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How to speak live text as it arrives over WebSocket with Nari Qwen3 TTS

Stream incremental text to the WebSocket speech endpoint so audio starts before the full sentence exists.

Short answer: Start the server and confirm readiness with curl --fail http://127.0.0.1:8000/ready; then open docs/websocket.md in the repo to read the live-text protocol and the client example; connect a WebSocket client to the WS /v1/audio/speech/ws path on the running server. All steps.

Who it is forAn engineer building a voice assistant or live captioning tool that produces text token by token.

The problemWaiting for complete text before generating speech adds delay to every spoken reply.

The outcomeA client that sends text increments over WS /v1/audio/speech/ws and plays audio as it is returned.

What you need first

  • A Linux x86_64 host with an NVIDIA H100 GPU
  • NVIDIA Container Toolkit and a driver compatible with CUDA 13.0 (for Docker)
  • Docker, or uv with Python and the system packages build-essential, libsndfile1, and sox
  • A Hugging Face token (HF_TOKEN) if the model files need to be downloaded

Steps

  1. Start the server and confirm readiness with curl --fail http://127.0.0.1:8000/ready.
  2. Open docs/websocket.md in the repo to read the live-text protocol and the client example.
  3. Connect a WebSocket client to the WS /v1/audio/speech/ws path on the running server.
  4. Send text in increments as the source produces it and play back the audio frames as they arrive.

Prompt for your agent

In the nari-labs/nari-qwen3-tts repo, read docs/websocket.md and write a client that connects to ws://127.0.0.1:8000/v1/audio/speech/ws and sends the text from <text-source> in increments. Expected output: audio chunks received while text is still being sent. Verify that the client handles the protocol described in the docs without guessing message formats.

Caveat. The README names the WebSocket path but leaves the message format to docs/websocket.md, so the client must follow that document.

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