pipecat/examples/multi-worker/ui-worker/hello-snapshot

hello-snapshot

The smallest possible UIWorker example. A static HTML page with a few news cards and a sidebar. The user speaks; the worker answers grounded in whatever's currently on screen.

What it shows

• The accessibility-snapshot pipeline: the client walks the DOM and streams a snapshot, which the UIWorker injects into its LLM context as <ui_state>.
• The UIWorker delegate setup: the main pipeline's LLM (the conversational layer) delegates every utterance to a HelloWorker (UIWorker) via the answer_about_screen tool (params.pipeline_worker.job("hello", name="respond", ...)) and speaks the result.
• The native RTVI⇄bus UI bridge built into PipelineWorker: with enable_rtvi=True (the default), inbound ui-snapshot messages are broadcast on the bus and the UIWorker stores them — no decorator or manual wiring.

Architecture

Main worker (PipelineWorker, owns transport + RTVI):
  transport.in → STT → user_agg → LLM → TTS → transport.out → assistant_agg
    └── answer_about_screen(query) tool
          └── params.pipeline_worker.job("hello", name="respond", payload={query})

HelloWorker (UIWorker):
  └── @tool answer(text)

Run

Two terminals.

Terminal 1 — bot:

cd examples/multi-worker/ui-worker/hello-snapshot
uv run python bot.py

The bot starts on http://localhost:7860.

Terminal 2 — client:

cd examples/multi-worker/ui-worker/hello-snapshot/client
npm install            # one-time
npm run dev

Open http://localhost:5173 and click Connect.

What to try

Once connected, ask the worker:

• "What's on this page?" — it summarizes the layout (heading, three stories, trending tags sidebar).
• "What was the second story about?" — sibling order in the snapshot matches reading order, so "second" resolves cleanly.
• "Which story was about energy?" — the worker grounds against the actual content, not just titles.
• "What tags are trending?" — exercises sidebar reading.
• "What's the capital of France?" — the worker answers from general knowledge when the question has nothing to do with the page.

If you scroll the page (in a smaller window) or resize, the snapshot re-emits. Off-screen elements get an [offscreen] tag the worker respects when answering positional questions like "what do I see right now."

Requirements

• OPENAI_API_KEY
• DEEPGRAM_API_KEY
• CARTESIA_API_KEY

A .env in the example folder is the easiest way to set these (see examples/multi-worker/env.example).

What this example doesn't show

The read-side foundation only — no acting on the page (scroll_to, highlight, ...), form filling, selection-based deixis, or async task cards. Those build on this same skeleton.