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Remove all references to yapf as it's no longer used (#26251)

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Signed-off-by: Harry Mellor <19981378+hmellor@users.noreply.github.com>
This commit is contained in:
Harry Mellor
2025-10-05 17:18:11 +01:00
committed by GitHub
parent d6953beb91
commit 4e256cadc2
78 changed files with 1992 additions and 1717 deletions
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388
tests/entrypoints/test_chat_utils.py
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@@ -15,6 +15,7 @@ from vllm.assets.video import VideoAsset
from vllm.config import ModelConfig
from vllm.entrypoints.chat_utils import (
_try_extract_ast,
apply_mistral_chat_template,
load_chat_template,
parse_chat_messages,
parse_chat_messages_futures,
@@ -1855,17 +1856,17 @@ def test_resolve_hf_chat_template_kwargs(sample_json_schema, model, expected_kwa
# NOTE: Qwen2-Audio default chat template is specially defined inside
# processor class instead of using `tokenizer_config.json`
# yapf: disable
@pytest.mark.parametrize(
("model", "expected_format"),
[(PHI3V_MODEL_ID, "string"),
(QWEN2VL_MODEL_ID, "openai"),
(QWEN25VL_MODEL_ID, "openai"),
(ULTRAVOX_MODEL_ID, "string"),
(QWEN2AUDIO_MODEL_ID, "openai"),
(LLAMA_GUARD_MODEL_ID, "openai")],
[
(PHI3V_MODEL_ID, "string"),
(QWEN2VL_MODEL_ID, "openai"),
(QWEN25VL_MODEL_ID, "openai"),
(ULTRAVOX_MODEL_ID, "string"),
(QWEN2AUDIO_MODEL_ID, "openai"),
(LLAMA_GUARD_MODEL_ID, "openai"),
],
)
# yapf: enable
def test_resolve_content_format_hf_defined(model, expected_format):
model_info = HF_EXAMPLE_MODELS.find_hf_info(model)
model_info.check_available_online(on_fail="skip")
@@ -1879,7 +1880,8 @@ def test_resolve_content_format_hf_defined(model, expected_format):
hf_overrides=model_info.hf_overrides,
skip_tokenizer_init=model_info.skip_tokenizer_init,
enforce_eager=model_info.enforce_eager,
dtype=model_info.dtype)
dtype=model_info.dtype,
)
tokenizer = get_tokenizer(
model,
@@ -1911,18 +1913,18 @@ def test_resolve_content_format_hf_defined(model, expected_format):
assert resolved_format == expected_format
# yapf: disable
@pytest.mark.parametrize(
("model", "expected_format"),
[("Salesforce/blip2-opt-2.7b", "string"),
("facebook/chameleon-7b", "string"),
("deepseek-ai/deepseek-vl2-tiny", "string"),
("adept/fuyu-8b", "string"),
("google/paligemma-3b-mix-224", "string"),
("Qwen/Qwen-VL", "string"),
("Qwen/Qwen-VL-Chat", "string")],
[
("Salesforce/blip2-opt-2.7b", "string"),
("facebook/chameleon-7b", "string"),
("deepseek-ai/deepseek-vl2-tiny", "string"),
("adept/fuyu-8b", "string"),
("google/paligemma-3b-mix-224", "string"),
("Qwen/Qwen-VL", "string"),
("Qwen/Qwen-VL-Chat", "string"),
],
)
# yapf: enable
def test_resolve_content_format_fallbacks(model, expected_format):
model_info = HF_EXAMPLE_MODELS.find_hf_info(model)
model_info.check_available_online(on_fail="skip")
@@ -1936,7 +1938,8 @@ def test_resolve_content_format_fallbacks(model, expected_format):
hf_overrides=model_info.hf_overrides,
skip_tokenizer_init=model_info.skip_tokenizer_init,
enforce_eager=model_info.enforce_eager,
dtype=model_info.dtype)
dtype=model_info.dtype,
)
tokenizer = get_tokenizer(
model_config.tokenizer,
@@ -1968,30 +1971,30 @@ def test_resolve_content_format_fallbacks(model, expected_format):
assert resolved_format == expected_format
# yapf: disable
@pytest.mark.parametrize(
("template_path", "expected_format"),
