Fixed GET response

src/participation-hub/federated-learning-microservice/Dockerfile

 FROM python:3
 LABEL maintainer="Alexander Lercher"
 
-ENV http_proxy http://proxy.uni-klu.ac.at:3128/
-ENV https_proxy http://proxy.uni-klu.ac.at:3128/
+#ENV http_proxy http://proxy.uni-klu.ac.at:3128/
+#ENV https_proxy http://proxy.uni-klu.ac.at:3128/
 
 RUN apt-get update
 

src/participation-hub/federated-learning-microservice/app/main.py

@@ -35,4 +35,4 @@ else:
 
 # start app
 if __name__ == '__main__':
-    app.run(host='0.0.0.0', port=30424, debug=False, ssl_context=context) #<-- IF running locally comment ss_context
+    app.run(host='0.0.0.0', port=5000, debug=False, ssl_context=context) #<-- IF running locally comment ss_context

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

@@ -13,14 +13,14 @@ if os.path.exists(modules_path):
 def last(use_case: str):    
     #FORWARD TO GPU SERVER WITH IP AND PORT
 
-    url = f'https://{network_constants.FEDERATED_TRAINING_HOSTNAME}:{network_constants.FEDERATED_TRAINING_REST_PORT}/api/Developers/use_case/{use_case}/last_train:'
+    url = f'https://{network_constants.FEDERATED_TRAINING_HOSTNAME}:{network_constants.FEDERATED_TRAINING_REST_PORT}/api/Developers/use_case/{use_case}/last_train'
     
     response = requests.get(
             url,
             verify = False, 
             proxies = { "http":None, "https":None }
     )
-    return response
+    return json.loads(response.text)
 
 
 def upload_and_train(use_case: str, developer_id: int):
@@ -30,7 +30,7 @@ def upload_and_train(use_case: str, developer_id: int):
     #data = {'use_case' : use_case,
 #           'developer_id' : developer_id}
 
-    url = f'https://{network_constants.FEDERATED_TRAINING_HOSTNAME}:{network_constants.FEDERATED_TRAINING_REST_PORT}/api/Developers/use_cases/{use_case}/developer_id/{developer_id}/upload_and_train:'
+    url = f'https://{network_constants.FEDERATED_TRAINING_HOSTNAME}:{network_constants.FEDERATED_TRAINING_REST_PORT}/api/Developers/use_cases/{use_case}/developer_id/{developer_id}/upload_and_train'
     #url= 'gpu3.itec.aau.at/home/itec/bogdan/Articonf/smart/tools/federated-training/app/routes/developers'
     response = requests.post(
             url,
@@ -40,7 +40,7 @@ def upload_and_train(use_case: str, developer_id: int):
             #data = data
     )
 
-    return response
+    return json.loads(response.text)
 
 
 #upload_and_train("text_processing",1)

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

@@ -15,7 +15,7 @@ def last(use_case: str):
             verify = False, 
             proxies = { "http":None, "https":None }
     )
-    return response
+    return json.loads(response.text)
 
 
 def upload_and_train(use_case: str):
@@ -29,7 +29,7 @@ def upload_and_train(use_case: str):
             files= request.files
     )
 
-    return response
+    return json.loads(response.text)
 
 
 #last("text_processing")

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

@@ -15,7 +15,7 @@ def check_article(use_case: str,data_entry: str):
             verify = False, 
             proxies = { "http":None, "https":None }
     )
-    return response
+    return json.loads(response.text)
 
     
 

tools/federated-training/app/configs/routes.yml

@@ -31,7 +31,7 @@ paths:
       responses:
         '200':
           description: "Successful Request"
-        '404':
+        '400':
           description: "Use case train session data does not exist"
   /Owners/use_cases/{use_case}/upload_and_train:
     post:

tools/federated-training/app/routes/developers.py

@@ -3,7 +3,7 @@ import os
 from flask import Response, request
 import pandas as pd
 import sys
-
+from os.path import dirname, abspath
 modules_path = './'
 if os.path.exists(modules_path):
     sys.path.insert(1, modules_path)
@@ -31,10 +31,14 @@ def upload_and_train(use_case: str, developer_id: int):
 
     #COPY THE NEW DB TO THE FOLDER
     #TODO IMPLEMENT HERE
-    #file_dict = request.files
-    #db_File_True = file_dict["dataset_file1"]
-    #db_File_False = file_dict["dataset_file2"]
-
+    app_path = dirname(dirname(abspath(__file__)))
+    file_dict = request.files
+    db_File_True = file_dict["dataset_file1"]
+    db_File_False = file_dict["dataset_file2"]
+    true_csv_path = os.path.join(app_path+"/"+use_case_path+"db/", "True.csv")
+    false_csv_path = os.path.join(app_path+"/"+use_case_path+"db/", "False.csv")
+    db_File_True.save(true_csv_path)
+    db_File_False.save(false_csv_path)
     #THEN start processing
     last_train_metrics = main_proc.start_processing(use_case,developer_id)
     print("## Last train metrics")

tools/federated-training/app/routes/owners.py

@@ -6,6 +6,7 @@ from flask import Response, request
 import pandas as pd
 
 def last(use_case: str):   
+    print("ENTERED ROUTES LAST") 
     csv_path = './processing/'+use_case+'/ledger.csv'
     try:
         df = pd.read_csv(csv_path)
@@ -18,6 +19,8 @@ def last(use_case: str):
         print(e)
         return Response(status=400, response="Trained model data doesn't exist")
 
+def test_respons_funct(metricsJson):
+    return Response(status=200, response=metricsJson)
 
 def upload_and_train(use_case: str):