Use when the user runs /add-dictation or wants speech turned into text with Grok speech-to-text: a mic button that dictates into the composer, live captions, or transcribing recorded audio (files, uploads, URLs) with word timestamps, diarization, subtitles, meeting notes. STT, transcribe, transcription. For a voice agent that talks back use /add-voice.
Add Grok Speech to Text to an existing app: a mic button that dictates into the composer, live captions, or transcripts of recorded audio. Run on /add-dictation, typed Dictate, or clear “transcribe” intent. Cursor has no mic; wire the app, not the IDE.
Before any STT call, read the model-selection section and pass the latest listed model as model. Do not invent ids or reuse a stale one from this skill. REST: form field before file. Streaming: query param. Official examples currently send grok-voice-transcribe-2.0. Listed today: grok-voice-transcribe-2.0 (best), grok-voice-transcribe-1.0 (original; API default when model is omitted).
| Need | Path |
|---|---|
| Tap, speak, tap, text appears. Uploaded files. URLs. | Batch POST https://api.x.ai/v1/stt (default) |
| Text appears while speaking: captions, long dictation, push-to-talk | Streaming wss://api.x.ai/v1/stt through a backend relay |
Batch is the default for a composer mic button: one request, no socket, the key never leaves the server. Go streaming only when the UX needs interim text.
XAI_API_KEY, server side only. The STT docs document no ephemeral-token flow, and browsers cannot set WebSocket headers, so browser streaming goes through your backend relay. Do not invent a token flow.Map the app
/add-voice is installed, its waveform primary button stays as is; add the mic as a secondary ghost button beside it./add-voice ran, its PCM capture can feed streaming STT; pass its rate as sample_rate. 16 kHz is the model’s native rate; other supported rates (8000, 16000, 22050, 24000, 44100, 48000) are resampled server side.Batch path (default)
MediaRecorder → Blob → POST to your own route. The endpoint auto-detects containers (WAV, MP3, OGG, Opus, FLAC, AAC, MP4, M4A, MKV, WebM), so send whatever MediaRecorder produces.multipart/form-data. Option fields first, file last; fields after file may be ignored. file or url, max 500 MB. model from docs (latest listed).// server (any runtime with fetch + FormData)
export async function transcribe(blob: Blob, filename: string) {
const form = new FormData();
form.append("model", "grok-voice-transcribe-2.0"); // latest from docs; re-read model-selection
form.append("format", "true"); // written-form numbers/currency; requires language
form.append("language", "en");
// form.append("keyterm", "Acme"); // repeat per term, ≤100 terms × 50 chars
form.append("file", blob, filename); // last
const res = await fetch("https://api.x.ai/v1/stt", {
method: "POST",
headers: { Authorization: `Bearer ${process.env.XAI_API_KEY}` },
body: form,
});
if (!res.ok) throw new Error(`STT ${res.status}`); // 400 bad input, 413 >500 MB, 429 back off, 502 url fetch failed, 503 retry
return (await res.json()) as {
text: string; language: string; duration: number;
words?: { text: string; start: number; end: number; speaker?: number }[];
channels?: { index: number; text: string; words: unknown[] }[];
};
}// client
const mime = MediaRecorder.isTypeSupported("audio/webm;codecs=opus") ? "audio/webm;codecs=opus" : "audio/mp4";
const rec = new MediaRecorder(stream, { mimeType: mime });
const parts: BlobPart[] = [];
rec.ondataavailable = (e) => parts.push(e.data);
rec.onstop = async () => {
const fd = new FormData();
fd.append("file", new Blob(parts, { type: mime }), "dictation");
const { text } = await (await fetch("/api/dictation", { method: "POST", body: fd })).json();
insertAtCursor(text);
};
rec.start(); // second tap: rec.stop()model from docs (latest listed).import { WebSocketServer, WebSocket } from "ws";
new WebSocketServer({ port: 8788 }).on("connection", (client) => {
const q = new URLSearchParams({ model: "grok-voice-transcribe-2.0", sample_rate: "16000", encoding: "pcm", interim_results: "true", language: "en" });
