chore: import upstream snapshot with attribution
Continuous Integration / Pre-commit Linter (push) Has been cancelled
Continuous Integration / Mypy Check (Python 3.10) (push) Has been cancelled
Continuous Integration / Mypy Check (Python 3.11) (push) Has been cancelled
Continuous Integration / Mypy Check (Python 3.12) (push) Has been cancelled
Continuous Integration / Mypy Check (Python 3.13) (push) Has been cancelled
Continuous Integration / Unit Tests (Python 3.10) (push) Has been cancelled
Continuous Integration / Unit Tests (Python 3.11) (push) Has been cancelled
Continuous Integration / Unit Tests (Python 3.12) (push) Has been cancelled
Continuous Integration / Unit Tests (Python 3.13) (push) Has been cancelled
Continuous Integration / Unit Tests (Python 3.14) (push) Has been cancelled
Continuous Integration / A2A v0.3 Tests (Python 3.10) (push) Has been cancelled
Continuous Integration / A2A v0.3 Tests (Python 3.11) (push) Has been cancelled
Continuous Integration / A2A v0.3 Tests (Python 3.12) (push) Has been cancelled
Copybara PR Handler / close-imported-pr (push) Has been cancelled
Continuous Integration / A2A v0.3 Tests (Python 3.13) (push) Has been cancelled
Continuous Integration / A2A v0.3 Tests (Python 3.14) (push) Has been cancelled

This commit is contained in:
wehub-resource-sync
2026-07-13 13:25:13 +08:00
commit ec2b666284
2231 changed files with 491535 additions and 0 deletions
@@ -0,0 +1,53 @@
# 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
```mermaid
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:
```python
(
"START",
(make_uppercase, count_characters, reverse_string),
# ...
)
```
1. By continuing the sequence to another node after the tuple, the outputs of all nodes in the tuple will independently trigger that target node:
```python
(
"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.
@@ -0,0 +1,45 @@
# Copyright 2026 Google LLC
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from typing import Any
from google.adk import Event
from google.adk import Workflow
def make_uppercase(node_input: str):
return node_input.upper()
def count_characters(node_input: str):
return len(node_input)
def reverse_string(node_input: str):
return node_input[::-1]
async def send_message(node_input: Any):
yield Event(message=f"Triggered for input: {node_input}")
root_agent = Workflow(
name="root_agent",
edges=[(
"START",
(make_uppercase, count_characters, reverse_string),
send_message,
)],
input_schema=str,
)
@@ -0,0 +1,118 @@
{
"appName": "multi_triggers",
"events": [
{
"author": "user",
"content": {
"parts": [
{
"text": "go"
}
],
"role": "user"
},
"id": "e-1",
"invocationId": "i-1",
"nodeInfo": {
"path": ""
}
},
{
"author": "root_agent",
"branch": "make_uppercase@1",
"id": "e-2",
"invocationId": "i-1",
"nodeInfo": {
"outputFor": [
"root_agent@1/make_uppercase@1"
],
"path": "root_agent@1/make_uppercase@1"
},
"output": "GO"
},
{
"author": "root_agent",
"branch": "count_characters@1",
"id": "e-3",
"invocationId": "i-1",
"nodeInfo": {
"outputFor": [
"root_agent@1/count_characters@1"
],
"path": "root_agent@1/count_characters@1"
},
"output": 2
},
{
"author": "root_agent",
"branch": "reverse_string@1",
"id": "e-4",
"invocationId": "i-1",
"nodeInfo": {
"outputFor": [
"root_agent@1/reverse_string@1"
],
"path": "root_agent@1/reverse_string@1"
},
"output": "og"
},
{
"author": "root_agent",
"branch": "make_uppercase@1",
"content": {
"parts": [
{
"text": "Triggered for input: GO"
}
],
"role": "user"
},
"id": "e-5",
"invocationId": "i-1",
"nodeInfo": {
"path": "root_agent@1/send_message@1"
}
},
{
"author": "root_agent",
"branch": "count_characters@1",
"content": {
"parts": [
{
"text": "Triggered for input: 2"
}
],
"role": "user"
},
"id": "e-6",
"invocationId": "i-1",
"nodeInfo": {
"path": "root_agent@1/send_message@2"
}
},
{
"author": "root_agent",
"branch": "reverse_string@1",
"content": {
"parts": [
{
"text": "Triggered for input: og"
}
],
"role": "user"
},
"id": "e-7",
"invocationId": "i-1",
"nodeInfo": {
"path": "root_agent@1/send_message@3"
}
}
],
"id": "5cf6403e-fd4e-4fef-ad66-8ae78d26ba29",
"state": {
"__session_metadata__": {
"displayName": "go"
}
},
"userId": "user"
}