Learn advanced Dialogflow techniques in this comprehensive tutorial series. Master slot filling to gather user contact data, utilize contexts for connecting intents, and implement email validation using regex. Explore data management by saving information in Firebase Realtime Database and Firestore, including calculating average user age and persisting session data. Discover best practices for intent naming and avoiding conversation loops. Enhance user experience by implementing memory features and integrating external services like sending emails via Sendgrid and triggering Slack messages through webhooks from Firebase Functions.
Overview
Syllabus
Dialogflow Chatbot - Slot Filling - Getting a User's Contact Data.
Dialogflow Chatbot - Using Contexts to Connect Intents.
Dialogflow Chatbot - How to Validate Email Addresses (Using Regex).
Dialogflow Chatbot - Saving Data in the Realtime Database (Using the Inline Editor).
Dialogflow Chatbot - Read & Write Realtime Database - Calculate Average User Age.
Dialogflow Chatbot - Saving Data in the Firestore Database (Using the Inline Editor).
Dialogflow Chatbot - How to Persist Session Data to Firestore (Saving Pizza Orders in an Array).
Dialogflow Chatbot - How to Name Intents (Hierarchical Naming Convention).
Dialogflow Chatbot - How to Avoid Conversation Loops.
Dialogflow Chatbot – How to Make Your Bot Remember the User’s Name.
Dialogflow Chatbot - How to Send an Email from your Fulfilment via Sendgrid.
Dialogflow Chatbot - How to Trigger a Slack Message via Webhook from your Firebase Function.
Taught by
Peter Fessel
