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[V1][Core] Support MistralTokenizer for Structured Output (#14625)

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Signed-off-by: Aaron Pham <contact@aarnphm.xyz>
This commit is contained in:
Aaron Pham
2025-03-11 22:40:09 -04:00
committed by GitHub
parent 80e78d02ac
commit 77a318bd01
2 changed files with 102 additions and 26 deletions
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87
tests/v1/entrypoints/llm/test_struct_output_generate.py
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@@ -1,7 +1,10 @@
# SPDX-License-Identifier: Apache-2.0
from __future__ import annotations
import json
import re
from typing import Any
import jsonschema
import pytest
@@ -10,17 +13,27 @@ from vllm.entrypoints.llm import LLM
from vllm.outputs import RequestOutput
from vllm.sampling_params import GuidedDecodingParams, SamplingParams
MODEL_NAME = "Qwen/Qwen2.5-1.5B-Instruct"
GUIDED_DECODING_BACKENDS_V1 = ["xgrammar"]
@pytest.fixture
def model_name():
return [
"Qwen/Qwen2.5-1.5B-Instruct", "mistralai/Ministral-8B-Instruct-2410"
]
@pytest.mark.skip_global_cleanup
@pytest.mark.parametrize("guided_decoding_backend",
GUIDED_DECODING_BACKENDS_V1)
def test_guided_json_completion(monkeypatch, sample_json_schema,
guided_decoding_backend: str):
def test_guided_json_completion(
monkeypatch: pytest.MonkeyPatch,
sample_json_schema: dict[str, Any],
guided_decoding_backend: str,
model_name: str,
):
monkeypatch.setenv("VLLM_USE_V1", "1")
llm = LLM(model=MODEL_NAME, max_model_len=1024)
llm = LLM(model=model_name, max_model_len=1024)
sampling_params = SamplingParams(temperature=1.0,
max_tokens=1000,
guided_decoding=GuidedDecodingParams(
@@ -50,9 +63,13 @@ def test_guided_json_completion(monkeypatch, sample_json_schema,
@pytest.mark.skip_global_cleanup
@pytest.mark.parametrize("guided_decoding_backend",
GUIDED_DECODING_BACKENDS_V1)
def test_guided_json_object(monkeypatch, guided_decoding_backend: str):
def test_guided_json_object(
monkeypatch: pytest.MonkeyPatch,
guided_decoding_backend: str,
model_name: str,
):
monkeypatch.setenv("VLLM_USE_V1", "1")
llm = LLM(model=MODEL_NAME, max_model_len=1024)
llm = LLM(model=model_name, max_model_len=1024)
sampling_params = SamplingParams(temperature=1.0,
max_tokens=100,
n=2,
@@ -84,10 +101,14 @@ def test_guided_json_object(monkeypatch, guided_decoding_backend: str):
@pytest.mark.skip_global_cleanup
@pytest.mark.parametrize("guided_decoding_backend",
GUIDED_DECODING_BACKENDS_V1)
def test_guided_json_unsupported_schema(monkeypatch, unsupported_json_schema,
guided_decoding_backend: str):
def test_guided_json_unsupported_schema(
monkeypatch: pytest.MonkeyPatch,
unsupported_json_schema: dict[str, Any],
guided_decoding_backend: str,
model_name: str,
):
monkeypatch.setenv("VLLM_USE_V1", "1")
llm = LLM(model=MODEL_NAME, max_model_len=1024)
llm = LLM(model=model_name, max_model_len=1024)
sampling_params = SamplingParams(temperature=1.0,
max_tokens=1000,
guided_decoding=GuidedDecodingParams(
@@ -107,10 +128,14 @@ def test_guided_json_unsupported_schema(monkeypatch, unsupported_json_schema,
