Vercel AI SDK Integration

Introduction

Vercel AI SDK is a TypeScript toolkit for building AI-powered applications with React, Next.js, Vue, and more.

The Planck provider for Vercel AI SDK lives in this repository as the @inquantum/planck-ai-sdk-provider workspace package.

The provider is not published to npm yet. The checked-in Next.js example consumes it through a local file: dependency. Publish the package before using the npm, pnpm, Yarn, or Bun registry commands in an external project.

Integration Steps

You’ll also need to configure your provider API keys (OpenAI, Anthropic, etc.) at Planck Providers for BYOK (Bring Your Own Keys).

bash PLANCK_API_KEY=sk-planck-...

Install the local Planck AI SDK provider

The example declares the workspace package as a local dependency:

{
  "dependencies": {
    "@inquantum/planck-ai-sdk-provider": "file:../../packages/ai-sdk-provider"
  }
}

Build the unpublished package, then install the example:

cd packages/ai-sdk-provider
npm ci --workspaces=false
npm run build
cd ../../examples/vercel-ai-sdk-example
npm ci

Configure Vercel AI SDK with Planck

import { createPlanck } from '@inquantum/planck-ai-sdk-provider';
import { generateText } from 'ai';

// Initialize Planck provider
const planck = createPlanck({
  apiKey: process.env.PLANCK_API_KEY
});

// Use any model from 100+ providers
const result = await generateText({
  model: planck('claude-4.5-haiku'),
  prompt: 'Write a haiku about artificial intelligence'
});

console.log(result.text);

You can switch between 100+ models without changing your code. Just update the model name!

Complete Working Examples

Basic Text Generation

import { createPlanck } from "@inquantum/planck-ai-sdk-provider";
import { generateText } from "ai";

const planck = createPlanck({
  apiKey: process.env.PLANCK_API_KEY,
});

const { text } = await generateText({
  model: planck("gemini-2.5-flash-lite"),
  prompt: "What is Planck?",
});

console.log(text);

Streaming Text

import { createPlanck } from "@inquantum/planck-ai-sdk-provider";
import { streamText } from "ai";

const planck = createPlanck({
  apiKey: process.env.PLANCK_API_KEY,
});

const result = await streamText({
  model: planck("deepseek-v3.1-terminus"),
  prompt: "Write a short story about a robot learning to paint",
  maxOutputTokens: 300,
});

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

console.log("\n\nStream completed!");

Provider Selection

By default, Planck’s AI gateway automatically routes to the cheapest provider. You can also manually select a specific provider:

import { createPlanck } from "@inquantum/planck-ai-sdk-provider";
import { generateText } from "ai";

const planck = createPlanck({
  apiKey: process.env.PLANCK_API_KEY,
});

// Automatic routing (cheapest provider)
const autoResult = await generateText({
  model: planck("gpt-4o"),
  prompt: "Hello!",
});

// Manual provider selection
const manualResult = await generateText({
  model: planck("claude-4.5-sonnet/anthropic"),
  prompt: "Hello!",
});

// Multiple provider selection: first model/provider is used, if it fails, the second model/provider is used, and so on.
const fallbackResult = await generateText({
  model: planck("claude-4.5-sonnet/anthropic,gpt-4o/openai"),
  prompt: "Hello!",
});

With Custom Properties and Session Tracking

import { createPlanck } from "@inquantum/planck-ai-sdk-provider";
import { generateText } from "ai";

const planck = createPlanck({
  apiKey: process.env.PLANCK_API_KEY,
});

const result = await generateText({
  model: planck("claude-4.5-haiku", {
    requestMetadata: {
      requestId: crypto.randomUUID(),
      sessionId: "my-session",
      userId: "user-123",
      properties: {
        environment: "production",
        appVersion: "2.1.0",
        feature: "quantum-explanation",
      },
    },
  }),
  prompt: "Explain quantum computing",
});

