Modeling Guide

Similarity Scoring

This is an example graph for using a Leonardo Machine Learning Foundation (MLF) service. To get familiar with the service, you can run the graph and use the terminal to interactively create request messages.

The graph is composed of the following main components:
  • LeonardoML Client: The API client that connects to LeonardoMLF services.

  • Service-dependent preprocessing operator: This operator prepares the message individually for its assigned service (one of the following: Language Detector, Extract Doc Features, Image Classifier, Extract Img Features, Classify Product Img, Classify Product Text, Similarity Scorer, Changepoint Detector, Time Series Forecast, Topic Detector, Translator). It simplifies the input, which should be just the desired operation and the content to be send.

  • Terminal: The Terminal operator can be used in this graph to interactively create requests to the Leonardo MLF service.


  • The address for the Leonardo Machine Learning Foundation services.
  • Your API key for Leonardo MLF.

Configure and Run the Graph

Follow the steps below to run the training example from the Data Pipeline UI:
  1. Select the LeonardoML Client operator.
  2. In the configuration panel, enter the server address for Leonardo MLF (“host”), and your API key that you received from Leonardo MLF (“apiKey”).
  3. Run the graph, right-click on the Terminal operator, and select Open UI.
  4. Once in the terminal, press Enter to send the current line to the client. You will see a template for a request message as response. Copy and paste this message and adapt it to your needs, then re-send the message to the client.