From 6fd45e7b8a3dc216875428835036a9008cdc0fe3 Mon Sep 17 00:00:00 2001 From: Cyrus Leung Date: Tue, 26 Aug 2025 10:34:12 +0800 Subject: [PATCH] [CI/Build] Use vLLM client's user agent to fetch images (#23561) Signed-off-by: DarkLight1337 --- tests/entrypoints/openai/test_vision.py | 6 ++---- tests/entrypoints/openai/test_vision_embedding.py | 3 +-- 2 files changed, 3 insertions(+), 6 deletions(-) diff --git a/tests/entrypoints/openai/test_vision.py b/tests/entrypoints/openai/test_vision.py index 8259a81d7b6a1..eaa6c2c163af1 100644 --- a/tests/entrypoints/openai/test_vision.py +++ b/tests/entrypoints/openai/test_vision.py @@ -6,8 +6,6 @@ import json import openai import pytest import pytest_asyncio -import requests -from PIL import Image from transformers import AutoProcessor 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 intersect", + "This image shows a Venn diagram with three intersect", ], [ "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", "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( messages, tokenize=False, add_generation_prompt=True) diff --git a/tests/entrypoints/openai/test_vision_embedding.py b/tests/entrypoints/openai/test_vision_embedding.py index 4e6a21058658b..d3cc2fac6af57 100644 --- a/tests/entrypoints/openai/test_vision_embedding.py +++ b/tests/entrypoints/openai/test_vision_embedding.py @@ -5,7 +5,6 @@ import json import pytest import requests -from PIL import Image from transformers import AutoProcessor from vllm.entrypoints.openai.protocol import EmbeddingResponse @@ -64,7 +63,7 @@ def get_hf_prompt_tokens(model_name, content, image_url): placeholder = "<|image_1|> " 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") return inputs.input_ids.shape[1]