DeepPavlov: An Open Source Library for Conversational AI

Mikhail Arkhipov, Mikhail Burtsev, Yuri Kuratov

Abstract:

An open-source DeepPavlov library is specifically tailored for development of dia-
logue systems. The library prioritizes efficiency, modularity, and extensibility with
the goal to make it easier to create dialogue systems from scratch with limited data
available. It supports modular as well as end-to-end approaches to implementation
of conversational agents. In DeepPavlov framework an agent consists of skills and
every skill can be decomposed into components. Components are usually trainable
models which solve typical NLP tasks such as intent classification, named entity
recognition, sentiment analysis or pre-trained encoders for word or sentence level
embeddings. Sequence-to-sequence chit-chat, question answering or task-oriented
skills can be assembled from components provided in the library. ML models
implemented in DeepPavlov have performance on par with current state of the art
in the field [1].