How OpenHiggsfield Eliminated Next.js Server Action Bottlenecks for AI Video Generation

OpenHiggsfield, an open-source studio UI for multi-model video and image generation, tackled a core Next.js performance problem where Server Actions are serialized per client connection, causing UI freezes during concurrent AI tasks. The naive approach of firing individual polling actions for each generation job created a request queue that stalled user interactions like form submissions. To fix this, the team built a client-side coalescing engine that pools all active generation job IDs and dispatches a single batched Server Action per interval instead of multiple isolated ones. This single-flight fan-out architecture eliminates queue contention, keeping the UI responsive even while dozens of long-running inference tasks run in parallel. The platform also addresses API schema fragmentation across 38 AI providers — including Kling, ByteDance Seedance, and Black Forest Labs Flux — through a declarative multi-model catalog translation layer that unifies parameter validation and routing.