Sync from v0.13

vllm/reasoning/holo2_reasoning_parser.py

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+# SPDX-License-Identifier: Apache-2.0
+# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
+
+from collections.abc import Sequence
+
+from vllm.entrypoints.openai.protocol import ChatCompletionRequest, DeltaMessage
+from vllm.logger import init_logger
+from vllm.reasoning import (
+    ReasoningParser,
+)
+from vllm.reasoning.deepseek_r1_reasoning_parser import DeepSeekR1ReasoningParser
+from vllm.reasoning.identity_reasoning_parser import IdentityReasoningParser
+from vllm.tokenizers import TokenizerLike
+
+logger = init_logger(__name__)
+
+
+class Holo2ReasoningParser(ReasoningParser):
+    """
+    Reasoning parser for the Holo2 models which are based on Qwen3.
+
+    The Holo2 model uses <think>...</think> tokens to denote reasoning text but <think>
+    is part of the chat template. This parser extracts the reasoning content until
+    </think> in the model's output.
+
+    The model provides a switch to enable or disable reasoning
+    output via the 'thinking=False' parameter.
+
+    Chat template args:
+    - thinking: Whether to enable reasoning output (default: True)
+
+
+    Parsing rules on model output:
+        - thinking == False
+            -> Model output is treated as purely the content |content|
+        - thinking == True
+            -> Model output is |reasoning_content|</think>|content|
+    """
+
+    def __init__(self, tokenizer: TokenizerLike, *args, **kwargs):
+        super().__init__(tokenizer, *args, **kwargs)
+
+        chat_kwargs = kwargs.get("chat_template_kwargs", {}) or {}
+        # Deepseek V3 and Holo2 are similar. However, Holo2 models think by default.
+        # this parser without user specified chat template args is initiated once for
+        # all requests in the structured output manager. So it is important that without
+        # user specified chat template args, the default thinking is True.
+
+        enable_thinking = bool(chat_kwargs.get("thinking", True))
+
+        if enable_thinking:
+            self._parser = DeepSeekR1ReasoningParser(tokenizer, *args, **kwargs)
+        else:
+            self._parser = IdentityReasoningParser(tokenizer, *args, **kwargs)
+
+    def is_reasoning_end(self, input_ids: Sequence[int]) -> bool:
+        return self._parser.is_reasoning_end(input_ids)
+
+    def is_reasoning_end_streaming(
+        self, input_ids: list[int], delta_ids: list[int]
+    ) -> bool:
+        return self._parser.is_reasoning_end_streaming(input_ids, delta_ids)
+
+    def extract_content_ids(self, input_ids: list[int]) -> list[int]:
+        return self._parser.extract_content_ids(input_ids)
+
+    def extract_reasoning(
+        self, model_output: str, request: ChatCompletionRequest
+    ) -> tuple[str | None, str | None]:
+        return self._parser.extract_reasoning(model_output, request)
+
+    def extract_reasoning_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],
+    ) -> DeltaMessage | None:
+        return self._parser.extract_reasoning_streaming(
+            previous_text,
+            current_text,
+            delta_text,
+            previous_token_ids,
+            current_token_ids,
+            delta_token_ids,
+        )