> ## Documentation Index
> Fetch the complete documentation index at: https://futureagi.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.

# Is Helpful

> Evaluates whether the response is helpful in solving the user problem or answering their question

<CodeGroup>
  ```python Python theme={null}
  result = evaluator.evaluate(
      eval_templates="is_helpful",
      inputs={
          "input": "Why doesn't honey go bad?",
          "output": "Honey doesn't spoil because its low moisture and high acidity prevent the growth of bacteria and other microbes."
      },
      model_name="turing_flash"
  )

  print(result.eval_results[0].output)
  print(result.eval_results[0].reason)
  ```

  ```typescript JS/TS theme={null}
  import { Evaluator, Templates } from "@future-agi/ai-evaluation";

  const evaluator = new Evaluator();

  const result = await evaluator.evaluate(
    "is_helpful",
    {
      input: "Why doesn't honey go bad?",
      output: "Honey doesn't spoil because its low moisture and high acidity prevent the growth of bacteria and other microbes."
    },
    {
      modelName: "turing_flash",
    }
  );

  console.log(result);
  ```
</CodeGroup>

| **Input** |                    |          |                                    |
| --------- | ------------------ | -------- | ---------------------------------- |
|           | **Required Input** | **Type** | **Description**                    |
|           | `input`            | `string` | User query to the model            |
|           | `output`           | `string` | Model's response to the user query |

| **Output** |            |                                                                  |
| ---------- | ---------- | ---------------------------------------------------------------- |
|            | **Field**  | **Description**                                                  |
|            | **Result** | Returns Passed if the response is helpful, or Failed if it's not |
|            | **Reason** | Provides a detailed explanation of the evaluation                |

***

## Troubleshooting

If you encounter issues with this evaluation:

* Ensure that both the `input` (user query) and `output` (AI response) parameters are provided
* The helpfulness evaluation works best when the context of the request is clear
* If evaluating complex responses, make sure the entire response is included
* Consider combining with other evaluations like `completeness` or `factual-accuracy` for more comprehensive assessment

## Related Evaluations

* \*\*[completeness](/future-agi/get-started/evaluation/builtin-evals/completeness): Determines if the response addresses all aspects of the query
* \*\*[task-completion](/future-agi/get-started/evaluation/builtin-evals/task-completion): Checks if a specific requested task was accomplished
* \*\*[instruction-adherence](/future-agi/get-started/evaluation/builtin-evals/instruction-adherence): Evaluates if the response follows specific instructions
* \*\*[is-concise](/future-agi/get-started/evaluation/builtin-evals/is-concise): Assesses whether the response avoids unnecessary verbosity