--- title: SummaryProject sdk: docker app_file: src/api.py pinned: false --- # Project Deep Learning - Text Summarisation tool and it's application programming interface As part of the master course "Neural Network", for this university project, our task is about creating an application, an interface or a python library in the use of NLP (Natural Language Processing) with the help of an artificial neural network system. ## Description **Objectives of our project :** Create an interface which allows users to summarize a long text like press article into a brief version. To achieve this general objective, for the algorithm part, we would like to test two different deep learning methods : setting up a LSTM model and fine tuning a transformer model. For the interface part, we wanted to create an interface building with a fastAPI framework and put the application on Huggingface. ## Getting Started ### Get prepared * Open the link below directing towards our interface on huggingface. ``` https://huggingface.co/spaces/EveSa/SummaryProject ``` ### The interface * 1- Choose a model for your summarization task (LSTM/Fine-tuned T5) by clicking on the scroll-down list. And click the Select model button. * 2- Enter your text to summarize in the left section. * 3- Click on 'Go!' botton and you will get your summary! * 4- Don't forget to reset the app for your next try. The botton is at the right next to 'Go!'. ## In case you want to try to execute our scripts : ### Get prepared * In order to run the script, you need to : * 1- Create a virtual environment named ```.venv``` ``` python3 -m virtualenv .venv source .venv/bin/activate ``` * 2- Also install the dependencies ``` pip install -U -r requirements.txt ``` * You are now ready to execute the scripts ### The program api.py * Run the script with the command below : ``` python3 api.py ``` * This code generates the same page as on Huggingface in your browser. To do the task, you may follow the steps in the previous section. ## Authors Eve SAUVAGE Estelle SALMON Lingyun GAO ## License This project is licensed under the [M2 TAL] License