PaperText_Segmentation/segment_app.py

# 试题切割服务：TopicSegment predict


from gevent import monkey; monkey.patch_all()  # linux
from gevent.pywsgi import WSGIServer
from flask import Flask, jsonify
# from flask import request
from flask import request
import json
import time
from flask_cors import *

from PointerNet import config
from PointerNet.predictor import Predictor

logger = config.myLog(__name__, log_cate="TopicSegment_predict_log").getlog()

app = Flask(__name__)
app.debug = True
CORS(app, supports_credentials=True)


nerArgs = config.NerArgs()
pred = Predictor(nerArgs)


@app.route('/math_phy_TopicSegment_predict', methods=["POST", "GET"])
def topicType_predict():
    """
    物理题型预测
    post以json格式上传时，content可以传str或list
    :return:
    """
    content = request.json.get("content", "")  # 试题/试卷
    text_type = request.json.get("text_type", "stem_block")
    subject = request.json.get("subject", "数学")
    paper_id = request.json.get("paper_id", "temp_{}".format(int(time.time())))
    logger.info(json.dumps({"log_level": "info",
                            "request_ip": request.remote_addr,
                            "content": content,
                            "paper_id": paper_id,
                            "subject": subject,
                            "text_type": text_type}, ensure_ascii=False))

    if not content:
        return ""
    elif type(content) != str:
        return "只接受str传参类型"
    
    pred_res = pred.predict(content, con_type=text_type, paper_id=paper_id, subject=subject)


    
    logger.info(json.dumps({"log_level": "info",
                            "content": content,
                            "pred_res": pred_res}, ensure_ascii=False))

    return jsonify({"res":pred_res})


if __name__ == "__main__":
    server = WSGIServer((config.server_ip, config.server_port), app)
    server.serve_forever()