.SubCatsPerItemOverallSentiment

gd.validators.SubCatsPerItemOverallSentiment

class glyphdeck.validators.SubCatsPerItemOverallSentiment(
*,
sub_categories: list,
per_sub_category_sentiment_scores: list,
sentiment_score: float,
)

Bases: BaseValidatorModel

Validation model for representing sub-categories with individual sentiment scores and an overall sentiment score.

_field_count

The number of fields in the model.

Type:

int

sub_categories

All sub-categories identified inside the input in order of relevance.

Type:

list

per_sub_category_sentiment_scores

A list of sentiment scores corresponding to the list of identified sub-categories.

Type:

list

sentiment_score

The overall sentiment score.

Type:

float

model_fields: ClassVar[Dict[str, FieldInfo]] = {'per_sub_category_sentiment_scores': FieldInfo(annotation=list, required=True, description='A list of sentiment scores corresponding to the list of identified sub-categories. Each score is a 2 decimal value that represents sentiment of the corresponding sub-categories as it was used inside the input. Each score ranges from -1.00 (max negative sentiment) to 1.00 (max positive sentiment), with 0.00 indicating neutral sentiment. It must be between -1.00 and 1.00. The list should be of equal length to the list of corresponding sub-categories, and in the same order.'), 'sentiment_score': FieldInfo(annotation=float, required=True, description='A 2 decimal value that represents the overall sentiment of the input. Ranges from -1.00 (max negative sentiment) to 1.00 (max positive sentiment), with 0.00 indicating neutral sentiment. It must be between -1.00 and 1.00'), 'sub_categories': FieldInfo(annotation=list, required=True, description='All sub-categories identified inside the input in order of relevance, making sure to capture all the topics, with least 1 and no more than 30 categories. Each category name should be concise.')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

per_sub_category_sentiment_scores: list
sentiment_score: float
sub_categories: list