def api_gensim_summarization():
document = RequestService().get_parameter('document')
try:
ratio = float(request.args.get('ratio') if 'ratio' in request.args else '')
except ValueError:
ratio = 0.2
try:
word_count = int(request.args.get('word_count') if 'word_count' in request.args else '')
except ValueError:
word_count = None
try:
split = bool(request.args.get('split') if 'split' in request.args else 'True')
except ValueError:
split = True
result = gensim.summarize(document=document, ratio=ratio, word_count=word_count, split=split)
return jsonify(result)
def api_textblob_language_detection():
document = RequestService().get_parameter('document')
result = textblob.detect_language(document=document)
return jsonify(result)
def api_vader_sentiment_analysis_nlp():
document = RequestService().get_parameter('document')
result = nltk.vader_sentiment_analysis(document=document)
return jsonify(result)
def api_textblob_spelling_correction():
document = RequestService().get_parameter('document')
result = textblob.spelling_correction(document=document)
return jsonify(result)
def api_textblob_translation():
document = RequestService().get_parameter('document')
language = RequestService().get_parameter('language')
result = textblob.translate(document=document, language=language)
return jsonify(result)
def api_spacy_similarity():
model = RequestService().get_parameter('model')
document = RequestService().get_parameter('document')
similarTo = RequestService().get_parameter('similarTo')
result = spacy.similarity(model, document, similarTo)
return jsonify(result)
def api_textblob_nlp():
document = RequestService().get_parameter('document')
result = textblob.nlp(document=document)
return jsonify(result)
def api_allennlp_open_information_extraction():
document = RequestService().get_parameter('document')
model = allenNlp.open_information_extraction(document=document)
return jsonify(model)
def api_spacy():
model = RequestService().get_parameter('model')
document = RequestService().get_parameter('document')
result = spacy.nlp(model, document)
return jsonify(result)
def api_allennlp_coreference_resolution():
document = RequestService().get_parameter('document')
model = allenNlp.coreference_resolution(document=document)
return jsonify(model)
def api_allennlp_dependency_parsing():
document = RequestService().get_parameter('document')
model = allenNlp.dependency_parsing(document=document)
return jsonify(model)
def api_allennlp_textual_entailment():
document = RequestService().get_parameter('document')
hypothesis = RequestService().get_parameter('hypothesis')
model = allenNlp.textual_entailment(document=document, hypothesis=hypothesis)
return jsonify(model)
def api_allennlp_machine_comprehension():
document = RequestService().get_parameter('document')
question = RequestService().get_parameter('question')
model = allenNlp.machine_comprehension(document=document, question=question)
return jsonify(model)
def api_allennlp_semantic_role_labeling():
document = RequestService().get_parameter('document')
model = allenNlp.semantic_role_labeling(document=document)
return jsonify(model)
def api_allennlp_named_entity_recognition():
document = RequestService().get_parameter('document')
model = allenNlp.named_entity_recognition(document=document)
return jsonify(model)
def api_allennlp_event2mind():
document = RequestService().get_parameter('document')
model = allenNlp.event2mind(document=document)
return jsonify(model)