feat: Implement DeepEvalEvaluator

[shadeMe]

Related to #250.

We introduce DeepEvalEvaluator, a component that uses the DeepEval LLM evaluation framework to calculate evaluation metrics for RAG pipelines (among others). Refer deepset-ai/haystack#6784 for an overview of the API design.

This PR introduces the following user-facing classes:

• DeepEvalMetric - A enumeration that lists the supported DeepEval metrics. Currently, only those metrics that are related to RAG pipelines are supported.
• DeepEvalEvaluator - Th pipeline component interfaces with the evaluation framework. It accepts a single metric and its optional parameters. The inputs to the pipeline are dynamically configured depending on the metric. This is done with help of a metric descriptor table that contains metadata concerning input/output conversion formats, expected inputs/outputs, etc.

The output of the component is a nested list of metric results. Each input can have one or more results, depending on the metric. Each result is a dictionary containing the following keys and values:

• name - The name of the metric.
• score - The score of the metric.
• explanation - An optional explanation of the score.

[masci]

I'm not familiar with deepeval but code looks good to me. I left a question about api docs now that we merged the CI job that will attempt to run hatch run docs on integrations' changes merged on main. Another option might be making that CI job more resilient.

[masci]

Thanks for adding the docs, LGTM