Conversational AI with Rasa NLU and Core

Demo application for the PyData Conference in Amsterdam 2018

You can find the slides for the presentation at Slideshare.

Installation

The notebooks contain the installation instructions as their first step. Basically, you'll need a virtualenv with rasa_core, rasa_nlu[spacy] and spacy installed.

Also make sure to install a spacy language model for en.

Notebooks

rasa-moodbot-demo-starter this is what we are going to start with
rasa-moodbot-demo-complete this is how our notebook should look like once we are done
rasa-moodbot-demo-complete-executed if hell breaks loose, this is a backup notebook with all the output cells filled

The additional files (nlu.md, stories.md, domain.yml, config.yml, story_eval.pdf, story_graph.png) will be explained and created in the notebooks.

Once you ran the notebooks, there should be a models/ folder containing your trained Rasa model.

Additional Material

Running duckling locally

run the duckling docker container
```
 docker run -p 8000:8000 rasa/duckling
```

add the duckling component to your pipeline:

 - name: "ner_duckling_http"
   url: localhost:8000

Slides