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from clarifai.rest import ClarifaiApp

app = ClarifaiApp()
def get_concept_tags(image_url):
    response_data = app.tag_urls([image_url])

    tags = []
    for concept in response_data['outputs'][0]['data']['concepts']:
        tags.append(concept['name'])

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from flask import Flask, request
from twilio.twiml.messaging_response import MessagingResponse

from clarifai_tagger import get_concept_tags

app = Flask(__name__)

#this is a list of concepts we will look for among all possible Clarifai concepts
spooky_concepts = ['scary','eerie','dark','monochrome','spider','spiderweb',
                    'arachnid','phobia','fog','mystery','shadow','abandoned',

everling-prime

from IPython.display import Image
from IPython.core.display import HTML 
Image(url="")

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def prepare_for_fasttext(tweets_df):

  with open('tweets.txt', 'w') as file:
    for i, row in tweets_df.iterrows():
      if row['class'] == 0:
        label = ' __label__ hate_speech'
      if row['class'] == 1:
        label = ' __label__ offensive_language'
      else:
        label = ' __label__ neither'

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def memo(f):
    "Memoize function f, whose args must all be hashable."
    cache = {}
    def fmemo(*args):
        if args not in cache:
            cache[args] = f(*args)
        return cache[args]
    fmemo.cache = cache
    return fmemo

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