Allow for multiple tables from the same BigQuery dataset

[ryan-szns]

Currently, the UI and app only supports connecting to one table per BigQuery Data Agent.

Given the flexibility of the Conversational API's Python SDK, it would be a low effort, high reward feature to append more BigQueryTableReferences to the table_references list.

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[gemini-code-assist]

Summary of Changes

Hello @ryan-szns, 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 introduces the capability for a BigQuery Data Agent to reference multiple tables from the same dataset. The UI has been updated to accept a comma-separated list of table IDs, and the backend logic now processes these into individual BigQueryTableReference objects, enhancing the flexibility of data agent configurations.

Highlights

• Intent: This pull request aims to enhance the BigQuery Data Agent functionality by allowing it to connect to multiple tables from the same BigQuery dataset. Previously, the UI and application only supported a single table reference per agent. This change leverages the underlying Conversational API's Python SDK to append multiple BigQueryTableReference objects, providing greater flexibility.
• Changes Overview: The core change involves modifying the BigQuery data source configuration in the UI to accept multiple table IDs and updating the backend logic to process these IDs into a list of BigQueryTableReference objects. This transitions from a single table input field to a multi-line text area for comma-separated table IDs.
• File Changes: The changes are confined to app_pages/agents.py.
• app_pages/agents.py: The bq_table_id st.text_input field has been replaced with a bq_table_ids st.text_area to allow users to input multiple BigQuery table IDs, separated by commas. The associated logic has been updated to parse this comma-separated string, iterate through each table ID, and create a list of BigQueryTableReference objects. Each object is populated with the common project_id and dataset_id, but with its unique table_id, before being assigned to datasource_references.bq.table_references.
• Reviewer Activity: No specific reviewer activity has been noted in the provided context.

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[gemini-code-assist]

Code Review

Overall, this is a great enhancement that adds valuable flexibility for BigQuery data sources. The changes are well-contained and the logic is sound. I have one suggestion to improve the code's readability and adhere to Python best practices.