[Frontend] supports deepseekv32 chat template

vllm/config/model.py

@@ -84,7 +84,7 @@
     "transcription",
     "draft",
 ]
-TokenizerMode = Literal["auto", "hf", "slow", "mistral"]
+TokenizerMode = Literal["auto", "hf", "slow", "mistral", "deepseek_v32"]
 ModelDType = Literal["auto", "half", "float16", "bfloat16", "float", "float32"]
 LogprobsMode = Literal[
     "raw_logits", "raw_logprobs", "processed_logits", "processed_logprobs"
@@ -141,6 +141,7 @@ class ModelConfig:
     - "hf" will use the fast tokenizer if available.\n
     - "slow" will always use the slow tokenizer.\n
     - "mistral" will always use the tokenizer from `mistral_common`.\n
+    - "deepseek_v32" will always use the tokenizer from `deepseek_v32`.\n
     - Other custom values can be supported via plugins."""
     trust_remote_code: bool = False
     """Trust remote code (e.g., from HuggingFace) when downloading the model

vllm/entrypoints/openai/serving_engine.py

@@ -106,7 +106,7 @@
 from vllm.pooling_params import PoolingParams
 from vllm.reasoning import ReasoningParser, ReasoningParserManager
 from vllm.sampling_params import BeamSearchParams, SamplingParams
-from vllm.tokenizers import MistralTokenizer, TokenizerLike
+from vllm.tokenizers import DeepseekV32Tokenizer, MistralTokenizer, TokenizerLike
 from vllm.tracing import (
     contains_trace_headers,
     extract_trace_headers,
@@ -1129,6 +1129,13 @@ async def _preprocess_chat(
                 messages=messages,
                 **_chat_template_kwargs,
             )
+        elif isinstance(tokenizer, DeepseekV32Tokenizer):
+            request_prompt = tokenizer.apply_chat_template(
+                conversation=conversation,
+                messages=messages,
+                model_config=model_config,
+                **_chat_template_kwargs,
+            )
         else:
             request_prompt = apply_hf_chat_template(
                 tokenizer=tokenizer,

vllm/tokenizers/__init__.py

@@ -1,6 +1,7 @@
 # SPDX-License-Identifier: Apache-2.0
 # SPDX-FileCopyrightText: Copyright contributors to the vLLM project
 
+from .deepseekv32 import DeepseekV32Tokenizer
 from .hf import HfTokenizer
 from .mistral import MistralTokenizer
 from .protocol import TokenizerLike
@@ -21,4 +22,5 @@
     "get_tokenizer",
     "cached_tokenizer_from_config",
     "init_tokenizer_from_config",
+    "DeepseekV32Tokenizer",
 ]