/PromptEngineering

How To Improve Your Own Prompting On The LLM Model.

Primary LanguageJupyter Notebook

Promt-Enginnering

ChatGPT Prompt Engineering for Developers

This Course is designed to improve and understand how a regular user can improve their prompt interaction using LLM like ChatGPT/ GPT model. Famous Instructor Andrew NG is teaching in very easy manner how to improve and interact with GPT LLM models. And extract meaningful output from the prompt.

This course is free and worth of spending a time to learn about promt engineering.


Prerequisite

  1. This project is based on Python notebook that were taken from the session.To manage the dependencies I have used virtualenv and poetry to create reproducable environment.

  2. Setup the environment.

    • Create a virtual environment on location where you have downloaded this project and also install poetry in the virtual environment.

      python -m  venv <project-name> poetry
    • Activate the virtual environment.

      # For Nix Systems/ Mac OS
      source scripts/activate
      
      # For Windows Systems
      ./Scripts/Activate.ps1
    • Activate the shell from poetry to make sure everything works fine as poetry is installed in the environment.

      python -m poetry shell
    • move the folder named PromtENG, where pyproject.toml poetry file is located. Then install the dependencies using the below command.

      python -m poetry install
    • Now run the jupyter notebook server.

      python -n jupyter notebook
  3. Add your OpenAI API Key in the .env file, where environment variable name mentioned as OPENAI_API_KEY.

  4. Make sure the OpenAI module is installed in the environment. Check with the below command.

    python -m pip show openai

Total 9 video lectures. Follow the notebooks from the folder: promteng


At the end of the seesion also chance the to join the DeepLearning.AI community as per invite.