gemini-code-assist[bot] commented on PR #37652: URL: https://github.com/apache/beam/pull/37652#issuecomment-3930393012
## Summary of Changes Hello @claudevdm, I'm Gemini Code Assist[^1]! 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 necessary adjustments following a previous rename of `Chunk` to `EmbeddableItem`. The primary focus is on maintaining API stability and providing a smooth transition for users by ensuring backward compatibility for configuration arguments in the BigQuery ingestion module. It also includes a minor update to a SQL query alias and a routine CI trigger file modification. ### Highlights * **Backward Compatibility for SchemaConfig**: The `SchemaConfig` class in `bigquery.py` was refactored from a dataclass to a standard class with an `__init__` method. This change introduces backward compatibility for the `chunk_to_dict_fn` argument, now aliased to `embeddable_to_dict_fn`, and issues a `DeprecationWarning` when the old argument is used. * **SQL Query Alias Adjustment**: In `bigquery_vector_search.py`, a SQL query alias was updated from `embeddable_items` to `chunks` within the `VECTOR_SEARCH` function, aligning with naming conventions. * **CI Trigger Update**: A trivial modification was made to a GitHub Actions trigger file to ensure the associated test suite runs. 🧠**New Feature in Public Preview:** You can now enable **Memory** to help **Gemini Code Assist** learn from your team's feedback. This makes future code reviews more consistent and personalized to your project's style. **Click [here](https://codeassist.google/code-review/login) to enable Memory in your admin console.** <details> <summary><b>Changelog</b></summary> * **.github/trigger_files/beam_PostCommit_Python_Xlang_Gcp_Direct.json** * Incremented the `modification` field to trigger CI. * **sdks/python/apache_beam/ml/rag/enrichment/bigquery_vector_search.py** * Updated the SQL alias from `embeddable_items` to `chunks` in the `VECTOR_SEARCH` query. * **sdks/python/apache_beam/ml/rag/ingestion/bigquery.py** * Refactored `SchemaConfig` from a dataclass to a standard class with an `__init__` method. * Introduced `ChunkToDictFn` as a backward-compatible alias for `EmbeddableToDictFn`. * Added logic to `SchemaConfig.__init__` to handle `chunk_to_dict_fn` as a deprecated argument, mapping it to `embeddable_to_dict_fn` and issuing a `DeprecationWarning`. * Implemented validation to ensure `embeddable_to_dict_fn` is provided and to catch unexpected keyword arguments in `SchemaConfig`'s constructor. </details> <details> <summary><b>Activity</b></summary> * The pull request was opened by claudevdm to fix breaking changes from renaming `Chunk` to `EmbeddableItem`. </details> <details> <summary><b>Using Gemini Code Assist</b></summary> <br> The full guide for Gemini Code Assist can be found on our [documentation page](https://developers.google.com/gemini-code-assist/docs/review-github-code), here are some quick tips. <b>Invoking Gemini</b> You can request assistance from Gemini at any point by creating a comment using either `/gemini <command>` or `@gemini-code-assist <command>`. 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