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80 lines
3.2 KiB
Python
80 lines
3.2 KiB
Python
from rasa.nlu.classifiers.diet_classifier import DIETClassifier
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from rasa.nlu.classifiers.fallback_classifier import FallbackClassifier
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from rasa.nlu.classifiers.keyword_intent_classifier import KeywordIntentClassifier
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from rasa.nlu.classifiers.logistic_regression_classifier import (
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LogisticRegressionClassifier,
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)
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from rasa.nlu.classifiers.mitie_intent_classifier import MitieIntentClassifier
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from rasa.nlu.classifiers.sklearn_intent_classifier import SklearnIntentClassifier
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from rasa.nlu.extractors.crf_entity_extractor import CRFEntityExtractor
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from rasa.nlu.extractors.duckling_entity_extractor import DucklingEntityExtractor
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from rasa.nlu.extractors.entity_synonyms import EntitySynonymMapper
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from rasa.nlu.extractors.mitie_entity_extractor import MitieEntityExtractor
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from rasa.nlu.extractors.spacy_entity_extractor import SpacyEntityExtractor
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from rasa.nlu.extractors.regex_entity_extractor import RegexEntityExtractor
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from rasa.nlu.featurizers.sparse_featurizer.lexical_syntactic_featurizer import (
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LexicalSyntacticFeaturizer,
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)
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from rasa.nlu.featurizers.dense_featurizer.convert_featurizer import ConveRTFeaturizer
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from rasa.nlu.featurizers.dense_featurizer.mitie_featurizer import MitieFeaturizer
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from rasa.nlu.featurizers.dense_featurizer.spacy_featurizer import SpacyFeaturizer
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from rasa.nlu.featurizers.sparse_featurizer.count_vectors_featurizer import (
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CountVectorsFeaturizer,
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)
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from rasa.nlu.featurizers.dense_featurizer.lm_featurizer import LanguageModelFeaturizer
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from rasa.nlu.featurizers.sparse_featurizer.regex_featurizer import RegexFeaturizer
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from rasa.nlu.selectors.response_selector import ResponseSelector
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from rasa.nlu.tokenizers.jieba_tokenizer import JiebaTokenizer
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from rasa.nlu.tokenizers.mitie_tokenizer import MitieTokenizer
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from rasa.nlu.tokenizers.spacy_tokenizer import SpacyTokenizer
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from rasa.nlu.tokenizers.whitespace_tokenizer import WhitespaceTokenizer
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from rasa.nlu.utils.mitie_utils import MitieNLP
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from rasa.nlu.utils.spacy_utils import SpacyNLP
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from rasa.core.policies.ted_policy import TEDPolicy
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from rasa.core.policies.memoization import MemoizationPolicy, AugmentedMemoizationPolicy
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from rasa.core.policies.rule_policy import RulePolicy
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from rasa.core.policies.unexpected_intent_policy import UnexpecTEDIntentPolicy
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DEFAULT_COMPONENTS = [
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# Message Classifiers
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DIETClassifier,
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FallbackClassifier,
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KeywordIntentClassifier,
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MitieIntentClassifier,
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SklearnIntentClassifier,
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LogisticRegressionClassifier,
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# Response Selectors
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ResponseSelector,
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# Message Entity Extractors
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CRFEntityExtractor,
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DucklingEntityExtractor,
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EntitySynonymMapper,
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MitieEntityExtractor,
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SpacyEntityExtractor,
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RegexEntityExtractor,
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# Message Feauturizers
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LexicalSyntacticFeaturizer,
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ConveRTFeaturizer,
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MitieFeaturizer,
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SpacyFeaturizer,
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CountVectorsFeaturizer,
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LanguageModelFeaturizer,
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RegexFeaturizer,
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# Tokenizers
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JiebaTokenizer,
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MitieTokenizer,
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SpacyTokenizer,
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WhitespaceTokenizer,
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# Language Model Providers
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MitieNLP,
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SpacyNLP,
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# Dialogue Management Policies
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TEDPolicy,
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UnexpecTEDIntentPolicy,
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RulePolicy,
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MemoizationPolicy,
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AugmentedMemoizationPolicy,
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]
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