[V1] Set structured output backend to auto by default (#15724)

Signed-off-by: Russell Bryant <rbryant@redhat.com>

tests/entrypoints/openai/test_chat.py

@@ -20,8 +20,6 @@ from .test_completion import zephyr_lora_files  # noqa: F401
 # any model with a chat template should work here
 MODEL_NAME = "HuggingFaceH4/zephyr-7b-beta"
 
-GUIDED_DECODING_BACKENDS = ["outlines", "lm-format-enforcer", "xgrammar"]
-
 
 @pytest.fixture(scope="module")
 def monkeypatch_module():
@@ -487,20 +485,9 @@ async def test_chat_completion_stream_options(client: openai.AsyncOpenAI,
     assert last_completion_tokens == 10
 
 
-# NOTE: Not sure why, but when I place this after `test_guided_regex_chat`
-# (i.e. using the same ordering as in the Completions API tests), the test
-# will fail on the second `guided_decoding_backend` even when I swap their order
-# (ref: https://github.com/vllm-project/vllm/pull/5526#issuecomment-2173772256)
 @pytest.mark.asyncio
-@pytest.mark.parametrize("guided_decoding_backend", GUIDED_DECODING_BACKENDS)
 async def test_guided_choice_chat(client: openai.AsyncOpenAI,
-                                  is_v1_server: bool,
-                                  guided_decoding_backend: str,
                                   sample_guided_choice):
-
-    if is_v1_server and guided_decoding_backend != 'xgrammar':
-        pytest.skip("Only xgrammar backend is supported with V1")
-
     messages = [{
         "role": "system",
         "content": "you are a helpful assistant"
@@ -515,8 +502,7 @@ async def test_guided_choice_chat(client: openai.AsyncOpenAI,
         messages=messages,
         max_completion_tokens=10,
         temperature=0.7,
-        extra_body=dict(guided_choice=sample_guided_choice,
+        extra_body=dict(guided_choice=sample_guided_choice))
-                        guided_decoding_backend=guided_decoding_backend))
     choice1 = chat_completion.choices[0].message.content
     assert choice1 in sample_guided_choice
 
@@ -530,22 +516,16 @@ async def test_guided_choice_chat(client: openai.AsyncOpenAI,
         messages=messages,
         max_completion_tokens=10,
         temperature=0.7,
-        extra_body=dict(guided_choice=sample_guided_choice,
+        extra_body=dict(guided_choice=sample_guided_choice))
-                        guided_decoding_backend=guided_decoding_backend))
     choice2 = chat_completion.choices[0].message.content
     assert choice2 in sample_guided_choice
     assert choice1 != choice2
 
 
 @pytest.mark.asyncio
-@pytest.mark.parametrize("guided_decoding_backend", GUIDED_DECODING_BACKENDS)
+async def test_guided_json_chat(client: openai.AsyncOpenAI,
-async def test_guided_json_chat(client: openai.AsyncOpenAI, is_v1_server: bool,
-                                guided_decoding_backend: str,
                                 sample_json_schema):
 
-    if is_v1_server:
-        pytest.skip("sample_json_schema has features unsupported in V1")
-
     messages = [{
         "role": "system",
         "content": "you are a helpful assistant"
@@ -560,8 +540,7 @@ async def test_guided_json_chat(client: openai.AsyncOpenAI, is_v1_server: bool,
         model=MODEL_NAME,
         messages=messages,
         max_completion_tokens=1000,
-        extra_body=dict(guided_json=sample_json_schema,
+        extra_body=dict(guided_json=sample_json_schema))
-                        guided_decoding_backend=guided_decoding_backend))
     message = chat_completion.choices[0].message
     assert message.content is not None
     json1 = json.loads(message.content)
@@ -578,8 +557,7 @@ async def test_guided_json_chat(client: openai.AsyncOpenAI, is_v1_server: bool,
         model=MODEL_NAME,
         messages=messages,
         max_completion_tokens=1000,
-        extra_body=dict(guided_json=sample_json_schema,
+        extra_body=dict(guided_json=sample_json_schema))
-                        guided_decoding_backend=guided_decoding_backend))
     message = chat_completion.choices[0].message
     assert message.content is not None
     json2 = json.loads(message.content)
@@ -589,13 +567,7 @@ async def test_guided_json_chat(client: openai.AsyncOpenAI, is_v1_server: bool,
 
