feat:add dockerfile

Issue-ID: USECASEUI-525
Signed-off-by: wangy122 <wangy122@chinatelecom.cn>
Change-Id: Ifca8abdfff479216bb0ea6b84d2c61fb640039f5

1 files changed, 108 insertions, 0 deletions

diff --git a/scripts/api_squad_online.py b/scripts/api_squad_online.py
new file mode 100644
index 0000000..9cc6b08
--- /dev/null
+++ b/scripts/api_squad_online.py
@@ -0,0 +1,108 @@
+
+#!/usr/bin/env python
+# coding: utf-8
+
+# auther = 'liuzhiyong'
+# date = 20201204
+
+
+
+from __future__ import absolute_import
+from __future__ import division
+from __future__ import print_function
+import json
+import datetime
+import threading
+import sys
+from flask import Flask, abort, request, jsonify
+from concurrent.futures import ThreadPoolExecutor
+
+import collections
+import math
+import os
+import random
+import modeling
+import optimization
+import tokenization
+import six
+import tensorflow as tf
+import pandas as pd
+import numpy as np
+import requests
+from global_setting import *
+from create_squad_features import get_squad_feature_result
+
+
+app = Flask(__name__)
+
+
+class AI2Flask:
+
+    def __init__(self, port=5000,workers=4):
+        self.app = app
+        self.port = port
+
+
+        
+        @app.route('/api/online/predict', methods=['POST'])
+        def text_analyse():
+            if not request.json:
+                abort(400)
+           
+            else:
+                try:
+                    try:
+                        title = request.json['title']
+                    except:
+                        title = 'Not available'
+                    text_origin = request.json['text']
+                   
+
+                    if len(text_origin) > 800:
+                        text = text_origin[:800]
+                    else:
+                        text = text_origin
+
+                    result = {}
+                    for ques in questions:
+                        tmp = get_squad_feature_result(title=title,text=text,tokenizer=tokenizer_ch,question=[ques],url='http://localhost:8502/v1/models/predict:predict')
+                        result[ques] = dict(tmp)[ques]
+                              
+                    
+                    print('finished!!')
+                    return json.dumps(result)
+ 
+            
+                except KeyError as e:
+                    return jsonify({"Des": 'KeyError: {}'.format(str(e)), "Result": 'None', "Status": "Error"})
+                except Exception as e:
+                    return jsonify({"Des": str(e), "Result": 'None', "Status": "Error"})
+        
+        
+    
+
+
+
+        @app.route('/api/online/load', methods=['POST'])
+        def load_model():
+            if not request.json:
+                abort(400)
+            else:
+                try:
+                    path = request.json['path']
+                    flag = os.system('./load_model.sh ' + path + ' ' + CUDA_VISIBLE_DEVICES)
+                    if flag == 0:
+                        return jsonify({"Des": "Model loaded successfully !", "Status": "OK"})
+                    else:
+                        return jsonify({"Des": "Model loaded failed , check the logs !", "Status": "Error"})
+                except Exception as e:
+                    return jsonify({"Des": str(e), "Status": "Error"})
+
+    def start(self):
+        self.app.run(host="0.0.0.0", port=self.port, threaded=True)
+
+
+if __name__ == '__main__':
+    port = sys.argv[1]
+    AI2Flask(port=port).start()
+