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

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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 15:06:22 +01:00
committed by GitHub
parent 17edd8a807
commit d6953beb91
1508 changed files with 115244 additions and 94146 deletions
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48
tests/entrypoints/pooling/openai/test_vision_embedding.py
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@@ -50,16 +50,15 @@ def server():
@pytest.fixture(scope="session")
def base64_encoded_image(local_asset_server) -> dict[str, str]:
return {
image_url:
encode_image_base64(local_asset_server.get_image_asset(image_url))
image_url: encode_image_base64(local_asset_server.get_image_asset(image_url))
for image_url in TEST_IMAGE_ASSETS
}
def get_hf_prompt_tokens(model_name, content, image_url):
processor = AutoProcessor.from_pretrained(model_name,
trust_remote_code=True,
num_crops=4)
processor = AutoProcessor.from_pretrained(
model_name, trust_remote_code=True, num_crops=4
)
placeholder = "<|image_1|> "
prompt = f"{placeholder}{content}"
@@ -71,39 +70,28 @@ def get_hf_prompt_tokens(model_name, content, image_url):
@pytest.mark.asyncio
@pytest.mark.parametrize("model_name", [MODEL_NAME])
@pytest.mark.parametrize("image_url", TEST_IMAGE_ASSETS, indirect=True)
async def test_image_embedding(server: RemoteOpenAIServer, model_name: str,
image_url: str):
async def test_image_embedding(
server: RemoteOpenAIServer, model_name: str, image_url: str
):
content_text = "Represent the given image."
messages = [{
"role":
"user",
"content": [
{
"type": "image_url",
"image_url": {
"url": image_url
}
},
{
"type": "text",
"text": content_text
},
],
}]
messages = [
{
"role": "user",
"content": [
{"type": "image_url", "image_url": {"url": image_url}},
{"type": "text", "text": content_text},
],
}
]
response = requests.post(
server.url_for("v1/embeddings"),
json={
"model": model_name,
"messages": messages,
"encoding_format": "float"
},
json={"model": model_name, "messages": messages, "encoding_format": "float"},
)
response.raise_for_status()
embeddings = EmbeddingResponse.model_validate(response.json())
hf_prompt_tokens = get_hf_prompt_tokens(model_name, content_text,
image_url)
hf_prompt_tokens = get_hf_prompt_tokens(model_name, content_text, image_url)
assert embeddings.id is not None
assert len(embeddings.data) == 1