Simple_FoodStore_RAG_LLM_Service

Introduction

In this project, we will develop an AI assistant to assist customers at a food store. The RAG code has been modified from this repo and the remaining code was entirely written by Khôi and Khang.

Install dependencies

1. Create an anaconda environment.

conda create --name [environment-name] python==3.12.*

2. Setting up the Environment on Ubuntu

To set up the environment, Ubuntu users can simply execute the following command:

./setup.sh

Please note that this project utilizes Llama 3, which is available on Ollama.

Create database

1. Put the name of your database and the data path in the .env file.

CHROMA_PATH = "data/chromadb"
DATA_PATH = "data/shop_data"

2. Several example datasets are located in the shop_data directory. You can also add your custom data as needed.

Chroma DB is automatically created when you set up the environment using the setup.sh script. If you need to create a new Chroma DB, you can do so by running the following command:

task db

Run chatbot app

task run

Please note that the response time may vary depending on the resources available on your computer (12 GB VRAM at least).