trinity.common.workflows package

trinity.common.workflows package#

Subpackages#

Submodules#

Module contents#

Workflow module

class trinity.common.workflows.Task(workflow: ~typing.Type[~trinity.common.workflows.workflow.Workflow] | None = None, repeat_times: int | None = None, format_args: ~trinity.common.config.FormatConfig = <factory>, rollout_args: ~trinity.common.config.GenerationConfig = <factory>, workflow_args: dict = <factory>, reward_fn_args: dict = <factory>, is_eval: bool = False, reward_fn: ~typing.Type[~trinity.common.rewards.reward_fn.RewardFn] | None = None, raw_task: dict | None = None, batch_id: int | str = '', task_id: int | str = '', index: dict = <factory>)[source]#

Bases: dict

A Task class that defines a task and its associated reward function / workflow.

workflow: Type[Workflow] = None#
repeat_times: int | None = None#
format_args: FormatConfig#
rollout_args: GenerationConfig#
workflow_args: dict#
reward_fn_args: dict#
is_eval: bool = False#
reward_fn: Type[RewardFn] | None = None#
raw_task: dict | None = None#
batch_id: int | str = ''#
task_id: int | str = ''#
index: dict#
to_workflow(model: ModelWrapper, auxiliary_models: List[ModelWrapper] | None = None) → Workflow[source]#

Convert the task to a workflow.

Parameters:

  • model (ModelWrapper) – The rollout model for the workflow.

  • auxiliary_models (List[ModelWrapper]) – The auxiliary model wrappers. Workflows can access both the ModelWrapper and OpenAI client via self.auxiliary_model_wrappers and self.auxiliary_models respectively.

Returns:

The generated workflow object.

Return type:

Workflow

property task_desc: str | None#
property truth: str | None#
to_dict() → dict[source]#
__init__(workflow: ~typing.Type[~trinity.common.workflows.workflow.Workflow] | None = None, repeat_times: int | None = None, format_args: ~trinity.common.config.FormatConfig = <factory>, rollout_args: ~trinity.common.config.GenerationConfig = <factory>, workflow_args: dict = <factory>, reward_fn_args: dict = <factory>, is_eval: bool = False, reward_fn: ~typing.Type[~trinity.common.rewards.reward_fn.RewardFn] | None = None, raw_task: dict | None = None, batch_id: int | str = '', task_id: int | str = '', index: dict = <factory>) → None#
class trinity.common.workflows.Workflow(*, task: Task, model: ModelWrapper, auxiliary_models: List[ModelWrapper] | None = None)[source]#

Bases: object

The base workflow class.

A workflow is a runnable object which generates a list of experiences.

auxiliary_model_wrappers#

List of ModelWrapper instances for auxiliary models.

auxiliary_models#

List of OpenAI clients (sync or async based on is_async) for auxiliary models.

can_reset: bool = False#
can_repeat: bool = False#
is_async: bool = False#
__init__(*, task: Task, model: ModelWrapper, auxiliary_models: List[ModelWrapper] | None = None)[source]#
property resettable#

Deprecated, use cls.can_reset instead.

property repeatable#

Deprecated, use cls.can_repeat instead. A workflow is repeatable if it can be run multiple times within the run() or run_async() method.

property asynchronous#

Deprecated, use cls.is_async instead. Whether the workflow runs in async mode.

reset(task: Task)[source]#

Reset the workflow.

set_repeat_times(repeat_times: int, run_id_base: int) → None[source]#

Set the number of times to repeat the workflow. :param repeat_times: number of times to repeat the workflow (if repeatable). :type repeat_times: int :param run_id_base: base run_id for setting run_id in experiences. :type run_id_base: int

run() → List[Experience][source]#

Run workflow and return a list of experiences.

async run_async() → List[Experience][source]#

Run workflow in async and return a list of experiences.

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