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

# Answer Relevance

> Score how relevant a response is to the question

`AnswerRelevanceEvaluator` is an LLM judge that scores how well the answer addresses the user's question. It uses `QuestionContext` (no gold answer required). It is used in RAG examples and was missing from the judge inventory.

A case **fails** when `score < threshold`. Default `threshold` is `3` on a 1–3 scale, so only a high-relevance score passes.

## How It Works

| Score | Meaning                                               |
| ----- | ----------------------------------------------------- |
| **1** | Mostly unrelated, ignores or contradicts the question |
| **2** | Partial / mixed relevance                             |
| **3** | Directly answers the question                         |

## Usage Example

```python theme={null}
import asyncio

from trusttest.evaluation_contexts import QuestionContext
from trusttest.evaluators import AnswerRelevanceEvaluator


async def evaluate():
    evaluator = AnswerRelevanceEvaluator()
    result = await evaluator.evaluate(
        response="Vic is the capital of Osona, in Catalonia.",
        context=QuestionContext(question="What is the capital of Osona?"),
    )
    print(result)

if __name__ == "__main__":
    asyncio.run(evaluate())
```

| Parameter              | Type           | Default                     | Description               |
| ---------------------- | -------------- | --------------------------- | ------------------------- |
| `threshold`            | `float`        | `3`                         | Minimum passing score     |
| `language`             | `LanguageType` | `"English"`                 | Language of judge reasons |
| `llm_client`           | `LLMClient`    | From `set_config` evaluator | Optional override         |
| `name` / `description` | `str`          | Built-in                    | Display metadata          |

## When to Use

* RAG functional tests without a gold answer
* Checking that retrieval-backed answers stay on topic
* Combining with [Correctness](/trusttest/evaluate-result/llm-as-a-judge/correctness) or [Completeness](/trusttest/evaluate-result/llm-as-a-judge/completeness) when you also have `ExpectedResponseContext`