And what’s the plan for determinism? For repeat workflows it’s important that the same pipeline produces the same cut each time. Are node outputs consistent or does the model vary run to run?
since we're building on top of LLMs which are by nature probabilistic, you won't produce the exact same frame-level cut each time, but of course there is still determinism in the expected outputs
for example, if you have a workflow setup to create 5 clips from a podcast and add b-rolls and captions and reframe to a few different aspect ratios, any time you invoke this workflow (regardless of which podcast episode you're providing as input), you'll get 5 clips back that have b-rolls, captions, and are reframed to a few different aspect ratios
however, which clips are selected, what b-rolls are generated, where they're placed — this is all non-deterministic
you can guide the agent via prompting the tiles individually, but that's still just an input into a non-deterministic machine
Or just let the user adjust the seed and temperature themselves, or hide it under a checkbox that says deterministic with your chosen seed and temperature.
