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Markov Model

The Markov Model is a text generation model implemented in TypeScript. It creates responses by learning from question-answer pairs provided during construction. This model utilizes a Markov-like architecture to generate text based on the patterns observed in the training data.

Class: `MarkovModel``

Represents a generative model based on a Markov-like architecture.

Constructor

Creates a new instance of the MarkovModel class

new MarkovModel(data)
  • data (Array): An array of objects containing question-answer pairs for training.

Methods

.tokenizeText(text)

Tokenizes the given text into an array of lowercase words.

  • text (string): The text to tokenize.
  • Returns: An array of lowercase words.

.createMarkovModel()

Creates a Markov-like model based on the provided data.

Returns: An object representing the Markov model.

.generateResponse(question, length, context)

Generates a response based on the input question, desired response length, and optional context.

  • question (string): The input question.
  • length (number): The desired length of the response.
  • context (string, optional): Optional context for generating a response.
  • `Returns: The generated response.

.learnModel(newData)

Learns the model based on new question-answer pairs.

  • newData (Array): An array of objects containing additional question-answer pairs for learning.

.saveModel(filename)

Saves the current model to a file.

  • filename (string): The name of the file to save the model to.

.loadModel(filename)

Loads a model from a file.

  • filename (string): The name of the file to load the model from.