Coder Social home page Coder Social logo

tavallaie / annif Goto Github PK

View Code? Open in Web Editor NEW

This project forked from natlibfi/annif

0.0 0.0 0.0 8.29 MB

Annif is a multi-algorithm automated subject indexing tool for libraries, archives and museums.

Home Page: https://annif.org

License: Other

Shell 0.20% Python 96.15% CSS 0.76% HTML 2.46% Dockerfile 0.44%

annif's Introduction

DOI License Container image CI/CD codecov Scrutinizer Code Quality Code Climate OpenSSF Scorecard codebeat badge CodeQL Quality Gate Status docs Code style: black

Annif is an automated subject indexing toolkit. It was originally created as a statistical automated indexing tool that used metadata from the Finna.fi discovery interface as a training corpus.

This repo contains a rewritten production version of Annif based on the prototype.

Finto AI is a service based on Annif; see the source code of Finto AI and the ๐Ÿค— Hugging Face Hub collection containing the models Finto AI uses.

Basic install

Annif is developed and tested on Linux. If you want to run Annif on Windows or Mac OS, the recommended way is to use Docker (see below) or a Linux virtual machine.

You will need Python 3.9-3.12 to install Annif.

The recommended way is to install Annif from PyPI into a virtual environment.

python3 -m venv annif-venv
source annif-venv/bin/activate
pip install annif

You will also need NLTK data files:

python -m nltk.downloader punkt

Start up the application:

annif

See Getting Started in the wiki for more details.

Shell compeletions

Annif supports tab-key completion in bash, zsh and fish shells for commands and options and project id, vocabulary id and path parameters.

To enable the completion support in your current terminal session use annif completion command with the option according to your shell to produce the completion script and source it. For example, run

source <(annif completion --bash)

To enable the completion support in all new sessions first add the completion script in your home directory:

annif completion --bash > ~/.annif-complete.bash

Then make the script to be automatically sourced for new terminal sessions by adding the following to your ~/.bashrc file (or in some alternative startup file):

source ~/.annif-complete.bash

For details and usage for other shells see Click documentation.

Docker install

You can use Annif as a pre-built Docker container image from quay.io/natlibfi/annif repository. Please see the wiki documentation for details.

Development install

A development version of Annif can be installed by cloning the GitHub repository. Poetry is used for managing dependencies and virtual environment for the development version.

See CONTRIBUTING.md for information on unit tests, code style, development flow etc. details that are useful when participating in Annif development.

Installation and setup

Clone the repository.

Switch into the repository directory.

Install pipx and Poetry if you don't have them. First pipx:

python3 -m pip install --user pipx
python3 -m pipx ensurepath

Open a new shell, and then install Poetry:

pipx install poetry

Poetry can be installed also without pipx: check the Poetry documentation.

Create a virtual environment and install dependencies:

poetry install

By default development dependencies are included. Use option -E to install dependencies for selected optional features (-E "extra1 extra2" for multiple extras), or install all of them with --all-extras. By default the virtual environment directory is not under the project directory, but there is a setting for selecting this.

Enter the virtual environment:

poetry shell

You will also need NLTK data files:

python -m nltk.downloader punkt

Start up the application:

annif

Getting help

Many resources are available:

Publications / How to cite

See below for some articles about Annif in peer-reviewed Open Access journals. The software itself is also archived on Zenodo and has a citable DOI.

Citing the software itself

See "Cite this repository" in the details of the repository.

Annif articles

  • Golub, K.; Suominen, O.; Mohammed, A.; Aagaard, H.; Osterman, O, 2024. Automated Dewey Decimal Classification of Swedish library metadata using Annif software. Journal of Documentation, in press. https://doi.org/10.1108/JD-01-2022-0026
    See BibTex
    @article{golub2024annif,
      title={Automated Dewey Decimal Classification of Swedish library metadata using Annif software},
      author={Golub, Koraljka and Suominen, Osma and Mohammed, Ahmed Taiye and Aagaard, Harriet and Osterman, Olof},
      journal={J. Doc.},
      year={in press},
      doi = {10.1108/JD-01-2022-0026},
      url={https://www.emerald.com/insight/content/doi/10.1108/JD-01-2022-0026},
    }
    
  • Suominen, O.; Inkinen, J.; Lehtinen, M., 2022. Annif and Finto AI: Developing and Implementing Automated Subject Indexing. JLIS.It, 13(1), pp. 265โ€“282. URL: https://www.jlis.it/index.php/jlis/article/view/437
    See BibTex
    @article{suominen2022annif,
      title={Annif and Finto AI: Developing and Implementing Automated Subject Indexing},
      author={Suominen, Osma and Inkinen, Juho and Lehtinen, Mona},
      journal={JLIS.it},
      volume={13},
      number={1},
      pages={265--282},
      year={2022},
      doi = {10.4403/jlis.it-12740},
      url={https://www.jlis.it/index.php/jlis/article/view/437},
    }
    
  • Suominen, O.; Koskenniemi, I, 2022. Annif Analyzer Shootout: Comparing text lemmatization methods for automated subject indexing. Code4Lib Journal, (54). URL: https://journal.code4lib.org/articles/16719
    See BibTex
    @article{suominen2022analyzer,
      title={Annif Analyzer Shootout: Comparing text lemmatization methods for automated subject indexing},
      author={Suominen, Osma and Koskenniemi, Ilkka},
      journal={Code4Lib J.},
      number={54},
      year={2022},
      url={https://journal.code4lib.org/articles/16719},
    }
    
  • Suominen, O., 2019. Annif: DIY automated subject indexing using multiple algorithms. LIBER Quarterly, 29(1), pp.1โ€“25. DOI: https://doi.org/10.18352/lq.10285
    See BibTex
    @article{suominen2019annif,
      title={Annif: DIY automated subject indexing using multiple algorithms},
      author={Suominen, Osma},
      journal={{LIBER} Quarterly},
      volume={29},
      number={1},
      pages={1--25},
      year={2019},
      doi = {10.18352/lq.10285},
      url = {https://doi.org/10.18352/lq.10285}
    }
    

License

The code in this repository is licensed under Apache License 2.0, except for the dependencies included under annif/static/css and annif/static/js, which have their own licenses, see the file headers for details. Please note that the YAKE library is licended under GPLv3, while Annif is licensed under the Apache License 2.0. The licenses are compatible, but depending on legal interpretation, the terms of the GPLv3 (for example the requirement to publish corresponding source code when publishing an executable application) may be considered to apply to the whole of Annif+Yake if you decide to install the optional Yake dependency.

annif's People

Contributors

osma avatar juhoinkinen avatar tvirolai avatar mo-fu avatar dependabot[bot] avatar unnikohonen avatar kinow avatar mvsjober avatar monalehtinen avatar dwinston avatar lgtm-migrator avatar zuphilip avatar rneatherway avatar step-security-bot avatar

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    ๐Ÿ–– Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. ๐Ÿ“Š๐Ÿ“ˆ๐ŸŽ‰

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google โค๏ธ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.