The Python Component System (PCS) is an API and CLI for building, running, and sharing Python code. AgentOS is a set of libraries built on top of PCS that make it easy to build, run, and share agents that use Reinforcement Learning.
# Start the local web server in a separate tab
# Clear the local DB by visiting http://localhost:8000/empty_database in your browser
cd example_agents/sb3_agent
rm -rf mlruns/
agentos run sb3_agent --function-name learn
agentos run sb3_agent --function-name evaluate
USE_LOCAL_SERVER=True agentos publish <agent run ID printed out after previous previous command>
# Now visit http://localhost:8000 and see the result of your run
Next on my list is to port, next up are the tests:
The run details page (currently the links just go to the API endpoint)
This ports the run overview page (http://localhost:8000/runs) to the new models.
Here's the demo script to populate the DB again:
Next on my list is to port, next up are the tests:
The run details page (currently the links just go to the API endpoint)The run overview page (http://localhost:8000/runs)