const up = new WebSocket(`wss://api.x.ai/v1/stt?${q}`, { headers: { Authorization: `Bearer ${process.env.XAI_API_KEY}` } });
up.on("message", (d) => client.send(d.toString())); // transcript.* and error events
client.on("message", (d, isBinary) => up.readyState === WebSocket.OPEN && up.send(d, { binary: isBinary })); // audio + finalize/audio.done
const end = () => { client.close(); up.close(); };
up.on("close", end); up.on("error", end); client.on("close", end);
});transcript.created before sending. MediaRecorder output is a container, not raw frames; do not stream it.const ws = new WebSocket(relayUrl); ws.binaryType = "arraybuffer";
const ctx = new AudioContext({ sampleRate: 16000 }); // if ctx.sampleRate !== 16000, downsample in the worklet
await ctx.audioWorklet.addModule("/pcm16-worklet.js"); // Float32 → Int16LE, posts one 3,200-byte frame per 100 ms
const node = new AudioWorkletNode(ctx, "pcm16");
ctx.createMediaStreamSource(stream).connect(node);
let ready = false;
node.port.onmessage = (e) => ready && ws.readyState === WebSocket.OPEN && ws.send(e.data);
let committed = "", locked = "", live = "";
ws.addEventListener("message", (e) => {
const ev = JSON.parse(e.data);
if (ev.type === "transcript.created") ready = true;
else if (ev.type === "transcript.partial") {
if (ev.speech_final) { committed += ev.text + " "; locked = ""; live = ""; } // complete stitched utterance
else if (ev.is_final) { locked += ev.text + " "; live = ""; } // chunk final: text will not change
else live = ev.text; // interim: may change
render(committed + locked + live);
} else if (ev.type === "transcript.done") ws.close(); // after audio.done
else if (ev.type === "error") showError(ev.message); // most errors close the socket
});
// stop: ws.send(JSON.stringify({ type: "audio.done" }))
// push-to-talk release: ws.send(JSON.stringify({ type: "Finalize" })) then keep streaming (docs show both `finalize` and `Finalize`; the examples use `Finalize`)| Want | Set |
|---|---|
| Latest STT | Read docs #model-selection, pass that model. Snapshot: grok-voice-transcribe-2.0. Omit → grok-voice-transcribe-1.0. Batch: form field. Streaming: query param. |
| Text while speaking | interim_results=true |
“one hundred dollars” → $100 | streaming: language=en; batch: format=true + language=en |
| Product names, jargon | keyterm= repeated |
| Not cut off mid-sentence while dictating numbers | smart_turn=0.7&smart_turn_timeout=3000 |
| Faster or slower end of utterance | endpointing= ms, default 400 |
| Who said what (meetings) | diarize=true → words[].speaker |
| Agent and customer on separate channels | multichannel=true&channels=2 (PCM only, not Opus) |
| Keep “um”, “uh” | filler_words=true (removed by default) |
| Low bandwidth or mobile | encoding=opus, exactly one raw Opus packet per frame, omit sample_rate |
| Raw audio to batch | `audio_format=pcm |
| Quiet or telephony audio | lower vad_threshold (streaming default 0.08, batch 0.5) |
import os, requests
r = requests.post(
"https://api.x.ai/v1/stt",
headers={"Authorization": f"Bearer {os.environ['XAI_API_KEY']}"},
data=[("model", "grok-voice-transcribe-2.0"), ("format", "true"), ("language", "en")],
files={"file": ("dictation.webm", blob, "audio/webm")}, # requests sends data fields before files
)
r.raise_for_status(); text = r.json()["text"]
# streaming: websockets.connect(url, additional_headers={"Authorization": f"Bearer {key}"}); await ws.send(pcm_bytes)model from docs (currently grok-voice-transcribe-2.0): curl -X POST https://api.x.ai/v1/stt -H "Authorization: Bearer $XAI_API_KEY" -F model=grok-voice-transcribe-2.0 -F language=en -F file=@short.wav → 200 with text. Same call with -F format=true and no language → 400.speech_final text did not include the chunk finals: append instead of replacing locked). audio.done → transcript.done, socket closes.XAI_API_KEY; it must not be there./debug-voice; swap its hook points to transcript.* events./add-voice), speaking text (/add-read-aloud)c47b128
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