In April 2025, Almaz Gimaev enhanced labeling automation workflows in the supervisely/docs repository by developing an example that integrates collections with the labeling queue. Using Python and the Python SDK, Almaz demonstrated how to create, manage, and utilize collections to automate labeling tasks, updating the documentation to guide users through these processes. He improved onboarding and developer productivity by clarifying workflow scripts and fixing documentation typos, particularly in the tab widget section. Almaz’s work focused on API integration and documentation quality, providing clear, actionable examples that addressed both technical implementation and user understanding within a concise development period.