oruk — Python client for the oruk Speech API

Official Python SDK for oruk, the speech lab building audio models for English transcription, calibrated multilabel emotion detection, speaking-style classification, and unified audio analysis.

This SDK calls the file API: send a prerecorded English audio file (WAV, FLAC, MP3, M4A, OGG, or WebM; up to 30 MB / 60 minutes), get structured results back. Resonance is oruk’s flagship speech recognition model. Plans include audio minutes, measured by the second with a one-second minimum. The separate Realtime preview supports 32 locales and phrase-level emotion scores over WebSocket; see the realtime reference.

Install

python -m pip install https://oruk.ai/sdk/oruk-0.2.5-py3-none-any.whl

Quickstart

Create an account at oruk.ai (plans from $5/month, 7-day standard self-serve trial, card required, $0 today) and create an API key in the developer portal.

import os
from oruk import Oruk

with Oruk(api_key=os.environ["ORUK_API_KEY"]) as client:
    result = client.analyze("sample.wav", model="oruk-resonance")

print(result["text"])       # English transcript
print(result["emotions"])   # calibrated multilabel emotion scores
print(result["styles"])     # calibrated multilabel speaking-style scores

Endpoints

Every method accepts a path, Path, or binary file object, plus optional model= (oruk-resonance, oruk-fourier) and request_id= arguments. With model="oruk-resonance", pass diarize=True (and optionally num_speakers=) to label speakers: diarization locates the speaker turns, then Resonance scores each speaker turn, so every segment carries a speaker field with its own text, emotions, and styles. Diarization is included in plan minutes.

result = client.analyze("support-call.wav", model="oruk-resonance", diarize=True)
for seg in result["segments"]:
    print(seg["speaker"], seg["text"], seg["emotions"][0]["label"])

Emotion only: client.emotions(...) on Resonance runs the encoder and affect head and never invokes the transcription decoder, so nothing is transcribed, the result has no transcript. One audio minute uses one plan minute for either emotion-only or unified analysis; calling both separately processes the audio twice.

result = client.emotions("support-call.wav", model="oruk-resonance")
print(result["emotions"][0])            # {'label': 'happy', 'score': 0.97}
print(result.get("text"))               # None: no transcript is produced

The client sends a unique request ID per call and retries only 429 and transient 5xx responses with jittered backoff. Errors raise OrukAPIError with status, code, and request_id attributes.

Links

• Documentation and API reference: https://oruk.ai/docs
• Capabilities and scope: https://oruk.ai/capabilities
• Pricing: https://oruk.ai/pricing
• Benchmarks: https://oruk.ai/benchmarks/methodology
• Service status: https://oruk.ai/status

License

MIT