Class Categorization

Namespace: LMKit.TextAnalysis

Assembly: LM-Kit.NET.dll

Provides functionality to classify content into predefined categories using a language model.

public sealed class Categorization

Inheritance: object

Categorization

Inherited Members: object.Equals(object)

object.Equals(object, object)

object.GetHashCode()

object.GetType()

object.ReferenceEquals(object, object)

object.ToString()

Remarks

This engine supports categorization tasks for various content types, including plain text, images, PDF documents, HTML files, and Microsoft Office formats (DOCX, XLSX, PPTX).

For a complete list of supported file formats, see the Attachment class documentation.

Constructors

Categorization(LM): Initializes a new instance of the Categorization class using the specified language model.

Properties

AllowUnknownCategory: Gets or sets a value indicating whether the categorization engine can identify when content does not match any of the predefined categories. If set to true, the engine returns -1 (for single-category methods) or an empty list (for multi-category methods) when no suitable category is identified. If set to false, the engine always assigns the content to the nearest matching category, even if confidence is low.

Confidence: Gets the confidence level of the most recent categorization operation.

Guidance: Gets or sets optional guidance text that can influence the categorization process. This can be used to steer the model toward certain themes or constraints.

MaxInputTokens: Gets or sets the maximum number of input tokens that the categorization engine will analyze.

Model: Gets the underlying language model instance associated with this categorization object.

PreferredInferenceModality: Gets or sets the preferred modality for inference. This determines whether text, image, or both modalities are used when processing input. Defaults to Multimodal.

UseEmbeddingClassifier: Gets or sets a value indicating whether the classifier should use an embedding-based classification strategy. When set to true, the engine is forced to classify using embeddings instead of a completion-based approach.

Methods

GetBestCategory(IList<string>, Attachment, bool, CancellationToken): Classifies the content provided as an attachment into one of the predefined categories.

GetBestCategory(IList<string>, ImageBuffer, bool, CancellationToken): Classifies the content provided in an image into one of the predefined categories. The underlying language model must support vision input.

GetBestCategory(IList<string>, IList<string>, Attachment, bool, CancellationToken): Classifies the content provided as an attachment into one of the predefined categories.

GetBestCategory(IList<string>, IList<string>, string, bool, CancellationToken): Classifies the specified plain text into one of the predefined categories.

GetBestCategory(IList<string>, string, bool, CancellationToken): Classifies the specified plain text into one of the predefined categories.

GetBestCategoryAsync(IList<string>, Attachment, bool, CancellationToken): Asynchronously classifies the content provided as an attachment into one of the predefined categories.

GetBestCategoryAsync(IList<string>, IList<string>, Attachment, bool, CancellationToken): Asynchronously classifies the content provided as an attachment into one of the predefined categories.

GetBestCategoryAsync(IList<string>, IList<string>, ImageBuffer, bool, CancellationToken): Asynchronously classifies the given image into one of the predefined categories. The underlying language model must support vision input.

GetBestCategoryAsync(IList<string>, IList<string>, string, bool, CancellationToken): Asynchronously classifies the specified plain text into one of the predefined categories.

GetBestCategoryAsync(IList<string>, string, bool, CancellationToken): Asynchronously classifies the specified plain text into one of the predefined categories.

GetTopCategories(IList<string>, Attachment, int, bool, CancellationToken): Classifies the content provided as an attachment into up to a specified maximum number of categories.

GetTopCategories(IList<string>, ImageBuffer, int, bool, CancellationToken): Classifies the given image into up to a specified maximum number of categories. The underlying language model must support vision input.

GetTopCategories(IList<string>, IList<string>, Attachment, int, bool, CancellationToken): Classifies the content provided as an attachment into up to a specified maximum number of categories.

GetTopCategories(IList<string>, IList<string>, string, int, bool, CancellationToken): Classifies the specified plain text into up to a specified maximum number of categories.

GetTopCategories(IList<string>, string, int, bool, CancellationToken): Classifies the specified plain text into up to a specified maximum number of categories.

GetTopCategoriesAsync(IList<string>, Attachment, int, bool, CancellationToken): Asynchronously classifies the content provided as an attachment into up to a specified maximum number of categories.

GetTopCategoriesAsync(IList<string>, ImageBuffer, int, bool, CancellationToken): Asynchronously classifies the given image into up to a specified maximum number of categories. The underlying language model must support vision input.

GetTopCategoriesAsync(IList<string>, IList<string>, Attachment, int, bool, CancellationToken): Asynchronously classifies the content provided as an attachment into up to a specified maximum number of categories.

GetTopCategoriesAsync(IList<string>, IList<string>, string, int, bool, CancellationToken): Asynchronously classifies the specified plain text into up to a specified maximum number of categories.

GetTopCategoriesAsync(IList<string>, string, int, bool, CancellationToken): Asynchronously classifies the specified plain text into up to a specified maximum number of categories.

Table of Contents

Class Categorization

Remarks

Constructors

Properties

Methods