[("template_alpaca.jinja", "string"),
("template_baichuan.jinja", "string"),
("template_chatglm.jinja", "string"),
("template_chatglm2.jinja", "string"),
("template_chatml.jinja", "string"),
("template_dse_qwen2_vl.jinja", "openai"),
("template_falcon_180b.jinja", "string"),
("template_falcon.jinja", "string"),
("template_inkbot.jinja", "string"),
("template_teleflm.jinja", "string"),
("template_vlm2vec_phi3v.jinja", "openai"),
("template_vlm2vec_qwen2vl.jinja", "openai"),
("tool_chat_template_granite_20b_fc.jinja", "string"),
("tool_chat_template_hermes.jinja", "string"),
("tool_chat_template_internlm2_tool.jinja", "string"),
("tool_chat_template_llama3.1_json.jinja", "openai"),
("tool_chat_template_llama3.2_json.jinja", "openai"),
("tool_chat_template_mistral_parallel.jinja", "string"),
("tool_chat_template_mistral.jinja", "string")],
[
("template_alpaca.jinja", "string"),
("template_baichuan.jinja", "string"),
("template_chatglm.jinja", "string"),
("template_chatglm2.jinja", "string"),
("template_chatml.jinja", "string"),
("template_dse_qwen2_vl.jinja", "openai"),
("template_falcon_180b.jinja", "string"),
("template_falcon.jinja", "string"),
("template_inkbot.jinja", "string"),
("template_teleflm.jinja", "string"),
("template_vlm2vec_phi3v.jinja", "openai"),
("template_vlm2vec_qwen2vl.jinja", "openai"),
("tool_chat_template_granite_20b_fc.jinja", "string"),
("tool_chat_template_hermes.jinja", "string"),
("tool_chat_template_internlm2_tool.jinja", "string"),
("tool_chat_template_llama3.1_json.jinja", "openai"),
("tool_chat_template_llama3.2_json.jinja", "openai"),
("tool_chat_template_mistral_parallel.jinja", "string"),
("tool_chat_template_mistral.jinja", "string"),
],
)
# yapf: enable
def test_resolve_content_format_examples(template_path, expected_format):
model_config = ModelConfig(
PHI3V_MODEL_ID, # Dummy
@@ -2024,40 +2027,34 @@ def test_resolve_content_format_examples(template_path, expected_format):
assert resolved_format == expected_format
def test_parse_chat_messages_include_thinking_chunk(mistral_model_config,
mistral_tokenizer):
messages = [{
"role":
"system",
"content": [{
"type": "text",
"text": "You are a helpful assistant."
}, {
"type":
"thinking",
"closed":
True,
"thinking":
"Only return the answer when you are confident."
}]
}, {
"role": "user",
"content": "What is 2+2?"
}, {
"role":
"assistant",
"content": [{
"type": "text",
"text": "Let me think about it."
}, {
"type": "thinking",
"closed": True,
"thinking": "2+2 = 4"
}, {
"type": "text",
"text": "The answer is 4.",
}],
}]
def test_parse_chat_messages_include_thinking_chunk(
mistral_model_config, mistral_tokenizer
):
messages = [
{
"role": "system",
"content": [
{"type": "text", "text": "You are a helpful assistant."},
{
"type": "thinking",
"closed": True,
"thinking": "Only return the answer when you are confident.",
},
],
},
{"role": "user", "content": "What is 2+2?"},
{
"role": "assistant",
"content": [
{"type": "text", "text": "Let me think about it."},
{"type": "thinking", "closed": True, "thinking": "2+2 = 4"},
{
"type": "text",
"text": "The answer is 4.",
},
],
},
]
conversation_with_thinking, _, _ = parse_chat_messages(
messages,
@@ -2066,122 +2063,105 @@ def test_parse_chat_messages_include_thinking_chunk(mistral_model_config,
content_format="openai",
)
expected_conversation = [{
"role":
"system",
"content": [{
"type": "text",
"text": "You are a helpful assistant."
