biondizzle/vllm
1
0
Fork 0
Code Issues Pull Requests Actions 2 Packages Projects Releases Wiki Activity

Convert formatting to use ruff instead of yapf + isort (#26247)

Browse Source 
Signed-off-by: Harry Mellor <19981378+hmellor@users.noreply.github.com>
This commit is contained in:
Harry Mellor
2025-10-05 15:06:22 +01:00
committed by GitHub
parent 17edd8a807
commit d6953beb91
1508 changed files with 115244 additions and 94146 deletions
Download Patch File Download Diff File Expand all files Collapse all files

88
tests/entrypoints/llm/test_chat.py
View File

@@ -14,9 +14,7 @@ from ..openai.test_vision import TEST_IMAGE_ASSETS
def text_llm():
# pytest caches the fixture so we use weakref.proxy to
# enable garbage collection
llm = LLM(model="meta-llama/Llama-3.2-1B-Instruct",
enforce_eager=True,
seed=0)
llm = LLM(model="meta-llama/Llama-3.2-1B-Instruct", enforce_eager=True, seed=0)
yield weakref.proxy(llm)
@@ -28,14 +26,8 @@ def text_llm():
def test_chat(text_llm):
prompt1 = "Explain the concept of entropy."
messages = [
{
"role": "system",
"content": "You are a helpful assistant"
},
{
"role": "user",
"content": prompt1
},
{"role": "system", "content": "You are a helpful assistant"},
{"role": "user", "content": prompt1},
]
outputs = text_llm.chat(messages)
assert len(outputs) == 1
@@ -46,25 +38,13 @@ def test_multi_chat(text_llm):
prompt2 = "Explain what among us is."
conversation1 = [
{
"role": "system",
"content": "You are a helpful assistant"
},
{
"role": "user",
"content": prompt1
},
{"role": "system", "content": "You are a helpful assistant"},
{"role": "user", "content": prompt1},
]
conversation2 = [
{
"role": "system",
"content": "You are a helpful assistant"
},
{
"role": "user",
"content": prompt2
},
{"role": "system", "content": "You are a helpful assistant"},
{"role": "user", "content": prompt2},
]
messages = [conversation1, conversation2]
@@ -94,26 +74,22 @@ def vision_llm():
cleanup_dist_env_and_memory()
@pytest.mark.parametrize("image_urls",
[[TEST_IMAGE_ASSETS[0], TEST_IMAGE_ASSETS[1]]],
indirect=True)
@pytest.mark.parametrize(
"image_urls", [[TEST_IMAGE_ASSETS[0], TEST_IMAGE_ASSETS[1]]], indirect=True
)
def test_chat_multi_image(vision_llm, image_urls: list[str]):
messages = [{
"role":
"user",
"content": [
*({
"type": "image_url",
"image_url": {
"url": image_url
}
} for image_url in image_urls),
{
"type": "text",
"text": "What's in this image?"
},
],
}]
messages = [
{
"role": "user",
"content": [
*(
{"type": "image_url", "image_url": {"url": image_url}}
for image_url in image_urls
),
{"type": "text", "text": "What's in this image?"},
],
}
]
outputs = vision_llm.chat(messages)
assert len(outputs) >= 0
@@ -124,14 +100,8 @@ def test_llm_chat_tokenization_no_double_bos(text_llm):
Check we get a single BOS token for llama chat.
"""
messages = [
{
"role": "system",
"content": "You are a helpful assistant"
},
{
"role": "user",
"content": "Hello!"
},
{"role": "system", "content": "You are a helpful assistant"},
{"role": "user", "content": "Hello!"},
]
outputs = text_llm.chat(messages)
assert len(outputs) == 1
@@ -167,14 +137,8 @@ def thinking_llm():
@pytest.mark.parametrize("enable_thinking", [True, False])
def test_chat_extra_kwargs(thinking_llm, enable_thinking):
messages = [
{
"role": "system",
"content": "You are a helpful assistant"
},
{
"role": "user",
"content": "What is 1+1?"
},
{"role": "system", "content": "You are a helpful assistant"},
{"role": "user", "content": "What is 1+1?"},
]
outputs = thinking_llm.chat(