llmp.services.program.Program

class llmp.services.program.Program(signature: str, input_model: ~typing.Type[~pydantic.main.BaseModel] = None, output_model: ~typing.Type[~pydantic.main.BaseModel] = None, config: ~llmp.components.settings.program_settings.ProgramSettings = ProgramSettings(log_action=True, auto_optimize=True, generator_type='default', program_type=<PromptType.ZERO_SHOT: 'zero_shot'>, total_sample_size=20, max_few_shot_size=5, fr_optimization=True, fr_human_verification=True, test_size=5, test_set_selection='random', runs_per_input=5, metric='accuracy', early_stopping=True, early_stopping_patience=2, model_name='gpt-3.5-turbo', max_token=3000, temperature=0.9, top_p=1, best_of=1, frequency_penalty=0, presence_penalty=0, max_retry=3), load_if_exist: bool = True, **kwargs)

Attributes

job

Methods

__init__(signature[, input_model, ...])

__init__(signature: str, input_model: ~typing.Type[~pydantic.main.BaseModel] = None, output_model: ~typing.Type[~pydantic.main.BaseModel] = None, config: ~llmp.components.settings.program_settings.ProgramSettings = ProgramSettings(log_action=True, auto_optimize=True, generator_type='default', program_type=<PromptType.ZERO_SHOT: 'zero_shot'>, total_sample_size=20, max_few_shot_size=5, fr_optimization=True, fr_human_verification=True, test_size=5, test_set_selection='random', runs_per_input=5, metric='accuracy', early_stopping=True, early_stopping_patience=2, model_name='gpt-3.5-turbo', max_token=3000, temperature=0.9, top_p=1, best_of=1, frequency_penalty=0, presence_penalty=0, max_retry=3), load_if_exist: bool = True, **kwargs)