 
 @pytest.mark.asyncio
-@pytest.mark.parametrize("guided_decoding_backend", GUIDED_DECODING_BACKENDS)
+async def test_guided_regex_chat(client: openai.AsyncOpenAI, sample_regex):
-async def test_guided_regex_chat(client: openai.AsyncOpenAI,
-                                 is_v1_server: bool,
-                                 guided_decoding_backend: str, sample_regex):
-
-    if is_v1_server and guided_decoding_backend != 'xgrammar':
-        pytest.skip("Only xgrammar backend is supported with V1")
 
     messages = [{
         "role": "system",
@@ -610,8 +582,7 @@ async def test_guided_regex_chat(client: openai.AsyncOpenAI,
         model=MODEL_NAME,
         messages=messages,
         max_completion_tokens=20,
-        extra_body=dict(guided_regex=sample_regex,
+        extra_body=dict(guided_regex=sample_regex))
-                        guided_decoding_backend=guided_decoding_backend))
     ip1 = chat_completion.choices[0].message.content
     assert ip1 is not None
     assert re.fullmatch(sample_regex, ip1) is not None
@@ -622,8 +593,7 @@ async def test_guided_regex_chat(client: openai.AsyncOpenAI,
         model=MODEL_NAME,
         messages=messages,
         max_completion_tokens=20,
-        extra_body=dict(guided_regex=sample_regex,
+        extra_body=dict(guided_regex=sample_regex))
-                        guided_decoding_backend=guided_decoding_backend))
     ip2 = chat_completion.choices[0].message.content
     assert ip2 is not None
     assert re.fullmatch(sample_regex, ip2) is not None
@@ -652,15 +622,9 @@ async def test_guided_decoding_type_error(client: openai.AsyncOpenAI):
 
 
 @pytest.mark.asyncio
-@pytest.mark.parametrize("guided_decoding_backend", GUIDED_DECODING_BACKENDS)
 async def test_guided_choice_chat_logprobs(client: openai.AsyncOpenAI,
-                                           is_v1_server: bool,
-                                           guided_decoding_backend: str,
                                            sample_guided_choice):
 
-    if is_v1_server and guided_decoding_backend != 'xgrammar':
-        pytest.skip("Only xgrammar backend is supported with V1")
-
     messages = [{
         "role": "system",
         "content": "you are a helpful assistant"
@@ -676,8 +640,7 @@ async def test_guided_choice_chat_logprobs(client: openai.AsyncOpenAI,
         max_completion_tokens=10,
         logprobs=True,
         top_logprobs=5,
-        extra_body=dict(guided_choice=sample_guided_choice,
+        extra_body=dict(guided_choice=sample_guided_choice))
-                        guided_decoding_backend=guided_decoding_backend))
 
     assert chat_completion.choices[0].logprobs is not None
     assert chat_completion.choices[0].logprobs.content is not None
@@ -689,14 +652,7 @@ async def test_guided_choice_chat_logprobs(client: openai.AsyncOpenAI,
 
 
 @pytest.mark.asyncio
-@pytest.mark.parametrize("guided_decoding_backend", GUIDED_DECODING_BACKENDS)
+async def test_named_tool_use(client: openai.AsyncOpenAI, sample_json_schema):
-async def test_named_tool_use(client: openai.AsyncOpenAI, is_v1_server: bool,
-                              guided_decoding_backend: str,
-                              sample_json_schema):
-
-    if is_v1_server:
-        pytest.skip("sample_json_schema has features unsupported on V1")
-
     messages = [{
         "role": "system",
         "content": "you are a helpful assistant"
@@ -728,7 +684,7 @@ async def test_named_tool_use(client: openai.AsyncOpenAI, is_v1_server: bool,
                 "name": "dummy_function_name"
             }
         },
-        extra_body=dict(guided_decoding_backend=guided_decoding_backend))
+    )
     message = chat_completion.choices[0].message
     assert len(message.content) == 0
     json_string = message.tool_calls[0].function.arguments
@@ -763,7 +719,6 @@ async def test_named_tool_use(client: openai.AsyncOpenAI, is_v1_server: bool,
                 "name": "dummy_function_name"
             }
         },
-        extra_body=dict(guided_decoding_backend=guided_decoding_backend),
         stream=True)
 
