Hey Max, do you use a custom wrapper to interface with the API or is there some already established client you like to use?
If anyone else has a suggestion please let me know too.
llm -m o4-mini -f github:simonw/llm-hacker-news -s 'write a new plugin called llm_video_frames.py which takes video:path-to-video.mp4 and creates a temporary directory which it then populates with one frame per second of that video using ffmpeg - then it returns a list of [llm.Attachment(path="path-to-frame1.jpg"), ...] - it should also support passing video:video.mp4?fps=2 to increase to two frames per second, and if you pass ?timestamps=1 or ×tamps=1 then it should add a text timestamp to the bottom right conner of each image with the mm:ss timestamp of that frame (or hh:mm:ss if more than one hour in) and the filename of the video without the path as well.' -o reasoning_effort high
Any time I use it like that the prompt and response are logged to a local SQLite database.
More on that example here: https://simonwillison.net/2025/May/5/llm-video-frames/#how-i...
Simon: while that example is impressive, it is also complicated and hard to read in an HN comment.
Nowadays for writing code to interface with LLMs, I don't use client SDKs unless required, instead just hitting HTTP endpoints with libraries such as requests and httpx. It's also easier to upgrade to async if needed.
As an alternative you could always use OpenWebUI
It uses OpenRouter for the API layer to simplify use of APIs from multiple providers, though I'm also working on direct integration of model provider API keys—should release it this week.