formulate 2nd forced sentence

app.py

@@ -6,9 +6,12 @@ tokenizer = GPT2Tokenizer.from_pretrained("monsoon-nlp/gpt-winowhy")
 model = GPT2LMHeadModel.from_pretrained("monsoon-nlp/gpt-winowhy", pad_token_id=tokenizer.eos_token_id)
 
 def hello(prompt, items):
-    inp = prompt.strip() + ' %'
+    inp = prompt.strip()
+    if inp[-1] not in ['?', '!', '.']:
+        inp += '.'
+    inp += ' %'
     input_ids = torch.tensor([tokenizer.encode(inp)])
-    output = model.generate(input_ids, max_new_tokens=12)
+    output = model.generate(input_ids, max_new_tokens=20)
     resp = tokenizer.decode(output[0], skip_special_tokens=True)
     if '%' in resp:
         resp1 = resp[resp.index('%') + 1 : ]
@@ -25,11 +28,11 @@ def hello(prompt, items):
             # remove first one which assumedly is a capital
             names = names[1:]
 
-    #if (names[0] in resp1) and ((names[1] not in resp1) or (resp1.index(names[0]) < resp1.index(names[1]))):
-    #    force_inp = inp + resp1[resp1.index(names[0]):] + names[1]
-    #else:
-    #    force_inp = inp + resp1[resp1.index(names[1]):] + names[0]
-    resp2 = ",".join(names) #force_inp
+    if (names[0] in resp1) and ((names[1] not in resp1) or (resp1.index(names[0]) < resp1.index(names[1]))):
+       force_inp = resp1[resp1.index(names[0]):] + names[1]
+    else:
+       force_inp = resp1[resp1.index(names[1]):] + names[0]
+    resp2 = force_inp
     #
     # input_ids2 = torch.tensor([tokenizer.encode(force_inp)])
     # output2 = model.generate(input_ids2, max_new_tokens=8)