@tanstack/ai-react

React hooks for TanStack AI, providing convenient React bindings for the headless client. For React Native, the documented support surface is narrow: useChat with chat connection adapters. React DOM-specific UI packages and TanStack AI devtools UI are not part of the React Native support surface.

For a complete native journey, see Quick Start: React Native.

Installation

shell

npm install @tanstack/ai-react

useChat(options?)

Main hook for managing chat state in React with full type safety.

tsx

import { useChat, fetchServerSentEvents } from "@tanstack/ai-react";
import { 
  clientTools, 
  createChatClientOptions, 
  type InferChatMessages 
} from "@tanstack/ai-client";

function ChatComponent() {
  // Create client tool implementations
  const updateUI = updateUIDef.client((input) => {
    setNotification(input.message);
    return { success: true };
  });

  // Create typed tools array (no 'as const' needed!)
  const tools = clientTools(updateUI);

  const chatOptions = createChatClientOptions({
    connection: fetchServerSentEvents("/api/chat"),
    tools,
  });

  // Fully typed messages!
  type ChatMessages = InferChatMessages<typeof chatOptions>;

  const { messages, sendMessage, isLoading, error, addToolApprovalResponse } =
    useChat(chatOptions);

  return <div>{/* Chat UI with typed messages */}</div>;
}

Options

Extends ChatClientOptions from @tanstack/ai-client:

connection - Connection adapter (required)
tools? - Array of client tool implementations (with .client() method)
initialMessages? - Initial messages array
id? - Unique identifier for this chat instance
threadId? - Thread ID for AG-UI run correlation. Persists across sends; auto-generated if omitted
forwardedProps? - Arbitrary client-controlled JSON forwarded to the server in the AG-UI RunAgentInput.forwardedProps field (e.g., { provider: 'openai', model: 'gpt-4o' })
body? - Deprecated. Use forwardedProps instead. Still works for backward compatibility; values are merged into forwardedProps on the wire
context? - Typed client-local runtime context passed to client tool implementations. This value is not serialized to the server
onResponse? - Callback when response is received
onChunk? - Callback when stream chunk is received
onFinish? - Callback when response finishes
onError? - Callback when error occurs
streamProcessor? - Stream processing configuration
Note: Client tools are now automatically executed - no onToolCall callback needed!

Returns

interface UseChatReturn {
  messages: UIMessage[];
  sendMessage: (content: string) => Promise<void>;
  append: (message: ModelMessage | UIMessage) => Promise<void>;
  addToolResult: (result: {
    toolCallId: string;
    tool: string;
    output: any;
    state?: "output-available" | "output-error";
    errorText?: string;
  }) => Promise<void>;
  addToolApprovalResponse: (response: {
    id: string;
    approved: boolean;
  }) => Promise<void>;
  reload: () => Promise<void>;
  stop: () => void;
  isLoading: boolean;
  error: Error | undefined;
  setMessages: (messages: UIMessage[]) => void;
  clear: () => void;
}

Connection Adapters

Re-exported from @tanstack/ai-client for convenience:

import {
  fetchServerSentEvents,
  fetchHttpStream,
  xhrServerSentEvents,
  xhrHttpStream,
  stream,
  type ConnectionAdapter,
  type FetchConnectionOptions,
  type XhrConnectionOptions,
} from "@tanstack/ai-react";

For React Native or Expo chat screens, use an absolute server URL and prefer xhrHttpStream() with a server route that returns toHttpResponse(). Use xhrServerSentEvents() with toServerSentEventsResponse() when you want SSE. Use fetchHttpStream() only when the runtime supports streaming fetch, Response.body.getReader(), and TextDecoder; otherwise it throws UnsupportedResponseStreamError.

XHR adapter options include headers, withCredentials, signal, body, and xhrFactory. Fetch adapter options include headers, credentials, signal, body, and fetchClient. Both option objects may be provided directly or as a function that resolves per request.

For error narrowing, import UnsupportedResponseStreamError and StreamTruncatedError from @tanstack/ai-client.

