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h2oGPTe

h2oGPTe is an AI-powered search assistant for your internal teams to answer questions gleaned from large volumes of documents, websites and workplace content.

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Overview

This node operation creates a job for the creation of a topic model on a specified collection. Topic modeling is a technique used to discover abstract topics within a collection of documents, which can help in organizing, summarizing, and understanding large volumes of text data. This operation is useful when you want to asynchronously start the process of generating a topic model without blocking your workflow, allowing you to monitor or retrieve the job status later.

Practical examples include:

  • Automatically categorizing documents in a knowledge base by topics.
  • Summarizing themes from a large set of customer feedback or survey responses.
  • Enhancing search and recommendation systems by tagging content with discovered topics.

Properties

Name Meaning
Collection ID The unique identifier of the collection on which the topic model job will be created.
Additional Options Optional parameters; currently supports:
- Timeout: Time in seconds to wait before the request times out (default 0 means no timeout).

Output

The output of this operation is the full HTTP response from the API call that creates the topic model job. Typically, this includes details about the job such as its unique job ID, status, and any metadata related to the job creation. The json field in the output will contain this information, which can be used to track the progress or result of the topic model creation asynchronously.

No binary data is expected from this operation.

Dependencies

  • Requires an API key credential for authentication to the external service.
  • The node uses a base URL configured via credentials, targeting the /models/create_topic_model_job endpoint.
  • Proper permissions to access the specified collection and create jobs are necessary.

Troubleshooting

  • Missing or invalid Collection ID: Ensure the Collection ID is provided and valid; otherwise, the API will reject the request.
  • Timeout issues: If the job creation takes longer than expected, consider setting a higher timeout value in the additional options.
  • Authentication errors: Verify that the API key credential is correctly configured and has sufficient permissions.
  • API endpoint errors: Check network connectivity and that the base URL is correct and accessible.

Links and References

  • Topic Modeling Wikipedia
  • Refer to your API provider's documentation for "Create Topic Model Job" endpoint for detailed response structure and job management.

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