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https://github.com/dair-ai/maven-pe-for-llms-7

Code, Demos, and Exercises for Prompt Engineering for LLMs Course
https://github.com/dair-ai/maven-pe-for-llms-7

Last synced: 3 months ago
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Code, Demos, and Exercises for Prompt Engineering for LLMs Course

Host: GitHub
URL: https://github.com/dair-ai/maven-pe-for-llms-7
Owner: dair-ai
Created: 2024-01-17T21:14:12.000Z (about 1 year ago)
Default Branch: main
Last Pushed: 2024-01-25T17:12:06.000Z (about 1 year ago)
Last Synced: 2024-05-22T16:22:43.822Z (9 months ago)
Language: Jupyter Notebook
Size: 772 KB
Stars: 6
Watchers: 1
Forks: 2
Open Issues: 0
Metadata Files:
- Readme: README.md

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README

# Prompt Engineering for LLMs - Notebooks and Exercises

Welcome to the notebooks and exercises for the Prompt Engineering for LLMs course.

## 1. Sign up for an OpenAI Key

To run the notebooks in this repo, you are required to sign up for an OpenAI paid account.

## 2. Check out the repo

```sh
git clone https://github.com/dair-ai/maven-pe-for-llms-7.git
cd maven-pe-for-llms-7
```

If you already have the repo, go into it and make sure you have the latest.

```sh
cd maven-pe-for-llms-7
git pull origin master
```

If you have downloaded the zipped file instead, unzip it and go into the directory.

```sh
cd maven-pe-for-llms-7
```

## 3. Setup the environment

### Conda

If you don't have conda, you can install it [here](https://docs.conda.io/projects/conda/en/latest/user-guide/install/).

Once installed, run the following command to create a new environment called `pe-for-llms`.

```sh
conda create -n pe-for-llms
```

Next, activate the conda environment.

```sh
conda activate pe-for-llms
```

### Python environment

If you don't want to use conda, you can create a virtual environment using Python's `venv` module.

```sh
python3 -m venv .venv
```

Next, activate your environment (the command below is for Linux)
```sh
source .venv/bin/activate
```

## 4. Install the packages

Next, install the dependencies inside the requirements.txt file.

```sh
pip install -r requirements.txt
```

## 5. Run the Preparation Exercise

Run the prepare exercise notebook (found inside the [exercises folder](https://github.com/dair-ai/maven-pe-for-llms-7/blob/main/exercises/PE_for_LLMs_Preparation_Exercise.ipynb)). Before attempting the preparation exercise, add a `.env` file to your root folder and add your `OPENAI_API_KEY`.

That's it! You're all setup to start working on the notebooks and exercises.