NLPENGINE

This microservice is intended to extract structured information from raw text, to identify intents and entities for KBS bot.

This microservice requires to be populated with information of Agents and their Models, as follows.

class database.Agent(**kwargs)

An Agent refers to the main o domain or purpose of the chatbot.

Attributes:
param @id:Id to populate the database.
param @name:This name must be unique to identify the Agent.
class database.Model(**kwargs)

A Model refers to every model trained with the tool fasttext. These Models are specialized in identifying intents or a certain type of entity.

Attributes:
param @id:Used to populate the database
param @name:Unique to identify the Agent
param @url:Url to obtain model
param @entity_name:
 Name used to represent the entity type
param @model_type:
 If model is for entities or intents

Todo

When the model is not found, make this class to download model automatically.

Check also th API description here:

Check also the TODO lis for this project:

Todo

When the model is not found, make this class to download model automatically.

(The original entry is located in /home/docs/checkouts/readthedocs.org/user_builds/cb-nlp-engine-ms/checkouts/latest/kbsbot/nlpengine/database.py:docstring of database.Model, line 15.)

This project is part of the architecture described in: Herrera, Andre & Yaguachi, Lady & Piedra, Nelson. (2019). Building Conversational Interface for Customer Support Applied to Open Campus an Open Online Course Provider. 11-13. 10.1109/ICALT.2019.00011.