h2oGPTe icon

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.

Actions198

Overview

This node operation runs a self-test on a specified large language model (LLM). It allows users to verify the functionality and performance of an LLM by executing predefined test modes. This is useful for developers or teams who want to validate that their chosen model is working correctly within their environment before deploying it in production workflows.

Common scenarios include:

  • Validating a newly integrated LLM to ensure it responds as expected.
  • Running quick diagnostics on an LLM to check its health or readiness.
  • Comparing different models or configurations by running standardized self-tests.

Practical example:

  • A user selects a model named "gpt-4" and runs a "quick" self-test mode to confirm the model is operational.
  • Another user might run a "full" self-test mode on a custom LLM to perform comprehensive checks before using it in critical applications.

Properties

Name Meaning
Model Name The name identifier of the large language model (LLM) to be tested.
Mode The mode of the self-test to run. Options are: Quick, Rag, Full, Agent. Each represents a different level or type of testing.

Output

The output will contain the JSON response from the API endpoint that runs the self-test on the specified model. This typically includes details about the test results, such as success status, any errors encountered, and diagnostic information relevant to the model's performance.

If the node supports binary data output, it would represent raw data related to the self-test, but this operation primarily returns structured JSON data describing the test outcome.

Dependencies

  • Requires an API key credential for authentication with the external service hosting the LLMs.
  • The base URL for API requests is derived from the configured credentials.
  • The node sends a POST request to an endpoint formatted as /models/{model_name}/self_test/{mode}, where model_name and mode are user inputs.

Troubleshooting

  • Invalid Model Name: If the model name does not exist or is misspelled, the API may return an error indicating the model was not found. Verify the model name input.
  • Unsupported Mode: Using a mode value outside the allowed options (quick, rag, full, agent) may cause errors. Ensure the mode is one of the supported options.
  • Authentication Errors: Missing or invalid API credentials will prevent the request from succeeding. Confirm that the API key credential is properly configured.
  • Timeouts or Network Issues: Long-running tests (e.g., full mode) might take time; network issues can cause failures. Adjust timeout settings if available or retry later.
  • API Endpoint Changes: If the external API changes its endpoints or parameters, the node may fail. Keep the integration updated with the latest API documentation.

Links and References

  • Refer to the external LLM provider's API documentation for detailed descriptions of self-test modes and expected responses.
  • n8n documentation on how to configure API key credentials and use HTTP request nodes for custom integrations.

Discussion