# source for word embeddings: - german: https://www.deepset.ai/german-word-embeddings => https://int-emb-glove-de-wiki.s3.eu-central-1.amazonaws.com/vectors.txt # source for deployment https://realpython.com/flask-by-example-part-1-project-setup/ # source for word embedding techniques nlp programming course on udemy by "lazy programmer" # source for free .css stylesheet colorlib # free stock photo from pexels.com # venv initialisieren > python3 -m venv venv # venv aktivieren > source venv/bin/activate # dependencies installieren > pip install -r requirements.txt # app lokal starten, so dass jede änderung automatisch reloaded wird > FLASK_ENV=development flask run # app lokal im browser sehen http://localhost:5000/ # adress already in use > ps -fA | grep flask # app nach ec2 pushen https://www.twilio.com/blog/deploy-flask-python-app-aws 1. per ssh zu EC2 instanz verbinden mit > ssh ubuntu@<YOUR_IP_ADDRESS> also > ssh ubuntu@3.67.204.47 (IP aus AWS console => ec2 instanzen abgeguckt) 2. dateien syncen entweder via git > git clone / pull / push oder via rsync > sudo rsync -rv <FULL_PATH>/ ubuntu@<YOUR_IP_ADDRESS>:/home/ubuntu/deployedapp > sudo rsync -rv /Users/magdalena.aretz/code/nlp_scripts/data/GloVe_vectors_de_16000.txt ubuntu@3.67.204.47:/home/ubuntu/nlp_scripts/data/GloVe_vectors_de_16000.txt 3. tmux session aufmachen > tmux new -s test-deployment 4. app starten python3 app.py 5. status checken http://ec2-3-69-27-90.eu-central-1.compute.amazonaws.com:5000/ 16. detach tmux > ctrl + D 17. reaattach tmux > tmux attach -t test-deployment