@pytest.mark.skip_global_cleanup
@pytest.mark.parametrize("guided_decoding_backend",
GUIDED_DECODING_BACKENDS_V1)
def test_guided_grammar_ebnf(monkeypatch, sample_sql_ebnf,
guided_decoding_backend: str):
def test_guided_grammar_ebnf(
monkeypatch: pytest.MonkeyPatch,
sample_sql_ebnf: str,
guided_decoding_backend: str,
model_name: str,
):
monkeypatch.setenv("VLLM_USE_V1", "1")
llm = LLM(model=MODEL_NAME, max_model_len=1024)
llm = LLM(model=model_name, max_model_len=1024)
sampling_params = SamplingParams(temperature=0.8,
top_p=0.95,
max_tokens=1000,
@@ -145,10 +170,14 @@ def test_guided_grammar_ebnf(monkeypatch, sample_sql_ebnf,
@pytest.mark.skip_global_cleanup
@pytest.mark.parametrize("guided_decoding_backend",
GUIDED_DECODING_BACKENDS_V1)
def test_guided_grammar_lark(monkeypatch, sample_sql_lark,
guided_decoding_backend: str):
def test_guided_grammar_lark(
monkeypatch: pytest.MonkeyPatch,
sample_sql_lark: str,
guided_decoding_backend: str,
model_name: str,
):
monkeypatch.setenv("VLLM_USE_V1", "1")
llm = LLM(model=MODEL_NAME, max_model_len=1024)
llm = LLM(model=model_name, max_model_len=1024)
sampling_params = SamplingParams(temperature=0.8,
top_p=0.95,
max_tokens=1000,
@@ -188,10 +217,13 @@ def test_guided_grammar_lark(monkeypatch, sample_sql_lark,
@pytest.mark.skip_global_cleanup
@pytest.mark.parametrize("guided_decoding_backend",
GUIDED_DECODING_BACKENDS_V1)
def test_guided_grammar_ebnf_invalid(monkeypatch,
guided_decoding_backend: str):
def test_guided_grammar_ebnf_invalid(
monkeypatch: pytest.MonkeyPatch,
guided_decoding_backend: str,
model_name: str,
):
monkeypatch.setenv("VLLM_USE_V1", "1")
llm = LLM(model=MODEL_NAME, max_model_len=1024)
llm = LLM(model=model_name, max_model_len=1024)
sampling_params = SamplingParams(temperature=0.8,
top_p=0.95,
max_tokens=1000,
@@ -212,9 +244,14 @@ def test_guided_grammar_ebnf_invalid(monkeypatch,
@pytest.mark.skip_global_cleanup
@pytest.mark.parametrize("guided_decoding_backend",
GUIDED_DECODING_BACKENDS_V1)
def test_guided_regex(monkeypatch, sample_regex, guided_decoding_backend: str):
def test_guided_regex(
monkeypatch: pytest.MonkeyPatch,
sample_regex: str,
guided_decoding_backend: str,
model_name: str,
):
monkeypatch.setenv("VLLM_USE_V1", "1")
llm = LLM(model=MODEL_NAME, max_model_len=1024)
llm = LLM(model=model_name, max_model_len=1024)
sampling_params = SamplingParams(temperature=0.8,
top_p=0.95,
guided_decoding=GuidedDecodingParams(
@@ -243,10 +280,14 @@ def test_guided_regex(monkeypatch, sample_regex, guided_decoding_backend: str):
@pytest.mark.skip_global_cleanup
@pytest.mark.parametrize("guided_decoding_backend",
GUIDED_DECODING_BACKENDS_V1)
def test_guided_choice_completion(monkeypatch, sample_guided_choice,
guided_decoding_backend: str):
def test_guided_choice_completion(
monkeypatch: pytest.MonkeyPatch,
sample_guided_choice: str,
guided_decoding_backend: str,
model_name: str,
):
monkeypatch.setenv("VLLM_USE_V1", "1")
llm = LLM(model=MODEL_NAME, max_model_len=1024)
llm = LLM(model=model_name, max_model_len=1024)
sampling_params = SamplingParams(temperature=0.8,
top_p=0.95,
guided_decoding=GuidedDecodingParams(