}, {
"type": "text",
"text": "Only return the answer when you are confident."
}],
}, {
"role":
"user",
"content": [{
"type": "text",
"text": "What is 2+2?"
}],
}, {
"role":
"assistant",
"content": [
{
"type": "text",
"text": "Let me think about it."
},
{
"type": "text",
"text": "2+2 = 4"
},
{
"type": "text",
"text": "The answer is 4."
},
]
}]
expected_conversation = [
{
"role": "system",
"content": [
{"type": "text", "text": "You are a helpful assistant."},
{
"type": "text",
"text": "Only return the answer when you are confident.",
},
],
},
{
"role": "user",
"content": [{"type": "text", "text": "What is 2+2?"}],
},
{
"role": "assistant",
"content": [
{"type": "text", "text": "Let me think about it."},
{"type": "text", "text": "2+2 = 4"},
{"type": "text", "text": "The answer is 4."},
],
},
]
assert conversation_with_thinking == expected_conversation
def test_apply_mistral_chat_template_thinking_chunk():
# Moved import here to avoid yapf and isort conflicts
from vllm.entrypoints.chat_utils import apply_mistral_chat_template
messages = [{
"role":
"system",
"content": [{
"type": "text",
"text": "You are a helpful assistant."
}, {
"type":
"thinking",
"closed":
True,
"thinking":
"Only return the answer when you are confident."
}]
}, {
"role": "user",
"content": "What is 2+2?"
}, {
"role":
"assistant",
"content": [{
"type": "text",
"text": "Let me think about it."
}, {
"type": "thinking",
"closed": True,
"thinking": "2+2 = 4"
}, {
"type": "text",
"text": "The answer is 4.",
}],
}, {
"role": "user",
"content": "Thanks, what is 3+3?"
}]
messages = [
{
"role": "system",
"content": [
{"type": "text", "text": "You are a helpful assistant."},
{
"type": "thinking",
"closed": True,
"thinking": "Only return the answer when you are confident.",
},
],
},
{"role": "user", "content": "What is 2+2?"},
{
"role": "assistant",
"content": [
{"type": "text", "text": "Let me think about it."},
{"type": "thinking", "closed": True, "thinking": "2+2 = 4"},
{
"type": "text",
"text": "The answer is 4.",
},
],
},
{"role": "user", "content": "Thanks, what is 3+3?"},
]
# TODO(Julien): upon model release change to a tokenizer already configured.
# =================================================================
mistral_tokenizer = MistralTokenizer.from_pretrained(
"mistralai/Devstral-Small-2507")
"mistralai/Devstral-Small-2507"
)
assert isinstance(mistral_tokenizer.tokenizer, Tekkenizer)
# Add think special tokens to the tokenizer
mistral_tokenizer.tokenizer._all_special_tokens[35] = SpecialTokenInfo(
rank=35, is_control=True, token_str=SpecialTokens.begin_think.value)
rank=35, is_control=True, token_str=SpecialTokens.begin_think.value
)
mistral_tokenizer.tokenizer._all_special_tokens[36] = SpecialTokenInfo(
rank=36, is_control=True, token_str=SpecialTokens.end_think.value)
rank=36, is_control=True, token_str=SpecialTokens.end_think.value
)
mistral_tokenizer.tokenizer._special_tokens_reverse_vocab = {
k: v
for k, v in
mistral_tokenizer.tokenizer._special_tokens_reverse_vocab.items()
for k, v in mistral_tokenizer.tokenizer._special_tokens_reverse_vocab.items()
if v not in {35, 36}
}
mistral_tokenizer.tokenizer._special_tokens_reverse_vocab[
