Hi Romain On Sun, Apr 26, 2026 at 07:40:52PM -0500, Romain Beauxis via ffmpeg-devel wrote: > Hi Michael, > > Le ven. 24 avr. 2026 à 04:02, Michael Niedermayer via ffmpeg-devel > <[email protected]> a écrit : > > > > Hi > > > > Some question about fairy design > > > > Fairy is written in python, > > the main script does > > * fetches the forges data (separate thread, cache and all) > > * spawns LLM workers > > * old style UI with a simple yes/next/skip/redo/quit for each LLM response > > > > The LLM workers each call a seperate wraper (aka new process) > > which then contains the code specific for openai or in the future antropic > > and others > > > > The problem iam running into with this is, as i want to use multiple agents > > (ATM teh openai code uses 2, we use a gpt-5.4 nano to setup the container, > > well basically untar our git repositories) > > and then the main gpt-5.4 reviewing the code > > > > Now the easy thing is to just add a claude / antropic wraper but this > > actually feels like bad design > > > > what i was thinking is to rather get rid of the process and do these > > "wrapers" > > fully in python. > > The reason why, is simply, i want to be able to querry multiple LLMs > > and combine their reviews and these wraper feel a bit wrong for that > > > > Its easy to querry openai 3 times and have openai combine 3 results > > IN the openai wraper. But that will keep bloating up the wraper over time > > and make them increasingly non interchangeable and also have more logic > > where it doesnt belong > > > > And as my idea was to try to have both GPT and Claude > > do the review and combine their findings that kind of makes the > > wrappers at process level feel a bit heavy > > How are you planning on merging the reviews? I'm curious as to how > this can be done while keeping the review content at a reasonable > level of verbosity and accuracy..
I have no idea, i intend to figure that out when/if i implement that :) But the merging LLM would be supposed to "understand" the reviews it merges, not copy and paste. thx [...] -- Michael GnuPG fingerprint: 9FF2128B147EF6730BADF133611EC787040B0FAB Complexity theory is the science of finding the exact solution to an approximation. Benchmarking OTOH is finding an approximation of the exact
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