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Implement methods for logging model download events#743

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safaricd wants to merge 4 commits intomainfrom
ENG-414
Open

Implement methods for logging model download events#743
safaricd wants to merge 4 commits intomainfrom
ENG-414

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@safaricd
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@safaricd safaricd commented Jan 21, 2026

Issue

With this PR we set up logging failed and successful model loading events into our telemetry system. These are logged anonymously to identify common reasons for failure and further improve the user experience.

Do not merge this PR until a new tabpfn_common_utils package is released.

Motivation and Context


Public API Changes

  • No Public API changes

How Has This Been Tested?

Locally.

Checklist

  • The changes have been tested locally.
  • Documentation has been updated (if the public API or usage changes).
  • A changelog entry has been added (see changelog/README.md), or "no changelog needed" label requested.
  • The code follows the project's style guidelines.
  • I have considered the impact of these changes on the public API.

@safaricd safaricd requested a review from a team as a code owner January 21, 2026 04:52
@safaricd safaricd requested review from adrian-prior and removed request for a team January 21, 2026 04:52
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Code Review

This pull request introduces telemetry for model download events from Hugging Face. A new decorator, _log_huggingface_download_errors, is added to wrap the download function, capturing and logging success and failure events. The changes also include updating the tabpfn-common-utils dependency to a newer version that supports this telemetry.

The implementation is functionally correct. My main feedback is to refactor the new decorator to improve clarity and reduce its coupling with the decorated function, as it currently modifies the arguments passed to it. This will make the code easier to understand and maintain.

@safaricd safaricd requested review from noahho and removed request for adrian-prior January 21, 2026 05:06
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Not sure if this one is meant to help us understand HuggingFace Gating and if users struggle with that? If yes, I don't think it measures the right stats (time from error to resolution, which steps people took (e.g. are they logged in HF? Did they accept gating?) I'd drive this more from actual data we can interpret?). If no, what is the goal if this measurement.

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2 participants