diff --git a/Recommender.py b/Recommender.py
index 1b4b9c3..0853207 100644
--- a/Recommender.py
+++ b/Recommender.py
@@ -32,7 +32,7 @@ class Recommender:
             for i, material in new_material.iterrows():
                 self._match_tags(username, material, interest)
 
-    def make_recommendation(self, username):
+    def make_recommendation(self, username, name):
         if len(self.curr_recommendations[username]) == 0:
             return ""
         to_consider = [idx for idx, value in enumerate(self.recommended[username]) if value == False]
@@ -42,7 +42,7 @@ class Recommender:
         index = self.recommended[username][index]
         #while self.recommended[index] == True:
         #    index = random.choice(list(range(0, len(self.curr_recommendations))))
-        recommendation = "Hey " + username + "! This " + self.curr_recommendations[username][index][
+        recommendation = "Hey " + name + "! This " + self.curr_recommendations[username][index][
             'type'].lower() + " about " + ', '.join(
             self.curr_recommendations[username][index]['tags']).lower() + " was posted recently by " + \
                          self.curr_recommendations[username][index][
diff --git a/ResponseGenerator.py b/ResponseGenerator.py
index f7498fa..dcc67f2 100644
--- a/ResponseGenerator.py
+++ b/ResponseGenerator.py
@@ -88,11 +88,11 @@ class ResponseGenerator:
         return self.db[db_type].iloc[[I[0]][0]].reset_index(drop=True).loc[0]
 
 
-    def gen_response(self, action, utterance=None, username=None, vrename=None, state=None, consec_history=None, chitchat_history=None):
+    def gen_response(self, action, utterance=None, name=None, username=None, vrename=None, state=None, consec_history=None, chitchat_history=None):
         if action == "Help":
-            return "Hey it's Janet! I am here to help you make use of the datasets and papers in the catalogue of the " + vrename +" VRE. I can answer questions whose answers may be inside the papers. I can summarize papers for you. I can also chat with you. So, whichever it is, I am ready to chat!"
+            return "Hey " + name + "! it's Janet! I am here to help you make use of the datasets and papers in the catalogue of the " + vrename +" VRE. I can answer questions whose answers may be inside the papers. I can summarize papers for you. I can also chat with you. So, whichever it is, I am ready to chat!"
         elif action == "Recommend":
-            prompt = self.recommender.make_recommendation(username)
+            prompt = self.recommender.make_recommendation(username, name)
             if prompt != "":
                 return prompt
             else:
diff --git a/main.py b/main.py
index fc72bd9..b528d61 100644
--- a/main.py
+++ b/main.py
@@ -6,6 +6,7 @@ from flask import Flask, render_template, request, jsonify
 from flask_cors import CORS, cross_origin
 import psycopg2
 import spacy
+import requests
 import spacy_transformers
 import torch
 from transformers import AutoTokenizer, AutoModelForSeq2SeqLM, pipeline
@@ -40,20 +41,20 @@ cur = conn.cursor()
 
 users = {}
 
-def vre_fetch():
+def vre_fetch(token):
     while True:
         time.sleep(1000)
         print('getting new material')
-        vre.get_vre_update()
-        vre.index_periodic_update()
-        rg.update_index(vre.get_index())
-        rg.update_db(vre.get_db())
+        users[token]['args']['vre'].get_vre_update()
+        users[token]['args']['vre'].index_periodic_update()
+        users[token]['args']['rg'].update_index(vre.get_index())
+        users[token]['args']['rg'].update_db(vre.get_db())
 
-def user_interest_decay(user):
+def user_interest_decay(token):
     while True:
-        print("decaying interests after 3 minutes for " + user.username)
+        print("decaying interests after 3 minutes for " + users[token]['username'])
         time.sleep(180)
-        user.decay_interests()
+        users[token]['user'].decay_interests()
 
 def clear_inactive():
     while True:
@@ -69,34 +70,52 @@ def health():
 
