ChatGPTを用いたプロンプト・エンジニアリング

ChatGPTで開発をするための方法

準備

openai, python-dotenv (python 3.8.1以上）をインストール

「command」+「shift」+「.」 で、隠しファイルを表示

https://platform.openai.com/account/api-keys でキーを得る． 3ヶ月で180$を無料で使用できる． .env にOPENAI_API_KEY = <キー> を追加

.gitignore に .env を追加

import openai
import os
from dotenv import load_dotenv, find_dotenv

_ = load_dotenv(find_dotenv())

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

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"]

# 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)