gigastt-core

Core inference engine for gigastt — Russian speech recognition powered by GigaAM v3 via ONNX Runtime. No server dependencies, no tokio runtime requirement for inference — embed directly into any Rust application.

Usage

[dependencies]
gigastt-core = "2.0"

use gigastt_core::inference::Engine;
use gigastt_core::model;

// Download model on first run (~850 MB)
let model_dir = model::default_model_dir();
model::ensure_model(&model_dir, false, |p| {
    println!("Downloading: {:.0}%", p.percent());
}).await?;

// Load engine (pool_size controls concurrent sessions)
let engine = Engine::load(&model_dir, 1)?;

// Transcribe a file
let mut guard = engine.pool.checkout().await?;
let text = engine.transcribe_file("recording.wav", &mut guard)?;
println!("{text}");
// guard is returned to the pool on drop

Streaming recognition

use gigastt_core::inference::Engine;

let engine = Engine::load(&model_dir, 1)?;
let mut guard = engine.pool.checkout().await?;
let mut state = engine.create_state(&mut guard, false)?;

// Feed PCM16 chunks (16 kHz mono)
let segments = engine.process_chunk(&mut guard, &mut state, &pcm16_bytes, 16000)?;
for seg in &segments {
    println!("[partial] {}", seg.text);
}

// Flush remaining audio
let final_segments = engine.flush_state(&mut guard, &mut state)?;

Features

Features are compile-time and mutually exclusive (coreml / cuda).

What's included

• Inference engine — ONNX Runtime session pool, Conformer encoder, RNN-T decoder + joiner
• Mel spectrogram — 64 bins, FFT=320, hop=160, HTK scale
• BPE tokenizer — 1025 tokens with automatic punctuation
• Audio loading — WAV, M4A, MP3, OGG, FLAC via symphonia; resampling via rubato
• Model download — streaming from HuggingFace with SHA-256 verification + atomic rename
• INT8 quantization — native Rust quantizer, auto-detected at runtime
• Protocol types — ClientMessage, ServerMessage, TranscriptSegment for WebSocket/REST

Requirements

• Rust 1.85+ (edition 2024)
• protoc on PATH (brew install protobuf / apt install protobuf-compiler)

License

MIT