Configure agents

You can change the default agents configuration by mounting a config file into /opt/datalore/configs/agents-config.yaml inside the Datalore container. This config has the following format:

docker:
  network: <name-of-agents-network>
  dataloreHost: <host-of-datalore-server>
  instances:
    - <instance1-definition>
    - <instance2-definition>
      ...
    - <instanceN-definition>

By default, <name-of-agents-network> is datalore-agents-network, and <host-of-datalore-server is datalore.

Each instance definition has the following fields:

Mandatory fields
`id: basic-agent`	Specifies the unique id for the instance.
`default: true`	Specifies whether the instance is default. Make sure exactly one instance has this parameter set to `true`.
`label: "docker-base"`	Specifies the instance name shown in the UI.
`image: docker.io/jetbrains/datalore-agent:2023.3`	URI of the agent docker image, changed only to specify a custom agent image
Optional fields
`pullPolicy: "IF_ABSENT"`	Specifies when the image will be pulled. Acceptable values are: NEVER, ALWAYS, IF_ABSENT (default).
`cpus: 1.5`	Specifies how much of the available CPU resources a container can use. For example, if the host machine has two CPUs and you set `cpus` to 1.5, the container is guaranteed at most one and a half of the CPUs.
`memory: 4000000000`	Specifies the maximum amount of memory the container can use. The following suffixes are supported: M, Mi, G, Gi. Bytes are assumed when no suffix is specified.
env: - <env1-definition> - <env2-definition> ... - <envN-definition>	Defines environment variables on the agent. Each `env` definition contains a name and a value. Example: env: - name: DATALORE_SKIP_WARMUP value: true In the example, the `DATALORE_SKIP_WARMUP` environment value is set to `true` on the agent. In this case, the analysis server warmup is skipped on agent initialization, which leads to faster initialization at the cost of slower code completion for some time.
`initialPoolSize: 1`	Specifies the number of pre-warmed (pooled) agents. This is the minimum number of agents Datalore will keep started and yet unassigned to any computation. When a notebook is opened, Datalore assigns one of the pooled agents to that notebook and starts another agent to refill the pool. It might be useful to set `initialPoolSize` to a non-zero value if initialization of your agents takes a lot of time.
Options below are only used to adjust UI appearance, not to specify agent properties. To actually set limits for an agent, use the `cpus` and `memory` fields.
`shortName: "S"`	Specifies the short instance name. If it contains more than three letters, only the first three are displayed.
`numCPUs: 2`	Specifies the number of CPUs to display.
`cpuMemoryText: "8 GB"`	Specifies the agent RAM description.
`numGPUs: 1`	Specifies the number of GPUs to display.
`gpuMemoryText: "4 GB"`	Specifies the GPU memory description.
features: - "1 vCPU" - "16 GB RAM" - "1 NVIDIA GPU"	Specifies specific properties of this agent to display in the UI. Only properties containing the "RAM", "CPU", or "GPU"* substrings will be displayed in the agent selection window.*

Last modified: 08 June 2023