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arthtyagi
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ai-gateway

Route AI model calls through Vercel AI Gateway with failover and cost tracking.

1|Updated Apr 19, 2026
Search Tags:#rate limiting#vercel#model routing#cost tracking#audit logging#ai gateway#provider failover
One-click install
npx skills add https://github.com/arthtyagi/onloop --skill ai-gateway-arthtyagi
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: ai-gateway
Source: https://github.com/arthtyagi/onloop/tree/main/.agents/skills/ai-gateway
Command: npx skills add https://github.com/arthtyagi/onloop --skill ai-gateway-arthtyagi

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill helps you configure a unified AI model layer that routes requests across multiple providers, adds automatic failover, and gives you cost and usage visibility without juggling separate integrations.

Core Features & Use Cases

  • Unified model routing: Send requests through a single provider/model interface instead of wiring each vendor separately.
  • Resilience and governance: Add provider order, fallback models, rate limiting, audit logging, and budget controls for production use.
  • Cost and observability: Attribute spend with tags and users, apply caching where appropriate, and monitor usage across teams and environments.
  • Use case: A multi-tenant product can route chat traffic through Vercel AI Gateway, fail over when a provider is unavailable, and track spend by feature and user.

Quick Start

Use the ai-gateway skill to configure a provider/model route for your app, enable OIDC-based authentication, and add failover, tags, and budget-aware settings.

Frequently Asked Questions about ai-gateway

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I set up provider failover for AI model calls?▼

Provider failover is set up by configuring a provider order and fallback models through a unified AI gateway. This routes requests to the next available provider automatically when the primary model is unavailable, keeping inference resilient.

What is the best way to track AI model costs across multiple providers?▼

The best way to track AI model costs is by routing traffic through an AI gateway with cost tracking. You can attribute spend using tags and user identifiers, applying cache control and budget-aware settings to monitor usage across teams.

Can I apply per-user rate limiting to multi-provider AI inference?▼

Yes, you can apply per-user rate limiting to multi-provider AI inference by configuring an AI gateway. This allows you to enforce budget controls and governance on traffic routing through a unified model interface.

How do I configure Vercel AI Gateway authentication for production applications?▼

You configure Vercel AI Gateway authentication by setting up OIDC or API key authentication. This secures model routing and ensures that audit logging correctly attributes requests to specific users in production environments.

Does a unified AI model layer support audit logging for multi-tenant apps?▼

Yes, a unified AI model layer supports audit logging for multi-tenant apps. By routing chat traffic through an AI gateway, you can log usage, apply tags by feature, and maintain observable request records for each tenant.

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