assistant-ui Streaming
SkillDev toolsGuide for assistant-stream package and streaming protocols. Use when implementing streaming backends, custom protocols, or debugging stream issues.
Available today. Use it from your connected AI after setup.
No other account needed.
Connect ahel once, and every AI you use reads what you have installed.
Then ask your AI: use the assistant-ui Streaming skill
What this skill tells your AI
The instructions your AI receives, as published by utopusc/livinity-io in .agents/skills/streaming/SKILL.md and read by ahel’s review.
Always consult assistant-ui.com/llms.txt for latest API.
The assistant-stream package handles streaming from AI backends.
References
- ./references/data-stream.md -- AI SDK data stream format
- ./references/assistant-transport.md -- Native assistant-ui format
- ./references/encoders.md -- Encoders and decoders
When to Use
Using Vercel AI SDK?
├─ Yes → toUIMessageStreamResponse() (no assistant-stream needed)
└─ No → assistant-stream for custom backends
Installation
npm install assistant-stream
Custom Streaming Response
import { createAssistantStreamResponse } from "assistant-stream";
export async function POST(req: Request) {
return createAssistantStreamResponse(async (stream) => {
stream.appendText("Hello ");
stream.appendText("world!");
// Tool call example
const tool = stream.addToolCallPart({ toolCallId: "1", toolName: "get_weather" });
tool.argsText.append('{"city":"NYC"}');
tool.argsText.close();
tool.setResponse({ result: { temperature: 22 } });
stream.close();
});
}
With useLocalRuntime
useLocalRuntime expects ChatModelRunResult chunks. Yield content parts for streaming:
import { useLocalRuntime } from "@assistant-ui/react";
const runtime = useLocalRuntime({
model: {
async *run({ messages, abortSignal }) {
const response = await fetch("/api/chat", {
method: "POST",
body: JSON.stringify({ messages }),
signal: abortSignal,
});
const reader = response.body?.getReader();
const decoder = new TextDecoder();
let buffer = "";
while (reader) {
const { done, value } = await reader.read();
if (done) break;
buffer += decoder.decode(value, { stream: true });
const parts = buffer.split("\n");
buffer = parts.pop() ?? "";
for (const chunk of parts.filter(Boolean)) {
yield { content: [{ type: "text", text: chunk }] };
}
}
},
},
});
Debugging Streams
import { AssistantStream, DataStreamDecoder } from "assistant-stream";
const stream = AssistantStream.fromResponse(response, new DataStreamDecoder());
for await (const event of stream) {
console.log("Event:", JSON.stringify(event, null, 2));
}
Stream Event Types
part-startwithpart.type="text" | "reasoning" | "tool-call" | "source" | "file"text-deltawith streamed textresultwith tool resultsstep-start,step-finish,message-finisherrorstrings
Common Gotchas
Stream not updating UI
- Check Content-Type is
text/event-stream - Check for CORS errors
Tool calls not rendering
addToolCallPartneeds bothtoolCallIdandtoolName- Register tool UI with
makeAssistantToolUI
Partial text not showing
- Use
text-deltaevents for streaming
Signals
- GitHub stars
- 74
- Forks
- 3
- Last commit
- Aug 2026
ahel recommends instead
Advanced
- Catalog kind
- skill
- Gateway key
streaming-utopusc- Source
- github.com/utopusc/livinity-io