[Feature] Add callback mechanism to evaluation

I'm integrating fmeval with experiments tracking solutions (MLflow for now), and the lack of [callback mechanisms](https://www.askpython.com/python/built-in-methods/callback-functions-in-python) means that the tracing can only happen after an evaluation is completed.
Drawbacks:
- results can be recorded only once the evaluation has completed (similar to #278 )
- if the evaluation fails during the execution, the already generated values are lost

The suggested solution is to implement a callback mechanism to be able to tracks results as they're generated, simplifying integration with experiment tracking solutions.

Start by mapping the evaluation flow to identify where generated values become available and where failures discard them. Define the callback behavior and verify that partial results can be observed during evaluation and retained when execution fails.

Written by the indexing model from the issue text.