     output = []
@@ -888,7 +843,6 @@ async def test_required_tool_use(client: openai.AsyncOpenAI,
         model=model_name,
         tools=tools,
         tool_choice="required",
-        extra_body=dict(guided_decoding_backend="outlines"),
     )
 
     assert chat_completion.choices[0].message.tool_calls is not None
@@ -900,7 +854,6 @@ async def test_required_tool_use(client: openai.AsyncOpenAI,
         model=model_name,
         tools=tools,
         tool_choice="required",
-        extra_body=dict(guided_decoding_backend="outlines"),
         stream=True,
     )
 
@@ -914,12 +867,7 @@ async def test_required_tool_use(client: openai.AsyncOpenAI,
 
 @pytest.mark.asyncio
 async def test_inconsistent_tool_choice_and_tools(client: openai.AsyncOpenAI,
-                                                  is_v1_server: bool,
                                                   sample_json_schema):
-
-    if is_v1_server:
-        pytest.skip("sample_json_schema has features unsupported on V1")
-
     messages = [{
         "role": "system",
         "content": "you are a helpful assistant"

vllm/config.py

@@ -2976,7 +2976,7 @@ class DecodingConfig:
 
     # Which guided decoding algo to use.
     # 'outlines' / 'lm-format-enforcer' / 'xgrammar'
-    guided_decoding_backend: str = 'xgrammar'
+    guided_decoding_backend: str = "auto" if envs.VLLM_USE_V1 else "xgrammar"
 
     reasoning_backend: Optional[str] = None
 
@@ -3001,7 +3001,7 @@ class DecodingConfig:
 
     def __post_init__(self):
         v0_valid_guided_backends = [
-            'outlines', 'lm-format-enforcer', 'xgrammar'
+            'outlines', 'lm-format-enforcer', 'xgrammar', 'auto'
         ]
         v1_valid_guided_backends = ['xgrammar', 'guidance', 'auto']
 

vllm/engine/arg_utils.py

@@ -182,7 +182,7 @@ class EngineArgs:
     enable_chunked_prefill: Optional[bool] = None
     disable_chunked_mm_input: bool = False
 
-    guided_decoding_backend: str = 'xgrammar'
+    guided_decoding_backend: str = DecodingConfig.guided_decoding_backend
     logits_processor_pattern: Optional[str] = None
 
     speculative_config: Optional[Dict[str, Any]] = None
@@ -407,13 +407,13 @@ class EngineArgs:
         parser.add_argument(
             '--guided-decoding-backend',
             type=str,
-            default='xgrammar',
+            default=DecodingConfig.guided_decoding_backend,
             help='Which engine will be used for guided decoding'
             ' (JSON schema / regex etc) by default. Currently support '
             'https://github.com/mlc-ai/xgrammar and '
             'https://github.com/guidance-ai/llguidance.'
             'Valid backend values are "xgrammar", "guidance", and "auto". '
-            'With "auto", we will make opinionated choices based on request'
+            'With "auto", we will make opinionated choices based on request '
             'contents and what the backend libraries currently support, so '
             'the behavior is subject to change in each release.')
         parser.add_argument(

vllm/model_executor/guided_decoding/__init__.py

@@ -33,6 +33,12 @@ def maybe_backend_fallback(
         logger.warning("%s Falling back to use %s instead.", message, fallback)
         guided_params.backend = fallback
 
+    # `auto` was added for V1 to explicitly declare a mode that has fallbacks
+    # in place. If that is specified with V0, treat it as `xgrammar`, as we have
+    # fallbacks enabled for that and it is the V0 default.
+    if guided_params.backend == "auto":
+        guided_params.backend = "xgrammar"
+
     # lm-format-enforce doesn't support grammar, fallback to xgrammar
     if guided_params.backend_name == "lm-format-enforcer":
         if guided_params.grammar is not None: