build(deps): bump vllm from 0.5.3.post1 to 0.5.5 in /requirements
State: closed | Pull request: yes
Labels: name: stale

name: dependencies

Bumps [vllm](https://github.com/vllm-project/vllm) from 0.5.3.post1 to 0.5.5.
<details>
<summary>Release notes</summary>
<p><em>Sourced from <a href="https://github.com/vllm-project/vllm/releases">vllm's releases</a>.</em></p>
<blockquote>
<h2>v0.5.5</h2>
<h2>Highlights</h2>
<h3>Performance Update</h3>
<ul>
<li>We introduced a new mode that schedule multiple GPU steps in advance, reducing CPU overhead (<a href="https://redirect.github.com/vllm-project/vllm/issues/7000">#7000</a>, <a href="https://redirect.github.com/vllm-project/vllm/issues/7387">#7387</a>, <a href="https://redirect.github.com/vllm-project/vllm/issues/7452">#7452</a>, <a href="https://redirect.github.com/vllm-project/vllm/issues/7703">#7703</a>). Initial result shows 20% improvements in QPS for a single GPU running 8B and 30B models. You can set <code>--num-scheduler-steps 8</code> as a parameter to the API server (via <code>vllm serve</code>) or <code>AsyncLLMEngine</code>. We are working on expanding the coverage to <code>LLM</code> class and aiming to turning it on by default</li>
<li>Various enhancements:
<ul>
<li>Use flashinfer sampling kernel when avaiable, leading to 7% decoding throughput speedup (<a href="https://redirect.github.com/vllm-project/vllm/issues/7137">#7137</a>)</li>
<li>Reduce Python allocations, leading to 24% throughput speedup (<a href="https://redirect.github.com/vllm-project/vllm/issues/7162">#7162</a>, 7364)</li>
<li>Improvements to the zeromq based decoupled frontend (<a href="https://redirect.github.com/vllm-project/vllm/issues/7570">#7570</a>, <a href="https://redirect.github.com/vllm-project/vllm/issues/7716">#7716</a>, <a href="https://redirect.github.com/vllm-project/vllm/issues/7484">#7484</a>)</li>
</ul>
</li>
</ul>
<h3>Model Support</h3>
<ul>
<li>Support Jamba 1.5 (<a href="https://redirect.github.com/vllm-project/vllm/issues/7415">#7415</a>, <a href="https://redirect.github.com/vllm-project/vllm/issues/7601">#7601</a>, <a href="https://redirect.github.com/vllm-project/vllm/issues/6739">#6739</a>)</li>
<li>Support for the first audio model <code>UltravoxModel</code> (<a href="https://redirect.github.com/vllm-project/vllm/issues/7615">#7615</a>, <a href="https://redirect.github.com/vllm-project/vllm/issues/7446">#7446</a>)</li>
<li>Improvements to vision models:
<ul>
<li>Support image embeddings as input (<a href="https://redirect.github.com/vllm-project/vllm/issues/6613">#6613</a>)</li>
<li>Support SigLIP encoder and alternative decoders for LLaVA models (<a href="https://redirect.github.com/vllm-project/vllm/issues/7153">#7153</a>)</li>
</ul>
</li>
<li>Support loading GGUF model (<a href="https://redirect.github.com/vllm-project/vllm/issues/5191">#5191</a>) with tensor parallelism (<a href="https://redirect.github.com/vllm-project/vllm/issues/7520">#7520</a>)</li>
<li>Progress in encoder decoder models: support for serving encoder/decoder models (<a href="https://redirect.github.com/vllm-project/vllm/issues/7258">#7258</a>), and architecture for cross-attention (<a href="https://redirect.github.com/vllm-project/vllm/issues/4942">#4942</a>)</li>
</ul>
<h3>Hardware Support</h3>
<ul>
<li>AMD: Add fp8 Linear Layer for rocm (<a href="https://redirect.github.com/vllm-project/vllm/issues/7210">#7210</a>)</li>
<li>Enhancements to TPU support: load time W8A16 quantization (<a href="https://redirect.github.com/vllm-project/vllm/issues/7005">#7005</a>), optimized rope (<a href="https://redirect.github.com/vllm-project/vllm/issues/7635">#7635</a>), and support multi-host inference (<a href="https://redirect.github.com/vllm-project/vllm/issues/7457">#7457</a>).</li>
<li>Intel: various refactoring for worker, executor, and model runner (<a href="https://redirect.github.com/vllm-project/vllm/issues/7686">#7686</a>, <a href="https://redirect.github.com/vllm-project/vllm/issues/7712">#7712</a>)</li>
