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.
Represents a generative model based on a Markov-like architecture.
Creates a new instance of the MarkovModel class
new MarkovModel(data)
data
(Array): An array of objects containing question-answer pairs for training.
.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.