bigquery-conversational-analytics

About

A bigquery-conversational-analytics tool allows you to ask questions about your data in natural language.

This function takes a user's question (which can include conversational history for context) and references to specific BigQuery tables, and sends them to a stateless conversational API.

The API uses a GenAI agent to understand the question, generate and execute SQL queries and Python code, and formulate an answer. This function returns a detailed, sequential log of this entire process, which includes any generated SQL or Python code, the data retrieved, and the final text answer.

Note: This tool requires additional setup in your project. Please refer to the official Conversational Analytics API documentation for instructions.

bigquery-conversational-analytics accepts the following parameters:

• user_query_with_context: The user's question, potentially including conversation history and system instructions for context.
• table_references: A JSON string of a list of BigQuery tables to use as context. Each object in the list must contain projectId, datasetId, and tableId. Example: '[{"projectId": "my-gcp-project", "datasetId": "my_dataset", "tableId": "my_table"}]'

The tool's behavior regarding these parameters is influenced by the allowedDatasets restriction on the bigquery source:

• Without allowedDatasets restriction: The tool can use tables from any dataset specified in the table_references parameter.
• With allowedDatasets restriction: Before processing the request, the tool verifies that every table in table_references belongs to a dataset in the allowed list. If any table is from a dataset that is not in the list, the request is denied.

Compatible Sources

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Example

kind: tool
name: ask_data_insights
type: bigquery-conversational-analytics
source: my-bigquery-source
description: |
  Use this tool to perform data analysis, get insights, or answer complex 
  questions about the contents of specific BigQuery tables.

Reference