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❯ our pyproject sets index-strategy = unsafe-any-match so torch comes from the
  pytorch index. is that still right, and is it safe?
  ⎿  UserPromptSubmit says: Rema found 11 passages in 3 threads (uv#3137,
     uv#1497, uv#2775) and 1 doc (docs/concepts/indexes.md)

  Searched for 1 pattern, read 2 files (ctrl+o to expand)

⏺ No to both. The setting is outdated, and it's risky for this project in
  particular.

  It's out of date. ~~unsafe-any-match~~ is now just a deprecated alias for
  unsafe-first-match. uv only still accepts it for backwards compatibility
  [https://github.com/astral-sh/uv/issues/2775#issuecomment-2129535430]. uv now
  has three values: first-index (the default), unsafe-first-match and
  unsafe-best-match [uv-threads/docs/concepts/indexes.md].

  It's not safe, for two reasons:

  1. Dependency confusion. uv's default, first-index, exists to block attacks
     where someone publishes a package with the same name on a different index.
     The torchtriton compromise in December 2022 happened this way, through the
     PyTorch nightly index. The "unsafe-" strategies turn that protection off
     for every package, not just torch [uv-threads/docs/concepts/indexes.md].
  2. Old versions of ordinary packages. The PyTorch index also hosts outdated
     copies of common packages. With this strategy, uv picks the first index
     that has a compatible version, even when PyPI has a newer one. In a
     reported case this pulled certifi==2022.12.7, so the SSL certificates were
     two years out of date. idna, packaging, pillow, jinja2 and others were also
     downgraded [https://github.com/astral-sh/uv/issues/3137],
     [https://github.com/astral-sh/uv/issues/3137#issuecomment-2066688806]. Your
     pyproject.toml:5 lists certifi with no version bound, so you're exposed to
     exactly this.

  The better setup is to pin only torch to the PyTorch index and mark that index
  explicit, so nothing else can come from it. Then remove index-strategy so
  you're back on the safe default [uv-threads/docs/concepts/indexes.md]:

  [project]
  name = "ml-service"
  version = "0.1.0"
  requires-python = ">=3.11"
  dependencies = ["torch>=2.3", "fastapi>=0.110", "certifi"]

  [tool.uv.sources]
  torch = { index = "pytorch-cpu" }

  [[tool.uv.index]]
  name = "pytorch-cpu"
  url = "https://download.pytorch.org/whl/cpu"
  explicit = true

  This also replaces the old extra-index-url with a named [[tool.uv.index]]. The
  named index has to be defined in pyproject.toml itself. uv won't recognise a
  tool.uv.sources pin that points to an index set on the command line, in
  environment variables or in user-level config
  [uv-threads/docs/concepts/indexes.md]. If you ever need CUDA builds on Linux,
  you can give torch a list of sources chosen by platform markers.

  Want me to apply this and re-lock with uv lock?

✻ Cooked for 14s · done 9:36 PM

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❯ ues, apply it and re-lock
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