Sat Chad

YouTube Video: https://www.youtube.com/watch?v=PKLMzISoYq0

all-MiniLM-L6-v2 This is a sentence-transformers model: It maps sentences & paragraphs to a 384 dimensional dense vector space and can be used for tasks like clustering or semantic search.

https://huggingface.co/sentence-transformers/all-MiniLM-L6-v2#all-minilm-l6-v2

run yt1.py to get transcripts run up_quadrant to upsert vectors neural_searcher and service.py need to go into the FastAPI directory (~/python-server) that the front end calls the index.html is in /var/www/html and the js is inside the js folder

.

├── data
├── saylor-vids.txt
├── up_quadrant.py
└── yt1.py

run yt1 to get transcripts
run up_quadrant to do the upsert

Note: The FastAPI API is "neural_searcher.py" and not "app.py" !! My bad. This was very much an experiment which came good!