Contains the tool for viewing valency frames and adding user-defined senses to underlying sentences.
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README.md

cjvt-valency

Required submodules:

  • https://gitea.cjvt.si/kristjan/cjvt-corpusparser.git
$ git submodule init
$ git submodule update

Components

Database (2 containers)

Set db admin, user, pass, etc in 'Makefile'.
Spin up the database service and create users:

# $ make database-clean  # opt
$ make database-service
$ make database-users

Populate the database with data form files:

  • ssj500k.xml
  • kres.xml
  • kres_SRL.json

Set path to files in Makefile.

# spin up a container with python env
$ make python-env

# install our packages
$ make python-env-install

# run the code
$ make fill-database

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.

$ make python-env

# $ make backend-dev  # development
$ 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.