Pulse (Pre-Recorded)

Transcribe an audio file to text using the Pulse model. The fastest way to get a transcript when you already have a recording — pass either the raw bytes or a URL. ## When to use this Use this endpoint when you have a complete audio file (call recording, voicemail, podcast episode) and want the transcript back in one response. For live transcription as audio arrives, use the realtime WebSocket endpoint (`WSS /waves/v1/pulse/get_text`) instead. ## Input methods Send the audio in one of two ways: 1. **Raw bytes** — `Content-Type: application/octet-stream` with the audio in the body. All knobs (`language`, `word_timestamps`, etc.) are query parameters. 2. **URL** — `Content-Type: application/json` with `{"url": "..."}` in the body. Useful when the audio already lives in object storage. Same query parameters apply. Pulse autodetects the language across 30+ supported locales. Pass `language` explicitly when you already know it — detection is fast but skipping it is faster. ## Examples **cURL** (raw bytes) ```bash curl -X POST "https://api.smallest.ai/waves/v1/pulse/get_text?language=en&word_timestamps=true" \ -H "Authorization: Bearer $SMALLEST_API_KEY" \ -H "Content-Type: application/octet-stream" \ --data-binary "@./call.wav" ``` **cURL** (URL) ```bash curl -X POST "https://api.smallest.ai/waves/v1/pulse/get_text?language=en" \ -H "Authorization: Bearer $SMALLEST_API_KEY" \ -H "Content-Type: application/json" \ -d '{"url": "https://your-bucket.s3.amazonaws.com/call.wav"}' ``` **Python** (`pip install smallestai>=4.4.0`) ```python from smallestai import SmallestAI client = SmallestAI(token="YOUR_API_KEY") with open("./call.wav", "rb") as f: result = client.waves.transcribe_pulse( request=f.read(), language="en", word_timestamps=True, diarize=True, ) print(result.status) # "success" print(result.transcription) # the transcript string ``` **JavaScript / TypeScript** (using `fetch`) ```typescript import { readFileSync } from "node:fs"; const audio = readFileSync("./call.wav"); const params = new URLSearchParams({ language: "en", word_timestamps: "true", diarize: "true" }); const res = await fetch(`https://api.smallest.ai/waves/v1/pulse/get_text?${params}`, { method: "POST", headers: { Authorization: `Bearer ${process.env.SMALLEST_API_KEY}`, "Content-Type": "application/octet-stream", }, body: audio, }); const result = await res.json(); console.log(result.transcription); ``` ## Common gotchas - **Max file size is 25 MB.** Larger files return HTTP `413`. Compress to mono 16 kHz PCM if you're close to the limit; quality is unaffected. - **Formatting flags (`format`, `punctuate`, `capitalize`)** are accepted at the wire level and exposed in the Python SDK as of `smallestai>=4.4.0`. Today they currently return the same transcript regardless of value — pass them in your integration so it works as the behavior changes. - **Webhook-driven flow**: pass `webhook_url` to receive the transcript asynchronously. The endpoint returns immediately; the transcript hits your webhook when ready. Useful for long files where you don't want to hold an HTTP connection open. - **Speaker diarization** (`diarize=true`) adds latency. Skip it if you only need the words. - **JavaScript / TypeScript**: the official `smallestai` npm package predates the Pulse model, so call this endpoint with `fetch` or `axios` as shown above.