# cjvt-valency Required submodules: * `https://gitea.cjvt.si/kristjan/cjvt-corpusparser.git` ```bash $ git submodule init $ git submodule update ``` ## Components ### Credentials Copy `env.default` to `env.local` (gitignored). Modify database credentials in `env.local`. The file is used by `make`. ### Database (2 containers) Set db admin, user, pass, etc in 'Makefile'. Spin up the database service and create users: Make sure you create a folder for the data on host machine (see `mongodb-stack.yml` `volumes`. ```bash $ mkdir -p ${HOME}/mongo_container/data/ # default one # $ make database-clean # opt, removes docker services, not data $ make database-service $ make database-users # only first time; user data persists too ``` Populate the database with data form files: * ssj500k.xml * kres.xml * kres_SRL.json Set path to files in `Makefile`. ```bash # spin up a container with python env $ make python-env # install our packages $ make python-env-install # run the code # beforehand, set the data files in Makefile # instead of mounting directories into the container, you can # create a link inside ./data, that points to the desired location # I've separated the processes for better memory management $ make fill-database-ssj $ make fill-database-kres # You can detach from the running process using Ctrl-p + Ctrl-q # this is a long operation # if running on a remote server, use nohup: $ nohup $(make fill-database > fill-database.log) & ``` If all goes well, we should be able to inspect the database, filled with corpora, on `0.0.0.0:8087`. ### Flask backend (1 container) Relies heavily on the database. Set that up first. ```bash # spin up container $ make python-env # install our packages $ make python-env-install # needs to be ran once to modify a new database $ make backend-prepare-db # if you have the file prepared (sskj_senses.json), you can # fill the database with some senses $ make sskj-senses # with debugger $ make backend-dev # production $ make backend-prod ``` API endpoints: * GET word list (pre-cached) * GET reduced frames (pre-cached) * POST senses * User auth logic ### Vue frontend (1 container) Relies on Flask backend. Before running `make`, you might need to set the correct api address. Check `./src/frontend_vue/config/config_prod.json`. bash ``` # $ make frontend-dev # development $ make frontend-prod ``` App available on: `http://0.0.0.0:8080`. ## Production deployment Prerequisite: machine with free ports 80 and 8084. ### Database Either build the database from scratch (lenghty process) using above instructions or just migrate the database from the faculty server (recommended). Build container my-mongo: ```bash # run once and destroy containers $ make database-service ``` ### Backend Set database connection details in `/src/backend_flask/db_config.py`. Change 'valuser' and 'valuserpass' to the database user. ```bash mongodb://valuser:valuserpass@my_mongo/valdb ``` In the above line, replace `valuser` with the username and `valuserpass` with the password that was used to create the database tables (the values were set in the root Makefile). You can also set the number of workers in `/src/backend_flask/entrypoint.sh`. In line with `gunicorn -t 4 -b 127.0.0.1:8084 app:app`, edit the `-t` parameter. Rule of thumb is 2x number of available CPU cores. Build the backend container: ```bash # From git root $ make build-backend-flask ``` ### Frontend Set the server address (where backend will be runnig) in `src/frontend_vue/config/config_prod.json`. Build the `/dist` folder that contains the static app (we will be using Nginx to serve it). ```bash # From git root $ make build-frontend-prod ``` All set, now run the stack. Stack configuration in `production.yaml`. ```bash # From git root $ make deploy-prod-stack ``` ## Uploading a mongo dump There's a 15GB mongo dump containing the fully processed kres and ssj data. We can use that file to deploy our aplication. With this database, we will need a minimum of 8GB ram to serve the app. If the server is struggling, frontend will throw "Network errors". Check `0.0.0.0:8081` and remove (or backup) the current example database `valdb`. Run the stack with mongo port mapped: (uncomment the lines in `production.yaml`) ```yml ports: - 27017:27017 ``` Run a separate my-mongo container with the mounted data: ```bash $ mongo run -it --net host -v /dumps my-mongo /bin/bash ``` Inside the container (edit the uesrname, password): ```bash $ mongorestore /dumps/valdb --db valdb --uri=mongodb://valuser:valuserpass@0.0.0.0:27017 ``` After uploading, restart the stack with `27017` commented out.