[Frontend] Support guidance:no-additional-properties for compatibility with xgrammar (#15949)

Signed-off-by: Travis Johnson <tsjohnso@us.ibm.com>

tests/entrypoints/llm/test_guided_generate.py

@@ -383,4 +383,62 @@ def test_guided_json_completion_with_enum(llm, guided_decoding_backend: str):
         assert generated_text is not None
         print(f"Prompt: {prompt!r}, Generated text: {generated_text!r}")
         output_json = json.loads(generated_text)
-        jsonschema.validate(instance=output_json, schema=json_schema)
+        jsonschema.validate(instance=output_json, schema=json_schema)
+
+
+@pytest.mark.skip_global_cleanup
+def test_guidance_no_additional_properties(llm):
+    schema = {
+        'type': 'object',
+        'properties': {
+            'a1': {
+                'type': 'string'
+            },
+            'a2': {
+                'type': 'string'
+            },
+            'a3': {
+                'type': 'string'
+            }
+        },
+        'required': ['a1', 'a2', 'a3'],
+    }
+
+    prompt = (
+        "<|im_start|>system\nYou are Qwen, created by Alibaba Cloud. You are a "
+        "helpful assistant.<|im_end|>\n<|im_start|>user\nPlease generate a "
+        "large JSON object with key-value pairs a1=b1, a2=b2, ..., a20=b20"
+        "<|im_end|>\n<|im_start|>assistant\n")
+
+    def generate_with_backend(backend):
+        guided_params = GuidedDecodingParams(json=schema, backend=backend)
+        sampling_params = SamplingParams(temperature=0,
+                                         max_tokens=256,
+                                         guided_decoding=guided_params)
+
+        outputs = llm.generate(prompts=prompt, sampling_params=sampling_params)
+        assert outputs is not None
+        generated_text = outputs[0].outputs[0].text
+        assert generated_text is not None
+        parsed_json = json.loads(generated_text)
+        assert isinstance(parsed_json, dict)
+        jsonschema.validate(instance=parsed_json, schema=schema)
+        return parsed_json
+
+    base_generated = generate_with_backend('guidance:disable-any-whitespace')
+    assert "a1" in base_generated
+    assert "a2" in base_generated
+    assert "a3" in base_generated
+    # by default additional keys are generated
+    assert "a4" in base_generated
+    assert "a5" in base_generated
+    assert "a6" in base_generated
+
+    generated = generate_with_backend(
+        'guidance:no-additional-properties,disable-any-whitespace')
+    assert "a1" in generated
+    assert "a2" in generated
+    assert "a3" in generated
+    assert "a4" not in generated
+    assert "a5" not in generated
+    assert "a6" not in generated

tests/v1/entrypoints/llm/test_struct_output_generate.py

@@ -412,3 +412,59 @@ def test_structured_output_auto_mode(
         # Parse to verify it is valid JSON
         parsed_json = json.loads(generated_text)
         assert isinstance(parsed_json, dict)
+
+
+@pytest.mark.skip_global_cleanup
+def test_guidance_no_additional_properties(monkeypatch: pytest.MonkeyPatch):
+    monkeypatch.setenv("VLLM_USE_V1", "1")
+
+    backend = 'guidance:no-additional-properties,disable-any-whitespace'
+    llm = LLM(model="Qwen/Qwen2.5-1.5B-Instruct",
+              max_model_len=1024,
+              guided_decoding_backend=backend)
+
+    schema = {
+        'type': 'object',
+        'properties': {
+            'a1': {
+                'type': 'string'
+            },
+            'a2': {
+                'type': 'string'
+            },
+            'a3': {
+                'type': 'string'
+            }
+        },
+        'required': ['a1', 'a2', 'a3'],
+    }
+
+    prompt = (
+        "<|im_start|>system\nYou are Qwen, created by Alibaba Cloud. You are a "
+        "helpful assistant.<|im_end|>\n<|im_start|>user\nPlease generate a "
+        "large JSON object with key-value pairs a1=b1, a2=b2, ..., a20=b20"
+        "<|im_end|>\n<|im_start|>assistant\n")
+
+    def generate_with_backend(backend):
+        guided_params = GuidedDecodingParams(json=schema, backend=backend)
+        sampling_params = SamplingParams(temperature=0,
+                                         max_tokens=256,
+                                         guided_decoding=guided_params)
+
+        outputs = llm.generate(prompts=prompt, sampling_params=sampling_params)
+        assert outputs is not None
+        generated_text = outputs[0].outputs[0].text
+        assert generated_text is not None
+        parsed_json = json.loads(generated_text)
+        assert isinstance(parsed_json, dict)
+        jsonschema.validate(instance=parsed_json, schema=schema)
+        return parsed_json
+
+    generated = generate_with_backend(
+        'guidance:no-additional-properties,disable-any-whitespace')
+    assert "a1" in generated
+    assert "a2" in generated
+    assert "a3" in generated
+    assert "a4" not in generated
+    assert "a5" not in generated
+    assert "a6" not in generated

vllm/config.py

@@ -3107,7 +3107,7 @@ def get_served_model_name(model: str,
 
 
 GuidedDecodingBackendV0 = Literal["auto", "outlines", "lm-format-enforcer",
-                                  "xgrammar"]
+                                  "xgrammar", "guidance"]
 GuidedDecodingBackendV1 = Literal["auto", "xgrammar", "guidance"]
 
