from transformers import AutoTokenizer, AutoModelForSeq2SeqLM, AutoModel
import json
import spacy

from celebbot import CelebBot
from utils import *

DEBUG = False
QA_MODEL_ID = "google/flan-t5-large"
SENTTR_MODEL_ID = "sentence-transformers/all-mpnet-base-v2"

def main():
    celeb_data = get_celeb_data("data.json")
    message = "Please choose your favorite celebrity from\n"\
              "1. Cate Blanchett\n"\
              "2. David Beckham\n"\
              "3. Emma Watson\n"\
              "4. Lady Gaga\n"\
              "5. Madonna\n"\
              "6. Mark Zuckerberg\n"\
              "input name:\n"
    QA_tokenizer = AutoTokenizer.from_pretrained(QA_MODEL_ID)
    QA_model = AutoModelForSeq2SeqLM.from_pretrained(QA_MODEL_ID)
    sentTr_tokenizer = AutoTokenizer.from_pretrained(SENTTR_MODEL_ID)
    sentTr_model = AutoModel.from_pretrained(SENTTR_MODEL_ID)

    celeb_name = input(message)
    gender = celeb_data[celeb_name]["gender"]
    if celeb_name == "Madonna":
        name = "Madonna-American-singer-and-actress"
    elif celeb_name == "Anne Hathaway":
        name = "Anne-Hathaway-American-actress"
    else:
        name="-".join(celeb_name.split(" "))
    knowledge = get_article(f"https://www.britannica.com/biography/{name}")
    spacy_model = spacy.load("en_core_web_lg")
    knowledge_sents = [i.text.strip() for i in spacy_model(knowledge).sents]

    ai = CelebBot(celeb_name, gender, QA_tokenizer, QA_model, sentTr_tokenizer, sentTr_model, spacy_model, knowledge_sents)

    answers = []
    
    while True:
        if not DEBUG:
            ai.speech_to_text()
        else:
            ai.text = input("Your question: ")
            pass

        # ai.text = q
        if ai.text != "":
            print("me --> ", ai.text)

            answers.append(ai.question_answer())

            if not DEBUG:
                ai.text_to_speech()
        ai.text = ""

# Run the AI
if __name__ == "__main__":
    main()