[Frontend] Skip stop in reasoning content (#14550)

Signed-off-by: Ce Gao <cegao@tensorchord.ai>
Co-authored-by: Chauncey <chaunceyjiang@gmail.com>

tests/engine/test_stop_checker.py

@@ -0,0 +1,228 @@
+# SPDX-License-Identifier: Apache-2.0
+# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
+
+import pytest
+from transformers import AutoTokenizer
+
+from vllm.engine.output_processor.stop_checker import StopChecker
+from vllm.reasoning import ReasoningParser
+from vllm.sampling_params import SamplingParams
+from vllm.sequence import Sequence, SequenceStatus
+
+REASONING_MODEL_NAME = "deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B"
+
+
+class MockReasoningParser(ReasoningParser):
+    """Mock reasoning parser for testing purposes."""
+
+    def __init__(self,
+                 tokenizer: AutoTokenizer,
+                 reasoning_active: bool = False):
+        super().__init__(tokenizer)
+        self.reasoning_active = reasoning_active
+
+    def is_reasoning_end(self, input_ids: list[int]) -> bool:
+        return not self.reasoning_active
+
+    def extract_content_ids(self, input_ids: list[int]) -> list[int]:
+        return input_ids
+
+
+class MockSequence(Sequence):
+    """Mock sequence for testing purposes."""
+
+    def __init__(self, token_ids, output_text="test_output", eos_token_id=0):
+        self.token_ids = token_ids
+        self.output_text = output_text
+        self.eos_token_id = eos_token_id
+        self.status = SequenceStatus.RUNNING
+        self.stop_reason = None
+
+    def get_token_ids(self):
+        return self.token_ids
+
+    def get_last_token_id(self):
+        return self.token_ids[-1] if self.token_ids else None
+
+    def get_len(self):
+        return len(self.token_ids)
+
+    def get_output_len(self):
+        return len(self.token_ids) - 1  # Simulating prompt + outputs
+
+
+@pytest.fixture
+def deepseek_r1_qwen_tokenizer():
+    return AutoTokenizer.from_pretrained(REASONING_MODEL_NAME)
+
+
+@pytest.fixture
+def stop_checker():
+    return StopChecker(max_model_len=10,
+                       get_tokenizer_for_seq=deepseek_r1_qwen_tokenizer)
+
+
+@pytest.fixture
+def stop_checker_with_reasoner():
+    reasoner = MockReasoningParser(deepseek_r1_qwen_tokenizer)
+    return StopChecker(max_model_len=10,
+                       get_tokenizer_for_seq=deepseek_r1_qwen_tokenizer,
+                       reasoner=reasoner)
+
+
+def test_eos_token_stopping(stop_checker):
+    """Test sequence stopping when EOS token is encountered."""
+    seq = MockSequence(token_ids=[1, 2, 0], eos_token_id=0)
+    sampling_params = SamplingParams()
+
+    stop_checker.maybe_stop_sequence(seq,
+                                     new_char_count=1,
+                                     sampling_params=sampling_params)
+
+    assert seq.status == SequenceStatus.FINISHED_STOPPED
+
+
+def test_ignore_eos(stop_checker):
+    """Test sequence continuing when EOS token is ignored."""
+    seq = MockSequence(token_ids=[1, 2, 0], eos_token_id=0)
+    sampling_params = SamplingParams(ignore_eos=True)
+
+    stop_checker.maybe_stop_sequence(seq,
+                                     new_char_count=1,
+                                     sampling_params=sampling_params)
+
+    assert seq.status == SequenceStatus.RUNNING
+
+
+def test_min_tokens(stop_checker):
+    """Test min_tokens prevents early stopping."""
+    seq = MockSequence(token_ids=[1, 2, 0], eos_token_id=0)
+    sampling_params = SamplingParams(min_tokens=3)
+
+    stop_checker.maybe_stop_sequence(seq,
+                                     new_char_count=1,
+                                     sampling_params=sampling_params)
+
+    assert seq.status == SequenceStatus.RUNNING
+
+
+def test_stop_token_ids(stop_checker):
+    """Test sequence stopping with custom stop token IDs."""
+    seq = MockSequence(token_ids=[1, 2, 3], eos_token_id=0)
+    sampling_params = SamplingParams(stop_token_ids=[3])
+
+    stop_checker.maybe_stop_sequence(seq,
+                                     new_char_count=1,
+                                     sampling_params=sampling_params)
+
+    assert seq.status == SequenceStatus.FINISHED_STOPPED
+    assert seq.stop_reason == 3
+
+
+def test_stop_strings(stop_checker):
+    """Test sequence stopping with stop strings."""
