import openai
import gradio as gr
from PIL import Image
import requests

output= gr.Image()


def generateImage(prompt):
    response = openai.images.generate(
        model="dall-e-3",
        prompt=prompt,
        size="1024x1024",
        quality="standard",
        n=1,
    )
    return response.data[0].url

def handlePrompt(who, doing):
    prompt = f"{who} {doing}"
    print("Prompt:", prompt)
    try:
        url = generateImage(prompt)
        if url:
            image = Image.open(requests.get(url, stream=True).raw)
            return image
    except Exception as e:
        print("Error loading image:", e)

    # Fallback image if something goes wrong
    return Image.open("images/ug_logo.jpg")

with gr.Blocks() as demo:
    gr.Image(value="images/ug_logo.jpg", height=200, width=200)
    gr.HTML("<h1>Unified Ground Image Generator</h1>")
    gr.HTML("<p>Welcome to the People of Color in Climate Image Generator</p>")
    gr.HTML("<p>Please send any comments or images you like to jamil@unifiedground.com or tag @brooklyndadshow</p>")
    gr.HTML("<p>I want to see:</p>")

    who = gr.Radio(
        label="Who",
        choices=[
            "People of Color",
            "Black People",
            "Latino People",
            "Indigenous People",
            "Asian and Pacific Islander People"
        ],
        value="People of Color"
    )

    doing = gr.Radio(
        label="Action",
        choices=[
            "in Climate Jobs",
            "installing Solar and Battery Storage",
            "working in Off Shore Wind",
            "installing a heat pump"
        ],
        value="in Climate Jobs"
    )

    generate_btn = gr.Button("Generate Image")
    output_image = gr.Image(value="images/ug_logo.jpg", height=1024, width=1024, type="pil")

    generate_btn.click(fn=handlePrompt, inputs=[who, doing], outputs=output_image)

demo.launch()