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https://github.com/george-gca/ai_papers_searcher

Web app to search papers by keywords or similar papers
https://github.com/george-gca/ai_papers_searcher

artificial-intelligence flask flask-application papers python search webapp

Last synced: 3 months ago
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Web app to search papers by keywords or similar papers

Host: GitHub
URL: https://github.com/george-gca/ai_papers_searcher
Owner: george-gca
License: bsd-3-clause
Created: 2022-10-21T14:29:21.000Z (about 2 years ago)
Default Branch: main
Last Pushed: 2024-07-28T18:06:10.000Z (5 months ago)
Last Synced: 2024-10-11T19:26:35.238Z (3 months ago)
Topics: artificial-intelligence, flask, flask-application, papers, python, search, webapp
Language: HTML
Homepage: https://georgegca.pythonanywhere.com/
Size: 1.68 MB
Stars: 2
Watchers: 4
Forks: 1
Open Issues: 0
Metadata Files:
- Readme: README.md
- License: LICENSE

Awesome Lists containing this project

README

        # AI Papers Searcher

Web app to search papers by keywords or similar papers. Based on [CVPR_paper_search_tool by Jin Yamanaka](https://github.com/jiny2001/CVPR_paper_search_tool). I decided to split the code into multiple projects:

- [AI Papers Scrapper](https://github.com/george-gca/ai_papers_scrapper) - Download papers pdfs and other information from main AI conferences

- [AI Papers Cleaner](https://github.com/george-gca/ai_papers_cleaner) - Extract text from papers PDFs and abstracts, and remove uninformative words

- [AI Papers Search Tool](https://github.com/george-gca/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](https://www.pythonanywhere.com/). You can see a running example [here](https://georgegca.pythonanywhere.com/).

---

## [Google Lighthouse PageSpeed Insights](https://pagespeed.web.dev/analysis/https-georgegca-pythonanywhere-com/iu5e0f9uos?form_factor=desktop)

| [Desktop](https://htmlpreview.github.io/?https://github.com/george-gca/ai_papers_searcher/blob/main/lighthouse_results/desktop/georgegca_pythonanywhere_com__keywords_vqa.html) | [Mobile](https://htmlpreview.github.io/?https://github.com/george-gca/ai_papers_searcher/blob/main/lighthouse_results/mobile/georgegca_pythonanywhere_com__keywords_vqa.html) |

| --- | --- |

| ![Performance Insights](lighthouse_results/desktop/lighthouse_performance.svg) | ![Performance Insights](lighthouse_results/mobile/lighthouse_performance.svg) |

| ![Accessibility Insights](lighthouse_results/desktop/lighthouse_accessibility.svg) | ![Accessibility Insights](lighthouse_results/mobile/lighthouse_accessibility.svg) |

| ![Best Practices Insights](lighthouse_results/desktop/lighthouse_best-practices.svg) | ![Best Practices Insights](lighthouse_results/mobile/lighthouse_best-practices.svg) |

| ![SEO Insights](lighthouse_results/desktop/lighthouse_seo.svg) | ![SEO Insights](lighthouse_results/mobile/lighthouse_seo.svg) |

## Requirements

[Docker](https://www.docker.com/) or, for local installation:

- Python 3.11+

- [Poetry](https://python-poetry.org/docs/)

## Usage

Before running the app, you might need to import the relevant data from the [AI Papers Search Tool](https://github.com/george-gca/ai_papers_search_tool) directory. To do so, run:

```bash

bash copy_model_data.sh

```

To 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:

```bash

# create_abstracts_dict=1

```

Uncommenting 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.

### Running without Docker

You first need to install [Python Poetry](https://python-poetry.org/docs/). Then, you can install the dependencies and run the code:

```bash

poetry install

bash start_here.sh

```

### Running with Docker

To 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:

```bash

make

```

To call `start_here.sh` inside the container, run:

```bash

make run

```