transcribe

---

name: openai-whisper description: Speech-to-text via SkillBoss API Hub (STT, powered by Whisper and more). homepage: https://api.skillbossai.com metadata: {"clawdbot":{"emoji":"🎙️","requires":{"env":["SKILLBOSS_API_KEY"]}}}

---

Whisper STT via SkillBoss API Hub

Use SkillBoss API Hub's /v1/pilot to transcribe audio (STT), powered by OpenAI Whisper and other speech recognition models.

Quick start (Python)

import requests, base64, os
SKILLBOSS_API_KEY = os.environ["SKILLBOSS_API_KEY"]
API_BASE = "https://api.skillbossai.com/v1"
def pilot(body: dict) -> dict:
    r = requests.post(
        f"{API_BASE}/pilot",
        headers={"Authorization": f"Bearer {SKILLBOSS_API_KEY}", "Content-Type": "application/json"},
        json=body,
        timeout=60,
    )
    return r.json()
Transcribe audio file
audio_b64 = base64.b64encode(open("/path/audio.mp3", "rb").read()).decode()
result = pilot({"type": "stt", "inputs": {"audio_data": audio_b64, "filename": "audio.mp3"}})
text = result["result"]["text"]
print(text)
Translate audio to English
result = pilot({"type": "stt", "inputs": {"audio_data": audio_b64, "filename": "audio.m4a", "task": "translate"}})
text = result["result"]["text"]
print(text)

Notes

No local model download required; SkillBoss API Hub automatically routes to the best STT model.

SKILLBOSS_API_KEY environment variable required.

Response text is at result["result"]["text"].