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AI Gateway

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Overview

The Vercel AI SDK is a TypeScript toolkit for building AI-powered applications with streaming, structured outputs, and multi-model support. By connecting it to Orq.ai’s AI Gateway via the @orq-ai/vercel-provider, you get access to 300+ models with a single provider setup.

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Key Benefits

Orq.ai’s AI Gateway enhances Vercel AI applications with:

Complete Observability

Track every generation, stream, and structured output with detailed traces

Built-in Reliability

Automatic fallbacks, retries, and load balancing for production resilience

Cost Optimization

Real-time cost tracking and spend management across all AI operations

Multi-Provider Access

Access 300+ LLMs and 20+ providers through a single, unified integration

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Prerequisites

Before integrating Vercel AI with Orq.ai, ensure you have:
  • An Orq.ai account and API Key
  • Node.js 18 or higher
To set up an API key, see API keys & Endpoints.

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Installation

npm install @orq-ai/vercel-provider ai

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Configuration

Configure the Orq.ai provider with the API key:
TypeScript
import { createOrqAiProvider } from "@orq-ai/vercel-provider";

const orq = createOrqAiProvider({
  apiKey: process.env.ORQ_API_KEY,
});
base_url: https://api.orq.ai/v3/router

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Text Generation

TypeScript
import { createOrqAiProvider } from "@orq-ai/vercel-provider";
import { generateText } from "ai";

const orq = createOrqAiProvider({
  apiKey: process.env.ORQ_API_KEY,
});

const { text } = await generateText({
  model: orq("openai/gpt-4o"),
  prompt: "Write a haiku about programming",
});

console.log(text);

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Streaming Responses

TypeScript
import { createOrqAiProvider } from "@orq-ai/vercel-provider";
import { streamText } from "ai";

const orq = createOrqAiProvider({
  apiKey: process.env.ORQ_API_KEY,
});

const { textStream } = await streamText({
  model: orq("openai/gpt-4o"),
  messages: [
    { role: "system", content: "You are a helpful assistant." },
    { role: "user", content: "Explain quantum computing in two sentences." },
  ],
});

for await (const chunk of textStream) {
  process.stdout.write(chunk);
}

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Structured Output

Use a JSON system prompt and parse the response:
TypeScript
import { createOrqAiProvider } from "@orq-ai/vercel-provider";
import { generateText } from "ai";

const orq = createOrqAiProvider({
  apiKey: process.env.ORQ_API_KEY,
});

const { text } = await generateText({
  model: orq("openai/gpt-4o"),
  messages: [
    {
      role: "system",
      content: "You are a data assistant. Always respond with valid JSON only, no markdown.",
    },
    {
      role: "user",
      content: "Generate information about France with fields: name, capital, population, languages.",
    },
  ],
});

const country = JSON.parse(text);
console.log(country);

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Model Selection

With Orq.ai, you can use any supported model from 20+ providers:
TypeScript
import { createOrqAiProvider } from "@orq-ai/vercel-provider";
import { generateText } from "ai";

const orq = createOrqAiProvider({
  apiKey: process.env.ORQ_API_KEY,
});

// Use Claude
const claudeResult = await generateText({
  model: orq("anthropic/claude-sonnet-4-6"),
  prompt: "What is the largest planet?",
});

// Use Gemini
const geminiResult = await generateText({
  model: orq("google-ai/gemini-2.5-flash"),
  prompt: "What is the largest planet?",
});

// Use Groq
const groqResult = await generateText({
  model: orq("groq/llama-3.3-70b-versatile"),
  prompt: "What is the largest planet?",
});