[GptOss] Add GptOss reasoning parser to support structure output (vllm-project#22322)

Signed-off-by: Chen Zhang <[email protected]>
Co-authored-by: LiuXiaoxuanPKU <[email protected]>
Co-authored-by: simon-mo <[email protected]>
Co-authored-by: Woosuk Kwon <[email protected]>
Co-authored-by: Hongxia Yang <[email protected]>
Co-authored-by: Minseok Lee <[email protected]>
Co-authored-by: Yongye Zhu <[email protected]>

Author: 7 people

vllm/model_executor/models/config.py

@@ -247,13 +247,13 @@ def verify_and_update_config(vllm_config: "VllmConfig") -> None:
             config.max_model_len)
 
 
-class GptOssConfig(VerifyAndUpdateConfig):
+class GptOssForCausalLMConfig(VerifyAndUpdateConfig):
 
     @staticmethod
     def verify_and_update_config(vllm_config: "VllmConfig") -> None:
         decoding_config = vllm_config.decoding_config
         if decoding_config.reasoning_backend == "":
-            decoding_config.reasoning_backend = "openai"
+            decoding_config.reasoning_backend = "GptOss"
 
         # Increase the max capture size from 512 to 1024 for performance.
         # NOTE(woosuk): This will increase the number of CUDA graphs
@@ -373,5 +373,5 @@ def verify_and_update_config(cls, vllm_config: "VllmConfig") -> None:
     "JinaVLForRanking": JinaVLForSequenceClassificationConfig,
     "JambaForSequenceClassification": JambaForSequenceClassificationConfig,
     "GraniteMoeHybridForCausalLM": GraniteMoeHybridModelConfig,
-    "GptOssForCausalLM": GptOssConfig,
+    "GptOssForCausalLM": GptOssForCausalLMConfig,
 }

vllm/reasoning/__init__.py

@@ -4,6 +4,7 @@
 from .abs_reasoning_parsers import ReasoningParser, ReasoningParserManager
 from .deepseek_r1_reasoning_parser import DeepSeekR1ReasoningParser
 from .glm4_moe_reasoning_parser import Glm4MoeModelReasoningParser
+from .gptoss_reasoning_parser import GptOssReasoningParser
 from .granite_reasoning_parser import GraniteReasoningParser
 from .hunyuan_a13b_reasoning_parser import HunyuanA13BReasoningParser
 from .mistral_reasoning_parser import MistralReasoningParser
@@ -20,4 +21,5 @@
     "Glm4MoeModelReasoningParser",
     "MistralReasoningParser",
     "Step3ReasoningParser",
+    "GptOssReasoningParser",
 ]

vllm/reasoning/gptoss_reasoning_parser.py

@@ -0,0 +1,64 @@
+# SPDX-License-Identifier: Apache-2.0
+# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
+
+from collections.abc import Sequence
+from typing import Optional, Union
+
+from transformers import PreTrainedTokenizerBase
+
+from vllm.entrypoints.openai.protocol import (ChatCompletionRequest,
+                                              DeltaMessage)
+from vllm.logger import init_logger
+from vllm.reasoning import ReasoningParser, ReasoningParserManager
+
+logger = init_logger(__name__)
+
+
+@ReasoningParserManager.register_module("GptOss")
+class GptOssReasoningParser(ReasoningParser):
+    """
+    Reasoning parser for GptOss model.
+
+    The GptOss model uses harmony to extract reasoning content and this parser
+    is only used for detecting the end of the reasoning content.
+    """
+
+    def __init__(self, tokenizer: PreTrainedTokenizerBase):
+        super().__init__(tokenizer)
+        self.reasoning_end_token_ids = self.model_tokenizer.encode(
+            "<|start|>assistant<|channel|>final<|message|>")
+
+    def is_reasoning_end(self, input_ids: list[int]) -> bool:
+        end_token_ids = self.reasoning_end_token_ids
+        assert len(end_token_ids) > 0, "reasoning_end_token_ids is empty"
+        # Check if the end sequence is present in the input_ids.
+        # We search from the end of input_ids to find the last match.
+        for i in range(len(input_ids) - len(end_token_ids), -1, -1):
+            if input_ids[i:i + len(end_token_ids)] == end_token_ids:
+                return True
+        return False
+
+    def extract_content_ids(self, input_ids: list[int]) -> list[int]:
+        raise RuntimeError(
+            "GptOss model uses harmony to extract reasoning content. This "
+            "function should not be called.")
+
+    def extract_reasoning_content_streaming(
+        self,
+        previous_text: str,
+        current_text: str,
+        delta_text: str,
+        previous_token_ids: Sequence[int],
+        current_token_ids: Sequence[int],
+        delta_token_ids: Sequence[int],
+    ) -> Union[DeltaMessage, None]:
+        raise RuntimeError(
+            "GptOss model uses harmony to extract reasoning content. This "
+            "function should not be called.")
+
+    def extract_reasoning_content(
+            self, model_output: str, request: ChatCompletionRequest
+    ) -> tuple[Optional[str], Optional[str]]:
+        raise RuntimeError(
+            "GptOss model uses harmony to extract reasoning content. This "
+            "function should not be called.")