Week 1.1: Syllabus and Reviewing LLM Essentials

Introduction

To make the most out of this course, understand that LLMs are powerful tools for next token generation, leveraging advanced statistical analysis beyond simple models.

Prerequisites

Before you begin, ensure you have met the following requirements:

You have installed Python 3.6+.

Setup Instructions

Step 1: Clone the Repository

First, clone the repository to your local machine using the following command:

git clone [repository-url]
cd [repository-name]

Step 2: Create a Python Virtual Environment

Create a virtual environment using venv:

python3 -m venv venv

Step 3: Activate the Virtual Environment

Activate the virtual environment:

On Windows:
```
venv\Scripts\activate
```
On MacOS/Linux:
```
source venv/bin/activate
```

Step 4: Install Required Packages

Install the required packages using pip:

pip install -r requirements.txt

Step 5: Create a `.env` File

Create a .env file in the root directory of the project. Use the .env.sample file as a reference:

cp .env.sample .env

Step 6: Update `.env` File

Open the .env file and update the key values as necessary.

Step 7: Load Environmental Variables from the `.env` File

Use the following command to export all of your environmental variables while ignoring any comments:

export $(grep -v '^#' .env | xargs)

Alternatively - Load the Variables Inside Your Shell

If you experience problems using the .env file or do not wish to use one, you can load the variables directly from your shell. Use a command structured like this to load each variable:

export OPENAI_API_KEY=your-key-here

Usage

Running In-Class Examples

To run any in-class examples, execute the server file directly from the command line. For example:

python3 in_class_examples/[file-name]

justicart/ai-school-week-1.1-introduction