[Bugfix]: Fix structured output in multi-turn gpt-oss

tests/entrypoints/openai/test_gptoss_structural_tags_integration.py

@@ -23,6 +23,7 @@ def mock_tokenizer(self):
         """Create a mock tokenizer."""
         tokenizer = Mock()
         tokenizer.encode = Mock(return_value=[1, 2, 3, 4, 5])
+        tokenizer.vocab = {"<|end|>": 6}
         return tokenizer
 
     @pytest.fixture

tests/reasoning/test_gptoss_reasoning_parser.py

@@ -17,7 +17,9 @@ def gpt_oss_tokenizer():
 
 USER_MESSAGE_START = "<|start|>user<|message|>"
 REASONING_SECTION_START = "<|end|><|start|>assistant<|channel|>analysis<|message|>"
-ASSISTANT_CONTENT_START_PREFIX = "<|end|><|start|>assistant<|channel|>final"
+END = "<|end|>"
+ASSISTANT_START = "<|start|>assistant"
+ASSISTANT_CONTENT_START_PREFIX = END + ASSISTANT_START + "<|channel|>final"
 ASSISTANT_CONTENT_START_SUFFIX = "<|message|>"
 ASSISTANT_CONTENT_START = (
     ASSISTANT_CONTENT_START_PREFIX + ASSISTANT_CONTENT_START_SUFFIX
@@ -97,6 +99,20 @@ def gpt_oss_tokenizer():
     "is_reasoning_end": True,
 }
 
+MULTI_TURN_CONTENT = {
+    "output": USER_MESSAGE_START
+    + "1st turn user message"
+    + REASONING_SECTION_START
+    + "1st turn reasoning"
+    + ASSISTANT_CONTENT_START
+    + "1st turn response"
+    + END
+    + USER_MESSAGE_START
+    + "2nd turn user message"
+    + END
+    + ASSISTANT_START,
+    "is_reasoning_end": False,
+}
 TEST_CASES = [
     BASIC_CONTENT,
     BASIC_REASONING_ONLY,
@@ -106,6 +122,7 @@ def gpt_oss_tokenizer():
     COMPLEX_CONTENT_1,
     COMPLEX_CONTENT_1_WITH_CONTENT,
     COMPLEX_CONTENT_2,
+    MULTI_TURN_CONTENT,
 ]
 
 

tests/v1/structured_output/test_gptoss_structural_tags.py

@@ -25,6 +25,7 @@ def mock_tokenizer(self):
         """Create a mock tokenizer for testing."""
         tokenizer = Mock()
         tokenizer.encode = Mock(return_value=[1, 2, 3, 4, 5])
+        tokenizer.vocab = {"<|end|>": 6}
         return tokenizer
 
     @pytest.fixture

vllm/reasoning/gptoss_reasoning_parser.py

@@ -76,6 +76,9 @@ def __init__(self, tokenizer: PreTrainedTokenizerBase, *args, **kwargs):
             "<|channel|>final"
         )
         self.reasoning_end_token_ids_suffix = self.model_tokenizer.encode("<|message|>")
+        # We also need to check for the <|end|> token to avoid false positives from
+        # previous messages in multi-turn conversations.
+        self.eom_token_id = self.model_tokenizer.vocab["<|end|>"]
         self.reasoning_max_num_between_tokens = 20
 
     def is_reasoning_end(self, input_ids: Sequence[int]) -> bool:
@@ -86,6 +89,12 @@ def is_reasoning_end(self, input_ids: Sequence[int]) -> bool:
         # 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_prefix), -1, -1):
+            if input_ids[i] == self.eom_token_id:
+                # We looped backwards far enough to find the end of a previous message,
+                # which means we have searched the entirety of the current message
+                # and can exit early without searching further back into prior
+                # messages of the conversation.
+                return False
             if input_ids[i : i + len(end_token_ids_prefix)] == end_token_ids_prefix:
                 # We have found the prefix, now we look for the suffix after the prefix.
                 suffix_start = i + len(end_token_ids_prefix)