dream.py

dream.py

import base64
import json 
import sys
import uuid

from openai import OpenAI

import requests

from environs import Env

# Init environment
env = Env()
env.read_env()

api_key = env("OPENAI_API_KEY")

# Function to encode the image
def encode_image(image_path):
    with open(image_path, "rb") as image_file:
        return base64.b64encode(image_file.read()).decode('utf-8')

# Path to your image
image_path = "clouds.jpg"

# Getting the base64 string
base64_image = encode_image(image_path)

headers = {
    "Content-Type": "application/json",
    "Authorization": f"Bearer {api_key}"
}

prompt = "Here is a photo of a cloud.  Think about what also it might look like you can think  abstractly and freely. Give me a description of what it also might look like. Use your imagination like a child would, and describe what you imagine. Describe it in a way that could be used to make an illustration for a children's book. It needs to be concrete a cotton and similar generic responses not a good responses. Use child like wonder. The color is too important because it will always be white like clouds, instead focus more on the shapes. The description should not really talk about cloud, because we want to find the next closest things to clouds they look like. Try to make a descripton that matches says where the objects should be placed in the image. For example, the description should say something like the object should be placed in the top left corner of the image. The description should be a complete sentence. The description should be a complete sentence. Try to avoid clichés like cotton candy and sheep. Make the description as unique as possible, and make it beatiful and colorful and fun"

payload = {
    "model": "gpt-4-vision-preview",
    "messages": [
      {
        "role": "user",
        "content": [
          {
            "type": "text",
            "text": prompt
          },
          {
            "type": "image_url",
            "image_url": {
              "url": f"data:image/jpeg;base64,{base64_image}"
            }
          }
        ]
      }
    ],
    "max_tokens": 300
}

response = requests.post("https://api.openai.com/v1/chat/completions", headers=headers, json=payload)

pretty_json = json.dumps(response.json(), indent=4, sort_keys=True)
#print(pretty_json)

content = response.json()["choices"][0]["message"]["content"]

print(content)

print("Generating image...")

client = OpenAI()

response = client.images.generate(
  model="dall-e-3",
  prompt= content,
  size="1024x1024",
  quality="standard",
  n=1,
)

image_url = response.data[0].url


def download_file(url, filename):
    # Sends a GET request to the specified URL
    response = requests.get(url, stream=True)
    
    # Check if the request was successful
    if response.status_code == 200:
        # Open the file in binary write mode
        with open(filename, 'wb') as file:
            for chunk in response.iter_content(chunk_size=128):
                file.write(chunk)
        print(f"Downloaded '{filename}'.")
    else:
        print(f"Failed to download from '{url}'. Status code: {response.status_code}")


# Generate a random UUID
file_uuid = uuid.uuid4()

# Convert UUID to a string that can be used as a filename
filename = str(file_uuid) + '.png'  # Replace '.ext' with the desired file extension

download_file(image_url, filename)