Version: 3.x

Rasa as open source alternative to Microsoft LUIS - Migration Guide

Let's get started with migrating your application from LUIS to Rasa:

Step 1: Export your Training Data from LUIS

Go to your list of LUIS conversation apps and select the application you want to export.

Export menu

Select 'Export' > 'Export as JSON'. This will download a file with a .json extension that can be imported directly into Rasa.

Step 2: Create a Rasa Project

To create a Rasa project, run:

rasa init

This will create a directory called data. Remove the files in this directory, and move your json file into this directory.

rm -r data/*
mv /path/to/file.json data/

Step 3: Train your NLU model

To train a model using your LUIS data, run:

rasa train nlu

Step 4: Test your NLU model

Let's see how your NLU model will interpret some test messages. To start a testing session, run:

rasa shell nlu

This will prompt your for input. Type a test message and press 'Enter'. The output of your NLU model will be printed to the screen. You can keep entering messages and test as many as you like. Press 'control + C' to quit.

Step 5: Start a Server with your NLU Model

To start a server with your NLU model, run:

rasa run

This will start a server listening on port 5005.

To send a request to the server, run:

curl 'localhost:5005/model/parse?emulation_mode=luis' -d '{"text": "hello"}'
The `emulation_mode` parameter tells Rasa that you want your json
response to have the same format as you would get from LUIS.
You can also leave it out to get the result in the usual Rasa format.
## Terminology:
The words `intent`, `entity`, `role`, and `utterance` have the same meaning in Rasa as they do
in LUIS.
LUIS's `patterns` feature is very similar to Rasa NLU's [regex features](./training-data-format.mdx#regular-expressions)
LUIS's `phrase lists` feature does not currently have an equivalent in Rasa NLU.
Join the [Rasa Community Forum]( and let us know how your migration went!