Skip to content

Latest commit

 

History

History
67 lines (46 loc) · 2.12 KB

system-architecture.md

File metadata and controls

67 lines (46 loc) · 2.12 KB
Raw

System architecture

TARGER consists from three different parts:

  • Frontend
  • Backend
  • Batch processing (building the search index)

Frontend

The frontend is a webserver built with the Flask framework, to use the argument search engine with a web browser.

Backend

The backend contains logic for argument classification and generating the annotated results. It exposes a REST-like API which is used by the frontend. The backend depends on the BiLSTM-CNN-CRF architecture for sequence tagging. A Swagger API interface allows for quickly testing annotation and documents the API.

Reverse proxy

Both backend and frontend can run behind a reverse proxy like Nginx or Apache 2. However, you must configure the reverse proxy to forward the original address and some additional headers. If you don't specify X-Script-Name, the backend will confuse API endpoints and Swagger won't work.

Nginx configuration 
location /subdir {
    proxy_pass http://HOSTNAME:PORT;
    proxy_http_version 1.1;
    proxy_set_header Upgrade $http_upgrade;
    proxy_set_header Connection "upgrade";
    proxy_set_header Host $host;
    proxy_set_header X-Script-Name /subdir;
}
Apache 2 configuration 
<Location /subdir>
    Header add X-Script-Name "/subdir"
    RequestHeader set X-Script-Name "/subdir"
    
    ProxyPass http://HOSTNAME:PORT
    ProxyPassReverse http://HOSTNAME:PORT
</Location>

Batch processing

The batch processing module provides scripts for argument labeling and indexing to Elasticsearch.

Argument labeling

Data is being parsed and labeled by applying the model in a parallel way.

Elasticsearch indexing

Data produced by argument labeling is being parsed and saved to the ES index.