# StringDistanceEvalChain

> **Class** in `langchain_classic`

📖 [View in docs](https://reference.langchain.com/python/langchain-classic/evaluation/string_distance/base/StringDistanceEvalChain)

Compute string distances between the prediction and the reference.

Examples:
----------
>>> from langchain_classic.evaluation import StringDistanceEvalChain
>>> evaluator = StringDistanceEvalChain()
>>> evaluator.evaluate_strings(
        prediction="Mindy is the CTO",
        reference="Mindy is the CEO",
    )

Using the `load_evaluator` function:

>>> from langchain_classic.evaluation import load_evaluator
>>> evaluator = load_evaluator("string_distance")
>>> evaluator.evaluate_strings(
        prediction="The answer is three",
        reference="three",
    )

## Signature

```python
StringDistanceEvalChain()
```

## Extends

- `StringEvaluator`
- `_RapidFuzzChainMixin`

## Properties

- `requires_input`
- `requires_reference`
- `input_keys`
- `evaluation_name`

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[View source on GitHub](https://github.com/langchain-ai/langchain/blob/b302691ff9ad841804e93e5addbdc53b6974473b/libs/langchain/langchain_classic/evaluation/string_distance/base.py#L165)