# Source: https://www.promptfoo.dev/docs/configuration/expected-outputs/model-graded/answer-relevance/

# Answer Relevance

The `answer-relevance` assertion evaluates whether an LLM's output is relevant to the original query. It uses a combination of embedding similarity and LLM evaluation to determine relevance.

## How to use it

To use the `answer-relevance` assertion type, add it to your test configuration like this:

```yaml
assert:
  - type: answer-relevance
    threshold: 0.7  # Score between 0 and 1
```

## How it works

The answer relevance checker:

1. Uses an LLM to generate potential questions that the output could be answering
2. Compares these questions with the original query using embedding similarity
3. Calculates a relevance score based on the similarity scores

A higher threshold requires the output to be more closely related to the original query.

## Example Configuration

Here's a complete example showing how to use answer relevance:

```yaml
prompts:
  - "Tell me about {{topic}}"
providers:
  - openai:gpt-5
tests:
  - vars:
      topic: quantum computing
    assert:
      - type: answer-relevance
        threshold: 0.8
```

## Overriding the Providers

Answer relevance uses two types of providers:

- A text provider for generating questions
- An embedding provider for calculating similarity

You can override either or both:

```yaml
defaultTest:
  options:
    provider:
      text: gpt-5
      config:
        temperature: 0
      embedding:
        id: openai:text-embedding-ada-002
```

You can also override providers at the assertion level:

```yaml
assert:
  - type: answer-relevance
    threshold: 0.8
    provider:
      text: anthropic:claude-2
      embedding: cohere:embed-english-v3.0
```

## Customizing the Prompt

You can customize the question generation prompt using the `rubricPrompt` property:

```yaml
defaultTest:
  options:
    rubricPrompt: |
      Given this answer: {{output}}
      Generate 3 questions that this answer would be appropriate for.
      Make the questions specific and directly related to the content.
```

## Further reading

See [model-graded metrics](/docs/configuration/expected-outputs/model-graded/) for more options.