RuntimeWarning , RuntimeError (Python Al Chat Bot on Discord Server) - python-3.x

Question

My Aim: Be able to integrate Al Chatbot and Discord
import nltk
nltk.download('punkt')
from nltk.stem.lancaster import LancasterStemmer
stemmer=LancasterStemmer()
import numpy
import tflearn
import tensorflow
import random
import json
import pickle
import nest_asyncio
import asyncio
#---------------------------------------------------------------------------
import discord
import os
with open("intents.json") as file:
data=json.load(file)
print(data['intents'])
try:
with open("data.pickle","rb") as f:
words,labels,training,output=pickle.load(f)
except:
words=[]
labels=[]
docs_x=[]
docs_y=[]
for intent in data['intents']:
for pattern in intent['patterns']:
wrds=nltk.word_tokenize(pattern)
words.extend(wrds)
docs_x.append(wrds)
docs_y.append(intent["tag"])
if intent["tag"] not in labels:
labels.append(intent["tag"])
#remove duplicate
words=[stemmer.stem(w.lower()) for w in words if w != "?"]
words=sorted(list(set(words)))
labels=sorted(labels)
training=[]
output=[]
out_empty=[0 for _ in range(len(labels))]
for x, doc in enumerate(docs_x):
bag=[]
wrds=[stemmer.stem(w) for w in doc]
for w in words:
if w in wrds:
bag.append(1)
else:
bag.append(0)
output_row=out_empty[:]
output_row[labels.index(docs_y[x])]=1
training.append(bag)
output.append(output_row)
training=numpy.array(training)
output=numpy.array(output)
with open("data.pickle","wb") as f:
pickle.dump((words,labels,training,output),f)
tensorflow.compat.v1.reset_default_graph()
net=tflearn.input_data(shape=[None,len(training[0])])
net=tflearn.fully_connected(net,16)
net=tflearn.fully_connected(net,16)
net=tflearn.fully_connected(net,len(output[0]),activation="softmax")
net=tflearn.regression(net)
model=tflearn.DNN(net)
model.fit(training, output,n_epoch=10000,batch_size=16,show_metric=True )
model.save('C:/Users/Desktop/chatbot/model/model.tflearn')
model.load('C:/Users/Desktop/chatbot/model/model.tflearn')
def bag_of_words(s,words):
bag=[0 for _ in range(len(words))]
s_words=nltk.word_tokenize(s)
s_words=[stemmer.stem(word.lower()) for word in s_words]
for se in s_words:
for i,w in enumerate(words):
if w==se:
bag[i]=1
return numpy.array(bag)
def chat():
print("start talking with the bot (type quit to stop!")
while True:
inp=input("You:")
if inp.lower()=="quit":
break
results= model.predict([bag_of_words(inp,words)])[0]
# print("results:",results)
results_index=numpy.argmax(results)
if results[results_index]>0.7:
tag=labels[results_index]
print("tag:", tag)
for tg in data["intents"]:
if tg["tag"]==tag:
responses=tg['responses']
client=discord.Client() #FOR DISCORD--------------------------------------
async def on_message(message):
if inp.author == client.user:
return
if inp.content.startswith("$M-bot"):
response=responses.request(inp.content[7:])
await asyncio.sleep(5)
await inp.channel.send(response)
on_message(inp)
client.run("API KEY TAKEN FROM DISCORD for BOT")
print("Bot:",random.choice(responses))
else:
print("I didn't get that. Please try again")
chat()
Warnings and Errors (Pyconsole):
start talking with the bot (type quit to stop!
You:hello
tag: greeting
C:/Users/Desktop/chatbot/chatbot.py:154: RuntimeWarning: coroutine 'chat.<locals>.on_message' was never awaited
on_message(inp)
RuntimeWarning: Enable tracemalloc to get the object allocation traceback
Traceback (most recent call last):
File "F:\Anaconda\lib\site-packages\discord\client.py", line 713, in run
loop.run_forever()
File "F:\Anaconda\lib\asyncio\base_events.py", line 560, in run_forever
self._check_running()
File "F:\Anaconda\lib\asyncio\base_events.py", line 552, in _check_running
raise RuntimeError('This event loop is already running')
RuntimeError: This event loop is already running
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "F:\Anaconda\lib\site-packages\discord\client.py", line 90, in _cleanup_loop
_cancel_tasks(loop)
File "F:\Anaconda\lib\site-packages\discord\client.py", line 75, in _cancel_tasks
loop.run_until_complete(asyncio.gather(*tasks, return_exceptions=True))
File "F:\Anaconda\lib\asyncio\base_events.py", line 592, in run_until_complete
self._check_running()
File "F:\Anaconda\lib\asyncio\base_events.py", line 552, in _check_running
raise RuntimeError('This event loop is already running')
RuntimeError: This event loop is already running
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "C:/Users/Desktop/chatbot/chatbot.py", line 162, in <module>
chat()
File "C:/Users/Desktop/chatbot/chatbot.py", line 155, in chat
client.run("API KEY TAKEN FROM DISCORD for BOT")
File "F:\Anaconda\lib\site-packages\discord\client.py", line 719, in run
_cleanup_loop(loop)
File "F:\Anaconda\lib\site-packages\discord\client.py", line 95, in _cleanup_loop
loop.close()
File "F:\Anaconda\lib\asyncio\selector_events.py", line 89, in close
raise RuntimeError("Cannot close a running event loop")
RuntimeError: Cannot close a running event loop
PROBLEM: Hello Friends, I'm trying to make a chatbot that works on discord and can give its answers through the artificial intelligence model I built, but I am getting a RuntimeWarning: Enable tracemalloc to get the object allocation traceback and RuntimeError: This event loop is already running How can I solve these?

