> ## Documentation Index
> Fetch the complete documentation index at: https://docs.znapai.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Vercel AI SDK

> Learn how to integrate the Vercel AI SDK with OpenAI-compatible language models.

The **Vercel AI SDK** provides a simple and unified API for interacting with OpenAI-compatible language models. This guide explains how to integrate the SDK with OpenAI or any OpenAI-compatible API endpoint for text generation, streaming, image generation, and multimodal (vision) capabilities.

***

## Prerequisites

Before you begin, ensure you have:

* Node.js 18+
* An OpenAI-compatible API endpoint
* An API key
* npm or another package manager

***

## Installation

Install the required packages:

```bash theme={null}
npm install ai @ai-sdk/openai dotenv
```

### Package Overview

| Package          | Description                                                                |
| ---------------- | -------------------------------------------------------------------------- |
| `ai`             | Core Vercel AI SDK containing text generation, streaming, and image APIs.  |
| `@ai-sdk/openai` | OpenAI provider that supports both OpenAI and OpenAI-compatible endpoints. |
| `dotenv`         | Loads API keys and configuration from environment variables.               |

***

## Environment Variables

Create a `.env` file:

```env theme={null}
API_KEY=your_api_key
BASE_URL=https://your-openai-compatible-endpoint/v1
MODEL_NAME=gpt-4o-mini
IMAGE_MODEL_NAME=gpt-image-2
```

<Note>
  `BASE_URL` is optional when using the official OpenAI API. Specify it only when connecting to an OpenAI-compatible provider or proxy.
</Note>

***

## Client Configuration

Create a reusable client configuration.

```typescript theme={null}
import { createOpenAI } from '@ai-sdk/openai';
import * as dotenv from 'dotenv';

dotenv.config();

const apiKey = process.env.API_KEY;
const baseURL = process.env.BASE_URL;

export const MODEL = process.env.MODEL_NAME;

export const IMAGE_MODEL = process.env.IMAGE_MODEL_NAME;

export const openai = createOpenAI({
  apiKey,
  baseURL,
});
```

***

***

## Next Steps

To explore individual capabilities with code examples, check the following sections in the sidebar:

* [Text Generation](/integrations/vercel-ai-sdk-text)
* [Image Generation](/integrations/vercel-ai-sdk-image)
* [Image to Text (Vision)](/integrations/vercel-ai-sdk-vision)

***

## Best Practices

* Store API keys in environment variables.
* Reuse a single OpenAI client instance throughout your application.
* Use streaming for chat interfaces to improve user experience.
* Validate generation parameters before making requests.
* Handle API errors gracefully with retry or fallback logic.
* Use system prompts to define consistent assistant behavior.
* Keep prompts concise and specific for better model responses.

***

## Supported Features

| Feature                    | Supported |
| -------------------------- | --------- |
| Text Generation            | ✅         |
| Streaming Responses        | ✅         |
| System Prompts             | ✅         |
| Temperature                | ✅         |
| Top P                      | ✅         |
| Top K                      | ✅         |
| Max Tokens                 | ✅         |
| Frequency Penalty          | ✅         |
| Presence Penalty           | ✅         |
| Seed                       | ✅         |
| Stop Sequences             | ✅         |
| Image Generation           | ✅         |
| Vision (Image Input)       | ✅         |
| OpenAI-Compatible Base URL | ✅         |

***

## Next Steps

You are now ready to build applications using the Vercel AI SDK with any OpenAI-compatible endpoint. Explore additional SDK capabilities such as structured outputs, tool calling, agents, and chat history management as your application grows.