Classification : Implement Batch API for model evaluation

Current Behavior
For evaluation of fine-tuned models, we currently use the Responses API synchronously to generate predictions. These predictions are then compared against the true labels of the corresponding questions. However, this synchronous setup is difficult to manage and would require building a complex system to make the whole process asynchronous and more reliable.

Proposed Improvement
Instead of relying on the synchronous approach, we can leverage the OpenAI Batch API. By sending all evaluation queries together as a batch, we can retrieve the predictions from the batch output file and then compare them against the true labels. This would simplify the workflow and make the evaluation process more scalable and efficient.

document to refer : https://docs.google.com/document/d/1y2WLRUm2dZaQMetvb31XpDH5HqteRe4UNpziG8pq608/edit?tab=t.lbfxo8c09bqd#bookmark=id.1ib6z5f31fld

Überprüfe den aktuellen synchronen Responses API-Evaluierungsablauf im Repository und ziehe anschließend das verlinkte Designdokument für den vorgeschlagenen Batch-Workflow zu Rate. Als abgeschlossen gilt die Aufgabe, wenn Evaluierungsabfragen über die Batch API übermittelt werden, Vorhersagen aus der Batch-Ausgabedatei gelesen werden und diese Vorhersagen mit den entsprechenden tatsächlichen Labels verglichen werden.