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        Technology Used
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Technology Used
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Technology Used

Shoonya Backend
Built using Python and
Django
⁠
REST Framework,
Shoonya Backend
⁠
is used for storing, retrieving and modifying data pertaining to both user, workspace, organization, project and task management as well as annotation. It will be further enhanced to have functions to automate certain functionalities like extraction of data, generation of machine translation, and cleaning up audio.
Shoonya Frontend
Built using React,
Shoonya Frontend
⁠
facilitates user, workspace, organization, project and task management in the user interface and uses the frontend package of
Label Studio
⁠
, an open-source data labeling tool, to allow the language experts/ annotators to perform data annotation.
Label Studio Frontend
⁠
is a JavaScript web app developed using React and MobX-state-tree (MST).
Installing Frontend and Backend
Shoonya Backend can be installed by following the steps in the
README.md
⁠
of GitHub documentation.
Shoonya Frontend can be installed by following the steps in the
README.md
⁠
of GitHub documentation.
Shoonya Annotation Templates
Shoonya uses
Label Studio templates
⁠
for showing different UIs to the annotators/ language experts based on the annotation task to be done. These templates are Javascript XML (JSX) files which use tags to handle the visual layout of the annotation page as well as to specify the data to be annotated. Label Studio Frontend supports both in-built templates as well as custom templates developed by the user. In the current Shoonya version 0.1, OCR annotation task uses the existing template of Label Studio and the translation tasks (monolingual translation and translation editing) use the custom templates.
Shoonya Backend Models
With Shoonya being built using Django REST Framework and Python, a Django model represents a database table with each of its attributes representing a field. All the Django models pertaining to user, workspace, organization, project, task and data management are present
here
⁠
along with the specifications of each attribute of the model.
Database
PostgreSQL is the database used for Shoonya.
Shoonya Backend API
The APIs pertaining to user, workspace, organization, project, task and data management are present
here
⁠
.
Apart from the basic CRUD (Create, Read, Update and Delete) operations, the following are the APIs which are used to perform other operations:
A function API for splitting a block of text to separate sentences and storing each sentence in a separate dataset called ‘Sentence Text’.
A function API for storing a block of text annotated from an OCR document into a separate dataset called ‘Block Text’.
A project API for archiving and publishing a project
A project API for exporting a project
A project API for pulling new items to a project
A create project API which automatically creates annotation tasks for a project during project creation itself
A task API for assigning users to a task
Users API for invite generation for inviting new users to Shoonya
Users APIs for creating, refreshing and verifying JWTs (JSON Web Tokens)
Workspace API for assigning workspace manager
Workspace API for archiving the workspace

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