uqlm.scorers.baseclass.uncertainty.UncertaintyQuantifier#

class uqlm.scorers.baseclass.uncertainty.UncertaintyQuantifier(llm=None, device=None, system_prompt='You are a helpful assistant', max_calls_per_min=None, use_n_param=False, postprocessor=None)#

Bases: object

__init__(llm=None, device=None, system_prompt='You are a helpful assistant', max_calls_per_min=None, use_n_param=False, postprocessor=None)#

Parent class for uncertainty quantification of LLM responses

Parameters:

  • llm (BaseChatModel) – A langchain llm object to get passed to chain constructor. User is responsible for specifying temperature and other relevant parameters to the constructor of their llm object.

  • device (str or torch.device input or torch.device object, default="cpu") – Specifies the device that NLI model use for prediction. Only applies to ‘semantic_negentropy’, ‘noncontradiction’ scorers. Pass a torch.device to leverage GPU.

  • system_prompt (str or None, default="You are a helpful assistant.") – Optional argument for user to provide custom system prompt

  • max_calls_per_min (int, default=None) – Specifies how many api calls to make per minute to avoid a rate limit error. By default, no limit is specified.

  • use_n_param (bool, default=False) – Specifies whether to use n parameter for BaseChatModel. Not compatible with all BaseChatModel classes. If used, it speeds up the generation process substantially when num_responses > 1.

  • postprocessor (callable, default=None) – A user-defined function that takes a string input and returns a string. Used for postprocessing outputs.

Methods

__init__([llm, device, system_prompt, ...])

Parent class for uncertainty quantification of LLM responses

generate_candidate_responses(prompts)

This method generates multiple responses for uncertainty estimation.

generate_original_responses(prompts)

This method generates original responses for uncertainty estimation.
async generate_candidate_responses(prompts)#

This method generates multiple responses for uncertainty estimation. If specified in the child class, all responses are postprocessed using the callable function defined by the user.

Return type:

List[List[str]]

async generate_original_responses(prompts)#

This method generates original responses for uncertainty estimation. If specified in the child class, all responses are postprocessed using the callable function defined by the user.

Return type:

List[str]

References