import gradio as gr
import gradio.helpers
from datasets import load_dataset

import base64
import re
import os
import random
import requests
import time
from PIL import Image
from io import BytesIO
from typing import Tuple

import user_history
from share_btn import community_icon_html, loading_icon_html, share_js

# Define constants for map region size and overlay shapes
MAP_REGION_SIZE = 64
OVERLAY_SHAPES = ["square", "circle", "triangle"]

# Load pre-trained AI model for map concept generation
model = load_model("path/to/pretrained/model")

# Define function for generating map layout concepts using AI model
def generate_map_concept(text_description):
    # Preprocess text description
    processed_text = preprocess_text(text_description)
    
    # Generate map layout concept using AI model
    map_concept = model.generate(processed_text)
    
    return map_concept

# Define Gradio interface components
def gradio_ui():
    with gr.Group():
        with gr.Box():
            with gr.Row(elem_id="prompt-container").style(mobile_collapse=False, equal_height=True):
                with gr.Column():
                    num_regions = gr.Number(label="Number of Regions", value=1, min=1, max=10, step=1)
                    overlay_shape = gr.Radio(label="Overlay Shape", choices=OVERLAY_SHAPES, value=OVERLAY_SHAPES[0])
                    text_description = gr.Textbox(
                        label="Enter map description",
                        show_label=True,
                        max_lines=5,
                        placeholder="Enter a description for the map layout",
                    )
                    generate_btn = gr.Button("Generate Map Concept")
                    
                with gr.Column():
                    map_concept_output = gr.Image(label="Generated Map Concept", shape=(MAP_REGION_SIZE * 10, MAP_REGION_SIZE * 10))
                    
    # Set up event listeners
    generate_btn.click(fn=generate_map_concept, inputs=text_description, outputs=map_concept_output)
    
    # Launch Gradio interface
    gr.Interface(gradio_ui, theme="darkdefault").launch()

# Run the Gradio interface
gradio_ui()