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
and get your API key, and configure Portkey provider in your Vercel app:
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);
import { createPortkey } from '@portkey-ai/vercel-provider';
import { streamText } from 'ai';
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,
});
const result = await streamText({
model: portkey('gpt-4-turbo'), // This gets overwritten by config
prompt: 'Invent a new holiday and describe its traditions.',
});
for await (const chunk of result) {
console.log(chunk);
}
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.
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.
Here's how you'd use OpenAI with Portkey's Vercel integration:
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.
Reliability
Here is how you can modify your config to include the following Portkey features-