+    seq = MockSequence(token_ids=[1, 2, 3],
+                       output_text="test output with STOP",
+                       eos_token_id=0)
+    sampling_params = SamplingParams(stop=["STOP"])
+
+    stop_checker.maybe_stop_sequence(seq,
+                                     new_char_count=1,
+                                     sampling_params=sampling_params)
+
+    assert seq.status == SequenceStatus.FINISHED_STOPPED
+    assert seq.stop_reason == "STOP"
+    assert "STOP" not in seq.output_text  # Default behavior removes stop string
+
+
+def test_include_stop_str_in_output(stop_checker):
+    """Test keeping stop strings in output."""
+    seq = MockSequence(token_ids=[1, 2, 3],
+                       output_text="test output with STOP",
+                       eos_token_id=0)
+    sampling_params = SamplingParams(stop=["STOP"],
+                                     include_stop_str_in_output=True)
+
+    stop_checker.maybe_stop_sequence(seq,
+                                     new_char_count=5,
+                                     sampling_params=sampling_params)
+
+    assert seq.status == SequenceStatus.FINISHED_STOPPED
+    assert "STOP" in seq.output_text
+
+
+def test_max_tokens(stop_checker):
+    """Test sequence stopping at max_tokens."""
+    seq = MockSequence(token_ids=[1, 2, 3], eos_token_id=0)
+    sampling_params = SamplingParams(max_tokens=2)
+
+    stop_checker.maybe_stop_sequence(seq,
+                                     new_char_count=1,
+                                     sampling_params=sampling_params)
+
+    assert seq.status == SequenceStatus.FINISHED_LENGTH_CAPPED
+
+
+def test_max_model_len(stop_checker):
+    """Test sequence stopping at max_model_len."""
+    seq = MockSequence(token_ids=list(range(11)),
+                       eos_token_id=0)  # 11 tokens, max is 10
+    sampling_params = SamplingParams()
+
+    stop_checker.maybe_stop_sequence(seq,
+                                     new_char_count=1,
+                                     sampling_params=sampling_params)
+
+    assert seq.status == SequenceStatus.FINISHED_LENGTH_CAPPED
+
+
+def test_reasoning_skip_stops(stop_checker_with_reasoner):
+    """Test that stop tokens and strings are ignored during reasoning."""
+    # Set reasoning_active to True to simulate being in reasoning mode
+    stop_checker_with_reasoner.reasoner.reasoning_active = True
+
+    # Test with stop token
+    seq = MockSequence(token_ids=[1, 2, 3], eos_token_id=0)
+    sampling_params = SamplingParams(stop_token_ids=[3])
+
+    stop_checker_with_reasoner.maybe_stop_sequence(
+        seq, new_char_count=1, sampling_params=sampling_params)
+    assert seq.status == SequenceStatus.RUNNING
+
+    # Test with stop string
+    seq = MockSequence(token_ids=[1, 2, 3], output_text="test STOP")
+    sampling_params = SamplingParams(stop=["STOP"])
+
+    stop_checker_with_reasoner.maybe_stop_sequence(
+        seq, new_char_count=4, sampling_params=sampling_params)
+    assert seq.status == SequenceStatus.RUNNING
+
+    # But EOS token still stops the sequence
+    seq = MockSequence(token_ids=[1, 2, 0], eos_token_id=0)
+    sampling_params = SamplingParams()
+
+    stop_checker_with_reasoner.maybe_stop_sequence(
+        seq, new_char_count=1, sampling_params=sampling_params)
+    assert seq.status == SequenceStatus.FINISHED_STOPPED
+
+
+def test_reasoning_end_enables_stops(stop_checker_with_reasoner):
+    """Test that stop tokens work after reasoning ends."""
+    # Set reasoning_active to False to simulate being out of reasoning mode
+    stop_checker_with_reasoner.reasoner.reasoning_active = False
+
+    # Test with stop token
+    seq = MockSequence(token_ids=[1, 2, 3], eos_token_id=0)
+    sampling_params = SamplingParams(stop_token_ids=[3])
+
+    stop_checker_with_reasoner.maybe_stop_sequence(
+        seq, new_char_count=1, sampling_params=sampling_params)
+    assert seq.status == SequenceStatus.FINISHED_STOPPED
+
+    # Test with stop string
+    seq = MockSequence(token_ids=[1, 2, 3], output_text="test STOP")
+    sampling_params = SamplingParams(stop=["STOP"])
+
+    stop_checker_with_reasoner.maybe_stop_sequence(
+        seq, new_char_count=4, sampling_params=sampling_params)
+    assert seq.status == SequenceStatus.FINISHED_STOPPED