 @app.route("/api/dm", methods=['POST'])
 def init_dm():
-    username = request.get_json().get("username")
-    token = '2c1e8f88-461c-42c0-8cc1-b7660771c9a3-843339462'
-    if username not in users:
-        users[username] = {'dm': DM(), 'activity': 0, 'user': User(username, token)} 
-        threading.Thread(target=user_interest_decay, args=(users[username]['user'],), name='decayinterest_'+username).start()
-        message = {"answer": "your assigned name is " + username, "assignedname": username}
+    token = request.get_json().get("token")
+    headers = {"gcube-token": token, "Accept": "application/json"}
+    
+    if token not in users:
+        url = 'https://api.d4science.org/rest/2/people/profile'
+        response = requests.get(url, headers=headers)
+        username = response.json()['result']['username']
+        name = response.json()['result']['fullname'] 
+        
+        vre = VRE("assistedlab", token, retriever)
+        vre.init()
+        index = vre.get_index()
+        db = vre.get_db()
+        rg = ResponseGenerator(index,db, rec, generators, retriever)
+        args = {'vre': vre, 'rg': rg}
+
+        users[token] = {'username': username, 'name': name, 'dm': DM(), 'activity': 0, 'user': User(username, token), 'args': args} 
+
+        threading.Thread(target=vre_fetch, args=(token,), name='updatevre_'+users[token]['username']).start()
+        threading.Thread(target=user_interest_decay, args=(token,), name='decayinterest_'+users[token]['username']).start()
+        
+        message = {"answer": "Hi " + name.split()[0] + '!', "assignedname": username}
     else:
-        message = {"answer": "welcome back " + username, "assignedname": username}
+        message = {"answer": "welcome back " + users[token]['name'].split()[0] + '!', "assignedname": users[token]['username']}
     return message
 
 @app.route("/api/predict", methods=['POST'])
 def predict():
     text = request.get_json().get("message")
-    username = request.get_json().get("username")
-    dm = users[username]['dm']
-    user = users[username]['user']
+    token = request.get_json().get("token")
+    dm = users[token]['dm']
+    user = users[token]['user']
+    rg = users[token]['args']['rg']
+    vre = users[token]['args']['vre']
     message = {}
     if text == "<HELP_ON_START>":
         state = {'help': True, 'inactive': False, 'modified_query':"", 'intent':""}
         dm.update(state)
         action = dm.next_action()
-        response = rg.gen_response(action, vrename=vre.name)
+        response = rg.gen_response(action, vrename=vre.name, username=users[token]['username'], name=users[token]['name'].split()[0])
         message = {"answer": response}
     elif text == "<RECOMMEND_ON_IDLE>":
         state = {'help': False, 'inactive': True, 'modified_query':"recommed: ", 'intent':""}
         dm.update(state)
         action = dm.next_action()
-        response = rg.gen_response(action, username=user.username, vrename=vre.name)
+        response = rg.gen_response(action, username=users[token]['username'],name=users[token]['name'].split()[0], vrename=vre.name)
         message = {"answer": response}
         new_state = {'modified_query': response}
         dm.update(new_state)
@@ -114,7 +133,7 @@ def predict():
         new_user_interests = user.get_user_interests()
         new_vre_material = pd.concat([vre.db['paper_db'], vre.db['dataset_db']]).reset_index(drop=True)
         if (new_user_interests != old_user_interests or len(old_vre_material) != len(new_vre_material)):
-            rec.generate_recommendations(username, new_user_interests, new_vre_material)
+            rec.generate_recommendations(users[token]['username'], new_user_interests, new_vre_material)
         dm.update(state)
         action = dm.next_action()
         response = rg.gen_response(action=action, utterance=state['modified_query'], state=dm.get_recent_state(), consec_history=dm.get_consec_history(), chitchat_history=dm.get_chitchat_history(), vrename=vre.name)
@@ -124,9 +143,11 @@ def predict():
         new_state = {'modified_query': response, 'intent': state['intent']}
         dm.update(new_state)
     reply = jsonify(message)
-    users[username]['dm'] = dm
-    users[username]['user'] = user
-    users[username]['activity'] = 0
+    users[token]['dm'] = dm
+    users[token]['user'] = user
+    users[token]['activity'] = 0
+    users[token]['args']['vre'] = vre
+    users[token]['args']['rg'] = rg
     return reply
 
 @app.route('/api/feedback', methods = ['POST'])
@@ -170,21 +191,10 @@ if __name__ == "__main__":
                   'amb': amb_generator,
 		  'summ': summ_generator}
     
-    #load vre
-    token = '2c1e8f88-461c-42c0-8cc1-b7660771c9a3-843339462'
-    vre = VRE("assistedlab", token, retriever)
-    vre.init()
-    index = vre.get_index()
-    db = vre.get_db()
 
-    threading.Thread(target=vre_fetch, name='updatevre').start()
-    
     threading.Thread(target=clear_inactive, name='clear').start()
-    
     rec = Recommender(retriever)
 
-    rg = ResponseGenerator(index,db, rec, generators, retriever)
-
     
     cur.execute('CREATE TABLE IF NOT EXISTS feedback_experimental (id serial PRIMARY KEY,'
                                  'query text NOT NULL,'