Web app to search papers by keywords or similar papers. Based on CVPR_paper_search_tool by Jin Yamanaka. I decided to split the code into multiple projects:
- AI Papers Scrapper - Download papers pdfs and other information from main AI conferences
- AI Papers Cleaner - Extract text from papers PDFs and abstracts, and remove uninformative words
- AI Papers Search Tool - Automatic paper clustering
- this project - Web app to search papers by keywords or similar papers
I also added support for more conferences in a single web app, customized it a little further, and hosted it on PythonAnywhere. You can see a running example here.
| Desktop | Mobile |
|---|---|
 |
 |
 |
 |
 |
 |
 |
 |
Docker or, for local installation:
- Python 3.11+
- Poetry
Before running the app, you might need to import the relevant data from the AI Papers Search Tool directory. To do so, run:
bash copy_model_data.shTo make it easier to run the code, with or without Docker, I created a few helpers. Both ways use start_here.sh as an entry point. Since there are a few quirks when calling the specific code, I created this file with all the necessary commands to run the code. All you need to do is to uncomment the relevant lines and run the script:
# create_abstracts_dict=1Uncommenting this line will call abstracts_to_dict.py. This script will convert all papers abstracts to a list of numbers. This is done to try to save as much storage space as possible, since the abstracts will be replaced by the index of the words in a list of words. When displaying this information in the app, the words will be properly replaced. Then, it will call the flask app.
You first need to install Python Poetry. Then, you can install the dependencies and run the code:
poetry install
bash start_here.shTo help with the Docker setup, I created a Dockerfile and a Makefile. The Dockerfile contains all the instructions to create the Docker image. The Makefile contains the commands to build the image, run the container, and run the code inside the container. To build the image, simply run:
makeTo call start_here.sh inside the container, run:
make run