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from openai import AzureOpenAI
import json
from io import BytesIO
import requests
import re
import streamlit as st
def get_client():
client = AzureOpenAI(
api_version="2024-05-01-preview",
azure_endpoint=st.secrets['endpoint'],
api_key=st.secrets['key'],
)
return client
def generate_image(prompt):
client = get_client()
result = client.images.generate(
model="Dalle3",
prompt=prompt,
n=1
)
image_url = json.loads(result.model_dump_json())['data'][0]['url']
result = requests.get(image_url)
return BytesIO(result.content)
def generate_image_prompt(prompt):
payload = {
"messages": [
{
"role": "system",
"content": [
{
"type": "text",
"text": "You give a few examples of english prompts that help generate image base on user's input. Return prompts in bullet point"
}
]
},
{
"role": "user",
"content": [
{
"type": "text",
"text": prompt
}
]
}
],
"temperature": 0.9,
"top_p": 0.95,
"max_tokens": 800
}
response = requests.post(st.secrets['completionendpoint'], headers={"Content-Type": "application/json", "api-key": st.secrets['key']}, json=payload)
response.raise_for_status() # Will raise an HTTPError if the HTTP request returned an unsuccessful status code
return response.json()['choices'][0]['message']['content']
def process_image_prompt(response):
response = response.split('\n')
response = [re.sub(r"(?<!\\)['\"](.*?)(?<!\\)['\"]", r"\1", response[i]) for i in range(len(response))]
return response
if __name__ == "__main__":
response = generate_image_prompt('halong bay, vietnam')
response = process_image_prompt(response)
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