Portkey natively integrates with the Vercel AI SDK to make your apps production-ready and reliable. Just import Portkey’s Vercel package and use it as a provider in your Vercel AI app to enable all of Portkey features:
  • Full-stack observability and tracing for all requests
  • Interoperability across 250+ LLMS
  • Built-in 50+ SOTA guardrails
  • Simple & semantic caching to save costs & time
  • Route requests conditionally and make them robust with fallbacks, load-balancing, automatic retries, and more
  • Continuous improvement based on user feedback

​
Getting Started

​
1. Installation

npm install @portkey-ai/vercel-provider

​
2. Import & Configure Portkey Object

Sign up for Portkey and get your API key, and configure Portkey provider in your Vercel app: 
import { createPortkey } from '@portkey-ai/vercel-provider';

const portkeyConfig = {
      "provider": "openai", // Choose your provider (e.g., 'anthropic')
      "api_key": "OPENAI_API_KEY",
      "override_params": {
          "model": "gpt-4o" // Select from 250+ models
        }
};

const portkey = createPortkey({
  apiKey: 'YOUR_PORTKEY_API_KEY',
  config: portkeyConfig,
});
Portkey’s configs are a powerful way to manage & govern your app’s behaviour. Learn more about Configs here.

​
Using Vercel Functions

Portkey provider works with all of Vercel functions generateText & streamText. Here’s how to use them with Portkey: 
import { createPortkey } from '@portkey-ai/vercel-provider';
import { generateText } from 'ai';

const portkeyConfig = {
      "provider": "openai", // Choose your provider (e.g., 'anthropic')
      "api_key": "OPENAI_API_KEY",
      "override_params": {
          "model": "gpt-4o"
        }
};

const portkey = createPortkey({
  apiKey: 'YOUR_PORTKEY_API_KEY',
  config: portkeyConfig,
});

const { text } = await generateText({
  model: portkey.chatModel(''), // Provide an empty string, we defined the model in the config
  prompt: 'What is Portkey?',
});

console.log(text);
Portkey supports chatModel and completionModel to easily handle chatbots or text completions. In the above examples, we used portkey.chatModel for generateText and portkey.completionModel for streamText.

​
Tool Calling with Portkey

Portkey supports Tool calling with Vercel AI SDK. Here’s how- 
import { z } from 'zod';
import { generateText, tool } from 'ai';

const result = await generateText({
  model: portkey.chatModel('gpt-4-turbo'),
  tools: {
    weather: tool({
      description: 'Get the weather in a location',
      parameters: z.object({
        location: z.string().describe('The location to get the weather for'),
      }),
      execute: async ({ location }) => ({
        location,
        temperature: 72 + Math.floor(Math.random() * 21) - 10,
      }),
    }),
  },
  prompt: 'What is the weather in San Francisco?',
});

​
Portkey Features

Portkey Helps you make your Vercel app more robust and reliable. The portkey config is a modular way to make it work for you in whatever way you want.

​
Interoperability

Portkey allows you to easily switch between 250+ AI models by simply changing the model name in your configuration. This flexibility enables you to adapt to the evolving AI landscape without significant code changes. 
const portkeyConfig = {
      "provider": "openai",
      "api_key": "OPENAI_API_KEY",
      "override_params": {
          "model": "gpt-4o"
        }
};

​
Observability

Portkey’s OpenTelemetry-compliant observability suite gives you complete control over all your requests. And Portkey’s analytics dashboards provide 40+ key insights you’re looking for including cost, tokens, latency, etc. Fast.
Portkey's Observability Dashboard

​
Reliability

Portkey enhances the robustness of your AI applications with built-in features such as Caching, Fallback mechanisms, Load balancing, Conditional routing, Request timeouts, etc. Here is how you can modify your config to include the following Portkey features- 
import { createPortkey } from '@portkey-ai/vercel-provider';
import { generateText } from 'ai';

const portkeyConfig =  {
	"strategy": {
		"mode": "fallback"
	},
	"targets": [
		{
		"provider": "anthropic",
	      	"api_key": "Anthropic_API_KEY",
	      	"override_params": {
	          "model": "claude-3-5-sonnet-20240620"
	        } },
		{
		"provider": "openai",
     	 	"api_key": "OPENAI_API_KEY",
      		"override_params": {
          		"model": "gpt-4o"
        } }
	]
}

const portkey = createPortkey({
  apiKey: 'YOUR_PORTKEY_API_KEY',
  config: portkeyConfig,
});

const { text } = await generateText({
  model: portkey.chatModel(''),
  prompt: 'What is Portkey?',
});

console.log(text);
Learn more about Portkey’s AI gateway features in detail here.

​
Guardrails

Portkey Guardrails allow you to enforce LLM behavior in real-time, verifying both inputs and outputs against specified checks. You can create Guardrail checks in UI and then pass them in your Portkey Configs with before request or after request hooks. Read more about Guardrails here.

​
Portkey Config

Many of these features are driven by Portkey’s Config architecture. The Portkey app simplifies creating, managing, and versioning your Configs. For more information on using these features and setting up your Config, please refer to the Portkey documentation.