Show HN: LLMpeg

FFMpeg is one of those tools that is really quite hard to use. The sheer surface area of the possible commands and options is incredible and then there is so much arcane knowledge around the right settings. Its defaults aren't very good and lead to poor quality output in a lot of cases and you can get some really weird errors when you combine certain settings. Its an amazingly capable tool but its equipped with every foot gun going.

It's good that you have a "read" statement to force confirmation by the user of the command, but all it takes is one errant accidental enter to end up running arbitrary code returned from the LLM.

I'd constrain the tool to only run "ffmpeg" and extract the options/parameters from the LLM instead.

Most commonly I use ffmpeg to extract a slice of an audio or video file without re-encoding.

In case it interests folks, I made a tool called ffslice to do this: https://github.com/jchook/ffslice/

i think this type of interaction is the future in lots of areas. i can imagine we replace API's completely with a single endpoint where you hit it up with a description of what you want back. like, hit up 'news.ycombinator.com/api' with "give me all the highest rated submissions over the past week about LLMs". a server side LLM translates that to SQL, executes the query, returns the results.

this approach is broadly applicable to lots of domains just like FFMpeg. very very cool to see things moving in this direction.

Reminds me of llm-jq: https://github.com/simonw/llm-jq

The system prompt may be a bit too simple, especially when using gpt-4o-mini as the base LLM that doesn't adhere to prompts well.

> You write ffmpeg commands based on the description from the user. You should only respond with a command line command for ffmpeg, never any additional text. All responses should be a single line without any line breaks.

I recently tried to get Claude 3.5 Sonnet to solve an FFmpeg problem (write a command to output 5 equally-time-spaced frames from a video) with some aggressive prompt engineering and while it seems internally consistent, I went down a rabbit hole trying to figure out why it didn't output anything, as the LLMs assume integer frames-per-second which is definitely not the case in the real world!

Parsing simple English and converting it to ffmpeg commands can be done without an LLM, running locally, using megabytes of RAM.

Check out this AI:

  $ apt install cdecl
  [ ... ]
  After this operation, 62.5 kB of additional disk space will be used.
  [ ... ]
  $ cdecl
  Type `help' or `?' for help
  cdecl> declare foo as function (pointer to char) returning pointer to array 4 of pointer to function (double) returning double
  double (*(*foo(char *))[4])(double )

If FFMpeg's command line bugged me badly enough, I'd write "ffdecl".

Small nit: this should check/exit if OPENAI_API_KEY is empty

FFmpeg is a tool that I now use purely with LLM help (and it is the only such tool for me). I do however want to read the explanation of what the AI-suggested command does and understand it instead of just YOLO running it like in this project.

I have had the experience where GPT/LLAMA suggested parameters that would have produced unintended consequences and if I haven't read their explanation I would never know (resulting in e.g. a lower quality video).

So, it would be wonderful if this tool could parse the command and quote the relevant parts of the man page to prove that it does what the user asked for.

this might be the best use of llm's discovered to date

I'd probably use GitHub's `??` CLI or `llm-term` that already this without needing to install a purpose-specific tool. Do you provide any specific value add on top of these?

probably more helpful for learning than actual productivity with ffmpeg but really like this project (zap emoji)