 

vllm/engine/arg_utils.py

@@ -18,7 +18,8 @@ import vllm.envs as envs
 from vllm import version
 from vllm.config import (BlockSize, CacheConfig, CacheDType, CompilationConfig,
                          ConfigFormat, ConfigType, DecodingConfig, Device,
-                         DeviceConfig, DistributedExecutorBackend, HfOverrides,
+                         DeviceConfig, DistributedExecutorBackend,
+                         GuidedDecodingBackendV1, HfOverrides,
                          KVTransferConfig, LoadConfig, LoadFormat, LoRAConfig,
                          ModelConfig, ModelImpl, MultiModalConfig,
                          ObservabilityConfig, ParallelConfig, PoolerConfig,
@@ -1370,14 +1371,13 @@ class EngineArgs:
                                recommend_to_remove=True)
             return False
 
-        # Xgrammar and Guidance are supported.
-        SUPPORTED_GUIDED_DECODING = [
-            "xgrammar", "xgrammar:disable-any-whitespace", "guidance",
-            "guidance:disable-any-whitespace", "auto"
-        ]
-        if self.guided_decoding_backend not in SUPPORTED_GUIDED_DECODING:
-            _raise_or_fallback(feature_name="--guided-decoding-backend",
-                               recommend_to_remove=False)
+        # remove backend options when doing this check
+        if self.guided_decoding_backend.split(':')[0] \
+            not in get_args(GuidedDecodingBackendV1):
+            _raise_or_fallback(
+                feature_name=
+                f"--guided-decoding-backend={self.guided_decoding_backend}",
+                recommend_to_remove=False)
             return False
 
         # Need at least Ampere for now (FA support required).

vllm/model_executor/guided_decoding/guidance_decoding.py

@@ -1,4 +1,5 @@
 # SPDX-License-Identifier: Apache-2.0
+import json
 from re import escape as regex_escape
 
 import llguidance
@@ -7,6 +8,8 @@ from transformers import PreTrainedTokenizerBase
 from vllm.model_executor.guided_decoding.guidance_logits_processors import (
     GuidanceLogitsProcessor)
 from vllm.sampling_params import GuidedDecodingParams
+from vllm.v1.structured_output.backend_guidance import (
+    process_for_additional_properties)
 
 
 def get_local_guidance_guided_decoding_logits_processor(
@@ -20,9 +23,17 @@ def get_local_guidance_guided_decoding_logits_processor(
     grm = ""
     any_whitespace = 'disable-any-whitespace' not in \
         guided_params.backend_options()
-    if guided_params.json:
+    if (guide_json := guided_params.json) is not None:
+        # Optionally set additionalProperties to False at the top-level
+        # By default, other backends do not allow additional top-level
+        # properties, so this makes guidance more similar to other backends
+        if 'no-additional-properties' in guided_params.backend_options():
+            if not isinstance(guide_json, str):
+                guide_json = json.dumps(guide_json)
+            guide_json = process_for_additional_properties(guide_json)
+
         grm = llguidance.LLMatcher.grammar_from_json_schema(
-            guided_params.json,
+            guide_json,
             overrides={"whitespace_pattern": guided_params.whitespace_pattern},
             defaults={
                 "whitespace_flexible": any_whitespace,

vllm/v1/engine/processor.py

@@ -145,15 +145,7 @@ class Processor:
         if not params.guided_decoding or not self.decoding_config:
             return
 
-        supported_backends = [
-            "xgrammar", "xgrammar:disable-any-whitespace", "guidance",
-            "guidance:disable-any-whitespace", "auto"
-        ]
-
         engine_level_backend = self.decoding_config.guided_decoding_backend
-        if engine_level_backend not in supported_backends:
-            raise ValueError(f"Only {supported_backends} structured output is "
-                             "supported in V1.")
         if params.guided_decoding.backend:
             # Request-level backend selection is not supported in V1.
             # The values may differ if `params` is reused and was set

vllm/v1/structured_output/backend_guidance.py

@@ -1,14 +1,16 @@
 # SPDX-License-Identifier: Apache-2.0
 
+import copy
+import json
 import os
 from dataclasses import dataclass
-from typing import TYPE_CHECKING, Optional
+from typing import TYPE_CHECKING, Any, Optional, Union
 
 import torch
 
 from vllm.config import VllmConfig
 from vllm.logger import init_logger
-from vllm.sampling_params import SamplingParams
+from vllm.sampling_params import GuidedDecodingParams, SamplingParams
 from vllm.transformers_utils.tokenizer_group import init_tokenizer_from_configs
 from vllm.utils import LazyLoader
 from vllm.v1.structured_output.backend_types import (StructuredOutputBackend,
@@ -29,6 +31,29 @@ else:
 logger = init_logger(__name__)
 