vllm/engine/llm_engine.py

@@ -40,6 +40,7 @@ from vllm.multimodal.cache import processor_only_cache_from_config
 from vllm.multimodal.processing import EncDecMultiModalProcessor
 from vllm.outputs import (PoolingRequestOutput, RequestOutput,
                           RequestOutputFactory)
+from vllm.reasoning import ReasoningParser, ReasoningParserManager
 from vllm.sampling_params import RequestOutputKind, SamplingParams
 from vllm.sequence import (ExecuteModelRequest, ParallelSampleSequenceGroup,
                            Sequence, SequenceGroup, SequenceGroupBase,
@@ -372,6 +373,14 @@ class LLMEngine:
                 "vllm.llm_engine",
                 self.observability_config.otlp_traces_endpoint)
 
+        # Initialize reasoning parser if reasoning backend is set.
+        if self.decoding_config.reasoning_backend and \
+                self.tokenizer:
+            reasoner_class = ReasoningParserManager.get_reasoning_parser(
+                self.decoding_config.reasoning_backend)
+            self.reasoner: ReasoningParser = reasoner_class(
+                self.tokenizer.get_lora_tokenizer())
+
         # Create sequence output processor, e.g. for beam search or
         # speculative decoding.
         self.output_processor = (
@@ -381,8 +390,12 @@ class LLMEngine:
                 self.scheduler,
                 self.seq_counter,
                 get_tokenizer_for_seq,
-                stop_checker=StopChecker(self.scheduler_config.max_model_len,
-                                         get_tokenizer_for_seq),
+                stop_checker=StopChecker(
+                    self.scheduler_config.max_model_len,
+                    get_tokenizer_for_seq,
+                    self.reasoner if self.decoding_config.reasoning_backend
+                    and self.tokenizer else None,
+                ),
             ))
 
         self.seq_id_to_seq_group: Dict[str, SequenceGroupBase] = {}

vllm/engine/output_processor/stop_checker.py

@@ -4,6 +4,7 @@
 from typing import Callable, List, Optional, Tuple
 
 from vllm.lora.request import LoRARequest
+from vllm.reasoning import ReasoningParser
 from vllm.sampling_params import SamplingParams
 from vllm.sequence import Sequence, SequenceStatus
 from vllm.transformers_utils.tokenizer import AnyTokenizer
@@ -16,11 +17,16 @@ class StopChecker:
     emitted, or if we have exceeded the max model len.
     """
 
-    def __init__(self, max_model_len: int,
-                 get_tokenizer_for_seq: Callable[[Sequence], AnyTokenizer]):
+    def __init__(
+        self,
+        max_model_len: int,
+        get_tokenizer_for_seq: Callable[[Sequence], AnyTokenizer],
+        reasoner: Optional[ReasoningParser] = None,
+    ):
         # Do not use it directly, but use `self._get_max_model_len`.
         self._max_model_len = max_model_len
         self.get_tokenizer_for_seq = get_tokenizer_for_seq
+        self.reasoner = reasoner
 
     def _get_max_model_len(self, lora_req: Optional[LoRARequest]):
         if lora_req and lora_req.long_lora_max_len:
@@ -57,6 +63,11 @@ class StopChecker:
             seq.status = SequenceStatus.FINISHED_STOPPED
             return
 
+        # Skip stop string/token checks if in reasoning content generation
+        if self.reasoner is not None and \
+            not self.reasoner.is_reasoning_end(seq.get_token_ids()):
+            return
+
         # Check if a stop token was encountered.
         # This assumes a single token produced per step.
         last_token_id = seq.get_last_token_id()