comprehend_moderation.base_moderation_config.ModerationToxicityConfig
Create a new model by parsing and validating input data from keyword arguments.
comprehend_moderation.base_moderation_exceptions.ModerationIntentionError([...])
Exception raised if Intention entities are detected.
comprehend_moderation.base_moderation_exceptions.ModerationPiiError([...])
Exception raised if PII entities are detected.
comprehend_moderation.base_moderation_exceptions.ModerationToxicityError([...])
Exception raised if Toxic entities are detected.
comprehend_moderation.intent.ComprehendIntent(client)
comprehend_moderation.pii.ComprehendPII(client)
comprehend_moderation.toxicity.ComprehendToxicity(client)
langchain_experimental.cpal¶
Classes¶
cpal.constants.Constant(value[, names, ...])
Enum for constants used in the CPAL.
langchain_experimental.data_anonymizer¶
Classes¶
data_anonymizer.base.AnonymizerBase()
Base abstract class for anonymizers. It is public and non-virtual because it allows     wrapping the behavior for all methods in a base class.
data_anonymizer.base.ReversibleAnonymizerBase()
Base abstract class for reversible anonymizers.
data_anonymizer.deanonymizer_mapping.DeanonymizerMapping(...)
Functions¶
data_anonymizer.faker_presidio_mapping.get_pseudoanonymizer_mapping([seed])
langchain_experimental.fallacy_removal¶
The Chain runs a self-review of logical fallacies as determined by this paper  categorizing and defining logical fallacies https://arxiv.org/pdf/2212.07425.pdf. Modeled after Constitutional AI and in same format, but applying logical fallacies as generalized rules to remove in output
Classes¶