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File size: 2,611 Bytes
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title: ScriptFlow Hausa Inference
emoji: 🎬
colorFrom: indigo
colorTo: purple
sdk: gradio
sdk_version: 6.24.0
python_version: '3.12'
app_file: app.py
pinned: false
license: other
short_description: Hausa ASR + MT for ScriptFlow
---
# ScriptFlow inference service
Hausa ASR + Hausa→English MT, served over HTTP so the Render backend does not
have to hold ~2GB of model weights in a 512MB process.
- **ASR** — [`NCAIR1/Hausa-ASR`](https://huggingface.co/NCAIR1/Hausa-ASR) (Whisper-small fine-tune)
- **MT** — [`Helsinki-NLP/opus-mt-ha-en`](https://huggingface.co/Helsinki-NLP/opus-mt-ha-en)
## Deploying
1. Create a Space: **New Space → Gradio → Blank**, hardware **CPU basic (free)**.
Gradio rather than Docker because Docker Spaces need PRO. It costs nothing
here: Gradio is FastAPI underneath, so `/asr` and `/translate` sit at the
root exactly as they would have, with a status UI at `/ui`. `Dockerfile` is
kept for anyone who does have PRO — switch `sdk:` back to `docker` to use it.
2. Push the contents of this directory to it. `packages.txt` installs ffmpeg.
3. On the model page for `NCAIR1/Hausa-ASR`, **accept the licence** — the model
is gated (`gated: auto`), and without acceptance the download 403s.
4. In **Space → Settings → Secrets**, set:
- `HF_TOKEN` — a read token from the account that accepted the licence
- `SERVICE_TOKEN` — any random string; the backend must send the same value
Gradio serves its status page at `/`. The first request downloads weights and can take several minutes. `GET /`
answers immediately throughout and reports load state, so you can watch it come
up without holding a request open.
## API
`POST /asr` — raw audio bytes as the body, `X-Service-Token` header.
```json
{
"text": "...",
"duration": 41.2,
"wordLevel": true,
"words": [{"word": "sannu", "start": 0.4, "end": 0.9, "speaker": null}]
}
```
Times are relative to the audio posted; the backend adds each chunk's offset.
`end` may be `null` — that is meaningful, and the backend infers a real end from
the following word rather than inventing a duration here.
`POST /translate` — `{"texts": [...]}`, returns `{"translations": [...]}` with
one entry per input, same order.
## Notes
- Free Spaces sleep after inactivity; the first call after a sleep pays the
cold start again.
- CPU inference on Whisper-small runs roughly 1–3× realtime, so a 20-minute
chunk is minutes of compute, not seconds.
- `NCAIR1/Hausa-ASR` is licensed with a 1000 active end-user cap for
non-commercial use. Check that against how ScriptFlow ships.
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