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ADK Workflow Fan-Out / Fan-In Sample

Overview

This sample demonstrates how to run multiple nodes in parallel and aggregate their results using a Fan-Out / Fan-In pattern in ADK Workflows.

It takes an input string and fans out to three different processing functions concurrently: make_uppercase, count_characters, and reverse_string. Instead of independently triggering the downstream node (as seen in the multi_triggers sample), this workflow uses a JoinNode to wait for all the parallel processes to complete. Once all results are ready, the JoinNode packages them into a single dictionary and passes it to an aggregate node, which formats the final combined response.

In ADK Workflows, the JoinNode is a critical component for synchronizing parallel execution paths, ensuring that a downstream node only executes once all of its required upstream dependencies have furnished their outputs.

Sample Inputs

  • Hello World

  • ADK workflows

  • testing concurrent nodes

Graph

graph TD
    START --> make_uppercase
    START --> count_characters
    START --> reverse_string
    make_uppercase --> join_node[join_node <br/>Waits for all 3]
    count_characters --> join_node
    reverse_string --> join_node
    join_node --> aggregate

How To

  1. Define a JoinNode in your code:

    from google.adk.workflow import JoinNode
    
    join_node = JoinNode(name="join_for_results")
    
  2. In the Workflow edges definition, specify a tuple of nodes to fan out execution, followed by your join_node to fan in the results, and finally the node that processes the aggregated output:

    (
        "START",
        (make_uppercase, count_characters, reverse_string),
        join_node,
        aggregate,
    )
    
  3. The node following the JoinNode (in this case, aggregate) will receive a dict as its input. The keys of this dictionary are the names of the upstream nodes, and the values are their respective outputs:

    async def aggregate(node_input: dict[str, Any]):
      uppercase_result = node_input['make_uppercase']
      # ...