stt-streaming

Streaming speech-to-text pod for the Vocence ops fleet. Wraps NVIDIA Parakeet TDT 0.6B v3 behind a WebSocket that accepts raw 16 kHz mono PCM frames and emits interim (partial) and committed (final) transcripts in real time.

Single-GPU container (RTX 4090 / L4 / A10 / A100 class). Targets >=30 concurrent streams per 4090 with TTFP p95 <= 400 ms idle.

See stt-streaming-implementation.md for the full spec — protocol, env vars, performance targets, definition of done.

Quick start

# 1. Build
docker build -t vocence/stt-streaming:dev .

# 2. Run on a CUDA-capable GPU
docker run --rm --gpus all -p 8114:8114 \
  -e ASR_API_KEY=test_key_local_only \
  vocence/stt-streaming:dev

# 3. Smoke test
python scripts/smoke_test.py \
  --url ws://localhost:8114/v1/stream \
  --api-key test_key_local_only \
  --wav tests/fixtures/librispeech_short.wav

Expected: at least one partial, one final with the known transcript, clean close (1000).

Endpoints

Path	Purpose
GET /healthz	Liveness + readiness (status: ok / warming / degraded / error)
GET /metrics	Prometheus plaintext (asr_* counters, see spec §4.2)
WS /v1/stream	Streaming session — see spec §5 for the message protocol

All endpoints require X-API-Key: $ASR_API_KEY.

Configuration

Key env vars (full table in spec §7):

• ASR_API_KEY (required) — shared secret
• ASR_MODEL — HuggingFace model id, default nvidia/parakeet-tdt-0.6b-v3
• ASR_PORT — default 8114
• ASR_MAX_CONCURRENT — default 32

Model attribution

Parakeet TDT 0.6B v3 (c) NVIDIA, licensed CC-BY-4.0. Surfaced via /healthz model_attribution.