#CLIENT ID = 580839584422690827
import discord
import wikipedia
import random
import requests
import time
import tensorflow as tf
import numpy as np
start = time.time()
EMBEDDING_DIM = 512

def lstm_model(seq_len=150, batch_size=None, stateful=True):
  source = tf.keras.Input(
      name='seed', shape=(seq_len,), batch_size=batch_size, dtype=tf.int32)

  embedding = tf.keras.layers.Embedding(input_dim=256, output_dim=EMBEDDING_DIM)(source)
  lstm_1 = tf.keras.layers.LSTM(EMBEDDING_DIM, stateful=stateful, return_sequences=True)(embedding)
  lstm_2 = tf.keras.layers.LSTM(EMBEDDING_DIM, stateful=stateful, return_sequences=True)(lstm_1)
  predicted_char = tf.keras.layers.TimeDistributed(tf.keras.layers.Dense(256, activation='softmax'))(lstm_2)
  model = tf.keras.Model(inputs=[source], outputs=[predicted_char])
  model.compile(
      optimizer=tf.train.RMSPropOptimizer(learning_rate=0.01),
      loss='sparse_categorical_crossentropy',
      metrics=['sparse_categorical_accuracy'])
  return model
#print(discord.__version__)  # check to make sure at least once you're on the right version!
token = replace this

client = discord.Client()  # starts the discord client.
loop = False

@client.event  # event decorator/wrapper. More on decorators here: https://pythonprogramming.net/decorators-intermediate-python-tutorial/
async def on_ready():  # method expected by client. This runs once when connected
    print(f'We have logged in as {client.user}')  # notification of login.


@client.event
async def on_message(message):  # event that happens per any message.
    print(f"{message.channel}: {message.author}: {message.author.name}: {message.content}")
    if "!wiki" in message.content.lower():
        await message.channel.send('Alright, you searched wikipedia for' + message.content.replace("!wiki", ""))
        try:
            sumy = wikipedia.summary(message.content.replace("!wiki", ""))
            await message.channel.send(sumy)
        except Exception as e:
            await message.channel.send("No article found")
    elif "!randnum" in message.content.lower():
        msg = message.content.lower()
        parsed_msg = msg.replace("!randnum", "")
        await message.channel.send("Random number generating between: " + parsed_msg)
        randnum = random.randint(*[int(number) for number in parsed_msg.split('-')])
        await message.channel.send(randnum)
    elif "!addme" in message.content.lower():
        await message.channel.send("https://discordapp.com/oauth2/authorize?client_id=580839584422690827&scope=bot&permissions=8")
    elif "!joke" in message.content.lower():
            r = requests.get('https://icanhazdadjoke.com', headers={"Accept":"application/json"})
            raw_joke = r.json()['joke'];
            await message.channel.send(raw_joke)
    elif "!image" in message.content.lower():
        await message.channel.send("https://media.tenor.com/images/1b3aa48cfa63240adfef3a61a179bec0/tenor.gif")
    elif("!trump" in message.content.lower() and time.time()-start < 30): # 30 second guard from spam
        PREDICT_LEN = 280
        prediction_model = lstm_model(seq_len=1, batch_size=BATCH_SIZE, stateful=True)
        prediction_model.load_weights('thedonald.h5')
        seed_txt = message.content.lower()[6:]
        seed = transform(seed_txt)
        seed = np.repeat(np.expand_dims(seed, 0), BATCH_SIZE, axis=0)
        prediction_model.reset_states()
        for i in range(len(seed_txt) - 1):
          prediction_model.predict(seed[:, i:i + 1])
        predictions = [seed[:, -1:]]
        for i in range(PREDICT_LEN):
          last_word = predictions[-1]
          next_probits = prediction_model.predict(last_word)[:, 0, :]
          next_idx = [
              np.random.choice(256, p=next_probits[i])
              for i in range(BATCH_SIZE)
          ]
          predictions.append(np.asarray(next_idx, dtype=np.int32))
        for i in range(BATCH_SIZE):
      p = [predictions[j][i] for j in range(PREDICT_LEN)]
      generated = ''.join([chr(c) for c in p])
      start=time.time()
      await message.channel.send(generated)
      start=time.time()
    if (str(message.author.name) == "Skierman" or str(message.author.name) == "TauPiPhi") and "who am i" in message.content.lower():
        await message.channel.send('The most amazing person ever!!!')
    if("Watch your profanity." in message.content.lower() and loop < 10):
        loop +=1
        await message.channel.send("Watch your fucking profanity.")
    elif(loop>=10):
        loop = 0


client.run(token)  # recall my token was saved!