ai_ui_stream

A pure-Dart client for the AI SDK UI Message Stream protocol (ai v7), the SSE format behind useChat. Point it at your chat endpoint and you get typed messages that update as the model streams, with tool calls, reasoning, sources, files, data parts and human-in-the-loop tool approval. No UI framework, no backend assumptions. Not affiliated with Vercel.

Install

dart pub add ai_ui_stream

Quick start

import 'package:ai_ui_stream/ai_ui_stream.dart';
import 'package:ai_ui_stream/http.dart';

final chat = ChatController(
  transport: HttpChatTransport(
    endpoint: Uri.parse('https://api.example.com/chat'),
    headers: () async => {'authorization': 'Bearer ${await getToken()}'},
  ),
);

chat.snapshots.listen((snapshot) => render(snapshot.messages));

await chat.sendText('Hello!');

Render the parts

Each UIMessage holds a list of UIParts that grow as the stream arrives. UIPart is sealed, so a switch is exhaustive:

Widget renderPart(UIPart part) => switch (part) {
      TextUIPart(:final text) => Text(text),
      ReasoningUIPart(:final text) => Text(text, style: dim),
      ToolUIPart(:final toolName, :final state) => ToolCard(toolName, state),
      FileUIPart(:final url) => Image.network(url),
      SourceUrlUIPart(:final url, :final title) => Link(url, title),
      _ => const SizedBox.shrink(),
    };

snapshot.status is submitted while waiting for the first byte, streaming during the reply, then ready or error (with snapshot.error).

ChatController

Method	Does
sendText(text) / sendMessage(message)	Sends a user message (text, or parts of any type).
regenerate({messageId})	Re-answers with trigger regenerate-message: drops the last reply, or the given assistant message (or what follows a given user message).
addToolOutput / addToolOutputError	Records a client tool's result locally; send with continueTurn().
continueTurn()	Resends the transcript without a new message.
resumeStream()	Reattaches to a running stream via ChatTransport.reconnect; no-op if it returns null.
respondToApprovals(decisions)	Answers pending tool approvals and resends (see below).
addToolApprovalResponse(...)	Records one approval decision locally, without sending.
clearError()	Moves an error status back to ready.
stop()	Cancels the turn and aborts the request; lastTurnAborted is set.
removeLastExchange() / seedMessages(...)	Drops the last exchange / loads history.

Every send takes optional extraBody and extraHeaders. Pass onFinish (ChatFinishDetails) and onError to the constructor to observe each turn's end, and idGenerator if your backend needs UUID ids.

Send methods never throw for a failed turn: they complete when the turn ends, and the failure is on status and error. A turn fails with ChatProtocolException unless the response is 2xx, text/event-stream and carries x-vercel-ai-ui-message-stream: v1, or when the stream ends without a finish or abort chunk.

Tool approval

A tool-approval-request chunk moves the tool part to ToolState.approvalRequested with a ToolApproval and lists it in chat.pendingApprovals (automatic approvals excluded). Answer with respondToApprovals:

await chat.respondToApprovals([
  for (final approval in chat.pendingApprovals)
    ApprovalDecision(
      approvalId: approval.approvalId,
      toolCallId: approval.toolCallId,
      toolName: approval.toolName,
      args: approval.input as Map<String, dynamic>,
      approved: true, // or false, with an optional `reason`
    ),
]);

Each part moves to approvalResponded and the transcript is resent with no new user message; the server continues the same assistant message, ending the part in outputAvailable or outputDenied. Pass userText to append a user message instead, for backends that reject a transcript ending in an assistant turn. For backends that predate the approval chunk, ChatController(inferApprovalOnFinish: true) treats a client tool still waiting on its input at finish as awaiting approval, using the toolCallId as the approval id.

Transport

HttpChatTransport lives in package:ai_ui_stream/http.dart so the core library stays free of package:http. It POSTs {id, messages, trigger, ...} as JSON with accept: text/event-stream, content-type: application/json and x-vercel-ai-ui-message-stream: v1; your headers() merge over them, and body: replaces the default body builder. stop() aborts the in-flight request (AbortableRequest, package:http >= 1.5). Without a client, the transport owns one and closes it on dispose(). See example/main.dart for a runnable CLI.

To use another HTTP client, auth scheme or body shape, extend ChatTransport:

import 'dart:convert';

import 'package:ai_ui_stream/ai_ui_stream.dart';
import 'package:http/http.dart' as http;

class MyTransport extends ChatTransport {
  final _client = http.Client();

  @override
  Future<ChatResponse> send(
    ChatRequest request, {
    required Future<void> abort,
  }) async {
    final req = http.AbortableRequest(
      'POST',
      Uri.parse('https://api.example.com/chat'),
      abortTrigger: abort,
    )
      ..headers['content-type'] = 'application/json'
      ..headers['accept'] = 'text/event-stream'
      ..body = jsonEncode({
        'id': request.conversationId,
        'trigger': request.trigger,
        'messages': request.messages.map((m) => m.toJson()).toList(),
      });
    final res = await _client.send(req);
    return ChatResponse(
      statusCode: res.statusCode,
      headers: {
        for (final e in res.headers.entries) e.key.toLowerCase(): e.value,
      },
      body: res.stream,
    );
  }

  @override
  void dispose() => _client.close();
}

ChatTransport.reconnect (default null) backs resumeStream(); extend rather than implement to inherit it.

Lower-level pieces

ChatController is built from parts you can use on their own: UiMessageStreamParser turns SSE bytes into UIStreamEvents, and MessageReducer.apply folds one event into a list of UIMessages.

Supported protocol

Every chunk type of the UI Message Stream is parsed; unknown ones are not dropped.

Chunk	Event	Result
start, message-metadata, finish	StartEvent, MessageMetadataEvent, FinishEvent	Message id and metadata (shallow-merged)
start-step, finish-step, reset-step	StartStepEvent, FinishStepEvent, ResetStepEvent	StepStartUIPart; reset-step drops the step's parts
abort	AbortEvent	Turn ends ready; lastTurnAborted
error	ErrorEvent	Turn ends in error with AiStreamException
text-start / -delta / -end	TextStartEvent, ...	TextUIPart
reasoning-start / -delta / -end	ReasoningStartEvent, ...	ReasoningUIPart
source-url, source-document	AppendPartEvent	SourceUrlUIPart, SourceDocumentUIPart
file, reasoning-file	AppendPartEvent	FileUIPart (isReasoning)
tool-input-start / -delta / -available	ToolInput*Event	ToolUIPart (static and dynamic-tool)
tool-input-error	ToolInputErrorEvent	ToolUIPart in outputError, raw input kept
tool-output-available / -error / -denied	ToolOutput*Event	outputAvailable / outputError / outputDenied
tool-approval-request / -response	ToolApprovalRequestEvent, ToolApprovalResponseEvent	ToolUIPart.approval
data-*	DataEvent	DataUIPart, or dataEvents only if transient
custom and any unknown type	UnknownStreamEvent	Surfaced as an event only; the reducer leaves the message unchanged
[DONE]	DoneEvent	Clean end of stream

A data-* chunk becomes a DataUIPart, replacing an earlier one with the same type and id. Transient chunks never touch the message. Listen to ChatController.dataEvents to see every DataEvent, transient ones included (for progress indicators, heartbeats and the like).

Tests run against byte-exact fixtures generated from ai@7.0.133; see test/fixtures/README.md.

License

Apache-2.0. See LICENSE.