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Add sentence tokenization to process longer texts. #71

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Add sentence tokenization to process longer texts. #71

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22 changes: 19 additions & 3 deletions api.py
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Original file line number Diff line number Diff line change
Expand Up @@ -3,6 +3,9 @@

from bert import Ner

import nltk.data
sent_detector = nltk.data.load('tokenizers/punkt/english.pickle')

app = Flask(__name__)
CORS(app)

Expand All @@ -11,12 +14,25 @@
@app.route("/predict",methods=['POST'])
def predict():
text = request.json["text"]
sentences = sent_detector.tokenize(text)

try:
out = model.predict(text)
return jsonify({"result":out})
ner_tagged_sentences = []
for sentence in sentences:
if len(sentence) < 512:
tagged_sentence = model.predict(sentence)
ner_tagged_sentences.extend(tagged_sentence)
else:
chunks = [sentence[x:x+512] for x in range(0, len(sentence), 512)]
tagged_sentence = []
for chunk in chunks:
ner_chunk = model.predict(chunk)
tagged_sentence.extend(ner_chunk)
ner_tagged_sentences.extend(tagged_sentence)
return jsonify({"result":ner_tagged_sentences})
except Exception as e:
print(e)
return jsonify({"result":"Model Failed"})

if __name__ == "__main__":
app.run('0.0.0.0',port=8000)
app.run('0.0.0.0',port=8000)