Add ssm_configs: model config schemas, registries, and a plugin system

[digicosmos86]

What ssm_configs is for

A small, separate package for describing models, split out from the code that runs them. A model config is just data — the model's name, its parameters and their allowed ranges, what the responses look like — so it doesn't need the simulators, NumPy, or a C compiler to be read. Keeping it standalone means HSSM and other tools can depend on the descriptions alone, and new models can be added without touching ssm-simulators.

Schemas and registries

• Schemas say what a valid config looks like. BaseConfigSchema holds what every model has (name, description, response columns, choices, parameter bounds); HSSMConfigSchema and RLSSMConfigSchema build on it for their model families. Configs are stored as JSON and checked against the schema when loaded, so a malformed config fails immediately with a clear message instead of much later.
• Registries are the lookup tables. There's one per model family — hssm_registry and rlssm_registry — and each knows two kinds of model: built-in ones shipped with the package, and external ones contributed by other packages. You ask a registry whether it knows a model (is_supported) and to load it (load_config), and it doesn't matter which kind it is. Each registry is a single shared instance, so everything in a program sees the same set of models.

The plugin system

Anyone can add a model by publishing a package — no changes to this repo:

• Name the package after the registry it belongs to plus the model name: hssm-my-cool-model adds my_cool_model to the HSSM registry.
• Declare one entry point and one small function returning the path to your JSON config. That's the whole contract.
• Installing the package is enough. Nobody has to import it — ssm_configs finds it on its own.
• The scan happens the first time a registry is actually used, not when the package is imported, so it costs nothing if you never look up a model.
• A broken plugin is skipped with a warning naming the package, and everything else keeps working. A plugin can't take over the name of a built-in model.

The example package

hssm_example_model/ at the repo root is a complete working plugin and the thing to copy when writing one. It's a real, self-contained package — its own pyproject.toml, depending only on ssm-configs — with four files: the config JSON, a fifteen-line module with the hook function, the pyproject.toml declaring the entry point, and a README. To adapt it: rename the package, drop in your own JSON, done. It's installed in this repo's dev environment, so the tests check the plugin path against a genuinely installed package rather than a stand-in.

Workspace change

• The repo is now a uv workspace: ssm-simulators at the root with ssm_configs and hssm_example_model as members. One shared environment and one uv sync for all three, while each stays a separately publishable package.
• ssm_configs is installed through the dev group, not as a runtime dependency, while it's still settling. The old config extra is gone.
• uv.lock is no longer tracked, since the workspace regenerates it.

Tests and CI

• 15 tests in ssm_configs/tests/ covering both ways a plugin gets registered, routing to the right registry, the lazy scan, and every failure case.
• The subpackage keeps its tests next to its code, so the root test run doesn't collect them — CI runs them in a step of their own across Python 3.12/3.13/3.14.
• Clean under ruff, mypy, ty, and pyrefly.

🤖 Generated with Claude Code

https://claude.ai/code/session_01MNAryd7vmPQvf8KD59p5PA

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[digicosmos86]

@krishnbera I started with a barebones implementation of ssm_configs (package name pending). This PR demonstrates how the registry system works and how to extend the system with plugins. It also touches a bit upon how Pydantic should validate JSONs. Definitely open to suggestions

@AlexanderFengler @cpaniaguam for awareness. Feel free to chime in too