hands-on lab

Creating a Weather Forecasting Chatbot with Dialogflow

Up to 1h
Get guided in a real environmentPractice with a step-by-step scenario in a real, provisioned environment.
Learn and validateUse validations to check your solutions every step of the way.
See resultsTrack your knowledge and monitor your progress.


A chatbot is only as useful as the information it helps to serve. In this lab you will learn how to make a chatbot that can look up the weather from a US Government forecasting API. This bot will be able to take any Latitude & Longitude coordinates inside of the United States, parse them, and give a plain text response.

Learning Objectives

Upon completion of this Lab you will be able to:

  • Integrate external sources of truth with Dialogflow
  • Leverage Google Cloud Functions to call external APIs
  • Expand Dialogflow to serve real-world data

Intended Audience

This lab is intended for:

  • Machine learning engineers
  • Anyone interested in bots


You should possess:

  • A basic understanding of Dialogflow Intents, Entities, and Responses is required
  • A basic understanding of NodeJS is recommended
  • A basic understanding of Google Cloud is helpful but not required

The following content is sufficient to fulfill these prerequisites:

About the author

Learning paths

Calculated Systems was founded by experts in Hadoop, Google Cloud and AWS. Calculated Systems enables code-free capture, mapping and transformation of data in the cloud based on Apache NiFi, an open source project originally developed within the NSA. Calculated Systems accelerates time to market for new innovations while maintaining data integrity.  With cloud automation tools, deep industry expertise, and experience productionalizing workloads development cycles are cut down to a fraction of their normal time. The ability to quickly develop large scale data ingestion and processing  decreases the risk companies face in long development cycles. Calculated Systems is one of the industry leaders in Big Data transformation and education of these complex technologies.

Covered topics

Lab steps

SIgning in to the Dialogflow Console
Enabling the Dialogflow Inline Editor
Creating the Forecast Intent
Updating the Function
Handling Dynamic Responses
Deploying the Forecast API Service
Improving the Usefulness for End-Users