Natural language processing course: '; DROP TABLE TEAMS; --

Henri Sellis, Igor Sitek

Project 1: Conversational Agent with Retrieval-Augmented Generation

For our Natural Language Processing course group project, we are developing a conversational agent that retrieves additional information from Google Scholar documents, to increase the quality of answering questions. To accomplish this, first a number of most relevant tags are extracted from the user input, then corresponding queries are made to retrieve documents from Google Scholar, and finally the documents, along with the original user input, are fed to a Large Language Model, using prompt engineering.

Report

Local run

1. Copy the env file and fill the HuggingFace token.

   cp .env-copy .env

2. Install required packages (preferably in a new env).

   conda env create my_env

   conda activate my_env

   pip install -r requirements.txt

3. Download static dataset.

   python -m src.dataset_scraping

4. Run app.

   python -m src.app