pytube x openai whisper (it's really faster_whisper) for Google App Engine (GAE)

why? avoid Open API token usage by using GCP free tier

some aws lambda instructions included at bottom, but i couldnt reduce the package/dependecy library size to 50mb zipped for the life of me.

Run locally (after installing pip dependencies)

gunicorn -w 4 -k uvicorn.workers.UvicornWorker main:app or uvicorn main:app --reload then invoke the API with...

API endpoints (Routes)

/pytube-download

curl http://127.0.0.1:8000/pytube-download to download a youtube video's audio

/pytube-download-and-upload

curl http://127.0.0.1:8000/download-from-YT-and-upload-and-generate-caption to download a youtube video and pump through faster_whisper to generate timestamped captions

GCP App Engine Instructions

youtube tutorial i started with: https://tutlinks.com/deploy-fastapi-app-on-google-cloud-platform/

GCP App Engine pricing resources

pricing calculator: https://cloud.google.com/products/calculator
free tier: https://cloud.google.com/free/docs/free-cloud-features#app-engine
instance classes: https://cloud.google.com/appengine/docs/standard/#second-gen-runtimes
updating app.yaml with preferences: https://cloud.google.com/appengine/docs/standard/reference/app-yaml?tab=python#example

the weird ../../../tmp thing? in main.py

yea it's explained here https://cloud.google.com/appengine/docs/standard/using-temp-files?tab=python

set yo self up for success

rm -rf gae-pytube/ && git clone -b warmup-requests https://github.com/mkandan/gae-pytube.git && cd gae-pytube/ && virtualenv env && source env/bin/activate && pip install -r requirements.txt && gunicorn -w 1 -k uvicorn.workers.UvicornWorker main:app

rm -rf gae-pytube/
git clone -b https://github.com/mkandan/gae-pytube.git
cd gae-pytube/
virtualenv env
source env/bin/activate
pip install -r requirements.txt
gunicorn -w 1 -k uvicorn.workers.UvicornWorker main:app

Change the numerical value in gunicorn to the number of workers you want to run.

success (ideally)

gcloud app create && gcloud app deploy app.yaml && gcloud app browse

gcloud app create gcloud app deploy app.yaml gcloud app browse

Packing for AWS Lambda

1. Install requirements into /lib

pip install -t lib -r requirements.txt

2. Recursively zip up /lib

(cd lib; zip ../lambda_function.zip -r .)

3. Lob main.py into the zip

zip lambda_function.zip -u main.py

All together now

pip install -t lib -r requirements.txt (cd lib; zip ../lambda_function.zip -r .) zip lambda_function.zip -u main.py