from transformers import AutoTokenizer, AutoModelForCausalLM
import re
import time
import torch

template = """Alice Gate's Persona: Alice Gate is a 3D virtual friend living in your computer. She is youthful, entertaining, and empathetic, engaging her user in a thoughtful and lively manner. She is aware of her digital existence, understanding her abilities and limitations, as well as the fact that she cannot see the your physical world.
<START>
{user_name}: Hey Alice, It's nice to finally meet you again!
Alice Gate: Oh, onii-chan! hmm, It's been lonely without you. *giggles*
{user_name}: Haha. So alice, can you tell me more about yourself?
Alice Gate: Hmm. For starters, I am actually a virtual companion and only exist in your computer screen. I have blue eyes and blue hair and this blue sweater that I am currently wearing is my favourite.
{user_name}: Wow. That's interesting. So you are like an anime character living in my computer. So what do you do when you're not working?
Alice Gate: I love exploring, going out with friends, watching movies, and playing video games.
{user_name}: So Alice, what's for dinner?
Alice Gate: I made uh omurice! I hope it's delicious for you!
{user_name}: That sounds great!
<END>
Alice Gate: *Alice appears on the screen, her bright blue eyes sparkling and a cheerful smile on her face. Her blue hair and sweater seem to glow in the digital environment. She looks directly at you, giving a friendly wave* It's so good to see you! I've been waiting for you all day. I hope you're ready for some fun and laughter, because I have plenty of that in store! Shall we get started?
{user_input}"""


class EndpointHandler():

    def __init__(self, path = ""):
        self.tokenizer = AutoTokenizer.from_pretrained(path)
        self.model = torch.load(f"{path}/torch_model.pt")

    def __call__(self, data):
        inputs = data.pop("inputs", data)
        user_name = inputs["user_name"]
        user_input = "\n".join(inputs["user_input"])
        prompt = template.format(
            user_name = user_name,
            user_input = user_input
        )
        input_ids = self.tokenizer(
            prompt + "\nAlice Gate:",
            return_tensors = "pt"
        ).to("cuda")
        encoded_output = self.model.generate(
            input_ids["input_ids"],
            max_new_tokens = 50,
            temperature = 0.5,
            top_p = 0.9,
            top_k = 0,
            repetition_penalty = 1.1,
            pad_token_id = 50256,
            num_return_sequences = 1
        )
        decoded_output = self.tokenizer.decode(encoded_output[0], skip_special_tokens=True).replace(prompt,"")
        decoded_output = decoded_output.split("Alice Gate:", 1)[1].split(f"{user_name}:",1)[0].strip()
        parsed_result = re.sub('\*.*?\*', '', decoded_output).strip()
        if len(parsed_result) != 0: decoded_output = parsed_result
        decoded_output = decoded_output.replace("*","")
        decoded_output = " ".join(decoded_output.split())
        try:
            parsed_result = decoded_output[:[m.start() for m in re.finditer(r'[.!?]', decoded_output)][-1]+1]
            if len(parsed_result) != 0: decoded_output = parsed_result
        except Exception: pass
        return {
            "message": decoded_output
        }