Prompt Engineering for Python Developers

app.py

from openai import OpenAI
client = OpenAI()

import os
from dotenv import load_dotenv
api_key = os.getenv("OPENAI_API_KEY")    

def get_chat_completion(user_prompt, system_role='You are a helpful assistant', 
                        model='gpt-3.5-turbo', temperature=1):
    messages = [
        {'role': 'system', 'content': system_role},
        {'role': 'user', 'content': user_prompt}
    ]
    
    response = client.chat.completions.create(
        model=model,
        messages= messages,
        temperature=temperature
    )
    return response.choices[0].message.content


text = '''
Prompt engineering is a new discipline for developing and optimizing prompts \
to efficiently use language models for a wide variety of applications and research topics.
'''

prompt = f'''
Translate the text delimited by triple backticks from english to french.
```{text}```
'''

response = get_chat_completion(prompt)
print(response)