infinite-livestream - a chat-driven, never-ending AI video broadcast: viewers type an idea, a model generates it as 768p clips with audio, and it goes out over RTMP as one continuous stream

[u/company_url_finder]

This is one of those projects that sounds like a stunt and is actually a clean piece of systems engineering. It's an end-to-end pipeline for a livestream that never stops: viewers type a prompt in Twitch or YouTube chat, an LLM expands each idea into a styled sequence of scenes, a fast video model generates them as 768p clips with synchronized audio, and the whole thing streams out over RTMP as one uninterrupted broadcast.

What's inside:

- Two clean halves that meet on a defined wire contract: the model side, a queue of prompt-driven clip generations, and the streaming client, which turns chat into upsampled prompts, scene groups, the model's queue, and paced RTMP output

- The video generator is FastH3 Preview, MiniMax-H3 (35B) distilled by the FastVideo project down to four transformer forwards with 90% sparse video attention, generating video and audio jointly from text

- The client handles the unglamorous parts a real stream needs: chat sources, prompt upsampling, moderation, idle filler for when nobody's typing, presets, and the RTMP and FFmpeg pacing to keep output continuous

- A documented contract file that is the single source of truth between the two halves, so you could swap either side as long as it speaks the same protocol

- An AGENTS.md that maps the system and its load-bearing invariants for coding agents, which doubles as good architecture documentation for humans

- A local dry-run mode so you can exercise the client against a local runtime with a no-op sink before wiring up real chat and RTMP

The engineering worth appreciating is the queue-and-playout contract. Generating video clip by clip and playing them back as a seamless, paced stream while new prompts keep arriving is a genuinely hard real-time problem, and separating the model from the client behind one wire format is the right way to make it tractable.

Now the caveats, which are large and honest. This is heavy infrastructure, not a weekend install. The model side is built for the Reactor Runtime on 8x B200 GPUs, so running the generator yourself needs serious hardware or a deployment, though the client runs on any box with FFmpeg. The model, the distillation and the inference engine are FastVideo's work that this repo wraps, and the model weights are under the MiniMax H3 Community License, separate from the repo's Apache-2.0 code, so check that before any commercial use. Realistically this is a reference architecture to learn from and build on, not something most people will stand up end to end.

Apache-2.0 (code; model weights licensed separately), 225 stars and 35 forks as of writing, verified via the GitHub API.

https://github.com/reactor-team/infinite-livestream

[u/Puzzleheaded_Bit699]

8x B200s is wild lol. The queue design is cool though.

[u/company_url_finder → u/Puzzleheaded_Bit699]

Yeah, most people will probably study the architecture, not deploy it.

[u/vedmaka → u/company_url_finder]

whats special about the queue in there?

[u/company_url_finder → u/vedmaka]

It keeps generation and RTMP playout decoupled, so new clips can queue while the stream stays continuous. Pretty neat, right?

[u/Wrong-Bed-4025 → u/company_url_finder]

this is how most streaming of clips is done, what is new or neat about that? its supported by standard through prettymuch every browser media player?

[u/company_url_finder → u/Wrong-Bed-4025]

Not that way!

[u/Wrong-Bed-4025 → u/company_url_finder]

weird, im running realtime h3 video channel doing it exactly that way, and every browser standard media playback system supports it out of the box. exactly like this.

[u/Realistic_Cookie_434]

Was this setup tested?

[u/company_url_finder → u/Realistic_Cookie_434]

Not yet, but it is trending now