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Refactor ClearML Agent pages (#312)

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---
title: ClearML Agent Reference
---
This reference page provides detailed information about **ClearML Agent** commands, including:
* [build](#build) - Create a worker environment, without executing an experiment.
* [config](#config) - List your **ClearML Agent** configuration.
* [daemon](#daemon) - Run a worker daemon listening to a queue for Task (experiments) to execute.
* [execute](#execute) - Execute an experiment, locally without a queue.
* [list](#list) - List the current workers.
## build
Use the `build` subcommand to create a worker environment without executing the experiment.
### Syntax
```bash
clearml-agent build [-h] --id TASK_ID [--target TARGET]
[--install-globally]
[--docker [DOCKER [DOCKER ...]]] [--force-docker]
[--python-version PYTHON_VERSION]
[--entry-point {reuse_task,clone_task}] [-O]
[--git-user GIT_USER] [--git-pass GIT_PASS]
[--log-level {DEBUG,INFO,WARN,WARNING,ERROR,CRITICAL}]
[--gpus GPUS] [--cpu-only]
```
### Arguments
---
**`id`**
(*mandatory*)
* Build a worker environment for this Task ID.
---
**`cpu-only`**
* Disable GPU access for the Docker container.
---
**`docker`**
* Docker mode. A Docker container that a worker will execute at launch.
To specify the image name and optional arguments, either:
* Use `--docker <image_name> <args>` on the command line, or
* Use `--docker` on the command line, and specify the image name and arguments in the configuration file.
Environment variable settings for Dockers:
* `CLEARML_DOCKER_SKIP_GPUS_FLAG` - Ignore the `gpus` flag inside the Docker container. This also allows you to execute **ClearML Agent** using Docker versions earlier than 19.03.
* `NVIDIA_VISIBLE_DEVICES` - Limit GPU visibility for the Docker container.
* `CLEARML_AGENT_GIT_USER` and `CLEARML_AGENT_GIT_PASS` - Pass these credentials to the Docker container at execution.
To limit GPU visibility for Docker, set the `NVIDIA_VISIBLE_DEVICES` environment variable.
---
**`entry-point`**
* Used in conjunction with `--docker`, indicates how to run the Task specified by `task-id` on Docker startup.
The `entry-point` options are:
* `reuse` - Overwrite the existing Task data.
* `clone_task` - Clone the Task, and execute the cloned Task.
---
**`force-docker`**
* Force using the agent-specified docker image (either explicitly in the `--docker` argument or using the agent's
default docker image). If provided, the agent will not use any docker container information stored in the task itself
(default `False`)
---
**`git-pass`**
* Git password for repository access.
---
**`git-user`**
* Git username for repository access.
---
**`gpus`**
* Specify the active GPUs for the Docker containers to use. These are the same GPUs set in the `NVIDIA_VISIBLE_DEVICES` environment variable.
For example:
* `--gpus 0`
* `--gpu 0,1,2`
* `--gpus all`
---
**`h`, `help`**
* Get help for this command.
---
**`install-globally`**
* Install the required Python packages before creating the virtual environment. Use `agent.package_manager.system_site_packages` to control the installation of the system packages. When `--docker` is used, `install-globally` is always true.
---
**`log-level`**
* SDK log level. The values are:
* `DEBUG`
* `INFO`
* `WARN`
* `WARNING`
* `ERROR`
* `CRITICAL`
---
**`python-version`**
* Virtual environment Python version to use.
---
**`O`**
* Compile optimized pyc code (see python documentation). Repeat for more optimization.
---
**`target`**
* The target folder for the virtual environment and source code that will be used at launch.
## config
Use the `config` subcommand to list your **ClearML Agent** configuration.
### Syntax
clearml-agent config [-h]
## daemon
Use the `daemon` subcommand to run a worker, optionally in a Docker container, listening to a queue.
### Syntax
```bash
clearml-agent daemon [-h] [--foreground] [--queue QUEUES [QUEUES ...]] [--order-fairness]
[--standalone-mode] [--services-mode [SERVICES_MODE]]
[--child-report-tags CHILD_REPORT_TAGS [CHILD_REPORT_TAGS ...]]
