llm

class besser.bot.nlp.llm.llm.LLM(nlp_engine, name, parameters)

Bases: ABC

The LLM abstract class.

An LLM (Large Language Model) receives a text input and generates an output. Depending on the LLM, several tasks can be performed, such as question answering, translation, text classification, etc.

This class serves as a template to be implemented for specific LLM providers.

Parameters:

• nlp_engine (NLPEngine) – the NLPEngine that handles the NLP processes of the bot the LLM belongs to

• name (str) – the LLM name

• parameters (dict) – the LLM parameters

_nlp_engine

the NLPEngine that handles the NLP processes of the bot the LLM belongs to

Type:

NLPEngine

name

the LLM name

Type:

str

parameters

the LLM parameters

Type:

dict

_abc_impl = <_abc._abc_data object>

chat(session, parameters=None)

Make a prediction, i.e., generate an output.

This function can provide the chat history to the LLM for the output generation, simulating a conversation or remembering previous messages.

Parameters:

• session (Session) – the user session

• parameters (dict) – the LLM parameters. If none is provided, the RAG’s default value will be used

Returns:

the LLM output

Return type:

str

abstract initialize()

Initialize the LLM. This function is called during the bot training.

intent_classification(intent_classifier, message, parameters=None)

Predict the intent of a given message.

Instead of returning only the intent with the highest likelihood, return all predictions. Predictions include not only the intent scores but other information extracted from the message.

Parameters:

• intent_classifier (LLMIntentClassifier) – the intent classifier that is running the intent classification process

• message (str) – the message to predict the intent

• parameters (dict) – the LLM parameters. If none is provided, the RAG’s default value will be used

Returns:

the list of predictions made by the LLM.

Return type:

list[IntentClassifierPrediction]

abstract predict(message, parameters=None)

Make a prediction, i.e., generate an output.

Parameters:

• message (Any) – the LLM input text

• parameters (dict) – the LLM parameters to use in the prediction. If none is provided, the default LLM parameters will be used

Returns:

the LLM output

Return type:

str

set_parameters(parameters)

Set the LLM parameters.

Parameters:

parameters (dict) – the new LLM parameters