Stories (w/o 1:1 mapping between intents and responses)įorm-Filling (basic, added in v0.14 release) Slots (simple slots requiring custom classifiers for custom data types) As of the latest release, the following subset of functionality is supported:
#Gobot zero download
To build a Go-Bot-based goal-oriented skill, you need to provide Go-Bot framework with a dataset (in RASA v1 or DSTC2 formats), train model, download it, and then use it by either calling them natively from Python or by rising them as microservices and then calling them via its standard DeepPavlov REST API.Ĭurrently, we support two different approaches to define domain model and behavior of a given goal-oriented skill - using either a subset of the v1 of the RASA DSLs (domain.yml, nlu.md, stories.md) or a DSTC2 format. These goal-oriented skills can be written in Python (enabling using their corresponding Go-Bot-trained models natively) or in any other programming language (requiring running their corresponding Go-Bot-trained models as microservices). Go-Bot is an ML-driven framework designed to enable development of the goal-oriented skills for DeepPavlov Dream AI Assistant Platform. DeepPavlov skill/model REST service mounting How Do I: Use Form-Filling in Go-Bot Skill with RASA DSLs (v1).How Do I: Integrate Go-Bot-based Goal-Oriented Skill into DeepPavlov Deepy.How Do I: Build Go-Bot Skill with RASA DSLs (v1).How Do I: Integrate Intent Catcher into DeepPavlov Deepy.Advanced: Using Entity Linking and Wiki Parser As Standalone Services For KBQA.How Do I: Adding Templates For New SPARQL Queries.How Do I: Train Relation and Path Ranking Models.Training and inference on your own data.Building your own response base for bert ranking.Training and inference models on predifined datasets.NER-based Model for Sentence Boundary Detection Task.Advanced models (BERT and lemmatized models).
SQuAD with contexts without correct answers.BERT for Context Question Answering (SQuAD).BERT for Named Entity Recognition (Sequence Tagging).Frequently Asked Questions (FAQ) model.Other NLP-tasks on TensorFlow, Keras, or PyTorch.Text Classification on Keras or PyTorch.DataLearningIterator and DataFittingIterator.
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