Supercharge Your Apps with Power Automate and Azure ML

Table of Contents

1. Introduction
2. Features
3. Solution Components
4. Setting Up PowerApps
5. Data Sources
6. Power Automate Flow
7. Screens and Results
8. Demo
9. Azure AutoML Model
10. OpenAI Integration

Integrating Power Apps with Azure Machine Learning and OpenAI using Power Automate

In this article, we will explore how to integrate Power Apps with Azure Machine Learning and OpenAI using Power Automate. We will be focusing on building a health expense planner Power App that can track health expenses and provide personalized plans to save money. The sample app utilizes a machine learning model and OpenAI's API to predict health expenses and generate a detailed plan.

1. Introduction

The introduction section will provide an overview of the demo and explain how the health expense planner Power App works. It will highlight the importance of tracking health expenses and saving money.

2. Features

In this section, we will discuss the features of the health expense planner Power App. It will cover the different parameters the app takes into account, such as age, sex, BMI, number of children, and smoking habit. We will also explore how a custom-built SQL AutoML model integrated with Power Apps using Power Automate Flow provides a customized plan Based on these inputs.

3. Solution Components

This section will provide an overview of the solution components. It will discuss the Canvas App, Power Automate Flow, and the AutoML model used for making predictions. Screenshots of the app interface and the model endpoint will also be included.

4. Setting Up Power Apps

Here, we will explain the steps required to set up Power Apps for integration with Azure Machine Learning and OpenAI. It will include obtaining an API key from OpenAI, creating an account for Power Apps and Power Automate, and having an active account in Azure with a deployed Azure AutoML model for prediction endpoints.

5. Data Sources

In this section, we will discuss the data sources used in the Power App. It will cover the OpenAI connector and how it can be added to Power Apps. We will also explore how Power Automate Flow is used to send an HTTP request to the model endpoint and pass the JSON query back to the Power App.

6. Power Automate Flow

Here, we will Delve into the details of the Power Automate Flow used in the demo. It will explain how the flow sends a post request to the model endpoint, captures the input parameters in the query, and receives the response back. The response schema and its utilization in the Power App will also be discussed.

7. Screens and Results

This section will showcase how the screens in the Power App will look. It will provide examples of input parameters and the corresponding predicted expenses. The personalized plan generated by the app will be explained, highlighting the importance of urgent planning and considering age and health factors.

8. Demo

In the demo section, we will provide a step-by-step demonstration of how to use the health expense planner Power App. The process of providing input parameters, calling the Power Automate Flow and OpenAI connector, and receiving the response will be shown.

9. Azure AutoML Model

Here, we will discuss how to Create an Azure AutoML model using Azure Machine Learning Studio. The process of creating and deploying the best model and using its endpoints in the Power App will be explained.

10. OpenAI Integration

This section will cover how to obtain API keys from OpenAI and start the building process using OpenAI's capabilities. The inclusion of prompt text and necessary files in the OpenAI connector will be Mentioned.

By following this guide, You will be able to integrate Power Apps with Azure Machine Learning and OpenAI, and build a health expense planner app that can efficiently track and optimize health expenses.

Highlights

• Create a health expense planner Power App
• Integrate with Azure Machine Learning and OpenAI
• Predict health expenses using a machine learning model
• Generate personalized plans to save money
• Utilize Power Automate Flow for seamless integration

FAQ

Q: Can I use the health expense planner app with any insurance provider? A: Yes, the app is designed to work with any insurance provider as it focuses on tracking expenses and providing personalized plans.

Q: Do I need programming skills to set up Power Apps for integration? A: No, programming skills are not required. The setup process is straightforward and can be done using the provided steps.

Q: Is the app compatible with mobile devices? A: Yes, the app is designed to be compatible with both mobile and desktop devices, ensuring convenience and accessibility.

Q: Can I customize the parameters used for predicting health expenses? A: Yes, the app allows customization of parameters such as age, sex, BMI, number of children, and smoking habit to provide personalized predictions and plans.

Q: Are the predicted expenses accurate? A: The machine learning model used in the app provides accurate predictions based on the input parameters and relevant data. However, the accuracy may vary depending on individual factors.

Q: Can I modify the app to track expenses for other purposes? A: Yes, the app can be modified and customized to track expenses for various purposes other than health expenses. It can be adapted to fit different scenarios and needs.