diff --git a/dash_app/graph.py b/dash_app/graph.py
index 030349961932a8149c127f3d9da809e78a255f99..0cd53b8176063a6d64326778bacabc0d9a666b99 100644
--- a/dash_app/graph.py
+++ b/dash_app/graph.py
@@ -85,6 +85,7 @@ class Graph:
                               elements=elements,
                               userZoomingEnabled=False,
                               userPanningEnabled=False,
+                              maxZoom=2.0,
                               stylesheet=[
                                   {
                                       'selector': '[is_base_node > 0.5]',
diff --git a/dash_app/index.py b/dash_app/index.py
index 4667393647eb0efb7f0e4aaf983176ddd43546e7..dca4a0a0efd913b9baf3f6dfd25eb3644eedfb33 100644
--- a/dash_app/index.py
+++ b/dash_app/index.py
@@ -1,6 +1,7 @@
 import os
 from dash_app.app import app
 from dash_app.layout import layout
+import dash_app.callbacks
 
 
 app.layout = layout
diff --git a/dash_app/words.py b/dash_app/words.py
index 045914cd18bc52df1e46959266d72e76eeed9d3f..53d4180e4b950c4b2ca5b42be56650b2a7f0bd6c 100644
--- a/dash_app/words.py
+++ b/dash_app/words.py
@@ -6,12 +6,12 @@ class AssociatedWords:
 
     def __init__(self):
         print("\n Word2Vec model is loading. This can take a couple of minutes.")
-        # self.model = api.load('glove-twitter-200')
-        # print(" Word2Vec model is ready. Enjoy!!!\n")
+        self.model = api.load('glove-twitter-200')
+        print(" Word2Vec model is ready. Enjoy!!!\n")
 
     def get_associated_words(self, word, top_n=10):
-        # gensim_result = self.model.most_similar(word, topn=top_n)
-        gensim_result = [('apple', 1.0), ('banana', 1.0), ('strawberry', 1.0)]
+        gensim_result = self.model.most_similar(word, topn=top_n)
+        # gensim_result = [('apple', 1.0), ('banana', 1.0), ('strawberry', 1.0)]
         words = self.filter_results(gensim_result, word)
         return words