
Worked on enhancing model run tracking in the Labelbox/labelbox-python repository by introducing a model_app_id field to the model run creation flow. This addition, implemented using Python and focused on backend development and API integration, allowed for precise association of model runs with Foundry apps. The work included updating the ModelRun schema and exposing the new field through GraphQL, ensuring consistency across API responses and mutations. These changes improved traceability, observability, and analytics for model runs without introducing major bug fixes. The approach emphasized maintainability and alignment with repository standards, contributing to more robust and transparent backend workflows.
May 2025: Delivered end-to-end model run tracking enhancement in Labelbox Python integration by adding model_app_id to the model run creation flow, exposing it via GraphQL, and updating the ModelRun schema. This enables precise association of model runs with Foundry apps, improving observability, debugging, and analytics. No major bugs fixed this month; changes focused on API consistency, maintainability, and alignment with repo standards.
May 2025: Delivered end-to-end model run tracking enhancement in Labelbox Python integration by adding model_app_id to the model run creation flow, exposing it via GraphQL, and updating the ModelRun schema. This enables precise association of model runs with Foundry apps, improving observability, debugging, and analytics. No major bugs fixed this month; changes focused on API consistency, maintainability, and alignment with repo standards.

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