server.example.yaml

# nemo-speech combined HTTP server config.
#
# Load with:
#   nemo-speech serve --config config/server.example.yaml
#
# ASR, diarization, NMT, and TTS are enabled when their required model paths
# are present. Set `enabled: false` under ASR, NMT, or TTS to force it off.
http:
  enabled: true
  host: 127.0.0.1
  port: 8080
  threads: 4
  max-upload-mb: 512
  read-timeout: 30
  write-timeout: 30
  access-log: false
  log-format: text              # text | json
  playground: true
  # api-key: use NEMO_SPEECH_HTTP_API_KEY instead of storing secrets here
  # cors-origin: https://trusted-client.example
  # tls-cert: /run/secrets/server.crt
  # tls-key: /run/secrets/server.key

asr:
  enabled: true                 # true | false | auto
  backend:
    gpu: 0                      # GPU device index, -1 = CPU
  model:
    path: /models/nemotron-speech-streaming-en-0.6b.q8_0.gguf
  streaming:
    chunk_size: 0.16
    ctc_left_padding: 1.92
    ctc_right_padding: 1.92
    rnnt_right_context: 1
  decoder:
    kind: greedy                # greedy | flashlight
  vad:
    model_path:                 # empty = no VAD loaded
    masker:
      mask_enable: false
      onset: 0.5
      offset: 0.3
  endpointing:
    enable: true
    vad_based: false
    stop_history_eou_ms: 800
  postproc:
    # pnc_model_path: /models/pnc.gguf
    # itn_model_dir: /models/sparrowhawk_en
    # profanity_list_path: /models/profanity.txt

# This model also enables word-level speaker tags on ASR responses.
diar:
  model_path: nvidia/diar_streaming_sortformer_4spk-v2
  preset: streaming             # streaming | offline (larger chunks and caches)

tts:
  enabled: true                 # true | false | auto
  magpie-model: /models/magpie-tts/magpie_tts_multilingual_357m.v2602.f16.gguf
  codec-model: /models/nano-codec/nemo_nano_codec_22khz_1.89kbps_21.5fps.decoder.f16.gguf
  tokenizer-model-dir: /models/magpie-tts/extracted
  # tn-model-dir: /models/en_tn_grammars_cased   # written-form -> spoken-form TN

  language-code: en-US
  speaker: 0

  threads: 4
  codec-threads: 0              # 0 = use threads
  seed: -1                      # -1 = current time
  steps: -1                     # -1 = model default
  top-k: -1                     # -1 = model default

  chunk-frames: 4
  codec-queue-depth: 4
  codec-history-frames: -1
  codec-future-frames: 1
  window-ms: 0
  flush-partial-chunk: true

  use-cfg: true
  use-local-transformer: true
  use-kv-cache: true
  use-stateful-codec: true
  codec-cpu: false

  lt-backend: auto              # auto | cpu | cuda
  sampling-backend: auto        # CUDA with a CUDA Magpie/LT path; otherwise CPU
  uma-mode: auto                # auto | off | on
  longform: auto                # auto | off | on

  voice-name:
  warmup-enabled: true
  warmup-text: "Hello from Magpie T T S."
  warmup-steps: 8

# NMT (text translation) is built only when -DNEMO_SPEECH_BUILD_NMT=ON. Like ASR
# and TTS it is enabled automatically when its model path is present.
nmt:
  enabled: true                 # true | false | auto
  backend:
    gpu: 0                      # GPU device index, -1 = CPU
  model:
    path: /models/riva-translate-4b-instruct-v2.q8_0.gguf   # f16 also works
    n_ctx: 1024                 # raise for longer inputs; KV cache grows with n_ctx
  generation:
    max_new_tokens: 256
  pool:
    contexts: 1                 # concurrent decode contexts