-driven media intelligence with AWS Step Functions and Bedrock I scored 500 AI prompts across 8 quality dimensions — here's what broke How to Call Google Gemini API from Next.js (Free Tier, No Backend Needed) The Portal Protocol: Reclaiming Human Connection in the Age of AI How to Fix Your Team's Scattered Knowledge Problem With a Self-Hosted Forum Intro to tc Cloud Functors: A Graph-First Mental Model for the Modern Cloud Designing Multi-Tenant Backends With Both Ownership and Team Access I Built a Neumorphic CSS Library with 77+ Components — Here's What I Learned PostgreSQL Performance Optimization: Why Connection Pooling Is Critical at Scale Cómo construí un SaaS multi-rubro para gestionar expensas en Argentina con FastAPI + Vue 3 🚀 I Built an Ethical Hacking Scanner Tool – Open Source Project I Replaced /usage and /context in Claude Code With a Single Statusline A Pythonic Way to Handle Emails (IMAP/SMTP) with Auto-Discovery and AI-Ready Design I Collected 8.9 Million Polymarket Price Points — Here's What I Found About How Markets Really Move EcoTrack AI — Carbon Footprint Tracker & Dashboard Everyone's Using AI. No One Agrees How. 5 self-hosted ebook managers worth trying in 2026 Building Your First AI Agent with LangChain: From Chatbot to Autonomous Assistant
I Got Tired of Rewriting AI API Wrappers, So I Built a Ga...
Lolo · 2026-06-28 · via DEV Community

Lolo

Every side project starts the same way.

-Generate an OpenAI key.

-Add it to .env.

-Write a wrapper.

-Realize I also need Claude.

-Create another account.

-Another API key.

-Another billing dashboard.

Before the project even starts, I've already configured three different services.

At some point I thought why not just make this a proper API and host it publicly?

That's how Apiarium started.

Why Not LiteLLM or OpenRouter?

They're great projects. But I wanted something more opinionated:

  • Credit-based billing so users always know what they're spending
  • One normalized API across text, images, TTS, and transcription
  • A self-hosted backend I fully control
  • Simple pricing without per-model complexity

My target isn't teams running production AI infrastructure. It's developers building side projects who want one API key and a predictable bill.

How It Works

Client
   │
   ▼
Apiarium
   ├── /llm         → OpenAI, Anthropic (more coming)
   ├── /image       → gpt-image-1 (more coming)
   ├── /tts         → OpenAI TTS, ElevenLabs (soon)
   └── /transcribe  → Whisper (more coming)

*More providers coming.

Adding a new provider doesn't change the API contract.
Same endpoints, same auth, more options.

From the client's perspective, every provider looks exactly the same:

# GPT-4o-mini
curl -X POST https://api.apiarium.dev/llm \
  -H "Authorization: Bearer YOUR_KEY" \
  -H "Content-Type: application/json" \
  -d '{"model":"gpt-4o-mini","messages":[{"role":"user","content":"Hello"}]}'

# Switch to Claude — same endpoint, same auth
curl -X POST https://api.apiarium.dev/llm \
  -H "Authorization: Bearer YOUR_KEY" \
  -H "Content-Type: application/json" \
  -d '{"model":"claude-haiku","messages":[{"role":"user","content":"Hello"}]}'

The Technical Decisions

Credits instead of per-model pricing. Pricing by token across four providers is confusing. I landed on credits text generation costs 1–20 credits depending on the model, images cost 100, TTS costs 10 per 1,000 characters. One number, always visible.

Normalized error format. OpenAI and Anthropic return completely different error structures. Every error from Apiarium looks the same regardless of which provider caused it:

{
  "error": "Rate limit exceeded. Try again in 30 seconds.",
  "code": "rate_limit_exceeded",
  "retry_after": 30
}

Provider abstraction. Every provider adapter returns the same internal response format before it's sent back to the client. That means adding a new provider is mostly implementing one adapter instead of changing the whole API.

What I'd Do Differently

If I started again, I'd build the provider abstraction first instead of adding providers one by one. Every new model taught me another edge case around streaming, token accounting, or error handling. Designing for those differences upfront would've saved me time.

Where It Is Now

Launched a few days ago. Still early, but the infrastructure is solid and every endpoint works.

I'm mostly interested in whether this solves a real problem for other developers. If you've hit the same setup tax or think I'm solving the wrong problem entirely, I'd genuinely like to hear it.

If even one developer stops copy-pasting another ai-utils.js file because of this, I'll call it a success.

apiarium.dev · Docs