Build Converter Strategy

Build config dataclasses and strategy helpers for modality converter construction.

KwargsBuildConfig(kwargs=dict()) dataclass

Config for building a converter using raw keyword arguments.

build(cls)

Build a converter using raw keyword arguments.

Parameters:

Name	Type	Description	Default
cls	type[BaseModalityConverter]	The converter class to build.	required

Returns:

Name	Type	Description
BaseModalityConverter	BaseModalityConverter	The built converter.

LMRPBuildConfig(lmrp_config, extra_kwargs=dict()) dataclass

Config for building a converter using an LMRP configuration.

build(cls)

Build a converter using an LMRP configuration.

Parameters:

Name	Type	Description	Default
cls	type[BaseModalityConverter]	The converter class to build.	required

Returns:

Name	Type	Description
BaseModalityConverter	BaseModalityConverter	The built converter.

PresetBuildConfig(preset, extra_kwargs=dict()) dataclass

Config for building a converter using a named preset.

build(cls)

Build a converter using a named preset.

Parameters:

Name	Type	Description	Default
cls	type[BaseModalityConverter]	The converter class to build.	required

Returns:

Name	Type	Description
BaseModalityConverter	BaseModalityConverter	The built converter.

Raises:

Type	Description
ValueError	If the class does not implement from_preset.

build_config_from_params(strategy, preset, kwargs)

Construct the typed build config for the given strategy.

Parameters:

Name	Type	Description	Default
strategy	ModalityConverterBuildStrategy	The build strategy.	required
preset	str | None	The preset name, required for PRESET strategy.	required
kwargs	dict[str, Any]	Remaining keyword arguments from the caller.	required

Returns:

Name	Type	Description
ConverterBuildConfig	ConverterBuildConfig	Config instance carrying the build logic for the strategy.

Raises:

Type	Description
ValueError	If the strategy is unsupported or required params are missing.

determine_build_strategy(preset, kwargs)

Determine the build strategy from the provided configuration.

Priority by order: 1. LMRP config -> LMRP strategy 2. Preset -> PRESET strategy 3. Fallback -> KWARGS strategy

Parameters:

Name	Type	Description	Default
preset	str | None	The preset to use.	required
kwargs	dict[str, Any]	Additional keyword arguments.	required

Returns:

Name	Type	Description
ModalityConverterBuildStrategy	ModalityConverterBuildStrategy	The determined build strategy.

determine_transcript_approach(model_id)

Determine the canonical transcription approach based on model metadata.

Parameters:

Name	Type	Description	Default
model_id	ModelId	The model ID to inspect.	required

Returns:

Name	Type	Description
ModalityConverterApproach	'ModalityConverterApproach'	Canonical approach type (lm_based, asr, or transcript_fetch).

Raises:

Type	Description
ValueError	If the approach cannot be determined for the given model ID.

Example

Determining approach from model ID

from gllm_inference.schema.model_id import ModelId

model_id = ModelId.from_string("google/gemini-1.5-pro")
approach = determine_transcript_approach(model_id)
print(approach)  # ModalityConverterApproach.LM_BASED

model_id = ModelId.from_string("prosa/v2")
approach = determine_transcript_approach(model_id)
print(approach)  # ModalityConverterApproach.ASR

determine_transcript_provider(model_id)

Determine the transcript provider implied by a model ID.

Parameters:

Name	Type	Description	Default
model_id	ModelId	The model ID to inspect.	required

Returns:

Type	Description
str | None	str | None: Provider name when inferable (e.g. whisper, gemini), otherwise None.