【NLP】pyhanlp flask

D:\ProgramData\Anaconda3\Lib\site-packages\pyhanlp\__init__.py 加入

WordVectorModel = LazyLoadingJClass('com.hankcs.hanlp.mining.word2vec.WordVectorModel')

 

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# coding=utf-8 from flask import Flask from flask import request from flask import jsonify from flask import make_response,Response from flask_cors import CORS from pyhanlp import *   port = 9999 app = Flask(__name__) CORS(app, supports_credentials=True)   @app.route('/') def index():     str = "Hello, AI Server!"     print(str)     return str   # 成功请求 def successResp(data):     return jsonify(code=0, message="success", data=data)   # 错误请求 def errorResp(msg):     return jsonify(code=-1, message=msg)     # 分词服务 @app.route('/NLPWordSplit', methods=['POST']) def NLPWordSplit():     Article = request.form.get('Article')     print(Article)       if Article == None or Article == "" :         rst = make_response(errorResp("请输入正确的数据！"))         rst.headers['Access-Control-Allow-Origin'] = '*'         return rst       word = ""     for term in HanLP.segment(Article):         curWord = str(term.word)         if len(curWord) != 0:             word = word + " " + curWord     print(word)       return getResult(word)   # 词向量服务 @app.route('/NLPWordNearest', methods=['POST']) def NLPWordNearest():     Word = request.form.get('Word')     print(Word)       if Word == None or Word == "" :         rst = make_response(errorResp("请输入正确的数据！"))         rst.headers['Access-Control-Allow-Origin'] = '*'         return rst     try:         # WordVectorModel = LazyLoadingJClass('com.hankcs.hanlp.mining.word2vec.WordVectorModel')         # print(WordVectorModel)         # MODEL_FILE_NAME = r"E:\Model.txt"         # # 初始化模型         # word2vec = WordVectorModel(MODEL_FILE_NAME)         # print(word2vec)         if word2vec != None:             print("相关词分析")             word = word2vec.nearest(Word)             print(word)             data = ""             for x in word:                 if data == "":                     data = str(x).replace("=",":")                 else:                     data = data + "," + str(x).replace("=",":")             print(data)               word = "{" + data + "}"             # word = json.dumps(word)             # word = ','.join(word)             print(word)             return getResult(word)         else:             rst = make_response(errorResp("单词分析错误！"))             rst.headers['Access-Control-Allow-Origin'] = '*'             return rst     except Exception as e:         print("Exception:",e)     finally:         print("OK")   def getResult(word):     if word != "":         # 如果成功返回预测结果         rst = make_response(successResp(word))         rst.headers['Access-Control-Allow-Origin'] = '*'         return rst     else:         # 如果失败返回错误信息         rst = make_response(errorResp(word))         rst.headers['Access-Control-Allow-Origin'] = '*'         return rst   word2vec = None if __name__ == '__main__':     # if not jpype.isThreadAttachedToJVM():     #     jpype.attachThreadToJVM()     # WordVectorModel = jpype.JClass("com.hankcs.hanlp.mining.word2vec.WordVectorModel")     # print(WordVectorModel)     MODEL_FILE_NAME = r"E:\Model.txt"     # 初始化模型     word2vec = WordVectorModel(MODEL_FILE_NAME)     print("port:" + str(port))     app.run(debug = True,host = '0.0.0.0',port = port, threaded = True)