kristjan/cjvt-valency
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Contains the tool for viewing valency frames and adding user-defined senses to underlying sentences.
24 Commits 5 Branches 0 Tags 66 MiB
Python 46.6%
Vue 27.2%
JavaScript 18.5%
HTML 2.6%
Makefile 2.5%
Other 2.6%
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voje 7645c8724d frontend dev env fix
2019-03-22 18:00:56 +01:00
data corpusparser finished python dict representation; TODO .json and DB 2019-03-13 08:59:27 +01:00
dip_src frontend_devops fix 2019-03-20 17:49:34 +01:00
dockerfiles backend env dockerfile 2019-03-22 14:50:47 +01:00
src frontend dev env fix 2019-03-22 18:00:56 +01:00
.gitignore make frontend dev/prod ready 2019-03-19 08:11:26 +01:00
.gitmodules make fill_database 2019-03-17 17:25:59 +01:00
Makefile backend env dockerfile 2019-03-22 14:50:47 +01:00
README.md make fill_database 2019-03-17 17:25:59 +01:00

README.md

cjvt-valency

Required submodules:

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

Components

Database (2 containers)

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 on 0.0.0.0:8087.

Flask backend (1 container)

Input: see Database

API endpoints:

  • GET word list (pre-cached)
  • GET reduced frames (pre-cached)
  • POST senses
  • User auth logic

Vue frontend (1 container)

  • ngnix server

Deployment

Preflight:

  • get up DB
  • prepare DB

Flight:

  • start backend
  • start frontend