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191 lines
8.4 KiB
Markdown
191 lines
8.4 KiB
Markdown
---
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title: HF Realtime Voice
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emoji: 🎙️
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colorFrom: indigo
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colorTo: purple
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sdk: docker
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app_port: 7860
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pinned: false
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short_description: Voice chat over WebSocket against a HF speech-to-speech
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hf_oauth: true
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---
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# Realtime Voice Demo (WebSocket transport)
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Browser voice-chat UI for the
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[huggingface/speech-to-speech](https://github.com/huggingface/speech-to-speech)
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backend. The browser streams mic audio over a WebSocket using the OpenAI
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Realtime **GA** protocol and plays back the assistant's audio as it arrives.
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## Quick start (local)
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1. **Start the speech-to-speech backend** in realtime mode (from the repo root;
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see the [backend README](https://github.com/huggingface/speech-to-speech/blob/main/src/speech_to_speech/api/openai_realtime/README.md)
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for more model combinations):
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```bash
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uv run speech-to-speech \
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--mode realtime \
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--stt parakeet-tdt \
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--llm_backend transformers \
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--tts kokoro \
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--model_name "Qwen/Qwen3-4B-Instruct-2507" \
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--llm_device mps \
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--llm_torch_dtype float16 \
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--enable_live_transcription
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```
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The realtime server listens on `ws://localhost:8765/v1/realtime` by default
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(`--ws_host` / `--ws_port` to change).
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2. **Start this app**, pointing it at the backend with `SPEECH_TO_SPEECH_URL`:
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```bash
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uv pip install -r demo/requirements.txt
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export SPEECH_TO_SPEECH_URL=ws://localhost:8765/v1/realtime
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export SERPER_API_KEY=... # optional; web search is disabled without it
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uv run uvicorn --app-dir demo server:app --reload --port 7860
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```
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Or with Docker:
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```bash
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docker build -t s2s-demo demo/
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docker run -p 7860:7860 -e SPEECH_TO_SPEECH_URL=ws://host.docker.internal:8765/v1/realtime s2s-demo
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```
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3. Open <http://localhost:7860/>, click the orb, allow the mic, talk.
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> Browsers require **HTTPS or `localhost`** for `getUserMedia()` (mic + camera).
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> `127.0.0.1` and `localhost` both work; plain `http://192.168.x.y` does NOT.
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Smoke-test the backend from the shell:
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```bash
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websocat ws://localhost:8765/v1/realtime
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# -> you should get a session.created event back immediately
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```
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## How it works
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1. The browser opens a WebSocket on the configured `/v1/realtime` URL.
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2. Server pushes `session.created` on connect. Client replies with
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`session.update` (OpenAI Realtime **GA** schema: `session.audio.input`,
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`session.audio.output`, `session.output_modalities`).
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3. Client streams mic audio as PCM16 16 kHz mono base64 chunks
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(`input_audio_buffer.append`, one frame every ~40 ms).
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4. Server pushes `response.output_audio.delta` (PCM16 24 kHz mono base64)
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and transcript deltas.
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The backend exposes one concurrent session per pipeline unit
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(`--num_pipelines` to serve more).
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## Connecting to a backend
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Three modes, picked by env (`/api/config` tells the client which one is active):
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- **`SPEECH_TO_SPEECH_URL` env** — the mode you want for local use, and the
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highest priority. The browser connects **directly** to this realtime
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WebSocket URL; it's shown read-only in Settings. Setting it disables the
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load-balancer logic entirely (no `/api/session` proxy, no queue, no
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metering, no sign-in). Unlike the LB address it is not a secret. Accepts a
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full `ws(s)://host/v1/realtime` URL or a bare host like `localhost:8765`
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(the app adds `/v1/realtime`).
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- **Neither env set** — **Settings → Speech-to-speech server URL**: paste a
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full connect URL or a bare host, and the browser connects to it directly.
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- **`LOAD_BALANCER_URL` env** — multi-compute deployments only: the browser
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POSTs the same-origin `/api/session` proxy, the server forwards to the LB,
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and the browser dials the per-session compute URL the LB hands back. The LB
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address never reaches the browser; the Settings URL field is hidden.
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| `SPEECH_TO_SPEECH_URL` | `LOAD_BALANCER_URL` | `SPACE_ID` | Connection | URL field | Metering |
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|:---:|:---:|:---:|---|---|---|
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| ✅ | any | any | direct → pinned URL | visible, locked | off |
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| – | – | any | direct → user URL | editable | off |
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| – | ✅ | ✅ | LB proxy | hidden | **on** |
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| – | ✅ | – | LB proxy | hidden | off |
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**Settings → Restart** reconnects with the current voice, instructions and URL.
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## Tools
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The assistant can call two tools mid-conversation (toggle them from the **Tools**
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button, top-right):
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- **Web search** — Google results via Serper.dev, proxied server-side so the key
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never reaches the browser. Set `SERPER_API_KEY` as an env var / Space secret.
