[Frontend] Clean up type annotations for mistral tokenizer (#8314)

vllm/entrypoints/openai/serving_tokenization.py

@@ -2,7 +2,8 @@ from typing import List, Optional, Union
 
 from vllm.config import ModelConfig
 from vllm.engine.protocol import AsyncEngineClient
-from vllm.entrypoints.chat_utils import (apply_chat_template,
+from vllm.entrypoints.chat_utils import (apply_hf_chat_template,
+                                         apply_mistral_chat_template,
                                          load_chat_template,
                                          parse_chat_messages_futures)
 from vllm.entrypoints.logger import RequestLogger
@@ -18,6 +19,7 @@ from vllm.entrypoints.openai.protocol import (DetokenizeRequest,
 from vllm.entrypoints.openai.serving_engine import (LoRAModulePath,
                                                     OpenAIServing)
 from vllm.logger import init_logger
+from vllm.transformers_utils.tokenizer import MistralTokenizer
 from vllm.utils import random_uuid
 
 logger = init_logger(__name__)
@@ -66,6 +68,7 @@ class OpenAIServingTokenization(OpenAIServing):
 
         tokenizer = await self.async_engine_client.get_tokenizer(lora_request)
 
+        prompt: Union[str, List[int]]
         if isinstance(request, TokenizeChatRequest):
             model_config = self.model_config
 
@@ -77,12 +80,20 @@ class OpenAIServingTokenization(OpenAIServing):
                 logger.warning(
                     "Multi-modal inputs are ignored during tokenization")
 
-            prompt = apply_chat_template(
-                tokenizer,
-                conversation=conversation,
-                chat_template=self.chat_template,
-                add_generation_prompt=request.add_generation_prompt,
-            )
+            if isinstance(tokenizer, MistralTokenizer):
+                prompt = apply_mistral_chat_template(
+                    tokenizer,
+                    messages=request.messages,
+                    chat_template=self.chat_template,
+                    add_generation_prompt=request.add_generation_prompt,
+                )
+            else:
+                prompt = apply_hf_chat_template(
+                    tokenizer,
+                    conversation=conversation,
+                    chat_template=self.chat_template,
+                    add_generation_prompt=request.add_generation_prompt,
+                )
         else:
             prompt = request.prompt