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[Bugfix] Fix Mistral guided generation using xgrammar (#15704)

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Signed-off-by: Julien Denize <julien.denize@mistral.ai>
This commit is contained in:
Julien Denize
2025-03-30 05:20:19 +02:00
committed by GitHub
parent 045533716b
commit 6909a76201
2 changed files with 34 additions and 17 deletions
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33
tests/v1/entrypoints/llm/test_struct_output_generate.py
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@@ -15,11 +15,20 @@ from vllm.entrypoints.llm import LLM
from vllm.outputs import RequestOutput
from vllm.sampling_params import GuidedDecodingParams, SamplingParams
GUIDED_DECODING_BACKENDS_V1 = [
"xgrammar:disable-any-whitespace", "guidance:disable-any-whitespace"
PARAMS_MODELS_BACKENDS_TOKENIZER_MODE = [
("mistralai/Ministral-8B-Instruct-2410", "xgrammar:disable-any-whitespace",
"auto"),
("mistralai/Ministral-8B-Instruct-2410", "guidance:disable-any-whitespace",
"auto"),
("mistralai/Ministral-8B-Instruct-2410", "xgrammar:disable-any-whitespace",
"mistral"),
("Qwen/Qwen2.5-1.5B-Instruct", "xgrammar:disable-any-whitespace", "auto"),
("Qwen/Qwen2.5-1.5B-Instruct", "guidance:disable-any-whitespace", "auto"),
]
MODELS_TO_TEST = [
"Qwen/Qwen2.5-1.5B-Instruct", "mistralai/Ministral-8B-Instruct-2410"
PARAMS_MODELS_TOKENIZER_MODE = [
("mistralai/Ministral-8B-Instruct-2410", "auto"),
("Qwen/Qwen2.5-1.5B-Instruct", "auto"),
]
@@ -37,9 +46,8 @@ class CarDescription(BaseModel):
@pytest.mark.skip_global_cleanup
@pytest.mark.parametrize("guided_decoding_backend",
GUIDED_DECODING_BACKENDS_V1)
@pytest.mark.parametrize("model_name", MODELS_TO_TEST)
@pytest.mark.parametrize("model_name, guided_decoding_backend, tokenizer_mode",
PARAMS_MODELS_BACKENDS_TOKENIZER_MODE)
def test_structured_output(
monkeypatch: pytest.MonkeyPatch,
sample_json_schema: dict[str, Any],
@@ -49,6 +57,7 @@ def test_structured_output(
sample_regex: str,
sample_guided_choice: str,
guided_decoding_backend: str,
tokenizer_mode: str,
model_name: str,
):
monkeypatch.setenv("VLLM_USE_V1", "1")
@@ -58,7 +67,8 @@ def test_structured_output(
llm = LLM(model=model_name,
enforce_eager=True,
max_model_len=1024,
guided_decoding_backend=guided_decoding_backend)
guided_decoding_backend=guided_decoding_backend,
tokenizer_mode=tokenizer_mode)
#
# Test 1: Generate JSON output based on a provided schema
@@ -324,17 +334,20 @@ def test_structured_output(
@pytest.mark.skip_global_cleanup
@pytest.mark.parametrize("model_name", MODELS_TO_TEST)
@pytest.mark.parametrize("model_name, tokenizer_mode",
PARAMS_MODELS_TOKENIZER_MODE)
def test_structured_output_auto_mode(
monkeypatch: pytest.MonkeyPatch,
unsupported_json_schema: dict[str, Any],
model_name: str,
tokenizer_mode: str,
):
monkeypatch.setenv("VLLM_USE_V1", "1")
llm = LLM(model=model_name,
max_model_len=1024,
guided_decoding_backend="auto")
guided_decoding_backend="auto",
tokenizer_mode=tokenizer_mode)
sampling_params = SamplingParams(
temperature=1.0,