Some things I think make this different and worthwhile:
• The extension immediately is usable for some real world SEO problems. Like redirect mapping or comparing and clustering data for content gaps. Though I would recommend to build a production system and not rely on this extension.
• There are some great articles and Python code out there. But not everyone feels comfortable with Python or code in general. This is why this is a more hands-on approach with an UI.
• Most code relies on commercial APIs which is an additional hurdle for some people. This is why this extension makes use of the free services of HuggingFace.
• Additionally: Making use of HuggingFace lets you experiment with different embedding models. (Disclaimer: while it does work there is still some work to make it more bugfree)
• I could have deployed this on my own domain (e.g. on <http://valentin.app|valentin.app>) but then this wouldn’t work offline that easily and people might think they would upload their private data to the internet / me. A real application would reduce this even more but then again it wouldn’t be feasible for me. That’s how I ended up with a Chrome extension.
Some things I’d love to talk about:
• Quality of different models for different use cases
• Approximate nearest neighbour algorithms like HNSW (used in this extension)
• pros & cons of vector quantization
<https://github.com/VorticonCmdr/simcheck>
<https://chromewebstore.google.com/detail/simcheck/eoefampiceefbaiejeialndangdcbbgb>
