> For the complete documentation index, see [llms.txt](https://docs.raga.ai/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.raga.ai/ragaai-catalyst/ragaai-metric-library/guardrails/cosine-similarity.md).

# Cosine Similarity

Compare AI outputs with reference text using cosine similarity. Improve semantic consistency and accuracy.

**Objective**\
Measures the similarity between two pieces of text, ensuring consistency and relevance.

**Interpretation**\
A higher score typically means a higher degree of similarity (depending on implementation). A lower score indicates less similarity.

> *Implementation note*: Some may flip this scoring scale (i.e., 0 for identical texts and higher for differences). Ensure your usage matches your interpretation.

**Code Execution**

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

**Example**

* **Prompt**: “Summarize the product description.”
* **Context**: “Product X is a portable charger with a 10000mAh battery.”
* **Response**: “Product X is a small device that charges phones and has a 10000mAh battery.”
* **Metric Output**: `{"score": 0.85, "reason": "High similarity to the context."}`