google--adk-python/contributing/samples/workflows/multi_triggers

ADK Workflow Multi-Triggers Sample

Overview

This sample demonstrates how a single node can fan out to execute multiple downstream nodes concurrently, and how multiple upstream nodes can trigger a single downstream node independently in ADK Workflows.

In this example, the START node fans out to three different processing functions (make_uppercase, count_characters, and reverse_string). Each of these functions receives the initial user input string, processes it, and then independently outputs its result.

Because the subsequent send_message node receives a continuous flow of outputs and does not use an aggregation mechanism (like JoinNode), it is triggered multiple times—once for every upstream event.

Sample Inputs

• Hello World

• ADK workflows

• testing concurrent nodes

Graph

graph TD
    START --> make_uppercase
    START --> count_characters
    START --> reverse_string
    make_uppercase --> send_message
    count_characters --> send_message
    reverse_string --> send_message

How To

1. You can specify a tuple of nodes within an edge to create a parallel fan-out segment where the same input is provided to multiple nodes:

   (
       "START",
       (make_uppercase, count_characters, reverse_string),
       # ...
   )
   

2. By continuing the sequence to another node after the tuple, the outputs of all nodes in the tuple will independently trigger that target node:

   (
       "START",
       (make_uppercase, count_characters, reverse_string),
       send_message,
   )
   

   In this case, send_message will be executed once for make_uppercase's output, once for count_characters's output, and once for reverse_string's output.