conversational-analytics-ask-data-agent

A “conversational-analytics-ask-data-agent” tool allows conversational interaction with a Conversational Analytics source.

About

A conversational-analytics-ask-data-agent 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 a specific BigQuery Data Agent, 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:

  • cloud-gemini-data-analytics

conversational-analytics-ask-data-agent accepts the following parameters:

  • user_query_with_context: The question to ask the agent, potentially including conversation history for context.
  • data_agent_id: The ID of the data agent to ask.

Example

kind: tool
name: ask_data_agent
type: conversational-analytics-ask-data-agent
source: my-conversational-analytics-source
location: global
maxResults: 50
description: |
  Perform natural language data analysis and get insights by interacting 
  with a specific BigQuery Data Agent. This tool allows for conversational 
  queries and provides detailed responses based on the agent's configured 
  data sources.

Reference

fieldtyperequireddescription
typestringtrueMust be “conversational-analytics-ask-data-agent”.
sourcestringtrueName of the source for chat.
descriptionstringtrueDescription of the tool that is passed to the LLM.
locationstringfalseThe Google Cloud location (default: “global”).
maxResultsintegerfalseThe maximum number of data rows to return in the tool’s final response (default: 50). This only limits the amount of data included in the final tool return to prevent excessive token consumption, and does not affect the internal analytical process or intermediate steps.



Last modified August 14, 2026: chore(main): release 1.9.0 (#3744) (5de8f13)