Datasets

Overview

Datasets hold Messages, Inputs and Expected Outputs for models to use within Experiments.

• Inputs – Variables that can be used in the prompt message, e.g., {{firstname}}.
• Messages – The prompt template, structured with system, user, and assistant roles.
• Expected Outputs – Reference responses that evaluators use to compare against newly generated outputs.

To get experiments ready, make sure you have models available by adding them to your Model Garden.

Note: You don’t need to include all three entities when uploading a dataset. Depending on your experiment, you can choose to include only inputs, messages, or expected outputs as needed. For example, you can create a dataset with just inputs.

Prerequisites

To get started with Datasets, make sure you have access to a Project and the sufficient Permissions within the workspace.

Setting up a Dataset

To create a new Dataset use the + button on a Project Folder and select Dataset.

Once you enter a title for your dataset you will be taken to the Table View for your Dataset.

Your table has 3 columns:

• Inputs.
• Messages.
• Expected Outputs.

You can enter as many rows as needed in your Dataset

Adding an entry to the Dataset

To manually add a new entry click on the Add Row button. Here by clicking on each cell, you can fill in corresponding data.

Importing a CSV into a Data

To easily import Datasets you can choose to upload a .csv file containing your messages and reference details.

To do so, choose Import and drag-and-drop your file.

You will then be able to configure the mapping from column in your csv to fields in the Dataset collection. Each row represents a separate dataset entry.

🚧

Your .csv file must use , as a delimiter.

Creating an Experiment from Dataset

The next step to use a Dataset is to create an Experiment.

📘

To learn more about creating an Experiment, see Setting up an Experiment