My related-posts finder script (with LLM and GPT4 enhancement)
I've open-sourced the script I use to find related blog posts (and to describe why they're similar). Works on any set of markdown articles, so should fit into any SSG workflow. Uses embeddings to calculate the similarities, and GPT4 to add descriptive text.
My related-posts finder script (with LLM and GPT4 enhancement) launched on December 7, 2023 with 69 votes, #695 of 3,780 launches that month and more than 90% of that year's launches. The site was still online in September 2026, 2 years on.
In plain words
This open-source script finds related blog posts within markdown article collections and explains why they're similar. It works with any static site generator workflow by using embeddings to calculate content similarity and GPT-4 to generate descriptive text for the connections. It's designed for bloggers and content creators who want to automatically surface related articles without manual curation.
written from the facts on this page · September 2026
From the sources
How I used LLM embeddings to find related posts for my statically-generated blog and then used GPT4 to explain why they're similar.
If you're just interested in the code for this project, you can find it on GitHub: github.com/tomhazledine/related-posts . Try it out and let me know what you think 👍 I've been having a lot of fun lately with embeddings . They are a somewhat-overlooked sideshow to the current GPT/LLM/AI circus, but in my view they are even more interesting than the headline-grabbing chat apps. And unlike the chat interfaces, embeddings are a way to make LLMs actually useful without any of the worries about "hallucination" or just-plain-wrong content. A large part of what I've been using embeddings for is "natural language search" which (at the simplest level) involves defining how similar two bits of text…from tomhazledine.com
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