I was pleasantly surprised that this didn't overcomplicate the process of piping captions from yt-dlp to llm. It doesn't look like it relies on captions being available from YouTube, but this could be pretty easily overcome by adding a whisper.cpp step.
This setup is quite similar to the one fabric [1] patterns, the limitation i encountered while testing those with local llms was the prompt efficacy.
More specifically the output format of the prompt is rarely respected properly.
In addition to this the tone/sentiment of the answers vary a lot between models, as usual.
Are there more compliant models wrt respecting prompt instructions? (assuming comparable parameter sizing)
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[ 0.21 ms ] story [ 20.1 ms ] threadIn addition to this the tone/sentiment of the answers vary a lot between models, as usual.
Are there more compliant models wrt respecting prompt instructions? (assuming comparable parameter sizing)
[1] https://github.com/danielmiessler/fabric