Answer 1

Your error is because you keep reinitiating discord.Client. In every program, there should be only one instance of discord.Client. If you want to make it spit out the last response, you should move client out of the loop. Set the bot's response to a global variable and have the bot spit out the global variable when a command is sent

Answer 2

arrangements:
import nltk
nltk.download('punkt')
from nltk.stem.lancaster import LancasterStemmer
stemmer=LancasterStemmer()
import numpy
import tflearn
import tensorflow
import random
import json
import pickle
import nest_asyncio
import asyncio
#-------------------------------------------------------------------------------
import discord
import os
with open("intents.json") as file:
data=json.load(file)
print(data['intents'])
client=discord.Client() #OUT OF LOOP
#client.event #LISTEN EVENTS
async def on_message(message):
if message.author == client.user:
return
if message.content.startswith("$M-bot"):
response=responses.request(message.content[7:])
await message.channel.send(response)
try:
with open("data.pickle","rb") as f:
words,labels,training,output=pickle.load(f)
except:
words=[]
labels=[]
docs_x=[]
docs_y=[]
for intent in data['intents']:
for pattern in intent['patterns']:
wrds=nltk.word_tokenize(pattern)
words.extend(wrds)
docs_x.append(wrds)
docs_y.append(intent["tag"])
if intent["tag"] not in labels:
labels.append(intent["tag"])
#remove duplicate
words=[stemmer.stem(w.lower()) for w in words if w != "?"]
words=sorted(list(set(words)))
labels=sorted(labels)
training=[]
output=[]
out_empty=[0 for _ in range(len(labels))]
for x, doc in enumerate(docs_x):
bag=[]
wrds=[stemmer.stem(w) for w in doc]
for w in words:
if w in wrds:
bag.append(1)
else:
bag.append(0)
output_row=out_empty[:]
output_row[labels.index(docs_y[x])]=1
training.append(bag)
output.append(output_row)
training=numpy.array(training)
output=numpy.array(output)
with open("data.pickle","wb") as f:
pickle.dump((words,labels,training,output),f)
tensorflow.compat.v1.reset_default_graph()
net=tflearn.input_data(shape=[None,len(training[0])])
net=tflearn.fully_connected(net,16)
net=tflearn.fully_connected(net,16)
net=tflearn.fully_connected(net,len(output[0]),activation="softmax")
net=tflearn.regression(net)
model=tflearn.DNN(net)
model.fit(training, output,n_epoch=5000,batch_size=16,show_metric=True )
model.save('C:/Users/Desktop/chatbot/model/model.tflearn')
model.load('C:/Users/Desktop/chatbot/model/model.tflearn')
def bag_of_words(s,words):
bag=[0 for _ in range(len(words))]
s_words=nltk.word_tokenize(s)
s_words=[stemmer.stem(word.lower()) for word in s_words]
for se in s_words:
for i,w in enumerate(words):
if w==se:
bag[i]=1
return numpy.array(bag)
def chat():
global responses #GLOBAL VARIABLES
global inp #GLOBAL VARIABLES
print("start talking with the bot (type quit to stop!")
while True:
inp=input("You:")
if inp.lower()=="quit":
break
results= model.predict([bag_of_words(inp,words)])[0]
# print("results:",results)
results_index=numpy.argmax(results)
if results[results_index]>0.7:
tag=labels[results_index]
print("tag:", tag)
for tg in data["intents"]:
if tg["tag"]==tag:
responses=tg['responses']
print("Bot:",random.choice(responses))
else:
print("I didn't get that. Please try again")
chat()
client.run("API KEY")