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[CI/Build] Use vLLM client's user agent to fetch images (#23561)

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Signed-off-by: DarkLight1337 <tlleungac@connect.ust.hk>
This commit is contained in:
Cyrus Leung 2025-08-26 10:34:12 +08:00 committed by GitHub
parent 56dcf4e7e9
commit 6fd45e7b8a
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2 changed files with 3 additions and 6 deletions
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6
tests/entrypoints/openai/test_vision.py
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@ -6,8 +6,6 @@ import json
import openai import openai
import pytest import pytest
import pytest_asyncio import pytest_asyncio
import requests
from PIL import Image
from transformers import AutoProcessor from transformers import AutoProcessor
from vllm.multimodal.utils import encode_image_base64, fetch_image from vllm.multimodal.utils import encode_image_base64, fetch_image
@ -36,7 +34,7 @@ EXPECTED_MM_BEAM_SEARCH_RES = [
], ],
[ [
"The image shows a Venn diagram with three over", "The image shows a Venn diagram with three over",
"The image shows a Venn diagram with three intersect", "This image shows a Venn diagram with three intersect",
], ],
[ [
"This image displays a gradient of colors ranging from", "This image displays a gradient of colors ranging from",
@ -88,7 +86,7 @@ def get_hf_prompt_tokens(model_name, content, image_url):
"role": "user", "role": "user",
"content": f"{placeholder}{content}", "content": f"{placeholder}{content}",
}] }]
images = [Image.open(requests.get(image_url, stream=True).raw)] images = [fetch_image(image_url)]
prompt = processor.tokenizer.apply_chat_template( prompt = processor.tokenizer.apply_chat_template(
messages, tokenize=False, add_generation_prompt=True) messages, tokenize=False, add_generation_prompt=True)

3
tests/entrypoints/openai/test_vision_embedding.py
View File

@ -5,7 +5,6 @@ import json
import pytest import pytest
import requests import requests
from PIL import Image
from transformers import AutoProcessor from transformers import AutoProcessor
from vllm.entrypoints.openai.protocol import EmbeddingResponse from vllm.entrypoints.openai.protocol import EmbeddingResponse
@ -64,7 +63,7 @@ def get_hf_prompt_tokens(model_name, content, image_url):
placeholder = "<|image_1|> " placeholder = "<|image_1|> "
prompt = f"{placeholder}{content}" prompt = f"{placeholder}{content}"
images = [Image.open(requests.get(image_url, stream=True).raw)] images = [fetch_image(image_url)]
inputs = processor(prompt, images, return_tensors="pt") inputs = processor(prompt, images, return_tensors="pt")
return inputs.input_ids.shape[1] return inputs.input_ids.shape[1]