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.

It’s compatible with the following sources:

• bigquery

The tool takes the following input 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"}]'

Example

tools:
  ask_data_insights:
    kind: 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