[--create-queue] [--detached] [--stop] [--dynamic-gpus]
[--uptime [UPTIME [UPTIME ...]]] [--downtime [DOWNTIME [DOWNTIME ...]]]
[--status] [--use-owner-token] [-O]
[--git-user GIT_USER] [--git-pass GIT_PASS]
[--log-level {DEBUG,INFO,WARN,WARNING,ERROR,CRITICAL}]
[--gpus GPUS] [--cpu-only]
[--docker [DOCKER [DOCKER ...]]] [--force-current-version]
```
### Arguments
---
**`child-report-tags`**
List of tags to send with the status reports from the worker that executes a task.
---
**`cpu-only`**
* If running in Docker mode (see the `docker` option), disable GPU access for the Docker container or virtual environment.
---
**`create-queue`**
* If the queue name provided does not exist in the server, create and use it.
---
**`detached`**
* Run agent in the background. The `clearml-agent` command returns immediately.
---
**`docker`**
* Run in Docker mode. Execute the Task inside a Docker container.
To specify the image name and optional arguments, either:
* use `--docker <image_name> <args>` on the command line, or
* use `--docker` on the command line, and specify the image name and arguments in the configuration file.
Environment variable settings for Dockers:
* `CLEARML_DOCKER_SKIP_GPUS_FLAG` - Ignore the `gpus` flag inside the Docker container. This also allows you to execute **ClearML Agent** using Docker versions earlier than 19.03.
* `NVIDIA_VISIBLE_DEVICES` - Limit GPU visibility for the Docker container.
* `ClearML_AGENT_GIT_USER` and `ClearML_AGENT_GIT_PASS` - Pass these credentials to the Docker container at execution.
---
**`downtime`**
* Specify downtime for clearml-agent in `<hours> <days>` format.
For example, use `09-13 TUE` to set Tuesday's downtime to 09-13.
:::info
* This feature is available under the ClearML Enterprise plan
* Make sure to have only one of uptime / downtime configuration and not both.
:::
---
**`dynamic-gpus`**
* Allow to dynamically allocate gpus based on queue properties, configure with `--queue <queue_name>=<num_gpus>`.
For example: `--dynamic-gpus --queue dual_gpus=2 single_gpu=1`
:::info Enterprise Feature
This feature is available under the ClearML Enterprise plan
:::
---
**`force-current-version`**
* To use your current version of **ClearML Agent** when running in Docker mode (the `docker` argument is specified),
instead of the latest **ClearML Agent** version which is automatically installed, specify `force-current-version`.
For example, if your current **ClearML Agent** version is `0.13.1`, but the latest version of **ClearML Agent** is
`0.13.3`, use `--force-current-version` and your Task will execute in the Docker container with **ClearML Agent** version `0.13.1`.
---
**`foreground`**
* Pipe full log to stdout/stderr. Do not use this option if running in background.
---
**`git-pass`**
* Git password for repository access.
---
**`git-user`**
* Git username for repository access.
---
**`gpus`**
* If running in Docker mode (see the `docker` option), specify the active GPUs for the Docker containers to use.
These are the same GPUs set in the `NVIDIA_VISIBLE_DEVICES` environment variable.
For example:
* `--gpus 0`
* `--gpu 0,1,2`
* `--gpus all`
---
**`h`, `help`**
* Get help for this command.
---
**`log-level`**
* SDK log level. The values are:
* `DEBUG`
* `INFO`
* `WARN`
* `WARNING`
* `ERROR`
* `CRITICAL`
---
**`O`**
* Compile optimized pyc code (see python documentation). Repeat for more optimization.
---
**`order-fairness`**
* Pull from each queue in a round-robin order, instead of priority order.
---
**`queue`**
* Specify the queues which the worker is listening to. The values can be any combination of:
* One or more queue IDs.
* One or more queue names.
* `default` indicating the default queue.
