chore: import upstream snapshot with attribution

contributing/samples/workflows/dynamic_fan_out_fan_in/README.md

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+# Dynamic Fan-Out / Fan-In with Dynamic Nodes
+
+## Overview
+
+This sample demonstrates how to perform **Dynamic Fan-Out and Fan-In** using ADK's dynamic node scheduling (`ctx.run_node()`).
+
+Unlike static graph-based parallel execution (which requires pre-defined branches), this pattern allows you to determine the number of parallel tasks at runtime based on the input data.
+
+## Sample Inputs
+
+- `AI, Cloud Computing, Quantum Computing`
+
+- `Python, Go, Rust, TypeScript`
+
+## Graph
+
+```mermaid
+graph TD
+    START --> Orchestrator
+    Orchestrator --> Gen_0[Generator Task 0]
+    Orchestrator --> Gen_1[Generator Task 1]
+    Orchestrator --> Gen_N[Generator Task N]
+    Gen_0 --> Aggregator[Orchestrator Fan-In]
+    Gen_1 --> Aggregator
+    Gen_N --> Aggregator
+```
+
+## How To
+
+Key techniques demonstrated in this sample:
+
+1. **Dynamic Scheduling**: Using a loop to create tasks via `ctx.run_node()`.
+1. **Context Isolation**: Using `sub_branch` in `run_node` to isolate events for each parallel task, preventing context contamination.
+1. **`rerun_on_resume=True`**: Required on the orchestrator node to support resumption if any child node interrupts.
+
+### Code Snippet
+
+```python
+    # Fan-out: Schedule a dynamic node for each topic
+    tasks = []
+    for i, topic in enumerate(topics):
+        tasks.append(
+            ctx.run_node(
+                generator,
+                node_input=topic,
+                sub_branch=f"branch_{i}"
+            )
+        )
+
+    # Wait for all tasks to complete
+    results = await asyncio.gather(*tasks)
+```
+
+## Pro Tip: Custom `run_id`
+
+ADK auto-generates numeric IDs (e.g., `@1`), but you can pass a custom `run_id` to improve log readability (e.g., `generator@task_AI`) or map events to business keys.
+
+**Rules**:
+
+- **Unique**: Must be unique per node for fresh executions (otherwise returns cached results).
+- **Non-Numeric**: Must contain non-numeric characters to avoid collision with auto-generated IDs.

contributing/samples/workflows/dynamic_fan_out_fan_in/agent.py

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+# 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 __future__ import annotations
+
+import asyncio
+
+from google.adk import Agent
+from google.adk import Context
+from google.adk import Event
+from google.adk import Workflow
+from google.adk.workflow import node
+
+# Worker agent to generate a headline for a single topic
+generator = Agent(
+    name="generator",
+    instruction=(
+        "Write a catchy one-line headline about the topic provided in the user"
+        " message."
+    ),
+)
+
+
+@node(rerun_on_resume=True)
+async def orchestrator(ctx: Context, node_input: str) -> str:
+  """Orchestrator node that performs dynamic fan-out and fan-in."""
+  # Split input comma-separated string into topics
+  topics = [t.strip() for t in node_input.split(",") if t.strip()]
+  yield Event(message=f"Processing {len(topics)} topics in parallel.")
+
+  # Fan-out: Schedule a dynamic node for each topic
+  tasks = []
+  for i, topic in enumerate(topics):
+    tasks.append(
+        ctx.run_node(
+            generator,
+            node_input=topic,
+            use_sub_branch=True,
+        )
+    )
+
+  # Wait for all tasks to complete
+  results = await asyncio.gather(*tasks)
+
+  # Fan-in: Aggregate results
+  aggregated = "### Aggregated Headlines\n\n"
+  aggregated += "| Topic | Headline |\n"
+  aggregated += "| :--- | :--- |\n"
+  for topic, headline in zip(topics, results):
+    aggregated += f"| {topic} | {headline} |\n"
+
+  yield Event(message=aggregated)
+
+
+root_agent = Workflow(
+    name="dynamic_fan_out_fan_in",
+    edges=[("START", orchestrator)],
+)