📄 Response Generation¶

tasks.rag.response_generation

type: Task
input_fields: 
  contexts: List[str]
  contexts_ids: Union[List[int], List[str]]
  question: str
reference_fields: 
  reference_answers: List[str]
metrics: 
  - metrics.rag.response_generation.correctness.token_overlap
  - metrics.rag.response_generation.faithfullness.token_overlap
  - metrics.rag.response_generation.correctness.bert_score.deberta_large_mnli
augmentable_inputs: 
  - contexts
  - question
[source]

Explanation about Task¶

Task packs the different instance fields into dictionaries by their roles in the task.

Attributes:

input_fields (Union[Dict[str, str], List[str]]):
Dictionary with string names of instance input fields and types of respective values. In case a list is passed, each type will be assumed to be Any.

reference_fields (Union[Dict[str, str], List[str]]):
Dictionary with string names of instance output fields and types of respective values. In case a list is passed, each type will be assumed to be Any.

metrics (List[str]): List of names of metrics to be used in the task. prediction_type (Optional[str]):

Need to be consistent with all used metrics. Defaults to None, which means that it will be set to Any.

defaults (Optional[Dict[str, Any]]):
An optional dictionary with default values for chosen input/output keys. Needs to be consistent with names and types provided in ‘input_fields’ and/or ‘output_fields’ arguments. Will not overwrite values if already provided in a given instance.

The output instance contains three fields:
“input_fields” whose value is a sub-dictionary of the input instance, consisting of all the fields listed in Arg ‘input_fields’. “reference_fields” – for the fields listed in Arg “reference_fields”. “metrics” – to contain the value of Arg ‘metrics’

References: metrics.rag.response_generation.correctness.bert_score.deberta_large_mnli, metrics.rag.response_generation.faithfullness.token_overlap, metrics.rag.response_generation.correctness.token_overlap