镜像自地址
https://gitee.com/medical-alliance/Medical-nlp.git
已同步 2025-12-06 01:16:47 +00:00
33 行
971 B
Python
33 行
971 B
Python
from gensim.models import KeyedVectors
|
|
from flask import Flask, request, jsonify, send_file
|
|
from flasgger import Swagger
|
|
import os
|
|
import json
|
|
import time
|
|
|
|
time1 = time.time()
|
|
app = Flask(__name__)
|
|
app.config['JSON_AS_ASCII'] = False
|
|
app.config['JSONIFY_MIMETYPE'] = "application/json;charset=utf-8"
|
|
Swagger(app)
|
|
file = 'Tencent_AILab_ChineseEmbedding.txt'
|
|
wv_from_text = KeyedVectors.load_word2vec_format(file, binary=False) # 加载时间比较长
|
|
wv_from_text.init_sims(replace=True)
|
|
print("加载时间为:" + str(time.time() - time1))
|
|
|
|
|
|
@app.route('/api/tengxun', methods=['post'])
|
|
def to_kg():
|
|
data = request.data.decode('utf-8')
|
|
word = json.loads(data)['word']
|
|
if word in wv_from_text.wv.vocab.keys():
|
|
vec = wv_from_text[word]
|
|
return json.dumps({"result": wv_from_text.most_similar(positive=[vec], topn=20)})
|
|
else:
|
|
return json.dumps({"result": "没找到"})
|
|
|
|
|
|
if __name__ == '__main__':
|
|
app.run('0.0.0.0', port=8020)
|
|
~
|