aix.ai_models.base

Core types for AI model management.

This module provides a unified interface for managing, discovering, and connecting to AI models across multiple providers and deployment methods.

Classes

Connector()	Abstract base for model connectors/clients.
ConnectorRegistry()	Registry for managing model connectors.
Model(id, provider[, context_size, ...])	Represents an AI model with its metadata.
ModelRegistry(*[, storage_path])	Registry for managing AI models using Mapping interface.
ModelSource()	Abstract base for model discovery sources.

class aix.ai_models.base.Connector

Bases: ABC

Abstract base for model connectors/clients.

abstractmethod format_metadata(model)

Format model metadata for this connector.

Returns a dict that can be used to instantiate/connect via this connector.

Return type:

dict[str, Any]

abstract property name: str

Unique identifier for this connector.

class aix.ai_models.base.ConnectorRegistry

Bases: MutableMapping[str, Connector]

Registry for managing model connectors.

>>> registry = ConnectorRegistry()
>>> class MyConnector(Connector):
...     @property
...     def name(self) -> str:
...         return "my_connector"
...     def format_metadata(self, model: Model) -> dict[str, Any]:
...         return {"model": model.id}
>>> connector = MyConnector()
>>> registry[connector.name] = connector
>>> "my_connector" in registry
True

class aix.ai_models.base.Model(id, provider, context_size=None, is_local=False, capabilities=<factory>, cost_per_token=<factory>, tags=<factory>, connector_metadata=<factory>, custom_metadata=<factory>)

Bases: object

Represents an AI model with its metadata.

>>> model = Model(
...     id="gpt-4",
...     provider="openai",
...     context_size=8192,
...     is_local=False
... )
>>> model.id
'gpt-4'

matches_filter(**criteria)

Check if model matches given criteria.

Return type:

bool

>>> model = Model(id="gpt-4", provider="openai", is_local=False)
>>> model.matches_filter(provider="openai")
True
>>> model.matches_filter(is_local=True)
False

to_dict()

Convert model to dictionary representation.

Return type:

dict[str, Any]

class aix.ai_models.base.ModelRegistry(*, storage_path=None)

Bases: MutableMapping[str, Model]

Registry for managing AI models using Mapping interface.

>>> registry = ModelRegistry()
>>> registry["gpt-4"] = Model(id="gpt-4", provider="openai")
>>> "gpt-4" in registry
True
>>> len(registry)
1

filter(*, provider=None, is_local=None, min_context_size=None, max_context_size=None, has_capabilities=None, tags=None, custom_filter=None)

Filter models by multiple criteria.

Return type:

list[Model]

>>> registry = ModelRegistry()
>>> registry["gpt-4"] = Model(id="gpt-4", provider="openai", context_size=8192)
>>> registry["llama2"] = Model(id="llama2", provider="ollama", is_local=True)
>>> local_models = registry.filter(is_local=True)
>>> len(local_models)
1

class aix.ai_models.base.ModelSource

Bases: ABC

Abstract base for model discovery sources.

abstractmethod discover_models()

Discover available models from this source.

Yields Model instances for each discovered model.

Return type:

Iterable[Model]