nat.builder.child_builder

Classes

ChildBuilder

Helper class that provides a standard way to create an ABC using

Module Contents

class ChildBuilder(workflow_builder: nat.builder.builder.Builder)

Bases: nat.builder.builder.Builder

Helper class that provides a standard way to create an ABC using inheritance.

_workflow_builder

_dependencies

property sync_builder: nat.builder.sync_builder.SyncBuilder

Get the synchronous version of the builder.

Returns:

The SyncBuilder object (synchronous wrapper).

property dependencies: nat.data_models.function_dependencies.FunctionDependencies

async add_function(

name: str,

config: nat.data_models.function.FunctionBaseConfig,

) → nat.builder.function.Function

Add a function to the builder.

Args:

name: The name or reference for the function config: The configuration for the function

Returns:

The built function instance

async add_function_group(

name: str,

config: nat.data_models.function.FunctionGroupBaseConfig,

) → nat.builder.function.FunctionGroup

Add a function group to the builder.

Args:

name: The name or reference for the function group config: The configuration for the function group

Returns:

The built function group instance

async get_function(name: str) → nat.builder.function.Function

Get a function by name.

Args:

name: The name or reference of the function

Returns:

The built function instance

async get_function_group(name: str) → nat.builder.function.FunctionGroup

Get a function group by name.

Args:

name: The name or reference of the function group

Returns:

The built function group instance

get_function_config(

name: str,

) → nat.data_models.function.FunctionBaseConfig

Get the configuration for a function.

Args:

name: The name or reference of the function

Returns:

The configuration for the function

get_function_group_config(

name: str,

) → nat.data_models.function.FunctionGroupBaseConfig

Get the configuration for a function group.

Args:

name: The name or reference of the function group

Returns:

The configuration for the function group

async set_workflow(

config: nat.data_models.function.FunctionBaseConfig,

) → nat.builder.function.Function

Set the workflow function.

Args:

config: The configuration for the workflow function

Returns:

The built workflow function instance

get_workflow() → nat.builder.function.Function

Get the workflow function.

Returns:

The workflow function instance

get_workflow_config() → nat.data_models.function.FunctionBaseConfig

Get the configuration for the workflow.

Returns:

The configuration for the workflow function

async get_tools(

tool_names: collections.abc.Sequence[str | nat.data_models.component_ref.FunctionRef | nat.data_models.component_ref.FunctionGroupRef],

wrapper_type: nat.builder.framework_enum.LLMFrameworkEnum | str,

) → list[Any]

Get multiple tools by name wrapped in the specified framework type.

Args:

tool_names: The names or references of the tools (functions or function groups) wrapper_type: The LLM framework type to wrap the tools in

Returns:

List of tools wrapped in the specified framework type

async get_tool(

fn_name: str | nat.data_models.component_ref.FunctionRef,

wrapper_type: nat.builder.framework_enum.LLMFrameworkEnum | str,

)

Get a tool by name wrapped in the specified framework type.

Args:

fn_name: The name or reference of the tool (function) wrapper_type: The LLM framework type to wrap the tool in

Returns:

The tool wrapped in the specified framework type

async add_llm(name: str, config: nat.data_models.llm.LLMBaseConfig) → None

Add an LLM to the builder.

Args:

name: The name or reference for the LLM config: The configuration for the LLM

Returns:

The built LLM instance

async add_auth_provider(

name: str,

config: nat.data_models.authentication.AuthProviderBaseConfig,

) → nat.authentication.interfaces.AuthProviderBase

Add an authentication provider to the builder.

Args:

name: The name or reference for the authentication provider config: The configuration for the authentication provider

Returns:

The built authentication provider instance

async get_auth_provider(auth_provider_name: str)

Get an authentication provider by name.

Args:

auth_provider_name: The name or reference of the authentication provider

Returns:

The authentication provider instance

async get_llm(

llm_name: str,

wrapper_type: nat.builder.framework_enum.LLMFrameworkEnum | str,

) → Any

Get an LLM by name wrapped in the specified framework type.

Args:

llm_name: The name or reference of the LLM wrapper_type: The LLM framework type to wrap the LLM in

Returns:

The LLM wrapped in the specified framework type

get_llm_config(llm_name: str) → nat.data_models.llm.LLMBaseConfig

Get the configuration for an LLM.

Args:

llm_name: The name or reference of the LLM

Returns:

The configuration for the LLM

async add_embedder(

name: str,

config: nat.data_models.embedder.EmbedderBaseConfig,

) → None

Add an embedder to the builder.