</ul>
<h3>Others</h3>
<ul>
<li>Optimize prefix caching performance (<a href="https://redirect.github.com/vllm-project/vllm/issues/7193">#7193</a>)</li>
<li>Speculative decoding
<ul>
<li>Use target model max length as default for draft model (<a href="https://redirect.github.com/vllm-project/vllm/issues/7706">#7706</a>)</li>
<li>EAGLE Implementation with Top-1 proposer (<a href="https://redirect.github.com/vllm-project/vllm/issues/6830">#6830</a>)</li>
</ul>
</li>
<li>Entrypoints
<ul>
<li>A new <code>chat</code> method in the <code>LLM</code> class (<a href="https://redirect.github.com/vllm-project/vllm/issues/5049">#5049</a>)</li>
<li>Support embeddings in the run_batch API (<a href="https://redirect.github.com/vllm-project/vllm/issues/7132">#7132</a>)</li>
<li>Support <code>prompt_logprobs</code> in Chat Completion (<a href="https://redirect.github.com/vllm-project/vllm/issues/7453">#7453</a>)</li>
</ul>
</li>
<li>Quantizations
<ul>
<li>Expand MoE weight loading + Add Fused Marlin MoE Kernel (<a href="https://redirect.github.com/vllm-project/vllm/issues/7527">#7527</a>)</li>
<li>Machete - Hopper Optimized Mixed Precision Linear Kernel  (<a href="https://redirect.github.com/vllm-project/vllm/issues/7174">#7174</a>)</li>
</ul>
</li>
<li><code>torch.compile</code>: register custom ops for kernels (<a href="https://redirect.github.com/vllm-project/vllm/issues/7591">#7591</a>, <a href="https://redirect.github.com/vllm-project/vllm/issues/7594">#7594</a>, <a href="https://redirect.github.com/vllm-project/vllm/issues/7536">#7536</a>)</li>
</ul>
<h2>What's Changed</h2>
<ul>
<li>[ci][frontend] deduplicate tests by <a href="https://github.com/youkaichao"><code>@​youkaichao</code></a> in <a href="https://redirect.github.com/vllm-project/vllm/pull/7101">vllm-project/vllm#7101</a></li>
<li>[Doc] [SpecDecode] Update MLPSpeculator documentation by <a href="https://github.com/tdoublep"><code>@​tdoublep</code></a> in <a href="https://redirect.github.com/vllm-project/vllm/pull/7100">vllm-project/vllm#7100</a></li>
<li>[Bugfix] Specify device when loading LoRA and embedding tensors by <a href="https://github.com/jischein"><code>@​jischein</code></a> in <a href="https://redirect.github.com/vllm-project/vllm/pull/7129">vllm-project/vllm#7129</a></li>
<li>[MISC] Use non-blocking transfer in prepare_input by <a href="https://github.com/comaniac"><code>@​comaniac</code></a> in <a href="https://redirect.github.com/vllm-project/vllm/pull/7172">vllm-project/vllm#7172</a></li>
<li>[Core] Support loading GGUF model by <a href="https://github.com/Isotr0py"><code>@​Isotr0py</code></a> in <a href="https://redirect.github.com/vllm-project/vllm/pull/5191">vllm-project/vllm#5191</a></li>
<li>[Build] Add initial conditional testing spec by <a href="https://github.com/simon-mo"><code>@​simon-mo</code></a> in <a href="https://redirect.github.com/vllm-project/vllm/pull/6841">vllm-project/vllm#6841</a></li>
<li>[LoRA] Relax LoRA condition by <a href="https://github.com/jeejeelee"><code>@​jeejeelee</code></a> in <a href="https://redirect.github.com/vllm-project/vllm/pull/7146">vllm-project/vllm#7146</a></li>
<li>[Model] Support SigLIP encoder and alternative decoders for LLaVA models by <a href="https://github.com/DarkLight1337"><code>@​DarkLight1337</code></a> in <a href="https://redirect.github.com/vllm-project/vllm/pull/7153">vllm-project/vllm#7153</a></li>
<li>[BugFix] Fix DeepSeek remote code by <a href="https://github.com/dsikka"><code>@​dsikka</code></a> in <a href="https://redirect.github.com/vllm-project/vllm/pull/7178">vllm-project/vllm#7178</a></li>
<li>[ BugFix ] Fix ZMQ when <code>VLLM_PORT</code> is set by <a href="https://github.com/robertgshaw2-neuralmagic"><code>@​robertgshaw2-neuralmagic</code></a> in <a href="https://redirect.github.com/vllm-project/vllm/pull/7205">vllm-project/vllm#7205</a></li>
