saa-sdk
attenlabs/saa-sdk/llms.txt
SAA is the addressee layer for voice agents: one decision per utterance about whether speech was meant for your agent — so background speech, side conversations, and the agent's own TTS echo are filtered out before STT, LLM, or TTS. No wake word, model-agnostic, drop-in for the voice stack you already use. The classifier, model, and weights run server-side on attention labs' hosted service; the SDKs published on npm and PyPI are thin Apache-2.0 clients that only capture, encode, and…
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# SAA — Selective Auditory Attention
> SAA is the addressee layer for voice agents: one decision per utterance about whether speech was meant for your agent — so background speech, side conversations, and the agent's own TTS echo are filtered out before STT, LLM, or TTS. No wake word, model-agnostic, drop-in for the voice stack you already use. The classifier, model, and weights run server-side on attention labs' hosted service; the SDKs published on npm and PyPI are thin Apache-2.0 clients that only capture, encode, and stream media.
The mental model: audio in -> addressee gate (the SAA decision) -> only addressed audio out. You capture the media; SAA emits typed events. The key event is `turnReady` / `turn_ready` — one device-directed utterance (PCM16 @ 16 kHz), ready to forward to your STT or LLM. The SDKs also emit `prediction`, `vad`, `state`, `interrupt`, `config`, and `stats`, and expose `mute`/`unmute`, `setThreshold`/`set_threshold`, and `markResponding`/`mark_responding`.
## Install
- JavaScript / browser: `npm install @attenlabs/saa-js`
- Python (streaming SDK): `pip install attenlabs-saa`
- Python (LiveKit): `pip install saa-livekit-client`
- Python (Pipecat on Daily): `pip install saa-pipecat-client`
- API key: https://attentionlabs.ai
## Quickstart
JavaScript:
```js
import { AttentionClient } from "@attenlabs/saa-js";
const client = new AttentionClient({ token: process.env.SAA_API_KEY });
client.on("turnReady", (turn) => yourSTT.send(turn.audioBase64));
await client.start({ videoElement: document.querySelector("video") });
```
Python:
```python
from saa import AttentionClient
client = AttentionClient(token=os.environ["SAA_API_KEY"])
@client.on_turn_ready
def _(turn):
your_stt.send(turn.audio_base64)
client.start()
```
Audio-only deployments: omit `videoElement` (browser) or pass `enable_video=False` (Python).
To see live device-directed predictions on your own mic, run [examples/python](./examples/python) (terminal; set `SAA_API_KEY`) or [examples/web](./examples/web) (browser; paste your token) — your SAA API key is all you need.
## Packages
- [@attenlabs/saa-js](./packages/saa-js): JavaScript / browser SDK (npm)
- [attenlabs-saa](./packages/saa-py): Python streaming SDK (PyPI)
- [saa-livekit-client](./packages/saa-livekit-client): LiveKit Agents integration (PyPI)
- [saa-pipecat-client](./packages/saa-pipecat-client): Pipecat / Daily integration (PyPI)
## Examples
- [ElevenLabs](./examples/elevenlabs): managed speech-to-speech, gated via feed_audio
- [LiveKit](./examples/livekit): SAA gates an OpenAI Realtime agent (barge-in + interjection)
- [Pipecat on Daily](./examples/pipecat): SAA joins the Daily room and gates the pipeline
- [Twilio Media Streams](./examples/twilio): telephony bridge (mu-law 8 kHz <-> PCM16)
- [Python](./examples/python): microphone + camera streaming demo
- [Web](./examples/web): vanilla-JS browser client
## Documentation
- Reference docs: https://attentionlabs.ai/docs
- Repository: https://github.com/attenlabs/saa-sdk
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