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Dataiku DSS

Use the Dataiku DSS API

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Overview

This node integrates with the Dataiku DSS API, enabling users to perform a wide range of operations on Dataiku DSS resources directly from n8n workflows. Specifically, for the Machine Learning - Lab resource and the Update User Metadata for Trained Model operation, it allows updating the user metadata associated with a trained machine learning model within a project.

This functionality is useful in scenarios where you want to programmatically annotate or modify metadata for trained models, such as adding custom tags, notes, or other user-defined information that can help in model management, tracking, or deployment processes.

Practical example:
You have an automated workflow that retrains a model periodically. After training, you want to update the model's metadata with information about the training run, such as the date, parameters used, or performance metrics. This node operation lets you send that metadata update to Dataiku DSS seamlessly.

Properties

Name Meaning
Project Key The key identifier of the Dataiku DSS project containing the model.
Analysis ID The identifier of the analysis context related to the ML task.
ML Task ID The identifier of the machine learning task associated with the trained model.
Model Full ID The full identifier of the trained model whose user metadata will be updated.
Request Body JSON object containing the user metadata fields and values to update for the trained model.

Output

The node outputs the response from the Dataiku DSS API after attempting to update the user metadata. The output is provided as JSON data representing the result of the update operation.

  • If the update is successful, the output JSON typically contains confirmation details or the updated metadata.
  • If the operation involves downloading files (not applicable here), binary data would be returned, but for this operation, only JSON output is expected.

Dependencies

  • Requires valid Dataiku DSS API credentials, including:
    • The URL or address of the Dataiku DSS server.
    • A user API key for authentication.
  • The node uses HTTP requests to communicate with the Dataiku DSS REST API.
  • No additional external services are required beyond access to the Dataiku DSS instance.

Troubleshooting

  • Missing Credentials Error:
    If the node throws an error about missing credentials, ensure that the Dataiku DSS API credentials are properly configured in n8n and linked to the node.

  • Required Parameter Errors:
    The node validates required parameters such as Project Key, Analysis ID, ML Task ID, and Model Full ID. Missing any of these will cause an error. Double-check that all required inputs are provided.

  • API Request Failures:
    Network issues, incorrect API keys, or insufficient permissions may cause API call failures. Verify network connectivity, credential validity, and user permissions in Dataiku DSS.

  • Invalid JSON in Request Body:
    The Request Body must be valid JSON. Malformed JSON will cause errors. Use proper JSON formatting.

Links and References

If you need further details on other operations or resources, feel free to ask!

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