def prepare_index(dictionary, model, tfidf, documents):
if not os.path.isfile('soft_cosine.index'):
similarity_index = WordEmbeddingSimilarityIndex(model.wv)
similarity_matrix = SparseTermSimilarityMatrix(similarity_index,
dictionary, tfidf)
index = SoftCosineSimilarity(
tfidf[[dictionary.doc2bow(document) for document in documents]],
similarity_matrix)
index.save('soft_cosine.index')
return SoftCosineSimilarity.load('soft_cosine.index')
# dictionary, index and article_ids are used if past_behavior (SoftCosine) recommender is used
try:
lda_model = gensim.models.LdaModel.load("put path to model here")
except:
lda_model = None
try:
lda_dict = gensim.corpora.Dictionary.load("/put path to dict here")
except:
lda_dict = None
try:
dictionary = gensim.corpora.Dictionary.load("put path to dict here")
except:
dictionary = None
try:
index = SoftCosineSimilarity.load('put path to index here')
except:
index = None
try:
article_ids = pickle.load(open('put path to article ids here', 'rb'))
except:
article_ids = None
login.login_view = 'login'
if not app.debug:
if app.config['MAIL_SERVER']:
auth = None
if app.config['MAIL_USERNAME'] or app.config['MAIL_PASSWORD']:
auth = (app.config['MAIL_USERNAME'], app.config['MAIL_PASSWORD'])
secure = None
if app.config['MAIL_USE_TLS']:
