Comment by resonious
4 days ago
I tried this (though with a different tool called aichat) for extremely simple stuff like just "convert this mov to mp4" and it generated overly complex commands that failed due to missing libraries. When I removed the "crap" from the commands, they worked.
So much like code assistance, they still need a fair amount of baby sitting. A good boost for experienced operators but might suck for beginners.
Plus you need to know the format of your source file to design the command correctly. How many audio tracks, is the first video track a thumbnail or the video, are the subtitles tracks forced, etc.
And in some situations ffmpeg has some warts you have to go around. Like they introduced recently a moronic change of behaviour where the first sub tracks becomes forced/default irrespective of the original forced/default flag of the source. You need to add "-default_mode infer_no_subs" to counter that.
I usually just paste the output of `ffprobe` into Claude when it's ambiguous. Works a treat.
My feelings exactly, but I think that's OK!
It's another tool and one that might actually improve with time. I don't see GNU's man pages getting any better spontaneously.
Whoa, what if they started to use AI to auto-generate man pages...
> Whoa, what if they started to use AI to auto-generate man pages...
That’s the time to start my career in woodworking.
I already generate man pages (and POD) with Claude for my new projects. :D
It works really well.
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> what if they started to use AI to auto-generate man pages...
Then they'd be wrong about 20% of the time, and still no one would read them. ;-)
(NB: I'm of the age that I do read them, but I think I'm in the minority.)
Reading this feels like seing a guy getting his first car in 1920 and complaining he still has to drive it himself.
To me it's more like a guy getting his first car and complaining that the car is driving him in a direction that may or may not be correct, despite his best efforts to steer it where he wants to go. And the only way to know whether he ends up in the right place is to get out of the car, look around, and maybe ask more experienced drivers. Failing that, his only option is to get back in and hope to be luckier in the next trip.
Or he can just ditch the car and walk. Sure, it's slower and requires more effort, but he knows exactly how to do that and where it will take him.
The beer brewers in my home town used to have a self-driving horse and cart which knew the daily delivery route going by all pubs and didn't really need a human to steer it or indeed be conscious during the trip. Expectedly, the delivery guy would get drunk first thing in the morning and just get carted about collecting the money.
Pony & trap could be largely self-driving, after an initial training period. That would have been a distinct negative to "upgrading" for some, I'd imagine.
It's speed and load capacity vs self-driving.
If we could imagine wiring a pony to control a car, its brain, while good at navigation, would likely be inadequate at the speed that a car attains.
Sell that guy probably got carried home by his horse after drinking half a bottle of whiskey, so maybe he had a point.
Or maybe calling a cab and telling the cab driver each direction to get to the destination instead of the cab driver just taking you there.
My experience exactly.
I no longer check with these AI tools after a number of attempts. Unrelated, a friend thought there was a NFL football game last Saturday at noon. Checking with Google's Gemini, it said "no", but there was one between two teams whose season had ended two weeks before at 1:00 Eastern Time and 2:00 Central. (The times are backwards.)
Do LLMs have knowledge of current events?
Meta.ai got it right. The free chatGPT only has data up till 2021 or something like that.
> Do LLMs have knowledge of current events?
I don't think the notion of "current" has been explained to them. Thay just define it out of context.
I mean, some are capable of searching the web.
Ask them about the fire in LA in 2025 January.
> "convert this mov to mp4"
Did any of the commands look like the ones in the left window:
https://beta.gitsense.com/?chats=12850fe4-ffb1-4618-9215-c13...
The left window contains a summary of all the LLMs asked, including all commands. The right window contains the individual LLM responses.
I asked about gotchas with missing libraries as well, and Sonnet 3.5 said there were. Were these the same libraries that were missing for you?
Looking at this, I am pretty sure I also received a "libx264" clause. Removing it made the command work for me.
I don't disagree that we need to be cautious with LLMs, but I've personally stopped asking GPT-4/GPT-4 mini for technical answers. Sonnet 3.5 and DeepSeek V3 (which is much cheaper but still not as good as Sonnet) are your best bet for technical questions.
Where I find GPT to perform better than Sonnet is with text processing. GPT seems to better understand what I want when it comes to processing documents.
I'm convinced that no LLM provider has created or will create a moat, and that we will always need to shop around for an answer.
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libx264 is the best encoder for h264 ffmpeg has to offer so it's pretty important you bundle it in your ffmpeg install. Those commands are perfectly standard, I've been using something like that for 10+ years
what exactly do you want the llm to do here? if the ask was so unambiguous and simple that it could be reliably generated, then the interface wouldn't be so complicated to use in the first place! LLMs are not in any way best suited for one-shot prompt => perfect output, and expectations to that effect are extremely unreasonable. the reason why LLMs are still hard for beginners to use is because the software is hard to use correctly. as with LLM output goes life itself: the results you get from using a tool can only ever be as good as the (mental) model used to choose that tool & the inputs to begin with. if all the information required to generate the output were contained by the initial prompt, then there would be absolutely no need to use the LLM at all in the first place.
Hate to be that guy, but which LLM was doing the generation? GPT-4 Turbo / Claude 3.x have not really let me down in generating ffmpeg commands - especially for basic requests - with most of their failures resulting from domain-specific vagaries that an expert would need to weigh in on m
GPT-4
Fair enough. If you remember what you were testing with, I'd love to try it again to see if things are better now.
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Hate to be that guy, but which model works without fail for any task that ffmpeg can do?
"Writing working commands first try for every single ffmpeg feature that exists" is the highest bar I've ever heard of, I love it. I'm gonna start listing it as a requirement on job postings. Like an ffmpeg speedrun.
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I don't think there's a single human on or outside of this planet that can meet that requirement, but Claude has been pretty good to me. It's certainly a much better starting point than pouring over docs and SO posts.
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I know I struggled on getting a good command to “simply” make the videos from my Z8 smaller (in file size).
Usually the color was wrong and I don’t care enough to learn about colorspaces to figure out how to fix it and it’s utterly insane how difficult it is even with LLMs.
Just reencode it as is but a little more lossy. Is that so hard?
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This doesnt exist in reality so in one sense, you could challenge the relevance
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