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@GuanLuo GuanLuo commented Jul 22, 2025

Overview:

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  • closes GitHub issue: #xxx

Summary by CodeRabbit

  • New Features

    • Introduced a comprehensive multimodal example suite for distributed inference, including new processor, worker, and encoder components, as well as utilities for image loading, protocol handling, and model management.
    • Added RDMA-based data transfer framework and documentation for high-throughput GPU Direct RDMA between distributed workers.
    • Provided multiple launch scripts for aggregated and disaggregated multimodal serving pipelines, including support for Llama 4 models.
    • Included detailed documentation and usage instructions for deploying and testing multimodal pipelines on Kubernetes and local environments.
  • Documentation

    • Added extensive READMEs covering multimodal deployment scenarios, RDMA library usage, and step-by-step guides for launching and testing pipelines.
  • Chores

    • Updated Dockerfile and installation scripts to support building from a forked vLLM repository with configurable build arguments.
    • Re-exported the Endpoint class in the Python runtime bindings for streamlined access.

@GuanLuo GuanLuo changed the title Gluo/multi modal ux feat: multi-modal example with vLLM v1 and UX v2 Jul 24, 2025
@GuanLuo GuanLuo marked this pull request as ready for review July 24, 2025 02:24
@github-actions github-actions bot added the feat label Jul 24, 2025
@GuanLuo GuanLuo requested review from nnshah1 and whoisj as code owners July 24, 2025 02:24
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GuanLuo commented Aug 11, 2025

@grahamking yea I am reviving it, was blocked by vLLM merge and now we can proceed.
@atchernych can you approve this PR? Blocked by your request for change.

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GuanLuo commented Aug 12, 2025

/ok to test

@athreesh athreesh merged commit 9b87c89 into main Aug 12, 2025
11 of 12 checks passed
@athreesh athreesh deleted the gluo/multi-modal-ux branch August 12, 2025 23:55
hhzhang16 pushed a commit that referenced this pull request Aug 27, 2025
Co-authored-by: krishung5 <krish@nvidia.com>
Signed-off-by: Hannah Zhang <hannahz@nvidia.com>
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9 participants