[Model][VLM] Support Keye-VL-8B-Preview

[Kwai-Keye]

Purpose

• Support Keye-VL-8B-Preview

Example Serving Command

• The model can be served with

vllm serve \
    Kwai-Keye/Keye-VL-8B-Preview \
    --tensor-parallel-size 8 \
    --enable-prefix-caching \
    --gpu-memory-utilization 0.8 \
    --host 0.0.0.0 \
    --port 8001 \
    --trust-remote-code

Thank you for your time on reviewing this PR :)

[github-actions]

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[gemini-code-assist]

Summary of Changes

Hello @Kwai-Keye, I'm Gemini Code Assist¹! I'm currently reviewing this pull request and will post my feedback shortly. In the meantime, here's a summary to help you and other reviewers quickly get up to speed!

This pull request introduces full support for the Keye-VL-8B-Preview model within vLLM. It includes the necessary components for processing multimodal inputs (images and videos), integrating a vision encoder with the language model, and registering the new model for seamless deployment and serving.

Highlights

• New Model Support: Adds comprehensive support for the Keye-VL-8B-Preview Vision-Language Model (VLM), enabling it to be served by vLLM.
• Multimodal Processing: Implements a dedicated KeyeProcessor and related multimodal data handling components to correctly process image and video inputs for the Keye model, including tokenization and embedding integration.
• Vision Backbone Integration: Integrates a Siglip-based vision encoder and a projector module to extract and transform visual features, which are then merged with the language model's embeddings.
• Model Registration: Registers the KeyeForConditionalGeneration model within vLLM's internal registry, making it discoverable and loadable via its model name.
• Token Handling: Updates chat_utils.py to ensure the Keye model correctly uses Qwen-style vision tokens (<|vision_start|><|image_pad|><|vision_end|>, etc.) for multimodal inputs.

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[gemini-code-assist]

Code Review

The pull request introduces support for the Keye-VL-8B-Preview model, including its vision and multimodal processing components. The changes involve adding new model definitions and integrating them into the existing vLLM framework. The review identifies several areas for improvement related to code clarity, consistency, error handling, and adherence to best practices.

[DarkLight1337]

Thanks for adding this model. Left a few initial comments

[DarkLight1337]

LGTM now (I assume you have tested the examples already)

[Isotr0py]

LGTM now! Would be good if we can add SDPA support for ViT attention in a following PR.

[mergify]

This pull request has merge conflicts that must be resolved before it can be
merged. Please rebase the PR, @Kwai-Keye.

https://docs.github.com/en/pull-requests/collaborating-with-pull-requests/working-with-forks/syncing-a-fork

[Kwai-Keye]

LGTM now! Would be good if we can add SDPA support for ViT attention in a following PR.

Considering that xformers is a default dependency listed in requirements/cuda.txt, we've prioritized supporting the xformers backend first~ Kwai-Keye@475d004