from sentence_transformers import SentenceTransformer
from sklearn.metrics.pairwise import cosine_similarity

import nltk
nltk.download('all')
from nltk.corpus import wordnet as wn
import numpy as np

import gradio as gr
import pyjokes

def similarity(input, joke):
    return cosine_similarity(input, joke)


def get_best(input):
    model = SentenceTransformer('bert-base-nli-mean-tokens')
    max_similarity = -1
    max_idx = 0
    jokes = pyjokes.get_jokes(language='en', category='all')
    jokes_embedding = model.encode(jokes)
    input_embedding = model.encode(input)
    for idx, joke_embedding in enumerate(jokes_embedding):
        sim = similarity(joke_embedding.reshape(-1, 1), input_embedding.reshape(-1,1))
        if(np.sum(sim) > np.sum(max_similarity)):
            max_idx = idx
            max_similarity = sim
    if(np.sum(max_similarity) != -1):
        return jokes[max_idx]
    else:
        return None

def generate_list(input):
    result = []
    n = len(input)
    for Len in range(2, n + 1):
        for i in range(n - Len + 1):
            j = i + Len - 1
            tem = ""
            for k in range(i, j + 1):
                tem += input[k]
            result.append(tem)
    return result


def pattern(input):
    response = input
    for substr in generate_list(input):
        try :
          syn = wn.synsets(substr)[1].hypernyms()[0].hyponyms()[0].hyponyms()[0].lemmas()[0].name()
        except:
          continue
        if(syn != None):
            response = response.replace(substr, syn.upper())

    if(input == response):
      return None
    else :
      return response


def GPT(input):
    return None


def generator(input=None):
    response = []
    if input:

        out1 = GPT(input)
        if(out1):
            for out in out1:
                response.append(out)

        out2 = pattern(input)
        if(out2):
            response.append(out2)

        out3 = get_best(input)
        if(out3):
            response.append(out3)

    else:
        out1 = GPT("Hi, what's the matter")
        if(out1):
            for out in out1:
                response.append(out)

        out2 = pyjokes.get_joke(language='en', category='all')
        if(out2):
            response.append(out2)

    return response #[0] think of doing this

iface = gr.Interface(fn=generator, inputs="text", outputs="text")
iface.launch()