# Faithfulness RAG Metric

**Objective:** This metric determines the *proportion* of facts in the response that originate from the context information. The generated answer is considered faithful if all the claims made can be inferred from the provided context.

**Required Parameters**: `Prompt`, `Response`, `Context`

**Interpretation:**

* Lower faithfulness score indicates the model is not able to focus on the correct context document.
* Lower faithfulness score indicates the model is hallucinating and generating information not present in the context documents. 
* Lower faithfulness score indicates the Knowledge Base has contradicting information regarding the topic referred to in the prompt.

<figure><img src="https://1811327582-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FYbIiNdp1QbG4avl7VShw%2Fuploads%2FsP4Xne8uXyaZNXjWtleS%2Fimage.png?alt=media&#x26;token=6e7d6f04-87fb-4c99-b778-b645f56301bb" alt=""><figcaption></figcaption></figure>

**Code Execution:**

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

The "schema\_mapping" variable needs to be defined first and is a pre-requisite for evaluation runs. Learn how to set this variable [here](https://docs.raga.ai/ragaai-catalyst/concepts/running-ragaai-evals/executing-evaluations).

**Example**:

* Prompt: Who discovered penicillin?
* Context: Penicillin is one of the most important discoveries in medical science, marking the beginning of the antibiotic era. It was discovered in 1928 by Alexander Fleming, a Scottish bacteriologist.&#x20;
* Response: Alexander Dumas discovered penicillin.
* *Metric Output*: {‘score’: 0, ‘reason’: ‘As per context penicillin was discovered by Alexander Fleming’}

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