Translation + Classification + Extraction

app.py

@@ -5,12 +5,20 @@ from random import randrange
 import datetime
 from apscheduler.schedulers.background import BackgroundScheduler
 from apscheduler.triggers.cron import CronTrigger
+import tensorflow_text
+from tensorflow import keras
+import spacy
+from googletrans import Translator
+
 
 app = Flask(__name__)
 
 ordo = None
 hist = None
 lock_hist = None
+model_b = None
+model_s = None
+model_t = None
 
 def check_week_clear():
     global lock_hist
@@ -25,7 +33,8 @@ def check_week_clear():
         print("Done ! Schedule Reset.")
     return 0
 
-@app.before_first_request
+
+
 def start():
     global lock_hist
     global ordo
@@ -34,6 +43,22 @@ def start():
     hist = []
     lock_hist = []
 
+    # Chargement des deux modèles:
+    global model_b
+    global model_s
+    global model_t
+    print("Loading Translation Model ...")
+    model_t = Translator()
+    print("Model Translation Loaded")
+    print("Loading Model Bert ....")
+    model_b = keras.models.load_model('./static/model/model-classifier')
+    print("Model Bert Loaded")
+    print("Loading Model Spacy ...")
+    model_s = spacy.load("./static/model/model-extraction")
+    print("Model Spacy Loaded")
+    
+
+
 
 @app.route('/', methods = ['POST', 'GET'])
 def index():
@@ -56,16 +81,36 @@ def get_post_javascript_data():
     global hist
     jsdata = request.form['javascript_data']
     # Traitement NLP
-    
-    # Sending data to UI
-    nb_pages = randrange(4000, 10000)
-    result = ordo.add_creneau(nb_pages)
-    if result[0] == -1:
-        response = {'flask_data': f"Something is wrong : {result[1]}"}
+    global model_t
+    global model_b
+    global model_s
+
+    #Translation ...
+    translated_text = (model_t.translate(jsdata, dest='en')).text
+
+    print(f"Translated Text: {translated_text}")
+    #Classification + Extraction
+    y_pred_c = model_b.predict([translated_text])
+    print(f"Classifier : {y_pred_c}")
+    if y_pred_c[0] < 0.5:
+        response = {'flask_data': "Something is wrong : Your request is not accepted make sure to precise the name of the document and the number of pages"}
     else:
-        hist.append(result)
-        response = {'flask_data': f"Done : you can find your query in the calendar ! Take care. ! Nb Pages : {nb_pages}"}
-    
+        # Sending data to UI
+        doc = model_s(translated_text)
+        print(f'Extraction : {doc.ents}')
+        nb_pages = -1
+        for ent in doc.ents:
+            if ent.label_ == "DocName":
+                nb_pages = int(ent.text)
+                break
+        result = ordo.add_creneau(nb_pages)
+        
+        if result[0] == -1:
+            response = {'flask_data': f"Something is wrong : {result[1]}"}
+        else:
+            hist.append(result)
+            response = {'flask_data': f"Done : you can find your query in the calendar ! Take care. ! Nb Pages : {nb_pages}"}
+
     return json.dumps(response)
 
 @app.route('/ready', methods = ['POST'])
@@ -92,4 +137,5 @@ if __name__ == '__main__':
         check_week_clear,
         trigger=trigger
     )
+    start()
     app.run(debug=True)
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