Update README with context.

README.md

@@ -1,36 +1,54 @@
-[![Built with Cookiecutter](https://img.shields.io/badge/built%20with-Cookiecutter-ff69b4.svg?logo=cookiecutter)](https://github.com/cookiecutter/cookiecutter)
+[![Built with Cookiecutter](https://img.shields.io/badge/built%20with-Cookiecutter-ff69b4.svg?logo=cookiecutter)](https://github.com/thinknimble/tn-spa-bootstrapper)
 
-# Vector Demonstration
+# AI-Enabled Search Engine using 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!
+
+This repo demonstrates a prototype application that enables searching for job descriptions using an unstructured, English-language description of a job seeker.
+
+## Watch the Demo on Youtube
+
+[![Video: How We're Building AI Search Engines using LLM Embeddings](http://img.youtube.com/vi/ZCPUmC37HLU/0.jpg)](http://www.youtube.com/watch?v=ZCPUmC37HLU "How We're Building AI Search Engines using LLM Embeddings")
+
+## Links & Resources
+
+- https://www.sbert.net/ - Sentence Transformers package for Python
+- https://github.com/pgvector/pgvector - Vector database plugin for PostgreSQL
+- https://huggingface.co/spaces/mteb/leaderboard - The "Massive Text Embedding" leaderboard from HuggingFace. Look at this to find models you can use to generate embeddings.
+- https://www.djangoproject.com/
 
 ## Setup
 
 ### Docker
+
 If this is your first time...
+
 1. [Install Docker](https://www.docker.com/)
 1. Run `pipenv lock` to generate a Pipfile.lock
 1. Run `cd client && npm install` so you have node_modules available outside of Docker
 1. Back in the root directory, run `make build`
 1. `make run` to start the app
 1. If the DB is new, run `make create-test-data`
-    1. SuperUser `admin@thinknimble.com` with credentials from your `.env`
-    1. User `cypress@thinknimble.com` with credentials from your `.env` is used by the Cypress
-       tests
+   1. SuperUser `admin@thinknimble.com` with credentials from your `.env`
+   1. User `cypress@thinknimble.com` with credentials from your `.env` is used by the Cypress
+      tests
 1. View other available scripts/commands with `make commands`
 1. `localhost:8080` to view the app.
 1. `localhost:8000/staff/` to log into the Django admin
 1. `localhost:8000/api/docs/` to view backend API endpoints available for frontend development
 
-
 ### Backend
+
 If not using Docker...
 See the [backend README](server/README.md)
 
 ### Frontend
+
 If not using Docker...
 See the [frontend README](client/README.md)
 
-
 ## Testing & Linting Locally
+
 1. `pipenv install --dev`
 1. `pipenv run pytest server`
 1. `pipenv run black server`