import gradio as gr
import torch
from mario_gpt.dataset import MarioDataset
from mario_gpt.prompter import Prompter
from mario_gpt.lm import MarioLM
from mario_gpt.utils import view_level, convert_level_to_png

mario_lm = MarioLM()

device = torch.device('cuda')
mario_lm = mario_lm.to(device)
TILE_DIR = "data/tiles"



def update(pipes, enemies, blocks, elevation, temperature = 2.0, level_size = 1399, prompt = ""):
    if prompt == "":
        prompt = f"{pipes} pipes, {enemies} enemies, {blocks} blocks, {elevation} elevation"
    print(f"Using prompt: {prompt}")
    prompts = [prompt]
    generated_level = mario_lm.sample(
        prompts=prompts,
        num_steps=level_size,
        temperature=temperature,
        use_tqdm=True
    )
    img = convert_level_to_png(generated_level.squeeze(), TILE_DIR, mario_lm.tokenizer)[0]
    return img

with gr.Blocks() as demo:
    gr.Markdown("## Demo for ['MarioGPT: Open-Ended Text2Level Generation through Large Language Models'](https://github.com/shyamsn97/mario-gpt). Enter a text prompt or select parameters from below!")

    text_prompt = gr.Textbox(value="", label="Enter your MarioGPT prompt. ex: 'many pipes, many enemies, some blocks, low elevation', or compose your prompts below")
    with gr.Accordion(label="Compose your prompt", open=False):
        pipes = gr.Radio(["no", "little", "some", "many"], label="pipes")
        enemies = gr.Radio(["no", "little", "some", "many"], label="enemies")
        blocks = gr.Radio(["little", "some", "many"], label="blocks")
        elevation = gr.Radio(["low", "high"], label="elevation")
        temperature = gr.Number(value=2.0, label="temperature: Increase these for more stochastic, but lower quality, generations")
        level_size = gr.Number(value=1399, precision=0, label="level_size")
    
    btn = gr.Button("Generate level")
    level_image = gr.Image()
    

    

    btn.click(fn=update, inputs=[pipes, enemies, blocks, elevation, temperature, level_size, text_prompt], outputs=level_image)
    gr.Examples(
        examples=[
            ["many", "many", "some", "high"],
            ["no", "some", "many", "high", 2.0],
            ["many", "many", "little", "low", 2.0],
            ["no", "no", "many", "high", 2.4],
        ],
        inputs=[pipes, enemies, blocks, elevation],
        outputs=level_image,
        fn=update,
        cache_examples=True,
    )
demo.launch()