from colabcode import ColabCode ColabCode(port=10000)
except:
address = 'Không thể nhận biết'
try:
timestamp = ' '.join(dict_cls[2])
except:
timestamp = 'Không thể nhận biết'
try:
totalcost = totalcost[-1]
except:
totalcost = 'Không thể nhận biết'
# Trả về kết quả ra json
dict_out = {
"seller": seller,
"address": address,
"timestamp": timestamp,
"totalcost": totalcost,
}
return dict_out
# run server
server = ColabCode(
port=10001,
code=False,
authtoken='1tZN1OIxC54y7we1FQlNRXusGcS_4vwyHgHDwhUi9vTKsmRKc')
server.run_app(app=app)
Position_Names_Vec = np.load('/content/drive/MyDrive/Colab Notebooks/Job Analysis/Position_Names_Vec.npy', allow_pickle=True)
@app.get('/')
def index():
return {'message': 'This is the homepage of the API '}
@app.post('/predict')
def predict_job(data: Text):
word_seq, word_index =preprocessData([data.text], tokenizer)
pred=model.predict(word_seq)
output = []
max=0.0
for i in range(Position_Names_Vec.shape[0]):
cos= cosine_similarity([pred[0],Position_Names_Vec[i]])[0][1]
output.append(cos)
if cos > max:
max = cos
print(max)
dictionary = pd.DataFrame(Position_Names, columns=['Position'])
dictionary['Cosine'] = output
dictionary=dictionary.sort_values(by=['Cosine'], ascending=False)
return {'Position': dictionary.head(10)['Position'].tolist(), 'Cosine': dictionary.head(10)['Cosine'].tolist()}
from colabcode import ColabCode
server = ColabCode(port=10000, code=False)
server.run_app(app=app)
from colabcode import ColabCode ColabCode()