Unpakcer

Categorize browser bookmarks and Suggest site title.

Demo

Please click on the thumbnails

Features

• Categorize Bookmarks
• Generate titltes automatically by summary of text
• Importing multiple browser Bookmarks
• Editing Bookmarks
• Site Preview
• Support Chromium based browser and Firefox

Run Locally

Dependencies

• Docker
• Docker-Compose
• At least 16 GB memory

Recommends

• Nvidia Container Toolkit
• npm
• GPU with CUDA support
• 32GB memory

Run on Docker (Recommend)

Clone the project

  git clone https://github.com/KITA-DS12/vol11_bookmark

Go to the project directory

  cd vol11_bookmark

Obtain linkpreview's API Key

  echo VUE_APP_API_KEY={YOUR API KEY} > .env.local

Run Docker

If you have Nvidia GPU.

  docker-compose --profile gpu up 

If you want to run unpacker without GPU. Unpacker runs only CPU.

  docker-compose --profile cpu up

You can now access unpacker on localhost:8080

Run on Electron (Experimental)

Clone the project

  git clone https://github.com/KITA-DS12/vol11_bookmark

Go to the project directory

  cd vol11_bookmark

Obtain linkpreview's API Key

  echo VUE_APP_API_KEY={YOUR API KEY} > .env.local

Run Server

  docker-compose up server -d

Install Dependencies

  npm install

Run Electron

  yarn run electron:serve

Usage

1. Export your bookmark html file from your browser.
2. Upload Bookmark File.
3. Choose Target Folder.
4. Enter Category.
5. Modify Your Bookmark.
6. Download Categorized Bookmark HTML file.
7. Import HTML file to your browser.

FAQ

vue-cli-service not found when starting server

Run follow command in local.

npm install @vue/cli

Tech Stack

Client: Vue.js, Vuetify

Server: FastAPI, Pytorch, Transformer, HuggingFace

Acknowledgements

• README Editor
• Geek Project
• Geek Camp

We used the following Model

• Categorize Model
• Generate Title Model

Citation

• Laurer, Moritz, Wouter van Atteveldt, Andreu Salleras Casas, and Kasper Welbers. 2022. ‘Less Annotating, More Classifying – Addressing the Data Scarcity Issue of Supervised Machine Learning with Deep Transfer Learning and BERT - NLI’. Preprint, June. Open Science Framework. https://osf.io/74b8k.

• Hasan, T., Bhattacharjee, A., Islam, M., Mubasshir, K., Li, Y.F., Kang, Y.B., Rahman, M., & Shahriyar, R. (2021). XL-Sum: Large-Scale Multilingual Abstractive Summarization for 44 Languages. In Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021 (pp. 4693–4703). Association for Computational Linguistics.https://aclanthology.org/2021.findings-acl.413

License

GNU General Public License v3.0