RAG Model Implementation

This repository contains the implementation of the Retrieval-Augmented Generation (RAG) model, which combines the power of a retriever and a generator to provide informative answers to queries. This model is particularly useful for tasks that require external knowledge or context.

Installation

Before running the model, ensure you have the following packages installed:

• transformers
• faiss

You can install these packages using pip by running the following command:

pip install transformers faiss-cpu # Use faiss-cpu or faiss-gpu depending on your setup

Getting started

Navigate to the Root Directory

Open your terminal and navigate to the root directory of this project.

Run the Model

python3 code/main.py '[query]'

Ensure you include the query in quotes if it consists of multiple words.

Example

To get answers related to "How many people does it take to maneuver the .84 -mile course around Schenley Park's Flagstaff Hill?", run:

python3 code/main.py "How many people does it take to maneuver the .84 -mile course around Schenley Park's Flagstaff Hill?"

Authors

Yuxin (Vincy) Zheng (Andrew Id: yuxinzhe)

Xiaoyang (Jake) Wen (Andrew Id: xwen2)