[Model] Support multiple images for qwen-vl

[alex-jw-brooks]

This PR finishes exposing multi-image support for Qwen-VL (not Qwen2) as follow-up to #8029.

Multi-image offline inference example (.generate)

from vllm import LLM, SamplingParams
from vllm.multimodal.utils import fetch_image

question = "Can you compare these images?"
image_urls = [
    "https://upload.wikimedia.org/wikipedia/commons/d/da/2015_Kaczka_krzy%C5%BCowka_w_wodzie_%28samiec%29.jpg",
    "https://upload.wikimedia.org/wikipedia/commons/7/77/002_The_lion_king_Snyggve_in_the_Serengeti_National_Park_Photo_by_Giles_Laurent.jpg",
]

llm = LLM(
    model="Qwen/Qwen-VL-Chat",
    trust_remote_code=True,
    limit_mm_per_prompt={"image": len(image_urls)},
    dtype="half"
)


get_img_prompt = lambda img_num: f"Picture {img_num}: <img></img>\n"
placeholders = "".join(get_img_prompt(i) for i, _ in enumerate(image_urls, start=1))
prompt = f"<|im_start|>user\n{placeholders}{question}\n<|im_end|>\n<|im_start|>assistant\n"

sampling_params = SamplingParams(temperature=0.2, max_tokens=64)

outputs = llm.generate({
        "prompt": prompt,
        "multi_modal_data": {
            "image": [fetch_image(url) for url in image_urls]
        },
    },
    sampling_params=sampling_params
)

for o in outputs:
    generated_text = o.outputs[0].text
    print(generated_text)

The two images shown are different. The first image is of a male mallard duck swimming in a body of water, while the second image is of a male lion resting in the tall grass. The two images are unrelated and cannot be compared.<|im_end|>

Chat example:

Image numbering is already handled properly in the chat utils, so no extra changes needed there.

Server:

python -m vllm.entrypoints.openai.api_server \
    --device cuda \
    --model Qwen/Qwen-VL-Chat \
    --api-key token-abc123 \
    --chat-template examples/template_chatml.jinja \
    --tokenizer Qwen/Qwen-VL-Chat \
    --dtype=half \
    --limit-mm-per-prompt image=2 \
    --trust-remote-code &

Client:

from openai import OpenAI

client = OpenAI(base_url="http://localhost:8000/v1", api_key="token-abc123")

completion = client.chat.completions.create(
  model="Qwen/Qwen-VL-Chat",
  messages=[
    {
        "role": "user", "content": [
          {"type": "image_url", "image_url": {"url": "https://upload.wikimedia.org/wikipedia/commons/d/da/2015_Kaczka_krzy%C5%BCowka_w_wodzie_%28samiec%29.jpg"}},
          {"type": "image_url", "image_url": {"url": "https://upload.wikimedia.org/wikipedia/commons/7/77/002_The_lion_king_Snyggve_in_the_Serengeti_National_Park_Photo_by_Giles_Laurent.jpg"}},
          {"type": "text", "text": "Can you compare these images?"},
        ]
    }
  ]
)

print(completion.choices[0].message)

ChatCompletionMessage(content='The images shown are different and cannot be compared. Image 1 is a duck swimming in water, and Image 2 is a lion lying in the grass. They are completely different in both content and subject.<|im_end|>\n', refusal=None, role='assistant', function_call=None, tool_calls=[])

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[github-actions]

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[alex-jw-brooks]

FYI @DarkLight1337 since you reviewed the main PR for qwen-vl! 🙂

[DarkLight1337]

Could you add a test to verify the behavior of this model?

After #8201 is merged, can you update the example script for multi-image input to include this model as well?

[alex-jw-brooks]

Yup, definitely! I had recently started working on some stuff around the image processor to allow kwargs to be passed through as overrides for stuff pulled from the HF config - but before that, I was planning to open a PR to add some common test utils for building an InputContext and some dummy data for different multimodal models to test correctness of custom input mappers / processors, with tests for a few models as examples. I think it would be nice to have fast tests that only test the preprocessing correctness that can run without loading the full models.

I had started writing those tests for this model already - do you have any thoughts on adding those here to test this PR? Happy to do that and then submit a follow-up refactoring common stuff out + adding some tests for other models, or if you think it would be better, just adding an end-to-end test here for now and adding preprocessing tests in a separate PR

[DarkLight1337]

I had started writing those tests for this model already - do you have any thoughts on adding those here to test this PR?

Sure!

Happy to do that and then submit a follow-up refactoring common stuff out + adding some tests for other models, or if you think it would be better, just adding an end-to-end test here for now and adding preprocessing tests in a separate PR

I'm currently working on #7820, perhaps it would be best to refactor the tests after that to avoid introducing a bunch of merge conflicts.

[alex-jw-brooks]

Perfect, I'll add them to the test file to this model for now, and wait until after that's merged before making stuff common and adding similar tests for some other models 😄

[DarkLight1337]

Can we have an end-to-end correctness test for multi-image input just like the other models?

Otherwise LGTM!

[DarkLight1337]

LGTM, thanks for your help again!

[DarkLight1337]

Can you merge main into this branch to fix the CI failure?

[alex-jw-brooks]

No problem, thanks a lot for the quick reviews! Just did 🙂

Seems like there are still some failures, but they're unrelated (for marlin moe)

[DarkLight1337]

Sorry I forgot about this, Qwen2-VL has just been released so you have to update the examples file.

[alex-jw-brooks]

No worries at all, that's great news! Just rebased 😄