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.
Currently, running a example agent using the included registry file (components.yaml) creates a Run of a Component with a LocalRepo, which can't be "published" (i.e., added to a WebRegistry) because it doesn't provide reproducibility. Specifically, the WebRegistry.add_repo_spec() requires the spec that is passed in to have a url attribute.
Component.to_frozen_registry() handles this for the case of a component that has a dependency on a local repo, so we should be able to use this or extend it as necessary in a demo.
Currently, running a example agent using the included registry file (
components.yaml) creates a Run of a Component with a LocalRepo, which can't be "published" (i.e., added to a WebRegistry) because it doesn't provide reproducibility. Specifically, theWebRegistry.add_repo_spec()requires the spec that is passed in to have aurlattribute.Component.to_frozen_registry()handles this for the case of a component that has a dependency on a local repo, so we should be able to use this or extend it as necessary in a demo.