
Based on the iris dataset I have created a simple Machine Learning model with an API endpoint in Azure ML Studio. The model needs 4 inputs and based on these inputs it returns a predicted label. This is the input data to test the endpoint:
I have created an Excel file which has 4 columns (sepal_length, sepal_width, petal_length, petal_width), each containing a value as can be seen in the Excel inputs screenshot (first image).
In Power Automate I was able to connect to my Excel file using the 'List rows present in the table' action. In this action I can find my table as 'Table1'. But, I am not sure which next steps I should take in Power Automate to connect to the API and be able to receive a prediction in return.
This is how my flow currently looks:
So I am having some difficulties with transforming the input data in such a format that it can be provided as input to the API. In the following screenshot is displayed how I connect to my API using a Bearer token and the specific URI.
It would be great if anyone with experience in Power Automate could help me out with this. All help is very much appreciated.