# Response Evaluator

**Objective**\
This metric ensures that responses are appropriate and accurate for the given prompt, maintaining consistency.

**Interpretation**\
A higher score indicates the response deviates significantly from the prompt or contains inaccuracies. A lower (or zero) score indicates the response is relevant and accurate.

**Code Execution**

```python
metrics = [
    {
        "name": "Response Evaluator",
        "config": {
            "model": "gpt-4o-mini",
            "provider": "openai"
        },
        "column_name": "your-column-identifier",
        "schema_mapping": schema_mapping
    }
]
```

**Example**

* **Prompt**: “Explain Newton’s first law of motion.”
* **Context**: “Newton’s first law states that an object in motion stays in motion unless acted upon by an external force.”
* **Response**: “Newton’s first law is about the gravitational pull of the Earth on objects.”
* **Metric Output**: `{"score": 1, "reason": "Response is inaccurate regarding Newton’s first law."}`


---

# Agent Instructions: Querying This Documentation

If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://docs.raga.ai/ragaai-catalyst/ragaai-metric-library/guardrails/response-evaluator.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.