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Contract Q&A RAG System

Overview This repository contains the implementation of a simple RAG (Retrieval-Augmented Generation) system for Contract Q&A (Question & Answer) tasks. The goal of this project is to build, evaluate, and improve an AI-powered system capable of understanding and responding to questions related to legal contracts.

Project Structure

backend/src/: This directory contains the source code for the RAG system implementation. 
backend/notebooks/: This directory contains notebooks of the Rag system implementation
backend/data/: This directory holds any necessary data files, such as training datasets or contract documents. 
backend/tests/: This directory includes unit tests for the codebase. 
frontend/: includes the frontend codebase  
README.md: This file you are currently reading, providing an overview of the project. 
requirements.txt: A list of Python dependencies required to run the project.  

Getting Started

To set up and run the project locally, follow these steps:
  1. Clone the repository to your local machine:

    git clone https://github.com/lillianassefa/Contract-AI-Chatbot.git

    cd Contract-AI-Chatbot

  2. Install the required dependencies using pip:

    pip install -r requirements.txt

  3. Run the RAG system

    python src/main.py

SOURCE CODE

The initial stage of the rag implementation is written in the backend/notebooks directory. You will find two notebooks with different RAG implemenatations. The react app ui can be infered from the frontend directory as well.

CONTACT

For any inquires or feedback, please contact me at:

Lillian Alehegn
Lillianalehegn123@gmail.com

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A RAG implemented chatbot which is tailored for contracts generation.

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