Training Data Importers

Training Data Importers

These docs are for version 1.x of Rasa Open Source.

User Guide

NLU

Core

Conversation Design

API Reference

Migrate from (beta)

Reference

Warning: This document is for an old version of Rasa. The latest version is 1.10.26.

RasaFileImporter (default)

By default Rasa uses the importer RasaFileImporter. If you want to use it on its own, you don’t have to specify anything in your configuration file. If you want to use it together with other importers, add it to your configuration file:

importers:
- name: "RasaFileImporter"

MultiProjectImporter (experimental)

Warning: This feature is currently experimental and might change or be removed in the future. Please share your feedback on it in the forum to help us making this feature ready for production.

With this importer you can build a contextual AI assistant by combining multiple reusable Rasa projects. You might, for example, handle chitchat with one project and greet your users with another. These projects can be developed in isolation, and then combined at train time to create your assistant.

Writing a Custom Importer

If you are writing a custom importer, this importer has to implement the interface of TrainingDataImporter:

from typing import Optional, Text, Dict, List, Union

import rasa
from rasa.core.domain import Domain
from rasa.core.interpreter import RegexInterpreter, NaturalLanguageInterpreter
from rasa.core.training.structures import StoryGraph
from rasa.importers.importer import TrainingDataImporter
from rasa.nlu.training_data import TrainingData

class MyImporter(TrainingDataImporter):
    """Example implementation of a custom importer component."""

def __init__(self,
        config_file: Optional[Text] = None,
        domain_path: Optional[Text] = None,
        training_data_paths: Optional[Union[List[Text], Text]] = None,
        **kwargs: Dict
    ):
        pass