A simple AI Prompt Engineering example with OpenAI

auto_engineer_image.py

from openai import OpenAI

# Your API key must be saved in an env variable for this to work.
client = OpenAI()


# Get a prompt, embed it into a classification request to GPT
image_subject = input("Subject: ")
image_setting = input("Setting: ")
image_style = input("Style: ")
image_emotion = input("Emotion: ")

image_emotion_prompt = f'''
Create a 100 word summary of the following emotion.

{image_emotion}
'''

## EMOTION
print('============= EMOTIONAL PROMPT ================')
print(image_emotion_prompt)
emotion_response = client.chat.completions.create(
    model="gpt-4",
    messages=[
    {
        "role": "system",
        "content": "You are deeply sensitive and in touch with your feelings. Your goal is to help others deeply understand emotions." 
    },
    {
        "role": "user",
        "content": image_emotion_prompt
    }],
    temperature=1,
    max_tokens=200,
    top_p=1,
    frequency_penalty=0,
    presence_penalty=0
)
emotion_details = emotion_response.choices[0].message.content
print('--------- response -----------')
print(emotion_details)
print('------------------------------')

# We want the subject and setting to reflect the emotional content
image_subject_prompt = f'''
Create a detailed physical description of the following subject and setting.

Subject:

{image_subject}

Setting:

{image_setting}

Generate details that evoke the following emotional content:

{emotion_details}
'''

## SUBJECT
print('============= SUBJECT PROMPT ================')
print(image_subject_prompt)
subject_response = client.chat.completions.create(
    model="gpt-4",
    messages=[
    {
        "role": "system",
        "content": "You are a keen observer of all things. You notice and care about even the smallest details." 
    },
    {
        "role": "user",
        "content": image_subject_prompt
    }],
    temperature=1,
    max_tokens=2048,
    top_p=1,
    frequency_penalty=0,
    presence_penalty=0
)
subject_details = subject_response.choices[0].message.content
print('--------- response -----------')
print(subject_details)
print('------------------------------')

## STYLE
image_style_prompt = f'''
Create a 100 word summary of the following artistic style. Focus exclusively on the visual components of the style:

{image_style}
'''

print('============= STYLE PROMPT ================')
print(image_style_prompt)
style_response = client.chat.completions.create(
    model="gpt-4",
    messages=[
    {
        "role": "system",
        "content": "You are an art historian. Describe artistic styles in detail." 
    },
    {
        "role": "user",
        "content": image_style_prompt
    }],
    temperature=1,
    max_tokens=300,
    top_p=1,
    frequency_penalty=0,
    presence_penalty=0
)
style_details = style_response.choices[0].message.content
print('--------- response -----------')
print(style_details)
print('------------------------------')

request_for_image_prompt = f'''
Image content: 

{subject_details}

Image Style:

{style_details}
'''

print('============= FINAL IMAGE PROMPT ================')
print(request_for_image_prompt)
image_prompt_response = client.chat.completions.create(
    model="gpt-4",
    messages=[
    {
        "role": "system",
        "content": "You are a prompt engineer. Return a prompt that will help DALL-E make a beautiful image. Include generous details about the subject, setting, and style in your prompt." 
    },
    {
        "role": "user",
        "content": request_for_image_prompt
    }],
    temperature=1,
    max_tokens=2048,
    top_p=1,
    frequency_penalty=0,
    presence_penalty=0
)
generated_image_prompt = image_prompt_response.choices[0].message.content
print('============ FINAL RESULT ================')
print(generated_image_prompt)

# Ask for images -- Commented out because 
response_three = client.images.generate(
    model="dall-e-3",
    prompt=generated_image_prompt,
    size="1024x1024",
    quality="standard",
    n=1
)

image_url = response_three.data[0].url
print(image_url)
print()