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

text

                  [ START ]
                /     |      \
               /      |       \
              v       v        v
[make_uppercase] [count_characters] [reverse_string]
              \       |        /
               \      |       /
                v     v      v
               [  join_node  ]
             (Waits for all 3)
                      |
                      v
                [ aggregate ]

How To

Define a JoinNode in your code:

python

from google.adk.workflow import JoinNode

join_node = JoinNode(name="join_for_results")

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:
python
```
(
    "START",
    (make_uppercase, count_characters, reverse_string),
    join_node,
    aggregate,
)
```
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:
python
```
async def aggregate(node_input: dict[str, Any]):
  uppercase_result = node_input['make_uppercase']
  # ...
```