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https://github.com/rggh/satchad

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https://github.com/rggh/satchad

bitcoin docker fastapi findthatbit huggingface-transformers nginx numpy qdrant qdrant-vector-database sentence-transformers youtube

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findthatbit.com + findthatbit.info

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# 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!