WhisperBridge is the speech-to-text entry point in Llamatik. The library currently exposes a WAV-based transcription API.

Initialize the model#

val modelPath = WhisperBridge.getModelPath("ggml-base.en.bin")
val ok = WhisperBridge.initModel(modelPath)
check(ok)

Transcribe a file#

val text = WhisperBridge.transcribeWav(
    wavPath = "/path/to/audio.wav",
    language = "en"
)
println(text)

Language hint#

The language parameter is optional, but supplying it can improve reliability when you already know the input language.

Recommended workflow#

1. record or obtain audio
2. convert it to WAV if needed
3. initialize the model once
4. call transcribeWav(...) for each file
5. release the model when done

Cleanup#

WhisperBridge.release()

Practical notes#

• For best results, keep input audio clear and reasonably clean.
• Reuse the initialized model if you transcribe multiple files.
• WASM support is currently not available for WhisperBridge.