Add vLLM v0.18.1 source tree with KV transfer abort fix
third_party/vllm/ now tracked in git for direct patch management.
Based on vLLM v0.18.1 release with one patch applied:
vllm/v1/core/sched/scheduler.py:
Replace fatal assert with graceful skip when KV transfer callback
arrives for an already-aborted request during PD disaggregated serving.
Future vLLM modifications should be made directly in third_party/vllm/
and committed normally. The patches/ directory is kept as documentation
of what changed from upstream.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
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42
third_party/vllm/docs/deployment/frameworks/open-webui.md
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third_party/vllm/docs/deployment/frameworks/open-webui.md
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# Open WebUI
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[Open WebUI](https://github.com/open-webui/open-webui) is an extensible, feature-rich,
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and user-friendly self-hosted AI platform designed to operate entirely offline.
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It supports various LLM runners like Ollama and OpenAI-compatible APIs,
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with built-in RAG capabilities, making it a powerful AI deployment solution.
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To get started with Open WebUI using vLLM, follow these steps:
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1. Install the [Docker](https://docs.docker.com/engine/install/).
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2. Start the vLLM server with a supported chat completion model:
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```console
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vllm serve Qwen/Qwen3-0.6B-Chat
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```
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!!! note
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When starting the vLLM server, be sure to specify the host and port using the `--host` and `--port` flags.
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For example:
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```console
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vllm serve <model> --host 0.0.0.0 --port 8000
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```
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3. Start the Open WebUI Docker container:
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```console
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docker run -d \
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--name open-webui \
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-p 3000:8080 \
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-v open-webui:/app/backend/data \
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-e OPENAI_API_BASE_URL=http://0.0.0.0:8000/v1 \
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--restart always \
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ghcr.io/open-webui/open-webui:main
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```
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4. Open it in the browser: <http://open-webui-host:3000/>
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At the top of the page, you should see the model `Qwen/Qwen3-0.6B-Chat`.
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