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Without it, the tool is disabled unless the user pastes their own key in the
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Tools panel.
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- **Camera** — while enabled, a live self-view shows bottom-left; when the model
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calls the tool, the current frame is sent to the vision-language model so it can
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see what you're showing it.
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## Usage limits (deployed Space only)
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Conversation time is metered per UTC day by sign-in tier (see `limiter.py` /
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`auth.py`), but **only on the deployed Space** — metering turns on only when BOTH
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`LOAD_BALANCER_URL` and `SPACE_ID` (injected automatically by the HF Space
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runtime) are present. Running locally — even with `LOAD_BALANCER_URL` exported —
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leaves the app unmetered. Tunable via env:
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| Env | Default | What |
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|-----|---------|------|
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| `LIMIT_ANON_SEC` | `300` | Daily seconds for anonymous visitors (5 min) |
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| `LIMIT_FREE_SEC` | `600` | Daily seconds for signed-in non-PRO users (10 min) |
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| `UNLIMITED_ORGS` | _(adds to defaults)_ | Extra HF org names whose members get **unlimited** usage, like PRO |
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| `USAGE_HASH_SECRET` | _(random)_ | HMAC secret for hashing identity keys + signing the anon cookie |
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PRO members are always unlimited. Members of `cerebras`, `HuggingFaceM4`,
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`smolagents`, and `pollen-robotics` are unlimited out of the box (shown as
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"Team", not "PRO"); set `UNLIMITED_ORGS=my-team` to add more. Matched
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case-insensitively against the user's organisations from HF OAuth.
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## Settings (stored in `localStorage`)
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| Key | What |
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|-----|------|
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| Speech-to-speech server URL | Direct realtime WebSocket URL (hidden/locked when pinned by env) |
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| Voice | Qwen3-TTS speaker name (Aiden, Ryan, Dylan, Eric, Ono_Anna, Serena, Sohee, Uncle_Fu, Vivian) |
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| Instructions | System prompt sent in `session.update` once the WS opens |
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LocalStorage keys are namespaced `s2s.ws.*` so this app's settings do
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NOT collide with the WebRTC variant.
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## Files
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| File | Role |
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|------|------|
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| `index.html` | Single page, orb + settings modal (identical UI to the WebRTC app) |
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| `main.js` | State machine, settings, tools, camera, noise-gate UI wiring |
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| `ui/chat.js` | `ChatView`: history panel, ephemeral bubbles, transcript/tool streaming |
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| `ui/account.js` | `Account`: HF login chip + popover, daily-limit modal |
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| `ui/dom.js` | Shared helpers: `$`, `escHtml`, `truncateError`, `DEBUG` |
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| `auth.py` | HF OAuth + per-request identity (tier, hashed keys) |
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| `limiter.py` | SQLite per-day talk-time budget (chunked server-clock reservation) |
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| `ws/s2s-ws-client.js` | WebSocket handshake + OpenAI Realtime GA protocol |
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| `ws/codec.js` | base64 <-> PCM helpers + transcript extraction (pure) |
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| `ws/orb-visualizer.js` | `OrbVisualiser`: FFT bands -> orb CSS custom properties |
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| `worklets/mic-capture.js` | AudioWorklet: 48 kHz Float32 -> 16 kHz Int16 PCM, posts ~40 ms chunks |
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| `worklets/audio-playback.js` | AudioWorklet: 24 kHz Float32 ring buffer -> 48 kHz, linear interp, fade in/out |
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| `style.css` | Orb animations, layout, dark theme (verbatim from the WebRTC app) |
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## Audio pipeline notes
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- **Input**: `getUserMedia({ echoCancellation, noiseSuppression, autoGainControl })`
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feeds the `mic-capture` worklet at the `AudioContext` rate. The worklet
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resamples to 16 kHz (boxcar lowpass + decimation on the 48 -> 16 fast
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path, linear interpolation fallback for odd rates) and packs Int16 LE.
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- **Output**: `response.output_audio.delta` decodes to Int16 -> Float32
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and is posted to the `audio-playback` worklet. The worklet maintains a
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per-context ring buffer, linearly interpolates 24 -> 48, and applies
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short 32-frame fades on entry/exit to suppress clicks.
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- **Barge-in**: when the server VAD detects user speech mid-response
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(`input_audio_buffer.speech_started` while `ai-speaking`), the client
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posts `{ kind: "clear" }` to the playback worklet to wipe the queue
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immediately. The server itself cancels the in-flight response.
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## Credits
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- Backend: [huggingface/speech-to-speech](https://github.com/huggingface/speech-to-speech)
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- UI verbatim from `amir-tfrere/minimal-conversation-app-s2s-backend` (Pollen Robotics × Hugging Face)
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