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A 2D-force-graph visualizing interconnections in Rosa Luxemburg's works. It will recognize named entities (e.g. persons, locations, nationalities or religious or political groups) from any text source. Just drop files into the text folder. The app will also geolocate all found locations.

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ussiemer/rosa-graph-ui

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2d-force-graph of Rosa Luxemburg's works, ui elements are shown

rosa-graph-ui

A 2D-force-graph visualizing interconnections in Rosa Luxemburg's works. It will recognize named entities (e.g. persons, locations, nationalities or religious or political groups and organizations) from any text source. Just drop files into the text folder.

⚠️ Still in early alpha stage

  • Python backend
  • HTML, CSS, Vanilla Javascript frontend

Open Street Map

The app will try to geolocate all found locations.

2d-force-graph of Rosa Luxemburg's works, ui elements are shown

Text content

All Rosa texts are translations from marxists.org - All rights reserved.

Using

  • quart
  • markdown
  • textblob
  • spacy

Download spaCy modelss

python -m spacy download en_core_web_lg
python -m spacy download de_core_news_md
python -m spacy download pl_core_news_md
python -m spacy download ru_core_news_md
python -m spacy download uk_core_news_md
python -m spacy download zh_core_news_md
python -m spacy download ro_core_news_md
python -m spacy download it_core_news_md
python -m spacy download fr_core_news_md
python -m spacy download es_core_news_md

German NER

python -m spacy download de_core_news_lg # Or _md or _sm

Create .env file

BASE_URL=localhost
APP_NAME=rosa-graph
APP_DESCRIPTION=A forced graph that shows the lemma connections in works of Rosa Luxemburg
CONTACT_MAIL=
COMPANY_NAME=
STREET_ADDRESS=
CITY=
ZIP_CODE=
COUNTRY=
LEGAL_NAME=
HEADER_IMAGE=static/header.png
FOOTER_IMPRINT=rosa-graph
CODEBERG_USERNAME=
CODEBERG_URL=h
KEYWORDS=77
GEOCODE_API_KEY=

You will need an api key from https://geocode.maps.co/

Create virtual environment

    cd /path/to/your/app
    python3 -m venv venv
    source venv/bin/activate
    pip install -r requirements.txt

Or you can just use the docker container

sudo docker run -p 5000:5000 -e BASE_URL="http://localhost:5000" -e APP_NAME="your app name" --name container-name name

Folders in pages will be submenu categories

The hamburger navigation will automatically populate.

  • Create folder

  • Create index.md in folder as a landing-page

  ---
  title:
  author:
  date: 2024-06-05 10:00
  slug: index
  language: en
  ---

  <div id="nameofyourfolder-page-list">
      <p>Loading our services...</p>
  </div>

  • Create your md files. They will appear in the index page-list.

Meta information from markdown (*.md)

You can add any meta-information and use it in your markdown file.

  e.g. {{ page_metadata.yourmetaname }}

Meta information will render and connect to nodes.

pip install nodeenv

add text desc

''' nodeenv -p '''

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A 2D-force-graph visualizing interconnections in Rosa Luxemburg's works. It will recognize named entities (e.g. persons, locations, nationalities or religious or political groups) from any text source. Just drop files into the text folder. The app will also geolocate all found locations.

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