# 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:

```bash
mlserver --help
```

## mlserver

Command-line interface to manage MLServer models.

```bash
mlserver [OPTIONS] COMMAND [ARGS]...
```

### Options

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

## build

Build a Docker image for a custom MLServer runtime.

```bash
mlserver build [OPTIONS] FOLDER
```

### Options

* `-t`, `--tag` `<text>`
* `--no-cache` (Default: `False`)

### Arguments

* `FOLDER` Required argument

## dockerfile

Generate a Dockerfile

```bash
mlserver 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.

```bash
mlserver 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

```bash
mlserver init [OPTIONS]
```

### Options

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

## start

Start serving a machine learning model with MLServer.

```bash
mlserver start [OPTIONS] FOLDER
```

### Arguments

* `FOLDER` Required argument


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