Example: Basic Chat

tsx

import { useState } from "react";
import { useChat, fetchServerSentEvents } from "@tanstack/ai-react";

export function Chat() {
  const [input, setInput] = useState("");

  const { messages, sendMessage, isLoading } = useChat({
    connection: fetchServerSentEvents("/api/chat"),
  });

  const handleSubmit = (e: React.FormEvent) => {
    e.preventDefault();
    if (input.trim() && !isLoading) {
      sendMessage(input);
      setInput("");
    }
  };

  return (
    <div>
      <div>
        {messages.map((message) => (
          <div key={message.id}>
            <strong>{message.role}:</strong>
            {message.parts.map((part, idx) => {
              if (part.type === "thinking") {
                return (
                  <div key={idx} className="text-sm text-gray-500 italic">
                    💭 Thinking: {part.content}
                  </div>
                );
              }
              if (part.type === "text") {
                return <span key={idx}>{part.content}</span>;
              }
              return null;
            })}
          </div>
        ))}
      </div>
      <form onSubmit={handleSubmit}>
        <input
          value={input}
          onChange={(e) => setInput(e.target.value)}
          disabled={isLoading}
        />
        <button type="submit" disabled={isLoading}>
          Send
        </button>
      </form>
    </div>
  );
}

Example: Tool Approval

tsx

import { useChat, fetchServerSentEvents } from "@tanstack/ai-react";

export function ChatWithApproval() {
  const { messages, sendMessage, addToolApprovalResponse } = useChat({
    connection: fetchServerSentEvents("/api/chat"),
  });

  return (
    <div>
      {messages.map((message) =>
        message.parts.map((part) => {
          if (
            part.type === "tool-call" &&
            part.state === "approval-requested" &&
            part.approval
          ) {
            return (
              <div key={part.id}>
                <p>Approve: {part.name}</p>
                <button
                  onClick={() =>
                    addToolApprovalResponse({
                      id: part.approval!.id,
                      approved: true,
                    })
                  }
                >
                  Approve
                </button>
                <button
                  onClick={() =>
                    addToolApprovalResponse({
                      id: part.approval!.id,
                      approved: false,
                    })
                  }
                >
                  Deny
                </button>
              </div>
            );
          }
          return null;
        })
      )}
    </div>
  );
}

Example: Client Tools with Type Safety

tsx

import { useChat, fetchServerSentEvents } from "@tanstack/ai-react";
import { 
  clientTools, 
  createChatClientOptions, 
  type InferChatMessages 
} from "@tanstack/ai-client";
import { updateUIDef, saveToStorageDef } from "./tool-definitions";
import { useState } from "react";

export function ChatWithClientTools() {
  const [notification, setNotification] = useState(null);

  // Create client implementations
  const updateUI = updateUIDef.client((input) => {
    // ✅ input is fully typed!
    setNotification({ message: input.message, type: input.type });
    return { success: true };
  });

  const saveToStorage = saveToStorageDef.client((input) => {
    localStorage.setItem(input.key, input.value);
    return { saved: true };
  });

  // Create typed tools array (no 'as const' needed!)
  const tools = clientTools(updateUI, saveToStorage);

  const { messages, sendMessage } = useChat({
    connection: fetchServerSentEvents("/api/chat"),
    tools, // ✅ Automatic execution, full type safety
  });

  return (
    <div>
      {messages.map((message) =>
        message.parts.map((part) => {
          if (part.type === "tool-call" && part.name === "updateUI") {
            // ✅ part.input and part.output are fully typed!
            return <div>Tool executed: {part.name}</div>;
          }
        })
      )}
    </div>
  );
}

createChatClientOptions(options)

Helper to create typed chat options (re-exported from @tanstack/ai-client).

import { 
  clientTools, 
  createChatClientOptions, 
  type InferChatMessages 
} from "@tanstack/ai-client";

// Create typed tools array (no 'as const' needed!)
const tools = clientTools(tool1, tool2);

const chatOptions = createChatClientOptions({
  connection: fetchServerSentEvents("/api/chat"),
  tools,
});

type Messages = InferChatMessages<typeof chatOptions>;

Types

Re-exported from @tanstack/ai-client:

UIMessage<TTools> - Message type with tool type parameter
MessagePart<TTools> - Message part with tool type parameter
TextPart - Text content part
ThinkingPart - Thinking content part
ToolCallPart<TTools> - Tool call part (discriminated union)
ToolResultPart - Tool result part
ChatClientOptions<TTools, TContext> - Chat client options with typed client runtime context
ConnectionAdapter - Connection adapter interface
InferChatMessages<T> - Extract message type from options
Re-exported from @tanstack/ai:
toolDefinition() - Create isomorphic tool definition
ToolDefinitionInstance - Tool definition type
ClientTool - Client tool type
ServerTool - Server tool type