This project was created during the Conversational AI Workshop at the Software Engineering for Business Information Systems (sebis) chair at the Technical University of Munich (TUM).
This project aims to showcase how a conversational agent could be used as an interface to explore a dataset. More information on the dataset can be found here. The agent was built using Google Dialogflow and a Flask backend.
python3 -m pip install --user virtualenv
python3 -m venv dialogflow-env
source dialogflow-env/bin/activate
python3 -m pip install -r requirements.txt
To try out the demo, create a new Google Dialogflow project and import the history-agent.zip file. Locally start ngrok
with ngrok http 8000 to forward the Flask port to the Dialog Agent. The link provided by ngrok once started must be
entered in the Dialogflow project under the 'Fulfillment/Webhook/Url' tab.
First run the Flask App and then visit frontend.html file to play around with the demo.
