[ci] [windows] Route choco installs through cluster-local Nexus mirror (#24836)

## Summary
Windows CI (`ci_windows_x64_msvc`) sporadically fails at the
tool-install steps because `choco install` hits the public
`community.chocolatey.org` feed, which intermittently returns `503
(Service Unavailable)` (rate limiting / transient outages). See #24826.

This routes choco through the cluster-local Nexus proxy group
(`choco-group`) via its Kubernetes service FQDN, mirroring the approach
already used in
[ROCm/TheRock](https://github.com/ROCm/TheRock/commit/dd781140d887e35b6e3c84cc059e4c0f8d37068a).
The proxy only mirrors package *metadata*; binaries still download from
the upstream mirror named in the cached nuspec, which is enough to avoid
the community-feed 503s.

## Change
In `.github/workflows/ci_windows_x64_msvc.yml`, before installing
packages:
```yaml
choco source disable -n=chocolatey
choco source add -n=internal -s http://nexus-service.nexus-ns.svc.cluster.local:8081/repository/choco-group/ --priority=1
```

## Verification
Dispatched on a test branch on an `azure-windows-scale` runner (run
[32531536526](https://github.com/iree-org/iree/actions/runs/32531536526)).
Both choco steps completed with `success`, fetching every package
through the mirror with no 503s:
```
Disabled chocolatey
Added internal - http://nexus-service.nexus-ns.svc.cluster.local:8081/repository/choco-group/ (Priority 1)
Downloading package from source 'http://nexus-service.nexus-ns.svc.cluster.local:8081/repository/choco-group/'
Chocolatey installed 1/1 packages.   # ccache
Chocolatey installed 1/1 packages.   # sccache
Chocolatey installed 0/1 packages.   # cmake already present on image (no-op, step still succeeded)
Chocolatey installed 1/1 packages.   # ninja 1.12.1
```
This also confirms the `azure-windows-scale` runners are in the same
cluster and can resolve the Nexus service FQDN. The build step itself
was cancelled after the install steps passed, since only the choco
behavior was under test.

Closes #24826

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

Signed-off-by: Justin Chen <justchen@amd.com>
Signed-off-by: Artem Gindinson <gindinson@roofline.ai>
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
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  8. llvm-external-projects/
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  25. AUTHORS
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  30. CONTRIBUTING.md
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  32. LICENSE
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  36. RELEASING.md
README.md

IREE: Intermediate Representation Execution Environment

IREE (Intermediate Representation Execution Environment, pronounced as “eerie”) is an MLIR-based end-to-end compiler and runtime that lowers Machine Learning (ML) models to a unified IR that scales up to meet the needs of the datacenter and down to satisfy the constraints and special considerations of mobile and edge deployments.

See our website for project details, user guides, and instructions on building from source.

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DateTitleRecordingSlides
2025-06-10Data-Tiling in IREE: Achieving High Performance Through Compiler Design (AsiaLLVM)recordingslides
2025-05-17Introduction to GPU architecture and IREE's GPU CodeGen Pipelinerecordingslides
2025-02-12The Long Tail of AI: SPIR-V in IREE and MLIR (Vulkanised)recordingslides
2024-10-01Unveiling the Inner Workings of IREE: An MLIR-Based Compiler for Diverse Hardwarerecording
2021-06-09IREE Runtime Design Tech Talkrecordingslides
2020-08-20IREE CodeGen (MLIR Open Design Meeting)recordingslides
2020-03-18Interactive HAL IR Walkthroughrecording
2020-01-31End-to-end MLIR Workflow in IREE (MLIR Open Design Meeting)recordingslides

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IREE is licensed under the terms of the Apache 2.0 License with LLVM Exceptions. See LICENSE for more information.