import torch
from transformers import T5Tokenizer, GPT2LMHeadModel
from flask import Flask, request, jsonify
import cutlet

convertors = {}
for romaji_sys in ["hepburn", "kunrei", "nippon"]:
    convertors[romaji_sys] = cutlet.Cutlet(romaji_sys)

device = torch.device("cpu")
if torch.cuda.is_available():
    device = torch.device("cuda")

tokenizer = T5Tokenizer.from_pretrained("skytnt/gpt2-japanese-lyric-medium")
model = GPT2LMHeadModel.from_pretrained("skytnt/gpt2-japanese-lyric-medium")
model = model.to(device)


def gen_lyric(title: str, prompt_text: str):
    if len(title) != 0 or len(prompt_text) != 0:
        prompt_text = "<s>" + title + "[CLS]" + prompt_text
        prompt_text = prompt_text.replace("\n", "\\n ")
        prompt_tokens = tokenizer.tokenize(prompt_text)
        prompt_token_ids = tokenizer.convert_tokens_to_ids(prompt_tokens)
        prompt_tensor = torch.LongTensor(prompt_token_ids)
        prompt_tensor = prompt_tensor.view(1, -1).to(device)
    else:
        prompt_tensor = None
    # model forward
    output_sequences = model.generate(
        input_ids=prompt_tensor,
        max_length=512,
        top_p=0.95,
        top_k=40,
        temperature=1.0,
        do_sample=True,
        early_stopping=True,
        bos_token_id=tokenizer.bos_token_id,
        eos_token_id=tokenizer.eos_token_id,
        pad_token_id=tokenizer.pad_token_id,
        num_return_sequences=1
    )

    # convert model outputs to readable sentence
    generated_sequence = output_sequences.tolist()[0]
    generated_tokens = tokenizer.convert_ids_to_tokens(generated_sequence)
    generated_text = tokenizer.convert_tokens_to_string(generated_tokens)
    generated_text = "\n".join([s.strip() for s in generated_text.split('\\n')]).replace(' ', '\u3000').replace('<s>',
                                                                                                                '').replace(
        '</s>', '\n\n---end---')
    title_and_lyric = generated_text.split("[CLS]", 1)
    if len(title_and_lyric) == 1:
        title, lyric = "", title_and_lyric[0].strip()
    else:
        title, lyric = title_and_lyric[0].strip(), title_and_lyric[1].strip()
    return title, lyric


app = Flask(__name__, static_url_path="", static_folder="frontend/dist")

@app.route('/')
def index_page():
    return app.send_static_file("index.html")


@app.route('/gen', methods=["POST"])
def generate():
    if request.method == "POST":
        try:
            data = request.get_json()
            title = data['title']
            text = data['text']
            title, lyric = gen_lyric(title, text)
            result = {
                "state": 200,
                "title": title,
                "lyric": lyric
            }
        except Exception as e:
            result = {
                "state": 400,
                "msg": f"{e}"
            }
        return jsonify(result), result["state"]


@app.route('/romaji', methods=["POST"])
def romaji():
    if request.method == "POST":
        try:
            data = request.get_json()
            text = data['text']
            system = data['system']
            lines = []
            # 不支持带换行符的直接转换
            for line in text.split("\n"):
                lines.append(convertors[system].romaji(line))
            result = {
                "state": 200,
                "romaji": "\n".join(lines),
            }
        except Exception as e:
            result = {
                "state": 400,
                "msg": f"{e}"
            }
        return jsonify(result), result["state"]


if __name__ == '__main__':
    app.run(host="0.0.0.0", port=7860, debug=False, use_reloader=False)