View Demo (In the Future) . Report Bug . Request Feature
For this project you will need to have installed Conda or Miniconda and have a Kaggle account.
This also requires ~20Gb of RAM to run and a GPU is recommended
- Install the dependencies
make install
This will use the environment.yml
file and conda to create a new environment with all the required dependencies.
- (Optional) Download the Faiss index & Data checkpoint
make download_checkpoint
- Update the Index and Dataset
(Optional if you did step 2)
This will download the ArXiv dataset from Kaggle and create/update the Faiss index.
make update
- Run the following command to start the Streamlit app:
make run
For running the aplicattion, after following the installation steps, run the following command:
make run
If you desire to update the ArXiv dataset and the Faiss index, run the following command:
make update
- Add Taggs to the papers
- Provide a way to add the paper to Zotero
- Add button to find similar papers
- Show the categories
- Show the authors
- Provide a preview of the paper
- Question Answering to papers
- Add "make download_checkpoint"
- Filter papers by time
Contributions are what make the open source community such an amazing place to be learn, inspire, and create. Any contributions you make are greatly appreciated.
- If you have suggestions for adding or removing projects, feel free to open an issue to discuss it, or directly create a pull request after you edit the README.md file with necessary changes.
- Please make sure you check your spelling and grammar.
- Create individual PR for each suggestion.
- Fork the Project
- Create your Feature Branch (
git checkout -b feature/AmazingFeature
) - Commit your Changes (
git commit -m 'Add some AmazingFeature'
) - Push to the Branch (
git push origin feature/AmazingFeature
) - Open a Pull Request
Distributed under the MIT License. See LICENSE for more information.
- Miguel Caçador Peixoto - Physics Engineering Student