VideoForge
From a creative brief to a media pipeline.
AI video generation and media processing with asynchronous rendering and publishing integrations.
From a creative brief to a media pipeline.
Video generation is a multi-step process involving models, rendering, storage and publishing. These long-running operations need a reliable workflow rather than one large synchronous request.
What I built
I connected a Next.js frontend to FastAPI services, Celery jobs and FFmpeg processing. Model access through LiteLLM and OAuth-based publishing integrations bring generation and delivery into the same workflow.
Generation orchestration
AI-assisted generation workflows coordinate model requests with subsequent media-processing steps.
Asynchronous media work
Celery and FFmpeg handle rendering and processing outside the interactive web request.
Publishing connections
OAuth integrations with YouTube and Google Drive connect content creation to distribution and storage workflows.
Under the surface.
Follow a real product workflow through its application boundaries. Select any step to explore the implementation.
A creative brief becomes a staged media job.
A Celery chain coordinates script generation, speech, composition and upload, with a separate publishing integration.
Project brief
A project defines the material to create. Existing scripts or uploaded voiceovers can be reused by later pipeline stages.
Stable stage boundaries allow reused inputs, long-running work and meaningful failure states. Rendering, storage and publishing have distinct responsibilities.
Conceptual flow based on the implementation. Animated connections illustrate data movement, not live traffic.
Built around the constraints.
Model video creation as a pipeline. Isolate expensive rendering from the interface and make external integrations explicit boundaries.
Discuss the engineering ↗Keep exploring.
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