RASA NLU Demo

🏄 Introduction

The purpose of this repo is to showcase a NLU model built using DIET Classifier of Rasa Open Source. This repository includes a pre-trained model for the demonstration. The data is taken from an official rasa demo bot: Sara.

For details on training of model and preparation of data, see:

The model can be used for:

• Intent Classification
• Entity recognition

👷‍ Setting up

With Docker

1. Build container using Dockerfile from root directory

docker build -t rasa_nlu .

2. Start the NLU server using newly build docker container

docker run -p 5005:5005 rasa_nlu

This will build and start the a docker of the NLU server on the default port (5005) of the Rasa NLU.

Without Docker

1. [Optional] Create a python environment and activate it.

2. Install dependencies

pip install -r requirements.txt

3. Start the Rasa NLU server using;

rasa run --enable-api -m models/nlu_model.gz

This will start the Rasa NLU server on the default port 5005.

To test the API:

After starting the server, test the api on the following endpoint /model/parse. Example-

curl localhost:5005/model/parse -d '{"text":"I am mohit saini"}'