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MLServer CLI

The MLServer package includes a mlserver CLI designed to help with common tasks in a model’s lifecycle. You can see a high-level outline at any time via:

mlserver --help

root

Command-line interface to manage MLServer models.

root [OPTIONS] COMMAND [ARGS]...

Options

  • --version (Default: False) Show the version and exit.

build

Build a Docker image for a custom MLServer runtime.

root build [OPTIONS] FOLDER

Options

  • -t, --tag <text>

  • --no-cache (Default: False)

Arguments

  • FOLDER Required argument

dockerfile

Generate a Dockerfile

root dockerfile [OPTIONS] FOLDER

Options

  • -i, --include-dockerignore (Default: False)

Arguments

  • FOLDER Required argument

infer

Deprecated: This experimental feature will be removed in future work. Execute batch inference requests against V2 inference server.

Deprecated: This experimental feature will be removed in future work.

root infer [OPTIONS]

Options

  • --url, -u <text> (Default: localhost:8080; Env: MLSERVER_INFER_URL) URL of the MLServer to send inference requests to. Should not contain http or https.

  • --model-name, -m <text> (Required; Env: MLSERVER_INFER_MODEL_NAME) Name of the model to send inference requests to.

  • --input-data-path, -i <path> (Required; Env: MLSERVER_INFER_INPUT_DATA_PATH) Local path to the input file containing inference requests to be processed.

  • --output-data-path, -o <path> (Required; Env: MLSERVER_INFER_OUTPUT_DATA_PATH) Local path to the output file for the inference responses to be written to.

  • --workers, -w <integer> (Default: 10; Env: MLSERVER_INFER_WORKERS)

  • --retries, -r <integer> (Default: 3; Env: MLSERVER_INFER_RETRIES)

  • --batch-size, -s <integer> (Default: 1; Env: MLSERVER_INFER_BATCH_SIZE) Send inference requests grouped together as micro-batches.

  • --binary-data, -b (Default: False; Env: MLSERVER_INFER_BINARY_DATA) Send inference requests as binary data (not fully supported).

  • --verbose, -v (Default: False; Env: MLSERVER_INFER_VERBOSE) Verbose mode.

  • --extra-verbose, -vv (Default: False; Env: MLSERVER_INFER_EXTRA_VERBOSE) Extra verbose mode (shows detailed requests and responses).

  • --transport, -t <choice> (Options: rest | grpc; Default: rest; Env: MLSERVER_INFER_TRANSPORT) Transport type to use to send inference requests. Can be 'rest' or 'grpc' (not yet supported).

  • --request-headers, -H <text> (Env: MLSERVER_INFER_REQUEST_HEADERS) Headers to be set on each inference request send to the server. Multiple options are allowed as: -H 'Header1: Val1' -H 'Header2: Val2'. When setting up as environmental provide as 'Header1:Val1 Header2:Val2'.

  • --timeout <integer> (Default: 60; Env: MLSERVER_INFER_CONNECTION_TIMEOUT) Connection timeout to be passed to tritonclient.

  • --batch-interval <float> (Default: 0; Env: MLSERVER_INFER_BATCH_INTERVAL) Minimum time interval (in seconds) between requests made by each worker.

  • --batch-jitter <float> (Default: 0; Env: MLSERVER_INFER_BATCH_JITTER) Maximum random jitter (in seconds) added to batch interval between requests.

  • --use-ssl (Default: False; Env: MLSERVER_INFER_USE_SSL) Use SSL in communications with inference server.

  • --insecure (Default: False; Env: MLSERVER_INFER_INSECURE) Disable SSL verification in communications. Use with caution.

init

Generate a base project template

root init [OPTIONS]

Options

  • -t, --template <text> (Default: https://github.com/EthicalML/sml-security/)

start

Start serving a machine learning model with MLServer.

root start [OPTIONS] FOLDER

Arguments

  • FOLDER Required argument