import pickle
import numpy as np
import spacy,re
from nltk.tokenize import word_tokenize
from nltk.corpus import stopwords
import string,nltk

prediction=[]

def preprocess_text(text):
    nltk.download('punkt')
    nltk.download('stopwords')
    text = re.sub(r'(\w)\1{2,}', r'\1', text)
    tokens = word_tokenize(text)
    tokens = [token for token in tokens if token not in string.punctuation]
    tokens = [token.lower() for token in tokens]
    stop_words = set(stopwords.words('english'))
    tokens = [token for token in tokens ]
    return " ".join(tokens)

def remove_user_names(text):
    return re.sub("@\w+|@\W+","",text.lower())

def remove_web_url(text):
    return re.sub("http:(..([a-zA-Z0-9_]+)+([a-zA-Z0-9_]+)..([a-zA-Z0-9_]+)..(([a-zA-Z0-9_]+))).(([a-zA-Z0-9_]+))","website",text)

def remove_hastag(text):
    return re.sub("#\w+","",text)

def remove_all_special_char(text):
    return re.sub("[^\w\s]","",text)

def remove_more_space(text):
    return re.sub(' +',' ',text)

def remove(text):
    return remove_more_space(remove_all_special_char(remove_hastag(remove_web_url(remove_user_names(text)))))

nlp=spacy.load('en_core_web_lg')

emotion_emojies={
    "happiness":["😊","😂","🤣","😁","👌","👍","🙌","😜"],
    "love":["❤️","💕","😘","😍"],
    "sadness":["🤷‍♂️","😒","😫","😞"],
    "empty":["🪹","🫙","📪"],
    "enthusiasm":["😀","😃","🫡"],
    "neutral":["😐","😶","🫥","😑"],
    "worry":["😵‍💫","🤕","🥶","🤢"],
    "surprise":["😯","😮","🤭","🎊","🤭","😲","🙀"],
    "fun":["🎉","🎈","⚱️","😁"],
    "hate":["👎","🤬","😡"],
    "boredom":["🥱"],
    "relief":["😌","😮‍💨"],
    "anger":["🤐","😥","😴","😤","🤯","💢","😠"]
}

def predict(text):
    with open('model.pkl','rb') as f:
        model=pickle.load(f)
        prediction.append(model.predict(np.stack(nlp(preprocess_text(remove(text))).vector).reshape(1,300)))
        emoji=[emotion_emojies[emoji] for emoji in emotion_emojies.keys() if prediction[0][0]==emoji]
    return emoji

if "__main__"==__name__:
    text=input("Input the Text : ")
    print(predict(text))