Svelte 5 bindings for TanStack AI, providing reactive factory functions for the headless client using Svelte runes.
npm install @tanstack/ai-svelteFactory function for managing chat state in Svelte 5 with full type safety.
import { createChat, fetchServerSentEvents } from "@tanstack/ai-svelte";
import {
clientTools,
createChatClientOptions,
type InferChatMessages,
} from "@tanstack/ai-client";
// In <script> block
const updateUI = updateUIDef.client((input) => {
notification = input.message;
return { success: true };
});
const tools = clientTools(updateUI);
const chatOptions = createChatClientOptions({
connection: fetchServerSentEvents("/api/chat"),
tools,
});
// Fully typed messages!
type ChatMessages = InferChatMessages<typeof chatOptions>;
const chat = createChat(chatOptions);
// Access: chat.messages, chat.sendMessage, chat.isLoading, chat.errorExtends ChatClientOptions from @tanstack/ai-client (minus internal state callbacks):
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
live? - Enable live subscription mode (subscribes on creation)
onResponse? - Callback when response is received
onChunk? - Callback when stream chunk is received
onFinish? - Callback when response finishes
onError? - Callback when error occurs
onCustomEvent? - Callback for custom stream events
streamProcessor? - Stream processing configuration
Note: Client tools are now automatically executed - no onToolCall callback needed!
interface CreateChatReturn<TContext = unknown> {
readonly messages: UIMessage[];
sendMessage: (content: string | MultimodalContent) => 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;
readonly isLoading: boolean;
readonly error: Error | undefined;
readonly status: ChatClientState;
readonly isSubscribed: boolean;
readonly connectionStatus: ConnectionStatus;
readonly sessionGenerating: boolean;
setMessages: (messages: UIMessage[]) => void;
clear: () => void;
/** @deprecated Use `updateForwardedProps` instead. */
updateBody: (body: Record<string, any>) => void;
updateForwardedProps: (forwardedProps: Record<string, any>) => void;
updateContext: (context: TContext) => void;
}Key differences from React/Vue:
create* naming -- factory functions, not hooks. Call outside of any lifecycle.
Reactive getters -- state properties (messages, isLoading, error, status, isSubscribed, connectionStatus, sessionGenerating) are Svelte 5 $state via getters. Access directly (e.g., chat.messages, not chat.messages.value).
No automatic cleanup -- unlike React/Vue/Solid, createChat does not auto-dispose. Call chat.stop() manually when the component unmounts (e.g., in onDestroy or an $effect return).
updateForwardedProps() -- update AG-UI forwardedProps dynamically (e.g., for model selection). In Vue, changes to the forwardedProps option are synced via watch; in Svelte, call this method explicitly. The legacy updateBody() is still available but deprecated.
.svelte.ts files -- source files use the .svelte.ts extension for Svelte 5 rune support.
Re-exported from @tanstack/ai-client for convenience:
import {
fetchServerSentEvents,
fetchHttpStream,
stream,
type ConnectionAdapter,
} from "@tanstack/ai-svelte";<script lang="ts">
import { createChat, fetchServerSentEvents } from "@tanstack/ai-svelte";
let input = $state("");
const chat = createChat({
connection: fetchServerSentEvents("/api/chat"),
});
const handleSubmit = (e: Event) => {
e.preventDefault();
if (input.trim() && !chat.isLoading) {
chat.sendMessage(input);
input = "";
}
};
</script>
<div>
<div>
{#each chat.messages as message (message.id)}
<div>
<strong>{message.role}:</strong>
{#each message.parts as part, idx}
{#if part.type === "thinking"}
<div class="text-sm text-gray-500 italic">
Thinking: {part.content}
</div>
{:else if part.type === "text"}
<span>{part.content}</span>
{/if}
{/each}
</div>
{/each}
</div>
<form onsubmit={handleSubmit}>
<input bind:value={input} disabled={chat.isLoading} />
<button type="submit" disabled={chat.isLoading}>Send</button>
</form>
</div><script lang="ts">
import { createChat, fetchServerSentEvents } from "@tanstack/ai-svelte";
const chat = createChat({
connection: fetchServerSentEvents("/api/chat"),
});
</script>
<div>
{#each chat.messages as message (message.id)}
{#each message.parts as part}
{#if part.type === "tool-call" && part.state === "approval-requested" && part.approval}
<div>
<p>Approve: {part.name}</p>
<button
onclick={() =>
chat.addToolApprovalResponse({
id: part.approval.id,
approved: true,
})}
>
Approve
</button>
<button
onclick={() =>
chat.addToolApprovalResponse({
id: part.approval.id,
approved: false,
})}
>
Deny
</button>
</div>
{/if}
{/each}
{/each}
</div><script lang="ts">
import { createChat, fetchServerSentEvents } from "@tanstack/ai-svelte";
import {
clientTools,
createChatClientOptions,
type InferChatMessages,
} from "@tanstack/ai-client";
import { updateUIDef, saveToStorageDef } from "./tool-definitions";
let notification = $state(null);
// Create client implementations
const updateUI = updateUIDef.client((input) => {
// input is fully typed!
notification = { 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 chat = createChat({
connection: fetchServerSentEvents("/api/chat"),
tools, // Automatic execution, full type safety
});
</script>
<div>
{#each chat.messages as message (message.id)}
{#each message.parts as part}
{#if part.type === "tool-call" && part.name === "updateUI"}
<div>Tool executed: {part.name}</div>
{/if}
{/each}
{/each}
</div>Factory functions for one-shot generation tasks (images, speech, transcription, summarization, video). All share the same pattern: provide a connection or fetcher, call generate(), and read reactive state.
Base factory for custom generation types. All specialized functions below are built on this.
import { createGeneration, fetchServerSentEvents } from "@tanstack/ai-svelte";
const gen = createGeneration({
connection: fetchServerSentEvents("/api/generate/custom"),
});
// gen.generate({ prompt: 'Hello' })
// gen.result, gen.isLoading, gen.error, gen.statusOptions: connection?, fetcher?, id?, body?, onResult?, onError?, onProgress?, onChunk?
Returns: generate, result, isLoading, error, status, stop, reset, updateBody -- all state properties are reactive getters.
Image generation factory. generate() accepts ImageGenerateInput, result is ImageGenerationResult.
Text-to-speech factory. generate() accepts SpeechGenerateInput, result is TTSResult.
Audio transcription factory. generate() accepts TranscriptionGenerateInput, result is TranscriptionResult.
Text summarization factory. generate() accepts SummarizeGenerateInput, result is SummarizationResult.
Video generation factory with job polling. Returns additional jobId and videoStatus reactive getters. Accepts extra onJobCreated? and onStatusUpdate? callbacks.
No generation function includes automatic cleanup. Call .stop() manually when done.
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>;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
ChatRequestBody - Request body type
GenerationClientState - Generation lifecycle state
ImageGenerateInput - Image generation input type
SpeechGenerateInput - Speech generation input type
TranscriptionGenerateInput - Transcription input type
SummarizeGenerateInput - Summarization input type
VideoGenerateInput - Video generation input type
VideoGenerateResult - Video generation result type
VideoStatusInfo - Video job status info
Re-exported from @tanstack/ai:
toolDefinition() - Create isomorphic tool definition
ToolDefinitionInstance - Tool definition type
ClientTool - Client tool type
ServerTool - Server tool type