Getting Started with the Vercel AI SDK

The Vercel AI SDK is a powerful, open-source library designed to help you build AI-powered applications with any front-end framework and on any hosting platform. It provides a set of simple, composable tools that handle the complexities of interacting with large language models (LLMs), allowing you to focus on creating amazing user experiences.

This series of articles will guide you through the core concepts and features of the SDK, from basic text generation to building complex, autonomous agents.

Core Text Generation (generateText)

The most fundamental feature of any AI SDK is the ability to generate text. The Vercel AI SDK makes this incredibly simple with the generateText function. It provides a unified API for interacting with various model providers like OpenAI, Anthropic, and Google.

For a complete guide on how to get the most out of your models with carefully crafted instructions, see our article on Prompt Engineering.

From Text to Meaning: Embeddings (embed)

To build more advanced features like semantic search or recommendation engines, you need to go beyond simple text. Embeddings are numerical representations of your text that capture its underlying meaning. The SDK's embed and embedMany functions make creating these vectors trivial.

Learn how to convert text into meaning and build a simple semantic search engine in our Embeddings article.

Giving Your AI a Library: RAG

Retrieval-Augmented Generation (RAG) is a powerful technique for making your AI smarter and more trustworthy by allowing it to retrieve information from your own documents before answering a question. This reduces hallucinations and enables your AI to use private or up-to-date information.

Discover how to build a RAG pipeline from scratch in our guide: RAG: Giving Your AI an Open-Book Exam.

From Answering to Doing: Agents

An AI agent is an autonomous system that can reason, plan, and use tools to accomplish complex tasks. This is where the AI SDK truly shines, providing the building blocks for creating AI that can interact with APIs, browse the web, or perform actions on a user's behalf.

First, understand the high-level concepts in Agentic AI: The Shift from Answering to Accomplishing, then learn how to implement one in Building AI Agents.

Generating Interactive UI (generateUI)

The Vercel AI SDK can do more than just generate text; it can generate rich, interactive user interfaces. Using the generateUI function, you can have your AI render React components in response to a user's prompt, creating truly dynamic and conversational applications.

See how to turn natural language into user interfaces in our article on UI Generation.

Creating a Specialist: Fine-Tuning

When you need to change the fundamental behavior of a model—to teach it a specific tone, style, or complex skill—fine-tuning is the answer. It allows you to train a base model on your own data to create a true specialist.

Learn the workflow and best practices in Fine-Tuning: Giving Your AI a PhD.

Ensuring Quality: Evals

How do you know if your changes are making your AI better or worse? Evaluations are like unit tests for your AI systems. They provide a framework for "grading" your model's performance on a standardized set of test cases, ensuring quality and preventing regressions.

Learn how to build your own evaluation suite in AI Evals: Grading Your Model's Homework.