The traditional recommender system has been designed to mostly optimize for viewer consumption, and with the rise of short form videos, the boundaries between consumption and participation have blurred. This shift presents an opportunity to optimize recommender systems not only for passive consumption, but also for active participation in content creation. In this paper, we document the development of a recommender system that provides inspiration to existing content uploaders and new future content uploaders to encourage participation. Our contributions are two-fold: 1) Inspiration Framework: We present a novel framework for building a recommender system that goes beyond traditional consumption-focused metrics, specifically addressing the need for creative inspiration to lower barriers for participation. This framework is adaptable in the design of large-scale recommender systems in other domains. 2) Empirical Evaluation: We conduct systematic evaluation via live experiments to prove the values of the proposed system in increasing daily participation and participants.