Tag: natural language processing

I explored using LLMs for checking web API browser compatibility. Existing LLMs struggle with outdated data, so I experimented with MDN's Browser Compat Data (BCD). Initial trials using raw BCD JSON with GPT-4 had limitations. To improve this, I converted the BCD into English descriptions of API support and loaded it into a Polymath instance. This allows natural language queries about API compatibility across browsers, like "Is CSS Grid supported in Safari, Firefox, and Chrome?" or "When was CSS acos available in Chrome?". The results are promising, but further refinement is needed to ensure accuracy and reliability.

I built Ask Paul, a generative AI demo that answers front-end web dev questions using my content. It leverages Polymath-AI to index content, find related concepts, and generate summaries by creating embedding vectors, using cosine-similarity, and querying OpenAI. The implementation has a UI, a Polymath Client, and a Polymath Host. It's super cool how accessible this tech is now!