Updated funct for prediction

src/participation-hub/federated-learning-microservice/app/processing/text_processing/federated_algorithm.py

@@ -97,8 +97,12 @@ def load_latest_state():
     return restored_state[0]
 
 def make_prediction(input_prediction_data):
-    with open("processing/"+globals.USE_CASE+"/last_model",'rb') as f:
-        state = pickle.load(f)
+    try:
+        with open("processing/"+globals.USE_CASE+"/last_model",'rb') as f:
+            state = pickle.load(f)
+    except Exception as e:
+        print(e)
+        return None
     model_for_inference = get_simple_LSTM_model()
     state.model.assign_weights_to(model_for_inference)    
     

src/participation-hub/federated-learning-microservice/app/processing/text_processing/main_proc.py

@@ -68,4 +68,4 @@ def start_prediction(use_case, developer_id:int = -1):
 
     
 #start_processing("text_processing")
-start_prediction("text_processing")
+#start_prediction("text_processing")
\ No newline at end of file

src/participation-hub/federated-learning-microservice/app/routes/users.py

 
 
 from flask import Response, request
-
+import sys
 
 def check_article(use_case: str):
     #body = request.STRING
-    #TODO Working on it
-    #FOR USE_CASE {use_case} 
-
-    #insert body into the trained model
-    
-    #get the result
-    result = None #bool True/False
-    return Response(status=400, response=str(result))
+    use_case_path = 'processing/'+use_case+'/'
+    sys.path.append(use_case_path)
+    import main_proc
+
+
+    result = main_proc.start_prediction(use_case)
+    if result == None:
+        return Response(status = 404, response="Server doesn't have a trained model. Training of the model should be finished before attempting a prediction.")
\ No newline at end of file
+    return Response(status=200, response=result)
+
+#check_article("text_processing")
\ No newline at end of file