chore: import upstream snapshot with attribution

contributing/samples/workflows/multi_triggers/README.md

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+# 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.