[perf] skip add_special_tokens=False kwarg on chat-template tokenize for slow tokenizers (#25953)

Co-authored-by: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

python/sglang/srt/entrypoints/openai/serving_chat.py

@@ -181,6 +181,18 @@ class OpenAIServingChat(OpenAIServingBase):
         # Per-request response parser for custom decoding (set by _encode_messages)
         self._response_parser: Optional[ResponseParserProtocol] = None
 
+        # Probe whether ``encode("")`` returns specials. If it does, we must
+        # keep ``add_special_tokens=False`` at the chat-template encode site
+        # to avoid double BOS; otherwise the kwarg is a no-op and dropping it
+        # lets slow tokenizers (e.g. Kimi's TikTokenTokenizer) stay on the
+        # fast internal path.
+        try:
+            self._tokenizer_auto_adds_specials = (
+                len(self.tokenizer_manager.tokenizer.encode("")) > 0
+            )
+        except Exception:
+            self._tokenizer_auto_adds_specials = True
+
     def _handle_last_assistant_message(
         self,
         messages: List[Dict[str, Any]],
@@ -729,15 +741,28 @@ class OpenAIServingChat(OpenAIServingBase):
             if request.chat_template_kwargs:
                 extra_template_kwargs.update(request.chat_template_kwargs)
 
+            # Split apply_chat_template(tokenize=True) into render + encode so we
+            # can skip add_special_tokens=False on tokenizers that don't auto-add
+            # specials (Kimi-like, OpenAI-chat analogue of #25265). Chat
+            # templates already include role/special tokens, so the encode must
+            # avoid double BOS on tokenizers that would add it.
+            encode_kwargs = (
+                {"add_special_tokens": False}
+                if self._tokenizer_auto_adds_specials
+                else {}
+            )
             try:
-                prompt_ids = self.tokenizer_manager.tokenizer.apply_chat_template(
+                rendered_prompt = self.tokenizer_manager.tokenizer.apply_chat_template(
                     openai_compatible_messages,
-                    tokenize=True,
+                    tokenize=False,
                     add_generation_prompt=True,
                     tools=tools,
                     return_dict=False,
                     **extra_template_kwargs,
                 )
+                prompt_ids = self.tokenizer_manager.tokenizer.encode(
+                    rendered_prompt, **encode_kwargs
+                )
             except Exception as e:
                 # If the first attempt fails, try with flat function-only format.
                 # Some templates (e.g. Mistral) expect tools without the OpenAI wrapper.
@@ -747,13 +772,18 @@ class OpenAIServingChat(OpenAIServingBase):
                     else None
                 )
                 try:
-                    prompt_ids = self.tokenizer_manager.tokenizer.apply_chat_template(
+                    rendered_prompt = (
-                        openai_compatible_messages,
+                        self.tokenizer_manager.tokenizer.apply_chat_template(
-                        tokenize=True,
+                            openai_compatible_messages,
-                        add_generation_prompt=True,
+                            tokenize=False,
-                        tools=tools,
+                            add_generation_prompt=True,
-                        return_dict=False,
+                            tools=tools,
-                        **extra_template_kwargs,
+                            return_dict=False,
+                            **extra_template_kwargs,
+                        )
+                    )
+                    prompt_ids = self.tokenizer_manager.tokenizer.encode(
+                        rendered_prompt, **encode_kwargs
                     )
                 except jinja2.TemplateError as template_error:
                     # Template errors (e.g., from raise_exception in Jinja templates)