SpecialTokens.begin_think.value] = 35
SpecialTokens.begin_think.value
] = 35
mistral_tokenizer.tokenizer._special_tokens_reverse_vocab[
SpecialTokens.end_think.value] = 36
SpecialTokens.end_think.value
] = 36
mistral_tokenizer.instruct.BEGIN_THINK = 35
mistral_tokenizer.instruct.END_THINK = 36
# =================================================================
tokens_ids = apply_mistral_chat_template(mistral_tokenizer,
messages,
chat_template=None,
tools=None)
tokens_ids = apply_mistral_chat_template(
mistral_tokenizer, messages, chat_template=None, tools=None
)
string_tokens = mistral_tokenizer.mistral.decode(
tokens_ids, special_token_policy=SpecialTokenPolicy.KEEP)
tokens_ids, special_token_policy=SpecialTokenPolicy.KEEP
)
expected_tokens = (
r"<s>[SYSTEM_PROMPT]You are a helpful assistant.[THINK]Only return the"
r" answer when you are confident.[/THINK][/SYSTEM_PROMPT]"
r"[INST]What is 2+2?[/INST]"
r"Let me think about it.[THINK]2+2 = 4[/THINK]The answer is 4.</s>"
r"[INST]Thanks, what is 3+3?[/INST]")
r"[INST]Thanks, what is 3+3?[/INST]"
)
assert string_tokens == expected_tokens
@@ -2192,37 +2172,32 @@ def test_parse_chat_messages_single_empty_audio_with_uuid(
):
audio_uuid = "abcd"
conversation, mm_data, mm_uuids = parse_chat_messages(
[{
"role":
"user",
"content": [
{
"type": "input_audio",
"input_audio": {},
"uuid": audio_uuid,
},
{
"type": "text",
"text": "What does the audio say?"
},
],
}],
[
{
"role": "user",
"content": [
{
"type": "input_audio",
"input_audio": {},
"uuid": audio_uuid,
},
{"type": "text", "text": "What does the audio say?"},
],
}
],
qwen2_audio_model_config,
qwen2_audio_tokenizer,
content_format="string",
)
assert conversation == [{
"role":
"user",
"content":
"Audio 1: <|audio_bos|><|AUDIO|><|audio_eos|>\nWhat does the audio say?"
}]
assert conversation == [
{
"role": "user",
"content": "Audio 1: <|audio_bos|><|AUDIO|><|audio_eos|>\nWhat does the audio say?",
}
]
_assert_mm_data_inputs(mm_data, {"audio": 1})
_assert_mm_uuids(mm_uuids,
1,
modality="audio",
expected_uuids=[audio_uuid])
_assert_mm_uuids(mm_uuids, 1, modality="audio", expected_uuids=[audio_uuid])
@pytest.mark.asyncio
@@ -2232,34 +2207,29 @@ async def test_parse_chat_messages_single_empty_audio_with_uuid_async(
):
audio_uuid = "abcd"
conversation, mm_future, mm_uuids = parse_chat_messages_futures(
[{
"role":
"user",
"content": [
{
"type": "input_audio",
"input_audio": {},
"uuid": audio_uuid,
},
{
"type": "text",
"text": "What does the audio say?"
},
],
}],
[
{
"role": "user",
"content": [
{
"type": "input_audio",
"input_audio": {},
"uuid": audio_uuid,
},
{"type": "text", "text": "What does the audio say?"},
],
}
],
qwen2_audio_model_config,
qwen2_audio_tokenizer,
content_format="string",
)
assert conversation == [{
"role":
"user",
"content":
"Audio 1: <|audio_bos|><|AUDIO|><|audio_eos|>\nWhat does the audio say?"
}]
assert conversation == [
{
"role": "user",
"content": "Audio 1: <|audio_bos|><|AUDIO|><|audio_eos|>\nWhat does the audio say?",
}
]
_assert_mm_data_inputs(await mm_future, {"audio": 1})
_assert_mm_uuids(mm_uuids,
1,
modality="audio",
expected_uuids=[audio_uuid])
_assert_mm_uuids(mm_uuids, 1, modality="audio", expected_uuids=[audio_uuid])