How to use the spacy-annotator.displacy.parse.TrainEntities function in spacy-annotator
To help you get started, we’ve selected a few spacy-annotator examples, based on popular ways it is used in public projects.
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explosion / spacy-dev-resources / spacy-annotator / displacy / server.py View on Github 
def on_post(self, req, resp):
req_body = req.stream.read()
json_data = json.loads(req_body.decode('utf8'))
paragraphs = json_data.get('paragraphs')
model_name = json_data.get('model', 'en')
try:
model = get_model(model_name)
texts = [paragraph.get('text') for paragraph in paragraphs]
update_vocabulary(model, texts)
entities = []
for p in paragraphs:
e = TrainEntities(model, p.get('text'), p.get('tags'))
entities.append(e.to_json())
resp.body = json.dumps(entities, sort_keys=True, indent=2)
resp.content_type = 'application/json'
resp.status = falcon.HTTP_200
except Exception:
print("Unexpected error:", sys.exc_info()[0])
resp.status = falcon.HTTP_500spacy-annotator
SpaCy annotator for Named Entity Recognition (NER) using ipywidgets.