Args:

name: The name or reference for the embedder config: The configuration for the embedder

async get_embedder(

embedder_name: str,

wrapper_type: nat.builder.framework_enum.LLMFrameworkEnum | str,

) → Any

Get an embedder by name wrapped in the specified framework type.

Args:

embedder_name: The name or reference of the embedder wrapper_type: The LLM framework type to wrap the embedder in

Returns:

The embedder wrapped in the specified framework type

get_embedder_config(

embedder_name: str,

) → nat.data_models.embedder.EmbedderBaseConfig

Get the configuration for an embedder.

Args:

embedder_name: The name or reference of the embedder

Returns:

The configuration for the embedder

async add_memory_client(

name: str,

config: nat.data_models.memory.MemoryBaseConfig,

) → nat.memory.interfaces.MemoryEditor

Add a memory client to the builder.

Args:

name: The name or reference for the memory client config: The configuration for the memory client

Returns:

The built memory client instance

async get_memory_client(

memory_name: str,

) → nat.memory.interfaces.MemoryEditor

Return the instantiated memory client for the given name.

get_memory_client_config(

memory_name: str,

) → nat.data_models.memory.MemoryBaseConfig

Get the configuration for a memory client.

Args:

memory_name: The name or reference of the memory client

Returns:

The configuration for the memory client

async add_object_store(

name: str,

config: nat.data_models.object_store.ObjectStoreBaseConfig,

)

Add an object store to the builder.

Args:

name: The name or reference for the object store config: The configuration for the object store

Returns:

The built object store instance

async get_object_store_client(

object_store_name: str,

) → nat.object_store.interfaces.ObjectStore

Return the instantiated object store client for the given name.

get_object_store_config(

object_store_name: str,

) → nat.data_models.object_store.ObjectStoreBaseConfig

Get the configuration for an object store.

Args:

object_store_name: The name or reference of the object store

Returns:

The configuration for the object store

async add_trainer(

name: str | nat.data_models.component_ref.TrainerRef,

config: nat.data_models.finetuning.TrainerConfig,

) → nat.finetuning.interfaces.finetuning_runner.Trainer

Add a trainer to the builder.

Args:

name: The name or reference for the trainer config: The configuration for the trainer

Returns:

The built trainer instance

async add_trainer_adapter(

name: str | nat.data_models.component_ref.TrainerAdapterRef,

config: nat.data_models.finetuning.TrainerAdapterConfig,

) → nat.finetuning.interfaces.trainer_adapter.TrainerAdapter

Add a trainer adapter to the builder.

Args:

name: The name or reference for the trainer adapter config: The configuration for the trainer adapter

Returns:

The built trainer adapter instance

async add_trajectory_builder(

name: str | nat.data_models.component_ref.TrajectoryBuilderRef,

config: nat.data_models.finetuning.TrajectoryBuilderConfig,

) → nat.finetuning.interfaces.trajectory_builder.TrajectoryBuilder

Add a trajectory builder to the builder.

Args:

name: The name or reference for the trajectory builder config: The configuration for the trajectory builder

Returns:

The built trajectory builder instance

async get_trainer(

trainer_name: str | nat.data_models.component_ref.TrainerRef,

trajectory_builder: nat.finetuning.interfaces.trajectory_builder.TrajectoryBuilder,

trainer_adapter: nat.finetuning.interfaces.trainer_adapter.TrainerAdapter,

) → nat.finetuning.interfaces.finetuning_runner.Trainer

Get a trainer by name with the specified trajectory builder and trainer adapter.

Args:

trainer_name: The name or reference of the trainer trajectory_builder: The trajectory builder instance trainer_adapter: The trainer adapter instance

Returns:

The trainer instance

async get_trainer_config(

trainer_name: str | nat.data_models.component_ref.TrainerRef,

) → nat.data_models.finetuning.TrainerConfig

Get the configuration for a trainer.

Args:

trainer_name: The name or reference of the trainer

Returns:

The configuration for the trainer

async get_trainer_adapter_config(

trainer_adapter_name: str | nat.data_models.component_ref.TrainerAdapterRef,

) → nat.data_models.finetuning.TrainerAdapterConfig

Get the configuration for a trainer adapter.

Args:

trainer_adapter_name: The name or reference of the trainer adapter

Returns:

The configuration for the trainer adapter

async get_trajectory_builder_config(

trajectory_builder_name: str | nat.data_models.component_ref.TrajectoryBuilderRef,

) → nat.data_models.finetuning.TrajectoryBuilderConfig

Get the configuration for a trajectory builder.

Args:

trajectory_builder_name: The name or reference of the trajectory builder

Returns:

The configuration for the trajectory builder

async get_trainer_adapter(

trainer_adapter_name: str | nat.data_models.component_ref.TrainerAdapterRef,

) → nat.finetuning.interfaces.trainer_adapter.TrainerAdapter

Get a trainer adapter by name.

