mirror of
https://github.com/hanzoai/speech.git
synced 2026-10-04 07:37:19 +00:00
zeekayandHanzo Dev
6f516b97e5
Two values were computed here and thrown away, and both were the answer to a
question the caller had to ask.
DURATION. `segments, _ = load(model).transcribe(...)` discarded faster-whisper's
info, which carries the audio's duration. Transcription is billed per MINUTE by
everyone who sells it, so a response without a duration cannot be billed at all
— the ai plane metered every transcription at zero seconds no matter how much
audio was sent. transcribe returns it now, and verbose_json carries it exactly
as OpenAI's does (plain json stays {"text"}, so a client reading the standard
shape is untouched). It is `duration`, the audio SUBMITTED, never
`duration_after_vad`: a caller is charged for what they asked us to listen to,
not for how much of it turned out to be talking.
CONTAINER. `if response_format == "wav" ... else mp3` answered opus, aac, flac
and pcm with an MP3. The gateway then labelled the response from the REQUEST, so
a caller asking for opus received `Content-Type: audio/opus` wrapping an MP3 —
the API lying to whatever had to play it. ffmpeg in this image has libopus,
libmp3lame, aac, flac and pcm_s16le with the matching muxers, verified against
`ffmpeg -encoders` in the running pod, so every OpenAI format is really encoded
and anything else is a 400 that names what IS available. Substitution is gone,
not relabelled.
A suite arrives with them, and gates the build before the registry login so a
red run cannot publish. It stubs the two model calls, needing no weights and no
GPU, and answers in seconds.
The mutation that matters: stubbing `stt.transcribe` to test the ROUTE let the
duration fix be reverted with the suite still green. The tests that catch it
stub the MODEL and exercise the real function — testing the seam you fixed, not
the one above it.
Co-authored-by: Hanzo Dev <[email protected]>
speech
CPU speech for the Hanzo platform: STT (faster-whisper, CTranslate2 int8) and TTS (kokoro-onnx, 82M) behind one OpenAI-shaped surface.
Routes
POST /v1/audio/transcriptions— multipartfile+model(+language,response_format) →{"text": …}POST /v1/audio/speech—{model, input, voice, response_format}→ audio bytes (mp3 default, wav native)GET /v1/models,GET /healthz
Trust model
No auth of its own, in-cluster only. api.hanzo.ai fronts it through the ai
plane, which authenticates and meters every caller — a provider row pointing at
http://speech.hanzo.svc/v1 is the whole integration. Weights bake into the
image at build; the container boots without the network.
Run
uv sync && uv run uvicorn main:app --port 8000
Phase 2 is /v1/realtime: websocket full-duplex (silero-vad segmentation,
partial transcripts, kokoro frames, barge-in) plus camera-frame relay into the
multimodal models.