diff --git a/aiserver.py b/aiserver.py
index eaafeb5c..21a84bee 100644
--- a/aiserver.py
+++ b/aiserver.py
@@ -1318,21 +1318,21 @@ def calcsubmit(txt):
     anoteadded   = False # In case our budget runs out before we hit A.N. depth
     actionlen    = len(vars.actions)
 
-    winfo, mem, anotetxt, _ = calcsubmitbudgetheader(txt)
+    winfo, mem, anotetxt, found_entries = calcsubmitbudgetheader(txt)
 
     # For all transformers models
     if(vars.model != "InferKit"):
         subtxt, min, max = calcsubmitbudget(actionlen, winfo, mem, anotetxt)
         if(actionlen == 0):
             if(not vars.model in ["Colab", "OAI"]):
-                generate(subtxt, min, max)
+                generate(subtxt, min, max, found_entries=found_entries)
             elif(vars.model == "Colab"):
                 sendtocolab(subtxt, min, max)
             elif(vars.model == "OAI"):
                 oairequest(subtxt, min, max)
         else:
             if(not vars.model in ["Colab", "OAI"]):
-                generate(subtxt, min, max)
+                generate(subtxt, min, max, found_entries=found_entries)
             elif(vars.model == "Colab"):
                 sendtocolab(subtxt, min, max)
             elif(vars.model == "OAI"):
@@ -1397,7 +1397,7 @@ def calcsubmit(txt):
 #==================================================================#
 # Send text to generator and deal with output
 #==================================================================#
-def generate(txt, min, max):    
+def generate(txt, min, max, found_entries=set()):    
     print("{0}Min:{1}, Max:{2}, Txt:{3}{4}".format(colors.YELLOW, min, max, txt, colors.END))
     
     # Store context in memory to use it for comparison with generated content
@@ -1432,7 +1432,7 @@ def generate(txt, min, max):
             gen_in = gen_in.to('cpu')
 
         model.kai_scanner_head_length = gen_in.shape[-1]
-        model.kai_scanner_excluded_world_info = set()
+        model.kai_scanner_excluded_world_info = found_entries
 
         actions = vars.actions
         if(vars.dynamicscan):
@@ -1441,7 +1441,6 @@ def generate(txt, min, max):
         with torch.no_grad():
             already_generated = 0
             numseqs = vars.numseqs if not vars.dynamicscan else 1
-            found_entries = model.kai_scanner_excluded_world_info
             while True:
                 genout = generator(
                     gen_in,