Objective :- I want o generate an web link for other users in my team to interact with the bot

Here is the code which I am using in Google Cloud Shell

from flask import Flask,Response
import pandas as pd
import gspread
from oauth2client.service_account import ServiceAccountCredentials
from sklearn.svm import SVC
from sklearn.model_selection import train_test_split as tts
from sklearn.feature_extraction.text import TfidfVectorizer
from sklearn.preprocessing import LabelEncoder as LE
from sklearn.metrics.pairwise import cosine_similarity
import nltk
nltk.download('punkt')
from nltk.stem.lancaster import LancasterStemmer


scope = ['https://spreadsheets.google.com/feeds','https://www.googleapis.com/auth/drive']

credentials = ServiceAccountCredentials.from_json_keyfile_name('bot-1234.json', scope)
gc = gspread.authorize(credentials)
faq = pd.DataFrame(gc.open('Data Gathering').worksheet('Sheet1').get_all_records())

stemmer = LancasterStemmer()

def cleanup(sentence):
        word_tok = nltk.word_tokenize(sentence)
        stemmed_words = [stemmer.stem(w) for w in word_tok]

        return ' '.join(stemmed_words)
le = LE()

tfv = TfidfVectorizer(min_df=1, stop_words='english')

questions = faq['Questions'].values


X = []

for question in questions:
        X.append(cleanup(question))

tfv.fit(X)
le.fit(faq['Class'])

X = tfv.transform(X)
y = le.transform(faq['Class'])


trainx, testx, trainy, testy = tts(X, y, test_size=.25, random_state=42)

model = SVC(kernel='linear')
model.fit(trainx, trainy)
print("SVC:", model.score(testx, testy))

def get_max5(arr):
        ixarr = []
        for ix, el in enumerate(arr):
            ixarr.append((el, ix))
        ixarr.sort()

        ixs = []
        for i in ixarr[-5:]:
            ixs.append(i[1])

        return ixs[::-1]




app = Flask(__name__)
@app.route('/', methods=['GET','POST'])
def test():
 def chat():
        cnt = 0
        print("TYPE \"Q\" or \"END\" or \"Quit\" or \"E\" and hit ENTER to QUIT")
        print()
        print()
        DEBUG = False
        TOP5 = False

        print("BOT: Hi, Welcome to BOT - The Assistant!")
        while True:
            usr =input("You:")

            if usr.lower() == 'yes':
                print("BOT: Yes!")
                continue

            if usr.lower() == 'no':
                print("BOT: No?")
                continue

            if usr == 'DEBUG':
                DEBUG = True
                print("Debugging mode on")
                continue

            if usr == 'STOP':
                DEBUG = False
                print("Debugging mode off")
                continue

            if usr.lower() in ('q','quit','end','e') :
                print("BOT: It was good to be of help.")
                break

            if usr == 'TOP5':
                TOP5 = True
                print("Will display 5 most relevent results now")
                continue

            if usr == 'CONF':
                TOP5 = False
                print("Only the most relevent result will be displayed")
                continue

            t_usr = tfv.transform([cleanup(usr.strip().lower())])
            class_ = le.inverse_transform(model.predict(t_usr))
            questionset = faq[faq['Class']==class_[0]]

            if DEBUG:
                print("Question classified under category:", class_)
                print("{} Questions belong to this class".format(len(questionset)))


            cos_sims = []
            for question in questionset['Questions']:
                sims = cosine_similarity(tfv.transform([question]), t_usr)
                cos_sims.append(sims)

            ind = cos_sims.index(max(cos_sims))

            if DEBUG:
                question = questionset["Questions"][questionset.index[ind]]
                print("Assuming you asked: {}".format(question))

            if not TOP5:
                print("BOT:", faq['Answer'][questionset.index[ind]])
            else:
                inds = get_max5(cos_sims)
                for ix in inds:
                    print("Question: "+faq['Questions'][questionset.index[ix]])
                    print("Answer: "+faq['Answer'][questionset.index[ix]])
                    print('-'*50)

            print("\n"*2)
            outcome = input("Was this answer helpful? Yes/No: ").lower().strip()
            if outcome == 'yes':
                    cnt = 0
            elif outcome == 'no':
                inds = get_max5(cos_sims)
                sugg_choice = input("BOT: Do you want me to suggest you questions ? Yes/No: ").lower()
                if sugg_choice == 'yes':
                    q_cnt = 1
                    for ix in inds:
                        print(q_cnt,"Question: "+faq['Questions'][questionset.index[ix]])
                        # print("Answer> "+faq['Answer'][questionset.index[ix]])a............................
                        print('-'*50)
                        q_cnt += 1
                    num = int(input("Please enter the question number you find most relevant: "))
                    print("BOT: ", faq['Answer'][questionset.index[inds[num-1]]])

 return Response(chat(), mimetype='text/plain')       

if __name__ == '__main__':
    app.run(host='127.0.0.1', port=8080, debug=True)

Here is app.yaml file:-

runtime: python
# vm: true has been deprecated
# check how env:flex may affect your billing
env: flex
entrypoint: gunicorn -b :$PORT main:app

runtime_config:
    python_version: 3.7

Here is requirements.txt file:-

Flask ==0.11.1
gunicorn==19.6.0
gspread==3.1.0
oauth2client==4.1.3
PyOpenSSL==18.0.0
numpy==1.15.4
scikit-image==0.14.1
scikit-learn==0.20.1
scipy==1.1.0
nltk==3.4
pandas==0.23.4

Error :-

It runs smoothly in Cloud shell without any error. But in error logs it shows this

Traceback (most recent call last):
  File "/env/lib/python3.7/site-packages/flask/app.py", line 1988, in wsgi_app
    response = self.full_dispatch_request()
  File "/env/lib/python3.7/site-packages/flask/app.py", line 1641, in full_dispatch_request
    rv = self.handle_user_exception(e)
  File "/env/lib/python3.7/site-packages/flask/app.py", line 1544, in handle_user_exception
    reraise(exc_type, exc_value, tb)
  File "/env/lib/python3.7/site-packages/flask/_compat.py", line 33, in reraise
    raise value
  File "/env/lib/python3.7/site-packages/flask/app.py", line 1639, in full_dispatch_request
    rv = self.dispatch_request()
  File "/env/lib/python3.7/site-packages/flask/app.py", line 1625, in dispatch_request
    return self.view_functions[rule.endpoint](**req.view_args)
  File "/home/vmagent/app/main.py", line 170, in test
    return Response(chat(), mimetype='text/plain')
  File "/home/vmagent/app/main.py", line 90, in chat
    usr = input("You:")
EOFError: EOF when reading a line

Done lot of researching but unable to find how to make my bot work. I know the problem is with the code where I am asking it to interact with the app using flask and I am unable to fix it.

Please help!

0 Answers