Args:

trainer_adapter_name: The name or reference of the trainer adapter

Returns:

The trainer adapter instance

async get_trajectory_builder(

trajectory_builder_name: str | nat.data_models.component_ref.TrajectoryBuilderRef,

) → nat.finetuning.interfaces.trajectory_builder.TrajectoryBuilder

Get a trajectory builder by name.

Args:

trajectory_builder_name: The name or reference of the trajectory builder

Returns:

The trajectory builder instance

async add_ttc_strategy(

name: str,

config: nat.data_models.ttc_strategy.TTCStrategyBaseConfig,

) → None

Add a test-time compute strategy to the builder.

Args:

name: The name or reference for the TTC strategy config: The configuration for the TTC strategy

async get_ttc_strategy(

strategy_name: str | nat.data_models.component_ref.TTCStrategyRef,

pipeline_type: nat.experimental.test_time_compute.models.stage_enums.PipelineTypeEnum,

stage_type: nat.experimental.test_time_compute.models.stage_enums.StageTypeEnum,

) → nat.experimental.test_time_compute.models.strategy_base.StrategyBase

Get a test-time compute strategy by name.

Args:

strategy_name: The name or reference of the TTC strategy pipeline_type: The pipeline type for the strategy stage_type: The stage type for the strategy

Returns:

The TTC strategy instance

async get_ttc_strategy_config(

strategy_name: str | nat.data_models.component_ref.TTCStrategyRef,

pipeline_type: nat.experimental.test_time_compute.models.stage_enums.PipelineTypeEnum,

stage_type: nat.experimental.test_time_compute.models.stage_enums.StageTypeEnum,

) → nat.data_models.ttc_strategy.TTCStrategyBaseConfig

Get the configuration for a test-time compute strategy.

Args:

strategy_name: The name or reference of the TTC strategy pipeline_type: The pipeline type for the strategy stage_type: The stage type for the strategy

Returns:

The configuration for the TTC strategy

async add_retriever(

name: str,

config: nat.data_models.retriever.RetrieverBaseConfig,

) → None

Add a retriever to the builder.

Args:

name: The name or reference for the retriever config: The configuration for the retriever

async get_retriever(

retriever_name: str,

wrapper_type: nat.builder.framework_enum.LLMFrameworkEnum | str | None = None,

) → nat.retriever.interface.Retriever

Get a retriever by name.

Args:

retriever_name: The name or reference of the retriever wrapper_type: Optional LLM framework type to wrap the retriever in

Returns:

The retriever instance, optionally wrapped in the specified framework type

async get_retriever_config(

retriever_name: str,

) → nat.data_models.retriever.RetrieverBaseConfig

Get the configuration for a retriever.

Args:

retriever_name: The name or reference of the retriever

Returns:

The configuration for the retriever

get_user_manager() → nat.builder.builder.UserManagerHolder

Get the user manager holder.

Returns:

The user manager holder instance

get_function_dependencies(

fn_name: str,

) → nat.data_models.function_dependencies.FunctionDependencies

Get the dependencies for a function.

Args:

fn_name: The name of the function

Returns:

The function dependencies

get_function_group_dependencies(

fn_name: str,

) → nat.data_models.function_dependencies.FunctionDependencies

Get the dependencies for a function group.

Args:

fn_name: The name of the function group

Returns:

The function group dependencies

async add_middleware(

name: str | nat.data_models.component_ref.MiddlewareRef,

config: nat.data_models.middleware.MiddlewareBaseConfig,

) → nat.middleware.middleware.Middleware

Add middleware to the builder.

async get_middleware(

middleware_name: str | nat.data_models.component_ref.MiddlewareRef,

) → nat.middleware.middleware.Middleware

Get built middleware by name.

get_middleware_config(

middleware_name: str | nat.data_models.component_ref.MiddlewareRef,

) → nat.data_models.middleware.MiddlewareBaseConfig

Get the configuration for middleware.

static use(

config: nat.data_models.common.TypedBaseModel,

builder: nat.builder.builder.Builder,

) → collections.abc.Generator[ChildBuilder, None, None]

Context manager for temporarily setting the Builder object.

Parameters

configTypedBaseModel

The configuration to use within the context. Note: Not used for now, but required by the interface and will be used in the future.

builderBuilder

The Builder instance to use within the context.

Yields

ChildBuilder

The Builder instance that was set.

Examples

>>> with ChildBuilder.use(config, my_builder) as builder:
...     # builder is active in this context
...     assert Builder.current() == builder
>>> # Original builder is restored here