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spell.py
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spell.py
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from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
from __future__ import unicode_literals
from rasa_nlu.components import Component
import numpy as np
from rasa_nlu.tokenizers import Token
class SpellingCorrect(Component):
name = "SpellCorrection"
provides = ["token_spellchecked"]
requires = ["tokens_slangprocessed"]
defaults = {}
language_list = None
def __init__(self, component_config=None):
super(SpellingCorrect, self).__init__(component_config)
def train(self, training_data, cfg, **kwargs):
print("TRAINING SPELLCHECK")
pass
def process(self, message, **kwargs):
from textblob import Word
token_spellchecked=[]
T = None
for token in message.get("tokens_slangprocessed"):
w = Word(token.text).correct()
if len(w)>=1:
a = np.array(w)
print(str(token.text)+" corrected to "+str(a))
token_spellchecked.append(Token(str(a),0))
message.set("token_spellchecked", token_spellchecked)
def persist(self, model_dir):
pass
@classmethod
def load(cls, model_dir=None, model_metadata=None, cached_component=None,
**kwargs):
if cached_component:
return cached_component
else:
component_config = model_metadata.for_component(cls.name)
return cls(component_config)