readme.md

ChatGPT Prompt Engineering by DeepLearning.AI

Overview

This crash & free course on ChatGPT Prompt Engineering is offered by DeepLearning.AI and lectured by Andrew Ng and Isa Fulford from openai.

Course Plan

• Lesson1: Introduction
• Lesson2: Guidelines
• Lesson3: Iterative
• Lesson4: Summarizing
• Lesson5: Inferring
• Lesson6: Transforming
• Lesson7: Expanding
• Lesson8: Chatbot
• Lesson9: Conclusion

All notebook examples are available in the lab folder.

Setup

Load the API key and relevant Python libaries

import openai
import os

from dotenv import load_dotenv, find_dotenv
_ = load_dotenv(find_dotenv())

openai.api_key  = os.getenv('OPENAI_API_KEY')

Helper function

• This function will make it easier to use prompts and look at the generated outputs:

It uses OpenAI's gpt-3.5-turbo model and the chat completions endpoint.

def get_completion(prompt, model="gpt-3.5-turbo"):
    messages = [{"role": "user", "content": prompt}]
    response = openai.ChatCompletion.create(
        model=model,
        messages=messages,
        temperature=0, # this is the degree of randomness of the model's output
    )
    return response.choices[0].message["content"]

Usage

text = f"""
You should express what you want a model to do by \ 
providing instructions that are as clear and \ 
specific as you can possibly make them. \ 
This will guide the model towards the desired output, \ 
and reduce the chances of receiving irrelevant \ 
or incorrect responses. Don't confuse writing a \ 
clear prompt with writing a short prompt. \ 
In many cases, longer prompts provide more clarity \ 
and context for the model, which can lead to \ 
more detailed and relevant outputs.
"""
prompt = f"""
Summarize the text delimited by triple backticks \ 
into a single sentence.
```{text}```
"""
response = get_completion(prompt)
print(response)

Completion :

Clear and specific instructions should be provided to guide a model towards the desired output, and longer prompts can provide more clarity and context for the model, leading to more detailed and relevant outputs.

References

Main Course :

• https://learn.deeplearning.ai/chatgpt-prompt-eng/lesson/1/introduction

Others short Free Courses available on DeepLearning.AI :

• https://learn.deeplearning.ai/