> ## Documentation Index
> Fetch the complete documentation index at: https://docs.uptrain.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Response Matching

> Grades how well the response generated by the LLM aligns with the provided ground truth.

Response Matching compares the LLM-generated text with the gold (ideal) response using the defined score metric.

Columns required:

* `question`: The question asked by the user
* `response`: The response given by the model
* `ground_truth`: The ideal response

Optional Parameters:

* `method`: Different methods to check for response matching
  * `llm (default)`: Uses LLM to check if the response matches the ground truth
  * `exact`: Checks if the response is exactly the same as the ground\_truth
  * `rouge`: Uses ROUGE SCORE to check if the response matches the ground truth

### How to use it?

```python theme={null}
from uptrain import EvalLLM, ResponseMatching

OPENAI_API_KEY = "sk-********************"  # Insert your OpenAI key here

data = [{
    "question": "Who were the two finalists of the 2023 ICC Cricket World Cup?",
    "ground_truth": "The finalists of the 2023 ICC Cricket World Cup were India and Australia.",
    "response": "Australia was a finalist in the 2023 ICC Cricket World Cup."
}]

eval_llm = EvalLLM(openai_api_key=OPENAI_API_KEY)

res = eval_llm.evaluate(
    data = data,
    checks = [ResponseMatching(method = 'llm')]    # method: llm/exact/rouge
)
```

<Info>By default, we are using GPT 3.5 Turbo for evaluations. If you want to use a different model, check out this [tutorial](https://github.com/uptrain-ai/uptrain/blob/main/examples/open_source_evaluator_tutorial.ipynb).</Info>

Sample Response:

```json theme={null}
[
   {
      "response_match_precision": 1.0,
      "response_match_recall": 0.5,
      "score_response_match": 0.57,
      "response_match_method": "llm"
   }
]
```

<Note>A higher response matching score reflects that the generated response matches the ground truth.</Note>

The response generated contains information on Australia being a finalist and does not match the ground truth about both the finalists of the 2023 ICC Cricket World Cup.

Hence, resulting in a low response matching score.

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