import openai
import gradio as gr
from gradio.components import Textbox, Image, Text

# Set up OpenAI API credentials
openai.api_key = "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"

model_path = "models/dreamlike-art/dreamlike-photoreal-2.0"
model_prefix = "nsfw, photoreal style"
model = gr.Interface.load(model_path)

base_prompt = "give only one answer, limit is 36 words"

# Define the OpenAI prompt completion function
def generate_text(prompt):
    response = openai.Completion.create(
        model="text-davinci-003",
        prompt=f"{prompt}\n\nQ: {base_prompt}\nA:",
        #prompt=prompt,
        max_tokens=64,
        n=1,
        stop=None,
        temperature=0.5,
    )
    return response.choices[0].text.strip()

# Define the image generation function
def generate_image(prompt):
    # Generate text based on prompt
    text = generate_text(prompt)
    # Generate image based on text
    image = model(text)
    return text, image

# Define the Gradio interface
prompt_input = Textbox("Enter a prompt", lines=3)
text_output = Text("Output will appear here", lines=10)

image_output = Image()

iface = gr.Interface(
    generate_image,
    inputs=prompt_input,
    outputs=[text_output, image_output],
    title="Image Generator",
    description="Generates an image based on a prompt using OpenAI's GPT-3 and DALL-E models."
)

# Update the output boxes with the generated text and image
def update_output(text, image_url):
    # Get the current text in the output box
    current_text = text_output.value
    # Add the new text to the current text
    new_text = current_text + "\n\n" + text
    # Update the text output box with the new text
    text_output.update(new_text)

iface.interface_result_hooks = [update_output]

# Launch the interface
iface.launch()