Created SinglelineStopper, which interrupts token generation when a newline is reached if singleline mode is enabled

aiserver.py

@@ -2452,6 +2452,29 @@ def patch_transformers():
                 return True
             return False
             
+    class SinglelineStopper(StoppingCriteria):
+        # If singleline mode is enabled, it's pointless to generate output beyond the first newline.
+        def __init__(self, tokenizer):
+            self.tokenizer = tokenizer
+
+        def __call__(
+                self,
+                input_ids: torch.LongTensor,
+                scores: torch.FloatTensor,
+                **kwargs,
+        ) -> bool:
+            if not koboldai_vars.singleline:
+                return False
+
+            data = [tokenizer.decode(x) for x in input_ids]
+            if 'completed' not in self.__dict__:
+                self.completed = [False]*len(input_ids)
+
+            for i in range(len(input_ids)):
+                if (re.compile(r'\n').search(data[i][-1 * (len(koboldai_vars.chatname) + 1):]) is not None):
+                    self.completed[i] = True
+
+            return self.completed[i]
 
     class CoreStopper(StoppingCriteria):
         # Controls core generation stuff; aborting, counting generated tokens, etc
@@ -2560,6 +2583,7 @@ def patch_transformers():
         token_streamer = TokenStreamer(tokenizer=tokenizer)
 
         stopping_criteria.insert(0, ChatModeStopper(tokenizer=tokenizer))
+        stopping_criteria.insert(0, SinglelineStopper(tokenizer=tokenizer))
         stopping_criteria.insert(0, self.kai_scanner)
         token_streamer = TokenStreamer(tokenizer=tokenizer)
         stopping_criteria.insert(0, token_streamer)