Blog: Learn Machine Learning from a Google AI Engineer
Build a Conditional Template in Dialogflow for Google Assistant With Custom Payloads
What I like most about Dialogflow, (the tool to create Chatbots and Smart Assistants / Google Assistant apps), is that you can maintain your conversations within the Dialogflow UI. Many users write their complete FAQ content in intents and responses. You no longer need a developer to tweak your conversations or deploy your agent which makes it very scalable for large organizations. It’s also possible to load data from external systems. In that case, you are hosting parts of the conversation elsewhere. You could store these parts in language files or databases. Some organizations prefer to write the full conversation in the Dialogflow UI. That way your copywriters can maintain the full conversation.
It’s good to know that it is possible to use templates and conditionals within the Dialogflow UI. The trick here, is to make use of the custom payload response setting, which you can find in the Intent > Responses section.
What I like most about Dialogflow, (the tool to create Chatbots and Smart Assistants / Google Assistant apps), is that you can maintain your conversations within the Dialogflow UI. Many users write their complete FAQ content in intents and responses. You no longer need a developer to tweak your conversations or deploy your agent which makes it very scalable for large organizations. It’s also possible to load data from external systems. In that case, you are hosting parts of the conversation elsewhere. You could store these parts in language files or databases. Some organizations prefer to write the full conversation in the Dialogflow UI. That way your copywriters can maintain the full conversation.
It’s good to know that it is possible to use templates and conditionals within the Dialogflow UI. The trick here, is to make use of the custom payload response setting, which you can find in the Intent > Responses section.
Lee Boonstra
Lee Boonstra (they/them) has been a presence in the tech world since 2007, wearing many hats from AI software engineer to prompt engineer, web developer to technical trainer, and developer advocate.
With eight years of experience at Google (and AI) under their belt, they now hold the role of AI Software Engineer (SWE) at the Google Cloud office of the CTO. Leading innovation projects, Lee aims to disrupt markets and foster collaboration globally. Their expertise in Conversational and Voice technology, alongside (Generative) AI, has led to recognition as a respected public keynote speaker and published author for O’Reilly and Apress. Lee eases tech headaches and celebrates those light bulb moments.
Lee has written the Google/Kaggle Prompt Engineering whitepaper and two books: "Hands-on Sencha Touch 2" (O'Reilly) and their more recent work, "The Definitive Guide to Conversational AI with Dialogflow and Google Cloud" (Apress).