Tool Calling

import { createPlanck } from "@inquantum/planck-ai-sdk-provider";
import { generateText, tool } from "ai";
import { z } from "zod";

const planck = createPlanck({
  apiKey: process.env.PLANCK_API_KEY,
});

const result = await generateText({
  model: planck("gpt-4o"),
  prompt: "What is the weather like in San Francisco?",
  tools: {
    getWeather: tool({
      description: "Get weather for a location",
      inputSchema: z.object({
        location: z.string().describe("The city name"),
      }),
      execute: async (args) => {
        return `It's sunny in ${args.location}`;
      },
    }),
  },
});

console.log(result.text);

Planck Prompts Integration

Use prompts created in your Planck dashboard instead of hardcoding messages in your application:

import { createPlanck } from "@inquantum/planck-ai-sdk-provider";
import type { WithPlanckPrompt } from "@inquantum/planck-ai-sdk-provider";
import { generateText } from "ai";

const planck = createPlanck({
  apiKey: process.env.PLANCK_API_KEY,
});

const result = await generateText({
  model: planck("gpt-4o", {
    promptId: "sg45wqc",
    inputs: {
      customer_name: "Sarah Johnson",
      issue_type: "billing",
      account_type: "premium",
    },
    environment: "production",
    requestMetadata: {
      sessionId: "support-session-123",
      properties: {
        department: "customer-support",
      },
    },
  }),
  messages: [{ role: "user", content: "placeholder" }],
} as WithPlanckPrompt);

When using promptId, you must still pass a placeholder messages array to satisfy the Vercel AI SDK’s validation. The actual prompt content will be fetched from your Planck dashboard, and the placeholder messages will be ignored.

Benefits of using Planck prompts:

🎯 Centralized Management: Update prompts without code changes
👩🏻‍💻 Perfect for non-technical users: Create prompts using the Planck dashboard
🚀 Lower Latency: Single API call, no message construction overhead
🔧 A/B Testing: Test different prompt versions with environments
📊 Better Analytics: Track prompt performance across versions

Additional Examples

For a complete Geist-style Next.js application, see the Vercel AI SDK example. It includes routed examples for chat streaming, model discovery, embeddings, image generation, asynchronous video generation, and request feedback. The example consumes the unpublished provider directly from this monorepo.

AI Gateway Overview

Learn about Planck’s AI Gateway features and capabilities

Provider Routing

Configure intelligent routing and automatic failover

Model Registry

Browse all available models and providers

Prompt Management

Version and manage prompts with Planck Prompts

Custom Properties

Add metadata to track and filter your requests

Sessions

Track multi-turn conversations and user sessions

Rate Limiting

Configure rate limits for your applications

Caching

Reduce costs and latency with intelligent caching

Getting Started

AI Gateway

Observability & Analytics

Prompt Management

Async Logging

Custom Logs

Vercel AI SDK Integration

Introduction

Integration Steps

Complete Working Examples

Basic Text Generation

Streaming Text

Provider Selection

With Custom Properties and Session Tracking

Tool Calling

Planck Prompts Integration

Additional Examples

AI Gateway Overview

Provider Routing

Model Registry

Prompt Management

Custom Properties

Sessions

Rate Limiting

Caching

Additional Resources

​Introduction

​Integration Steps

​Complete Working Examples

​Basic Text Generation

​Streaming Text

​Provider Selection

​With Custom Properties and Session Tracking

​Tool Calling

​Planck Prompts Integration

​Additional Examples

​Related Documentation

AI Gateway Overview

Provider Routing

Model Registry

Prompt Management

Custom Properties

Sessions

Rate Limiting

Caching

​Additional Resources

Introduction

Integration Steps

Complete Working Examples

Basic Text Generation

Streaming Text

Provider Selection

With Custom Properties and Session Tracking

Tool Calling

Planck Prompts Integration

Additional Examples

Related Documentation

Additional Resources