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Basalt

Interact with Basalt API to manage prompts, monitoring, and datasets
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Overview

This node interacts with the Basalt API to create a new item (row) in a specified dataset. It is useful for users who want to programmatically add data entries to datasets managed by Basalt, such as adding new records with specific values, names, ideal outputs, and metadata. Practical examples include updating machine learning datasets with new training examples or adding data rows for analysis.

Use Case Examples

  1. Adding a new data row to a dataset with specific column values and metadata.
  2. Creating a dataset item with an ideal output for supervised learning tasks.

Properties

Name Meaning
Slug The unique identifier (slug) of the dataset where the item will be created.
Values A JSON object representing the values for each column in the dataset row to be created.
Item Options Additional optional properties for the dataset row, including name, ideal output, and metadata.
Request Options Options to control the request behavior such as batching, SSL certificate validation, proxy settings, and timeout.

Output

JSON

  • id - The unique identifier of the created dataset item.
  • slug - The slug of the dataset where the item was created.
  • values - The values of the dataset row as a JSON object.
  • name - The name of the dataset row, if provided.
  • idealOutput - The ideal output for the dataset row, if provided.
  • metadata - Additional metadata associated with the dataset row.

Dependencies

  • Basalt API with an API key credential

Troubleshooting

  • Ensure the dataset slug is correct and exists in Basalt to avoid 'dataset not found' errors.
  • Validate the JSON structure of the 'Values' and 'Metadata' fields to prevent request failures.
  • Check network connectivity and proxy settings if requests time out or fail.
  • If SSL certificate validation errors occur, consider enabling the 'Ignore SSL Issues' option cautiously.

Links

  • Basalt API Documentation - Official API documentation for Basalt, useful for understanding dataset item creation and other operations.

Discussion