google--adk-python/contributing/samples/hitl/request_input_tool

Request Input Tool Sample

Overview

This sample demonstrates how an LLM agent can proactively request clarification or confirmation from the user using the built-in request_input tool without losing its context/flow.

It showcases a highly realistic support assistant that dynamically constructs a JSON schema to only ask for missing details when creating IT support tickets.

Sample Inputs

• I want to file a technical ticket for a database crash.

  The agent will analyze the prompt, identify that the title and category are already provided, and dynamically call request_input with a schema requesting only description and priority.

• File a priority HIGH technical ticket titled database crash explained as the MySQL server throwing OOM errors.

  The agent has all required details and will call create_support_ticket immediately without needing clarification.

Graph

graph TD
    User[User Prompt] --> Agent[Support Assistant Agent]
    Agent -->|Needs Clarification| RequestInput[request_input tool]
    RequestInput -->|User Response| Agent
    Agent -->|All Details Gathered| CreateTicket[create_support_ticket tool]

How To

This sample uses Pattern B: Standalone Agents with the request_input tool:

1. Import request_input:

   from google.adk.tools import request_input
   

2. Add it to the LLM Agent's tools list:

   root_agent = Agent(
       name="support_assistant_agent",
       tools=[create_support_ticket, request_input],
       ...
   )
   

When the LLM decides it needs clarification, it calls request_input with a question and a dynamic response_schema. The ADK framework automatically intercepts this, yields a long-running interrupt to the client, and injects the user's reply back as a FunctionResponse into the LLM's chat history.