<li>[Bugfix] add gguf dependency by <a href="https://github.com/kpapis"><code>@​kpapis</code></a> in <a href="https://redirect.github.com/vllm-project/vllm/pull/7198">vllm-project/vllm#7198</a></li>
</ul>
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</blockquote>
<p>... (truncated)</p>
</details>
<details>
<summary>Commits</summary>
<ul>
<li><a href="https://github.com/vllm-project/vllm/commit/09c7792610ada9f88bbf87d32b472dd44bf23cc2"><code>09c7792</code></a> Bump version to v0.5.5 (<a href="https://redirect.github.com/vllm-project/vllm/issues/7823">#7823</a>)</li>
<li><a href="https://github.com/vllm-project/vllm/commit/f1df5dbfd6782408228f39bdc0722fa465629f0f"><code>f1df5db</code></a> [Misc] Update <code>marlin</code> to use vLLMParameters (<a href="https://redirect.github.com/vllm-project/vllm/issues/7803">#7803</a>)</li>
<li><a href="https://github.com/vllm-project/vllm/commit/35ee2ad6b9a850a25d94cab582de19de5bca6fbd"><code>35ee2ad</code></a> [github][misc] promote asking llm first (<a href="https://redirect.github.com/vllm-project/vllm/issues/7809">#7809</a>)</li>
<li><a href="https://github.com/vllm-project/vllm/commit/e25fee57c2e69161bd261f5986dc5aeb198bbd42"><code>e25fee5</code></a> [BugFix] Fix server crash on empty prompt (<a href="https://redirect.github.com/vllm-project/vllm/issues/7746">#7746</a>)</li>
<li><a href="https://github.com/vllm-project/vllm/commit/faeddb565d6a528d1cbd169e90bc538178fc2828"><code>faeddb5</code></a> [misc] Add Torch profiler support for CPU-only devices (<a href="https://redirect.github.com/vllm-project/vllm/issues/7806">#7806</a>)</li>
<li><a href="https://github.com/vllm-project/vllm/commit/fc5ebbd1d3453461ea6e00a78faf87c41d1aa625"><code>fc5ebbd</code></a> [Hardware][Intel GPU] refactor xpu_model_runner for tp (<a href="https://redirect.github.com/vllm-project/vllm/issues/7712">#7712</a>)</li>
<li><a href="https://github.com/vllm-project/vllm/commit/c01a6cb23144b67b473e569a25b6f9725bc3f85b"><code>c01a6cb</code></a> [Ray backend] Better error when pg topology is bad. (<a href="https://redirect.github.com/vllm-project/vllm/issues/7584">#7584</a>)</li>
<li><a href="https://github.com/vllm-project/vllm/commit/b903e1ba7fca15f0dc49ab49a9ec8107f625c048"><code>b903e1b</code></a> [Frontend] error suppression cleanup (<a href="https://redirect.github.com/vllm-project/vllm/issues/7786">#7786</a>)</li>
<li><a href="https://github.com/vllm-project/vllm/commit/a15224642832acdddd757ddc95ed40a0ad1be33d"><code>a152246</code></a> [Misc] fix typo in triton import warning (<a href="https://redirect.github.com/vllm-project/vllm/issues/7794">#7794</a>)</li>
<li><a href="https://github.com/vllm-project/vllm/commit/666ad0aa16f0c656e48e58b4f31ffe956b484d3b"><code>666ad0a</code></a> [ci] Cleanup &amp; refactor Dockerfile to pass different Python versions and scca...</li>
<li>Additional commits viewable in <a href="https://github.com/vllm-project/vllm/compare/v0.5.3.post1...v0.5.5">compare view</a></li>
</ul>
</details>
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Any reason to bump vllm to 0.5.5? This will probably break all of our vllm export tests btw. Can you test the steps here? https://docs.nvidia.com/nemo-framework/user-guide/latest/deployment/llm/optimized/vllm.html 

This PR is stale because it has been open for 14 days with no activity. Remove stale label or comment or update or this will be closed in 7 days.

This PR was closed because it has been inactive for 7 days since being marked as stale.

OK, I won't notify you again about this release, but will get in touch when a new version is available. If you'd rather skip all updates until the next major or minor version, let me know by commenting `@dependabot ignore this major version` or `@dependabot ignore this minor version`.

If you change your mind, just re-open this PR and I'll resolve any conflicts on it.