Aidar Dautov developed an end-of-sentence token handling control for the turbo-llm/turbo-alignment repository, focusing on improving chat data preprocessing. He introduced a configurable single_eos setting in the Python-based data processing pipeline, which prevents the double addition of EOS tokens during dataset preparation. This feature-flag style approach to configuration management allows for flexible extension of future preprocessing rules. By addressing duplicate EOS token insertion, Aidar enhanced the reliability and accuracy of chat dataset management, supporting cleaner downstream model training and evaluation. His work demonstrated a thoughtful application of data processing and configuration management skills to solve a targeted data quality issue.