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I’ve been building GoModel since December with a couple of contributors. It's an open-source AI gateway that sits between your app and model providers like OpenAI, Anthropic or others.

I built it for my startup to solve a few problems:

  - track AI usage and cost per client or team
  - switch models without changing app code
  - debug request flows more easily
  - reduce AI spendings with exact and semantic caching

How is it different?

  - ~17MB docker image
    - LiteLLM's image is more than 44x bigger ("docker.litellm.ai/berriai/litellm:latest" ~ 746 MB on amd64)
  - request workflow is visible and easy to inspect    
  - config is environment-variable-first by default

I'm posting now partly because of the recent LiteLLM supply-chain attack. Their team handled it impressively well, but some people are looking at alternatives anyway, and GoModel is one.

Website: https://gomodel.enterpilot.io

Any feedback is appreciated.

Some of the features: multi-track timeline, frame accurate seek, MP4 export, audio, video, image, and text tracks, and a WebGL backed canvas where available. It also works on mobile.

Under the hood, WebCodecs handles frame decode for timeline playback and scrubbing, which is what makes seeking responsive since decode runs on the hardware decoder when the browser supports it. FFmpeg compiled to WebAssembly handles final encode, format conversion, and anything WebCodecs does not cover. Rendering goes through Pixi.js on a WebGL canvas, with a software fallback when WebGL is not available. Projects live in IndexedDB and the heavy work runs in Web Workers so the UI stays responsive during exports.

Happy to answer technical questions about the tradeoffs involved in keeping the whole pipeline client-side. Any feedback welcome.

Link: https://vidstudio.app/video-editor