Implementing an AI Chatbot with Dialogflow
Dialogflow is one of the hottest computer-human interaction platforms on the market. It offers all the services and complexities of natural language processing and machine learning, but uses a straightforward interface that allows you to start developing Assistant, Alexa, and Cortana integrated applications today. In this lab, you will build a Google Assistant chatbot that submits helpdesk tickets. The following is a diagram of the chatbot application on Google Cloud Platform:
The exercises are ordered to reflect a common cloud developer process. You will:
Set up your lab and learn how to work with Dialogflow and your GCP environment.
Deploy a simple Dialogflow application.
Deploy a simple cloud function within GCP to connect with Dialogflow.
Test your chatbot.
What you'll learn
By the end of this lab, you will have an understanding of the following:
Basics concepts and constructs of Dialogflow, including intent, entity and context.
Life of a conversation.
This is an expert level lab. Before taking it, you should be comfortable with at least the basics of machine learning and natural language processing. Here are some Qwiklabs that can get you up to speed:
- Cloud Natural Language API: Qwik Start
- Google Cloud Speech API: Qwik Start
- Entity and Sentiment Analysis with the Natural Language API
- Classify Text into Categories with the Natural Language API
Once you are prepared, scroll down to dive into Dataflow.
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Create a Dialogflow agent
Allow Fulfillment to Store Help Ticket Data
Tickets are Logged in Datastore