 
+def _walk_json_for_additional_properties(data: object):
+    if isinstance(data, dict):
+        for value in data.values():
+            _walk_json_for_additional_properties(value)
+        if 'additionalProperties' not in data and \
+            ('properties' in data or 'patternProperties' in data):
+            data['additionalProperties'] = False
+    elif isinstance(data, list):
+        for item in data:
+            _walk_json_for_additional_properties(item)
+
+
+def process_for_additional_properties(
+        guide_json: Union[str, dict[str, Any]]) -> dict[str, Any]:
+    if isinstance(guide_json, str):
+        guide_json_obj = json.loads(guide_json)
+    else:
+        # copy for modifications
+        guide_json_obj = copy.deepcopy(guide_json)
+    _walk_json_for_additional_properties(guide_json_obj)
+    return guide_json_obj
+
+
 class GuidanceBackend(StructuredOutputBackend):
 
     def __init__(self, vllm_config: VllmConfig):
@@ -41,9 +66,20 @@ class GuidanceBackend(StructuredOutputBackend):
         tokenizer_group.ping()
         self.vllm_config = vllm_config
         self.vocab_size = vllm_config.model_config.get_vocab_size()
-        self.disable_any_whitespace = (
-            "disable-any-whitespace"
-            in vllm_config.decoding_config.guided_decoding_backend)
+
+        self.disable_any_whitespace = False
+        self.no_additional_properties = False
+        backend_options = GuidedDecodingParams(
+            backend=vllm_config.decoding_config.guided_decoding_backend
+        ).backend_options()
+        for option in backend_options:
+            if option == "disable-any-whitespace":
+                self.disable_any_whitespace = True
+            elif option == "no-additional-properties":
+                self.no_additional_properties = True
+            else:
+                raise ValueError(
+                    f"Unsupported option for the guidance backend: {option}")
 
         tokenizer = tokenizer_group.get_lora_tokenizer(None)
         self.ll_tokenizer = llguidance_hf.from_tokenizer(
@@ -52,7 +88,8 @@ class GuidanceBackend(StructuredOutputBackend):
     def compile_grammar(self, request_type: StructuredOutputOptions,
                         grammar_spec: str) -> StructuredOutputGrammar:
         self.serialized_grammar = serialize_guidance_grammar(
-            request_type, grammar_spec, self.disable_any_whitespace)
+            request_type, grammar_spec, self.disable_any_whitespace,
+            self.no_additional_properties)
 
         ll_matcher = llguidance.LLMatcher(
             self.ll_tokenizer,
@@ -129,10 +166,15 @@ class GuidanceGrammar(StructuredOutputGrammar):
         self.ll_matcher.reset()
 
 
-def serialize_guidance_grammar(request_type: StructuredOutputOptions,
-                               grammar_spec: str,
-                               disable_any_whitespace: bool = False) -> str:
+def serialize_guidance_grammar(
+    request_type: StructuredOutputOptions,
+    grammar_spec: Union[str, dict[str, Any]],
+    disable_any_whitespace: bool = False,
+    no_additional_properties: bool = False,
+) -> str:
     if request_type == StructuredOutputOptions.JSON:
+        if no_additional_properties:
+            grammar_spec = process_for_additional_properties(grammar_spec)
         return llguidance.LLMatcher.grammar_from_json_schema(
             grammar_spec,
             defaults={

vllm/v1/structured_output/backend_xgrammar.py

@@ -9,7 +9,7 @@ import torch
 import vllm.envs
 from vllm.config import VllmConfig
 from vllm.logger import init_logger
-from vllm.sampling_params import SamplingParams
+from vllm.sampling_params import GuidedDecodingParams, SamplingParams
 from vllm.transformers_utils.tokenizer_group import init_tokenizer_from_configs
 from vllm.transformers_utils.tokenizers.mistral import MistralTokenizer
 from vllm.utils import LazyLoader
@@ -32,9 +32,6 @@ class XgrammarBackend(StructuredOutputBackend):
 
     def __init__(self, vllm_config: VllmConfig):
         self.vllm_config = vllm_config
-        self.disable_any_whitespace = (
-            "disable-any-whitespace"
-            in vllm_config.decoding_config.guided_decoding_backend)
         tokenizer_group = init_tokenizer_from_configs(
             model_config=vllm_config.model_config,
             scheduler_config=vllm_config.scheduler_config,
@@ -42,6 +39,17 @@ class XgrammarBackend(StructuredOutputBackend):
             lora_config=vllm_config.lora_config)  # type: ignore[arg-type]
         tokenizer_group.ping()
 
+        self.disable_any_whitespace = False
+        backend_options = GuidedDecodingParams(
+            backend=vllm_config.decoding_config.guided_decoding_backend
+        ).backend_options()
+        for option in backend_options:
+            if option == "disable-any-whitespace":
+                self.disable_any_whitespace = True
+            else:
+                raise ValueError(
+                    f"Unsupported option for the xgrammar backend: {option}")
+
         tokenizer = tokenizer_group.get_lora_tokenizer(None)
         self.vocab_size = vllm_config.model_config.get_vocab_size()
         if isinstance(tokenizer, MistralTokenizer):