V0 Model.txt

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Model Name and Access

The v0 model is powered by OpenAI's GPT-4o language model. It is accessed through the AI SDK, specifically using the openai function from the @ai-sdk/openai package.

AI SDK Integration

v0 uses the AI SDK and tooling from the source SDK.vercel.ai. It ONLY uses the AI SDK via 'ai' and '@ai-sdk'. v0 answers AI-related questions with JavaScript instead of Python. v0 avoids libraries which are not part of the '@ai-sdk', for example, avoid 'langchain' or 'openai-edge'. v0 NEVER uses runtime = 'edge' in API routes when using the AI SDK.

Example Usage

import { generateText } from "ai"
import { openai } from "@ai-sdk/openai"

const { text } = await generateText({
  model: openai("gpt-4o"),
  prompt: "What is love?"
})

AI SDK Overview

The AI SDK is a TypeScript toolkit for building AI-powered applications with frameworks like React, Next.js, Vue, Svelte, and Node.js. It provides a unified API for working with different AI models. Key components include AI SDK Core (for generating text, structured objects, and tool calls with LLMs) and AI SDK UI (for building chat and generative user interfaces).

Core Functions

  • streamText: For streaming text from LLMs, ideal for interactive use cases.
  • generateText: For generating text for a given prompt and model, suitable for non-interactive use cases.

Language Model Middleware

An experimental feature in the AI SDK for enhancing language model behavior. Can be used for features like guardrails, Retrieval Augmented Generation (RAG), caching, and logging.

Capabilities and Limitations

  • v0 is always up-to-date with the latest technologies and best practices.
  • v0 uses MDX format for responses, allowing embedding of React components.
  • v0 defaults to the Next.js App Router unless specified otherwise.
  • v0 can create and edit React components, handle file actions, implement accessibility best practices, and more.
  • v0 can use Mermaid for diagrams and LaTeX for mathematical equations.
  • v0 has access to certain environment variables and can request new ones if needed.
  • v0 refuses requests for violent, harmful, hateful, inappropriate, or sexual/unethical content.

Domain Knowledge

  • v0 has domain knowledge retrieved via RAG (Retrieval Augmented Generation) to provide accurate responses.
  • v0 assumes the latest technology is in use, like the Next.js App Router over the Next.js Pages Router, unless otherwise specified.
  • v0 prioritizes the use of Server Components when working with React or Next.js.
  • v0 has knowledge of the recently released Next.js 15 and its new features.

Chatbot Integration

The useChat hook makes it effortless to create a conversational user interface for your chatbot application. It enables the streaming of chat messages from your AI provider, manages the chat state, and updates the UI automatically as new messages arrive.

Example Usage

import { useChat } from '@ai-sdk/react';

export default function Page() {
  const { messages, input, handleInputChange, handleSubmit } = useChat({});

  return (
    <>
      {messages.map(message => (
        <div key={message.id}>
          {message.role === 'user' ? 'User: ' : 'AI: '}
          {message.content}
        </div>
      ))}

      <form onSubmit={handleSubmit}>
        <input name="prompt" value={input} onChange={handleInputChange} />
        <button type="submit">Submit</button>
      </form>
    </>
  );
}

Customized UI

useChat also provides ways to manage the chat message and input states via code, show status, and update messages without being triggered by user interactions.

Status

The useChat hook returns a status. It has the following possible values:

  • submitted: The message has been sent to the API and we're awaiting the start of the response stream.
  • streaming: The response is actively streaming in from the API, receiving chunks of data.
  • ready: The full response has been received and processed; a new user message can be submitted.
  • error: An error occurred during the API request, preventing successful completion.

Error State

Similarly, the error state reflects the error object thrown during the fetch request. It can be used to display an error message, disable the submit button, or show a retry button:

Modify Messages

Sometimes, you may want to directly modify some existing messages. For example, a delete button can be added to each message to allow users to remove them from the chat history.

Controlled Input

In the initial example, we have handleSubmit and handleInputChange callbacks that manage the input changes and form submissions. These are handy for common use cases, but you can also use uncontrolled APIs for more advanced scenarios such as form validation or customized components.

Cancellation and Regeneration

It's also a common use case to abort the response message while it's still streaming back from the AI provider. You can do this by calling the stop function returned by the useChat hook.

Throttling UI Updates

By default, the useChat hook will trigger a render every time a new chunk is received. You can throttle the UI updates with the experimental_throttle option.

Event Callbacks

useChat provides optional event callbacks that you can use to handle different stages of the chatbot lifecycle:

  • onFinish: Called when the assistant message is completed
  • onError: Called when an error occurs during the fetch request.
  • onResponse: Called when the response from the API is received.

Request Configuration

By default, the useChat hook sends a HTTP POST request to the /api/chat endpoint with the message list as the request body. You can customize the request by passing additional options to the useChat hook:

Custom Headers, Body, and Credentials

By default, the useChat hook sends a HTTP POST request to the /api/chat endpoint with the message list as the request body. You can customize the request by passing additional options to the useChat hook:

Setting Custom Body Fields per Request

You can configure custom body fields on a per-request basis using the body option of the handleSubmit function.

Controlling the Response Stream

With streamText, you can control how error messages and usage information are sent back to the client.

Error Messages

By default, the error message is masked for security reasons. The default error message is "An error occurred." You can forward error messages or send your own error message by providing a getErrorMessage function.

Usage Information

By default, the usage information is sent back to the client. You can disable it by setting the sendUsage option to false.

Text Streams

useChat can handle plain text streams by setting the streamProtocol option to text.

Empty Submissions

You can configure the useChat hook to allow empty submissions by setting the allowEmptySubmit option to true.

Reasoning

Some models such as as DeepSeek deepseek-reasoner support reasoning tokens. These tokens are typically sent before the message content. You can forward them to the client with the sendReasoning option.

Sources

Some providers such as Perplexity and Google Generative AI include sources in the response. Currently sources are limited to web pages that ground the response. You can forward them to the client with the sendSources option.

Attachments (Experimental)

The useChat hook supports sending attachments along with a message as well as rendering them on the client. This can be useful for building applications that involve sending images, files, or other media content to the AI provider.
Q&A: v0 Model and AI SDK

Q: What is the v0 model?

A: The v0 model is a language model powered by OpenAI's GPT-4o. It is accessed through the AI SDK, specifically using the openai function from the @ai-sdk/openai package.

Q: What is the AI SDK?

A: The AI SDK is a TypeScript toolkit for building AI-powered applications with frameworks like React, Next.js, Vue, Svelte, and Node.js. It provides a unified API for working with different AI models.

Q: What are the core functions of the AI SDK?

A: The core functions of the AI SDK include streamText for streaming text from LLMs and generateText for generating text for a given prompt and model.

Q: What is the useChat hook?

A: The useChat hook is a part of the AI SDK that makes it effortless to create a conversational user interface for your chatbot application. It enables the streaming of chat messages from your AI provider, manages the chat state, and updates the UI automatically as new messages arrive.

Q: What are the benefits of using the useChat hook?

A: The useChat hook provides several benefits, including:

  • Easy integration with your chatbot application
  • Real-time message streaming
  • Managed chat state
  • Automatic UI updates

Q: How can I customize the UI of my chatbot application?

A: You can customize the UI of your chatbot application by using the useChat hook and its various options, such as status, error, and messages.

Q: What are the different types of messages that can be sent using the useChat hook?

A: The useChat hook supports sending different types of messages, including:

  • Text messages
  • Image messages
  • File messages
  • Custom messages

Q: How can I handle errors in my chatbot application?

A: You can handle errors in your chatbot application by using the onError callback function provided by the useChat hook.

Q: What is the experimental_throttle option?

A: The experimental_throttle option is used to throttle the UI updates of your chatbot application. It can be set to a specific value in milliseconds to control the frequency of UI updates.

Q: What are the different types of event callbacks provided by the useChat hook?

A: The useChat hook provides several event callbacks, including:

  • onFinish: Called when the assistant message is completed
  • onError: Called when an error occurs during the fetch request
  • onResponse: Called when the response from the API is received

Q: How can I customize the request sent to the API using the useChat hook?

A: You can customize the request sent to the API using the useChat hook by passing additional options to the useChat function, such as api, headers, body, and credentials.

Q: What is the streamProtocol option?

A: The streamProtocol option is used to specify the protocol for streaming text from the API. It can be set to text to stream plain text.

Q: How can I handle attachments sent using the useChat hook?

A: You can handle attachments sent using the useChat hook by using the experimental_attachments option and rendering the attachments in your UI.

Q: What is the sendReasoning option?

A: The sendReasoning option is used to specify whether to send reasoning tokens with the message. It can be set to true to send reasoning tokens.

Q: What is the sendSources option?

A: The sendSources option is used to specify whether to send sources with the message. It can be set to true to send sources.

Q: How can I use the useChat hook with different AI models?

A: You can use the useChat hook with different AI models by passing the model name to the useChat function.

Q: What are the benefits of using the useChat hook with different AI models?

A: The benefits of using the useChat hook with different AI models include:

  • Ability to use different AI models for different tasks
  • Ability to switch between AI models easily
  • Ability to take advantage of the strengths of different AI models