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Definition

The mean tokens test ensures that the mean number of tokens in the data is within a given range.

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Taxonomy

  • Task types: LLM.
  • Availability: and .

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Why it matters

  • Depending on the application you are building, you might want to limit the number of tokens generated by the LLM.
  • LLMs have a limited context window, so it is important to ensure that the number of tokens in the data is within the context window capacity.

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Test configuration examples

If you are writing a tests.json, here are a few valid configurations for the character length test: 
[
  {
    "name": "Mean number of tokens below 1500",
    "description": "Make sure that the average response has less than 1500 tokens",
    "type": "performance",
    "subtype": "metricThreshold",
    "thresholds": [
      {
        "insightName": "metrics",
        "insightParameters": null,
        "measurement": "meanTokens",
        "operator": "<",
        "value": 1500
      }
    ],
    "subpopulationFilters": null,
    "mode": "development",
    "usesValidationDataset": true, // Apply test to the validation set
    "usesTrainingDataset": false,
    "usesMlModel": false,
    "syncId": "b4dee7dc-4f15-48ca-a282-63e2c04e0689" // Some unique id
  }
]
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