Fix breaking changed by renaming chunk to embeddable

[claudevdm]

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[gemini-code-assist]

Summary of Changes

Hello @claudevdm, I'm Gemini Code Assist¹! I'm currently reviewing this pull request and will post my feedback shortly. In the meantime, here's a summary to help you and other reviewers quickly get up to speed!

This pull request addresses a breaking change within the BigQuery vector storage components by refactoring the SchemaConfig class for improved initialization and introducing deprecation handling for an older parameter name. It also standardizes terminology in a related BigQuery vector search query.

Highlights

• SchemaConfig Refactoring: Refactored the SchemaConfig class in bigquery.py from a dataclass to a standard class, introducing an __init__ method for more controlled initialization and validation.
• Backward Compatibility and Deprecation: Implemented backward compatibility and deprecation warnings for the chunk_to_dict_fn parameter within SchemaConfig's constructor, guiding users towards the preferred embeddable_to_dict_fn.
• BigQuery Query Terminology Update: Updated a BigQuery vector search query in bigquery_vector_search.py to use chunks instead of embeddable_items as an alias for the aggregated results.
• CI Trigger Update: Incremented a modification counter in the beam_PostCommit_Python_Xlang_Gcp_Direct.json CI trigger file.

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Changelog

• .github/trigger_files/beam_PostCommit_Python_Xlang_Gcp_Direct.json
  • Updated the modification counter to trigger CI.
• sdks/python/apache_beam/ml/rag/enrichment/bigquery_vector_search.py
  • Renamed the embeddable_items alias to chunks in the VECTOR_SEARCH query.
• sdks/python/apache_beam/ml/rag/ingestion/bigquery.py
  • Converted the SchemaConfig class from a dataclass to a standard class with an __init__ method.
  • Added a deprecation warning for the chunk_to_dict_fn parameter in SchemaConfig's constructor.
  • Made embeddable_to_dict_fn a required parameter in the SchemaConfig constructor.
  • Imported the warnings module.

Activity

• The pull request was created by claudevdm.

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[claudevdm]

/gemini review

[gemini-code-assist]

Code Review

This pull request introduces changes to the RAG API for BigQuery integration. The refactoring of SchemaConfig in sdks/python/apache_beam/ml/rag/ingestion/bigquery.py to support backward compatibility by handling a deprecated argument is a solid improvement. However, I've noted a potential inconsistency in sdks/python/apache_beam/ml/rag/enrichment/bigquery_vector_search.py, where a result alias is renamed to chunks, which seems to contradict the general trend of moving away from the Chunk terminology. I've added a specific comment with a suggestion to address this for better API consistency.

[claudevdm]

R: @damccorm

[claudevdm]

R: @Abacn

[claudevdm]

Failing tests look unrelated

[github-actions]

Stopping reviewer notifications for this pull request: review requested by someone other than the bot, ceding control. If you'd like to restart, comment assign set of reviewers

[github-actions]

Stopping reviewer notifications for this pull request: review requested by someone other than the bot, ceding control. If you'd like to restart, comment assign set of reviewers

[damccorm]

Thanks!