Let's Code an AI Search Engine with LLM Embeddings, Django, and pgvector

A lot of people have asked us for ideas of how they can leverage Large Language Models (LLMs) for their business applications. A common example is to use the native language comprehension capabilities of LLMs to find matching content. This makes LLMs an excellent tool for search!

In this video, ThinkNimble CTO William Huster walks through how he built a prototype application that enables searching for job descriptions using an unstructured, English-language description of a job seeker.

The code for this demo can be found here:

Technologies used in this demo:

- Django
- PostgreSQL + pgvector
- Python sentence-transformers library

Links and Resources:

[pranayaryal]

This guy is quite fast and knowledgeable. Dense content.I had initially increased the speed but had to bring it back to normal.

[JOHNSMITH-verq]

Dude this is good content. Legit. Serious project but still doable for solo dev. And obviously some serious chops by creator. Really handy.