During December 2024, Veronica Lyu developed and delivered Predictor logprobs support with flexible output for the stanfordnlp/dspy repository. She enhanced the LM client in Python to propagate and return logprob information alongside predictions, enabling end-to-end traceability for model evaluation and decision-making. Her work introduced output abstraction, allowing predictions to be returned as either strings or dictionaries, which supports diverse downstream integration scenarios. Focusing on API integration and language model workflows, Veronica’s engineering addressed the need for improved evaluation and calibration, resulting in more reliable analytics pipelines. The month’s efforts centered on robust feature delivery rather than bug fixes.