This is an open source starter pack for developers, to show how to automate full conversations in healthcare.
Step 1: To install HealthGo, please clone the repo:
git clone
cd healhtgo
Healthgo uses Python 3.5 and 3.6 and has not been tested with other versions. Use the requirements.txt file to install the appropriate dependencies via pip. If you do not have pip installed yet first do:
sudo easy_install pip
otherwise move to the next step directly.
Step 2: Install requirements:
pip install -r requirements.txt
Step 3: Install the spaCy English language model by running:
python3 -m spacy download en
This will install the bot and all of its requirements.
Step 1: Train the core model by running:
make train-core
This will train the Rasa Core model and store it inside the /models/current/dialogue folder of your project directory.
Step 2: Train the NLU model by running:
make train-nlu
This will train the NLU model and store it inside the /models/current/nlu folder of your project directory.
Step 3: In a new terminal start the server for the custom action by running:
make action-server
Step 4: Now to test the HealthGo with both these models you can run:
make cmdline
After the bot has loaded you can start chatting to it. If you start by saying Hi for example,
the bot will reply by asking you what you are looking for and show you a number of options in form of buttons.
Since those buttons do not show when testing the bot in the command line, you can imitate a button click by copy
and pasting the intent of the button of your choice as your input.
Try out different conversations and see what the current state of the bot can do! After playing around a bit you can try to modify and extend the bot by adding custom actions and intents for example. Find help for this in the Rasa Docs.
A helpful option to extend training data and get to know your bot is interactive learning, here you can correct your bot at every step in the conversation and automatically save the data for future training.
Step 5: To run HealthGo in interactive learning mode run:
make interactive
In order to chat to the Medicare Locator through Telegram you can do the following:
Step 1: First if you don't already use Telegram, download it and set it up with your phone. Once you are registered with Telegram you start by setting up a Telegram bot.
Step 2: To setup your own bot go to the Telegram BotFather,
enter /newbot and follow the instructions.
You should get your access_token, and the username you set will be your verify. Save this information as you will need it later.
Step 3: Now you will need to connect to Telegram via a webhook. To create a local webhook from your machine you can use Ngrok. Follow the instructions on their site to
set it up on your computer. Move ngrok to your working directory and in a new terminal run:
./ngrok http 5005
Ngrok will create a https address for your computer. For Telegram you need the address in this format:
https://xxxxxx.ngrok.io/webhooks/telegram/webhook
Step 4: Go to the credentials.yml file that you downloaded from the repo and input your personal access_token, verify and webhook_url.
You will have to update the webhook_url everytime you do redo Step 3, the access_token and verify will stay the same.
Step 5: In a new terminal start the server for the custom action by running:
make action-server
Step 6: In a new terminal connect to Telegram by running:
make telegram
Step 7: Now you and anyone on Telegram are able to chat to your bot. You can find it by searching for its name on Telegram.
Detailed information about this can also be found in the Rasa Docs.
For more information about Medicare APIs please visit data.medicare.gov
If you would like to run Healthgo on your website, follow the instructions here to place the chat widget on your website.
data/core/ - contains stories for Rasa Core
data/nlu_data.md - contains example NLU training data
actions.py - contains custom action/api code
domain.yml - the domain file for Core
nlu_config.yml - the NLU config file
core_config.yml - the Core config file
credentials.yml - contains credentials for the use with Telegram
endpoints.yml - contains url for endpoint
Run make help to see an overview of all make commands available.
train-nlu - Train the NLU model.
train-core - Train the Core model.
interactive - Run the Medicare Locator interactive learning mode.
cmdline - Run the bot on the command line.
action-server - Start the action server.
telegram - Run the bot in the Telegram channel.
Licensed under the GNU General Public License v3.