Skip to content

User Guide

Run PlugRL end to end: start a server, then start one or more env clients.

Quickstart

plugrl-run-server fpo-policy default fpo default \
    --policy.device cpu --algo.global-steps 500000 --algo.buffer-size 4096
plugrl-run-env-client mujoco-v1 --server-host 127.0.0.1 --server-port 8000 \
    --num-envs 1 --num-episodes 600 --runner.replan-steps 1 --runner.seed 0

That pair learns. Get Started explains the two flags that are not optional, and has the dummy connectivity check.

Verify

  • Server prints a WebSocket listening address.
  • Env client prints server metadata and steps episodes.

Workflow

  1. Start a training server with plugrl-run-server. (There is also plugrl-run-server-ray, but it is not a supported path today - see Get Started.)
  2. Start one or more env clients with plugrl-run-env-client <env_id>.

Components

  • plugrl-server: batches inference across connected workers, runs learning and checkpointing
  • plugrl-env-client: creates Gymnasium envs, sends infer, receives action, sends feedback
  • plugrl-protocol: WebSocket transport, message types, and msgpack serialization

Common options

  • Server default address is 0.0.0.0:8000.
  • Env client connects via --server-host and --server-port.

Troubleshooting

  • Env client keeps retrying: confirm the server is listening and the address is reachable.
  • Policy or algorithm not found in CLI: ensure the registration module is imported before the CLI is built.

Next steps