The purpose of this repo is to showcase a contextual AI assistant built with the open source Rasa Stack.
Sara is an alpha version and lives in our docs, helping developers getting started with our open source tools. It supports the following user goals:
- Understanding the Rasa Stack
- Installing the Rasa Stack
- Answering some FAQs around the Rasa Stack
- Subscribing to the Rasa newsletter
- Requesting a call with Rasa's sales team
- Handling basic chitchat
You can talk to Sara here and find planned enhancements for Sara in the Project Board
To install Sara, please clone the repo and run:
cd rasa-demo
pip install -e .
This will install the bot and all of its requirements. Note that it was written in Python 3 so might not work with PY2.
To train the core model: make train-core (this will take 2h+ and a significant amount of memory to train,
if you want to train it faster, try the training command with
--augmentation 0)
To train the NLU model: make train-nlu
To run Sara with both these models:
docker run -p 8000:8000 rasa/duckling
make run-cmdline
There are some custom actions that require connections to external services,
specifically ActionSubscribeNewsletter and ActionStoreSalesInfo. For these
to run you would need to have your own MailChimp newsletter and a Google sheet
to connect to.
If you would like to run Sara on your website, follow the instructions here to place the chat widget on your website.
data/core/ - contains stories for Rasa Core
data/nlu - contains example NLU training data
demo - contains custom action/api code
domain.yml - the domain file for Core
nlu_tensorflow.yml - the NLU config file
policy.yml - the Core config file
Licensed under the GNU General Public License v3. Copyright 2018 Rasa Technologies GmbH. Copy of the license. Licensees may convey the work under this license. There is no warranty for the work.