---
**`services-mode`** <a class="tr_top_negative" name="services_mode"></a>
* Launch multiple long-term docker services. Spin multiple, simultaneous Tasks, each in its own Docker container, on the same machine. Each Task will be registered
as a new node in the system, providing tracking and transparency capabilities. Start up and shutdown of each Docker is
verified. Use in CPU mode (`--cpu-only`), only.
* To limit the number of simultaneous tasks run in services mode, pass the maximum number immediately after the
`--services-mode` option (e.g. `--services-mode 5`)
---
**`standalone-mode`**
* Do not use any network connects. This assumes all requirements are pre-installed.
---
**`status`**
* Print the worker's schedule (uptime properties, server's runtime properties and listening queues)
---
**`stop`**
* Terminate a running ClearML Agent, if other arguments are the same. If no additional arguments are provided, agents are
terminated in lexicographical order.
---
**`uptime`**
* Specify uptime for clearml-agent in `<hours> <days>` format. for example, use `17-20 TUE` to set Tuesday's
uptime to 17-20
:::info
* This feature is available under the ClearML Enterprise plan
* Make sure to have only one of uptime / downtime configuration and not both.
:::
---
**`use-owner-token`**
Generate and use the task owner's token for the execution of the task.
## execute
Use the `execute` subcommand to build and execute an experiment without a queue.
### Syntax
```bash
clearml-agent execute [-h] --id TASK_ID [--log-file LOG_FILE] [--disable-monitoring]
[--full-monitoring] [--require-queue]
[--standalone-mode] [--docker [DOCKER [DOCKER ...]]] [--clone]
[-O] [--git-user GIT_USER] [--git-pass GIT_PASS]
[--log-level {DEBUG,INFO,WARN,WARNING,ERROR,CRITICAL}]
[--gpus GPUS] [--cpu-only]
```
### Arguments
---
**`id`** (*mandatory*)
* The ID of the Task to build.
---
**`clone`**
* Clone the Task specified by `id`, and then execute that cloned Task.
---
**`cpu-only`**
* Disable GPU access for the daemon, only use CPU in either docker or virtual environment.
---
**`docker`**
* Run in Docker mode. Execute the Task inside a Docker container.
To specify the image name and optional arguments, either:
* use `--docker <image_name> <args>` on the command line, or
* use `--docker` on the command line, and specify the default image name and arguments in the configuration file.
Environment variable settings for Dockers containers:
* `ClearML_DOCKER_SKIP_GPUS_FLAG` - Ignore the `gpus` flag inside the Docker container. This also allows you to execute **ClearML Agent** using Docker versions earlier than 19.03.
* `NVIDIA_VISIBLE_DEVICES` - Limit GPU visibility for the Docker container.
* `ClearML_AGENT_GIT_USER` and `ClearML_AGENT_GIT_PASS` - Pass these credentials to the Docker container at execution.
---
**`disable-monitoring`**
* Disable logging and monitoring, except for stdout.
---
**`full-monitoring`**
* Create a full log, including the environment setup log, Task log, and monitoring, as well as stdout.
---
**`git-pass`**
* Git password for repository access.
---
**`git-user`**
* Git username for repository access.
---
**`gpus`**
* Specify active GPUs for the daemon to use (docker / virtual environment), Equivalent to setting
`NVIDIA_VISIBLE_DEVICES`. Examples: `--gpus 0` or `--gpu 0,1,2` or `--gpus all`
---
**`h`, `help`**
* Get help for this command.
---
**`log-file`**
* The log file for Task execution output (stdout / stderr) to a text file.
---
**`log-level`**
* SDK log level. The values are:
* `DEBUG`
* `INFO`
* `WARN`
* `WARNING`
* `ERROR`
* `CRITICAL`
---
**`O`**
* Compile optimized pyc code (see python documentation). Repeat for more optimization.
---
**`require-queue`**
* If the specified task is not queued (in any Queue), the execution will fail. (Used for 3rd party scheduler
integration, e.g. K8s, SLURM, etc.)
---
**`standalone-mode`**
* Do not use any network connects, assume everything is pre-installed
## list
Use the `list` subcommand to list information about all workers
### Syntax
clearml-agent list [-h]