from flask import Flask, render_template, request, send_from_directory
#import numpy as np
import tensorflow as tf
from keras.preprocessing.text import Tokenizer
from tensorflow.keras.preprocessing.sequence import pad_sequences
from keras.models import Sequential
from keras.layers import Dense, Embedding, GRU
import pickle
import re

#import logging
#logging.basicConfig(filename='inputs.log', level=logging.INFO)

def read_pickle(path_in, file_name): 
    tmp=pickle.load(open(path_in + file_name + ".pk", "rb"))
    return tmp
filepath="/root/chatgpt_lstm/"
model=tf.keras.models.load_model(filepath+"allmodel")
tokenizer=read_pickle(filepath,"alltokenizer")

app = Flask(__name__)
#app.config['SQLALCHEMY_DATABASE_URI'] = 'sqlite:////tmp/test.db'
#db = SQLAlchemy(app)

#class Sentence(db.Model):
#    id = db.Column(db.Integer, primary_key=True)
#   text = db.Column(db.String(200), nullable=False)
#    prediction = db.Column(db.Float, nullable=False)

def language(st):
    chn=re.findall(r'[\u4e00-\u9fff]+',st)
    chn="".join(chn)               
    eng=re.findall(r'[A-Za-z]+',st)
    if(len(chn)>len(eng)):
        return True
    else:
        return False

def split_chinese(st):
    try:
        a=" ".join([*st])
        return a
    except:
        return ""
    

@app.route('/', methods=['GET', 'POST'])
def index():
    if request.method == 'POST':
        sentence = str(request.form['sentence'])
        sentence=sentence.replace("\n","").replace("\r","")
        #logging.info(f'Input: {sentence}')
        if language(sentence):
            sentence=split_chinese(sentence)
        new_sequences=tokenizer.texts_to_sequences([sentence])
        print(sentence)
        new_data=pad_sequences(new_sequences,maxlen=400)
        prediction=model.predict(new_data)[0][0]
        print(prediction)
        return render_template('index.html', prediction=prediction,sentence=sentence)
    else:
        return render_template('index.html')

@app.route('/amc', methods=['GET'])
def amc():
    directory = "/root/chatgpt_lstm/"
    filename = "amc.pdf"
    print("in")
    return send_from_directory(directory, filename, as_attachment=False)


#db.create_all()
if __name__ == '__main__': 
    context = ('cert.crt', 'private.key')
    app.run(host='0.0.0.0', port=443,ssl_context=context)
    #app.run(host='0.0.0.0',port=80)