# Coherence

**Objective**: The test is intended to check the coherence of the model response i.e if the model is able to generate ideas and arguments in a logical manner

**Parameters:**

`data:`

* `prompt` (str): The prompt for the response.
* `response` (str): The response to be evaluated.
* `context` (str, optional): The context for the response (default is None).

`arguments:`

* `strictness` (int, optional): The number of times response is evaluated (default is 1).
* `model` (str, optional): The model to be used for evaluation (default is "gpt-4").

**Interpretation**: Passed result signifies model is more coherent in its response to the given prompt. Failed result signifies model is less coherent in its response, giving unorganized or incorrect response.

```python
# Add tests with custom data
evaluator.add_test(
    test_names=["coherence_test"],
    data={
        "prompt": ["Can you explain the process of photosynthesis in detail?"],
        "response": ["Photosynthesis is a complex biochemical process in which plants convert light energy into chemical energy, utilizing water, carbon dioxide, chlorophyll, and enzymes."]
    },
    arguments={"model": "gpt-4", "threshold": 0.6},
).run()

evaluator.print_results()
```


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