README.md

LLM-with-RAG

I just wanna build my own LLM with RAG

Table of Contents

1. Introduction
2. Features
3. How to Set Up
4. Example Uses
5. To-Do List

Introduction

Welcome to the my LLM with RAG system! This system is designed for me the ease the learning as a master in HCMUT

Features

1. Update vector database

        curl -X POST http://localhost:8083/update
   

2. Ask questions with vector data

        curl -X POST -H "Content-Type: application/json" -d '{"query": "who is karger"}' http://localhost:8083/query
   

Nougat

Link: https://github.com/facebookresearch/nougat

  nougat data/web_data/Growth_of_Functions.pdf --markdown --no-skipping -m 0.1.0-base -o data/nougat

How to Set Up

Prerequisites

Before running the system, follow these steps to set up the environment:

1. Clone the Repository:

   • Close the Git repository to your local machine:

     git clone [repository_url]

2. Install Dependencies:

• Navigate to the project directory and install the required packages using the provided setup.txt file:

  pip install -r setup.txt

• To read .ppt file we need to run this code

    apt update
    apt install libreoffice 
  

3. Get OPENAI_API_KEY Key:

   • Google and get OPENAI_API_KEY from OpenAI

4. Create .env File:

   • Create a new file named .env in the project root directory.
   • Add the following line to the file

     OPENAI_API_KEY=YOUR_OPENAI_API_KEY

Run docker

For Linux you must open the port first:

  sudo ufw allow 8083

docker:

  docker build -t mrzaizai2k/llm_n_rag .
  docker run -p 8083:8083 -v data:/app/data -e OPENAI_API_KEY llm_test

Build, run docker compose:

  docker-compose up

Test docker on port 8083:

  curl -X POST -H "Content-Type: application/json" -d '{"query": "who is karger"}' http://localhost:8083/query
  curl -X POST http://localhost:8083/update

Example Uses

Explore practical implementations and demonstrations of the functions in the notebook folder. These examples showcase real-world scenarios, illustrating how the chatbot can be effectively utilized for stock market monitoring.

To-Do List

• Update some features with langchain
• Build the docker to use with my Telegram bot