bioptimus.models.backbones

Backbone feature-extractor models (H-Optimus-1, M-Optimus, Tissue-Seg, …). Model specifications are loaded from YAML config files in the configs/ directory. The Backbone factory wires them together with a pluggable client so that a single Backbone(...) call works for any backend (HTTP, AWS, GCP, …). Example:

backbone = Backbone("h1", base_url="http://localhost:8080")
backbone = Backbone("h1", backend="aws", endpoint_name="prod")

Backbone

class Backbone(model: str = 'h1',
               backend: Backend | str = Backend.REMOTE,
               **kwargs: Any)

Factory for creating backbone endpoint models. Model identity (spec, endpoint path) is read from YAML config files. The factory pairs each config with a pluggable client backend to produce a ready-to-use EndpointModel. Usage:

>>> Backbone("h1", base_url="http://localhost:8080")
>>> Backbone("h1", backend="aws", endpoint_name="ep")
>>> Backbone("h1", backend="huggingface")
>>> Backbone.available_backbones()
['h0', 'h0-mini', 'h1', 'm-optimus', 'tissue-seg']
>>> Backbone.available_backbones(backend="huggingface")
['h0', 'h0-mini', 'h1']

Backend

class Backend(str, Enum)

Supported inference backends.

available_backbones

@classmethod
def available_backbones(cls,
                        backend: Backend | str | None = None) -> List[str]

Returns registered backbone names, optionally filtered by backend.

If given, restrict the result to models the backend can serve. Only the "huggingface" backend is restrictive — it serves the embedding backbones that declare a huggingface build recipe (h0-mini, h0, h1). The "remote", "aws" and "local" backends can serve any registered model, so they return the full list.

Returns: Sorted list of backbone names. Raises:

KeyError - If backend is not a recognised backend.

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Backbone

Backend

available_backbones

​Backbone

​Backend

​available_backbones

Backbone

Backend

available_backbones