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* Introduces Ragas as a supported evaluation framework. This integration only supports the `RubricsScore` metric and OpenAI models. Users can pass in either a dataset with a pre-computed `user_input`, `reference` and `response` fields or they can provide a dataset containing `user_input` and `reference` along with information about a model endpoint that will be used for computing the `response` field.
## 0.4.2
* Adds the ability to provide a custom system prompt to the MMLU-based evaluators. When a system prompt is provided, LM-eval applies the chat template under the hood, else it will pass the model a barebones prompt.