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chore(deps): update dependency transformers to v5 [security] - autoclosed #14219

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chore(deps): update dependency transformers to v5 [security] - autoclosed #14219

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2 changes: 1 addition & 1 deletion dataflow/run-inference/requirements.txt
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Original file line number Diff line number Diff line change
@@ -1,3 +1,3 @@
apache-beam[gcp]==2.49.0
torch==2.2.2
transformers==4.38.0
transformers==5.0.0

@gemini-code-assist gemini-code-assist Bot May 23, 2026

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high

Upgrading to transformers v5 is a major version bump that introduces several breaking changes and potential dependency conflicts with the existing environment.

  • Dependency Compatibility: apache-beam[gcp]==2.49.0 is an older version (released mid-2023) that typically pins dependencies like protobuf (often < 4.24.0) and numpy. transformers v5 (released 2025) likely requires much newer versions of these libraries (e.g., protobuf >= 4.25.0). This mismatch will likely cause installation failures or runtime conflicts. Consider upgrading apache-beam to a more recent version (e.g., 2.60.0 or later).
  • Internal Refactors: The import from transformers.tokenization_utils import PreTrainedTokenizer in main.py (line 31) targets an internal module that has been significantly refactored in v5. It is recommended to import PreTrainedTokenizer directly from the top-level transformers package to ensure long-term compatibility.
  • Breaking Changes: In v5, AutoConfig.from_pretrained no longer supports loading from URLs, and tokenizer.decode behavior has been unified with batch_decode (returning a list for 2D inputs). Ensure the pipeline's input/output handling in main.py is compatible with these changes, especially the string encoding step at line 138.