[BREAKING] Python: Move orchestrations to dedicated package (#3685)

* Move orchestrations to dedicated package

* Merge main

* Fix markdown links

* Fix links

python/samples/getting_started/orchestrations/sequential_agents.py

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+# Copyright (c) Microsoft. All rights reserved.
+
+import asyncio
+from typing import cast
+
+from agent_framework import ChatMessage, WorkflowOutputEvent
+from agent_framework.azure import AzureOpenAIChatClient
+from agent_framework.orchestrations import SequentialBuilder
+from azure.identity import AzureCliCredential
+
+"""
+Sample: Sequential workflow (agent-focused API) with shared conversation context
+
+Build a high-level sequential workflow using SequentialBuilder and two domain agents.
+The shared conversation (list[ChatMessage]) flows through each participant. Each agent
+appends its assistant message to the context. The workflow outputs the final conversation
+list when complete.
+
+Note on internal adapters:
+- Sequential orchestration includes small adapter nodes for input normalization
+  ("input-conversation"), agent-response conversion ("to-conversation:<participant>"),
+  and completion ("complete"). These may appear as ExecutorInvoke/Completed events in
+  the stream—similar to how concurrent orchestration includes a dispatcher/aggregator.
+  You can safely ignore them when focusing on agent progress.
+
+Prerequisites:
+- Azure OpenAI access configured for AzureOpenAIChatClient (use az login + env vars)
+"""
+
+
+async def main() -> None:
+    # 1) Create agents
+    chat_client = AzureOpenAIChatClient(credential=AzureCliCredential())
+
+    writer = chat_client.as_agent(
+        instructions=("You are a concise copywriter. Provide a single, punchy marketing sentence based on the prompt."),
+        name="writer",
+    )
+
+    reviewer = chat_client.as_agent(
+        instructions=("You are a thoughtful reviewer. Give brief feedback on the previous assistant message."),
+        name="reviewer",
+    )
+
+    # 2) Build sequential workflow: writer -> reviewer
+    workflow = SequentialBuilder().participants([writer, reviewer]).build()
+
+    # 3) Run and collect outputs
+    outputs: list[list[ChatMessage]] = []
+    async for event in workflow.run_stream("Write a tagline for a budget-friendly eBike."):
+        if isinstance(event, WorkflowOutputEvent):
+            outputs.append(cast(list[ChatMessage], event.data))
+
+    if outputs:
+        print("===== Final Conversation =====")
+        for i, msg in enumerate(outputs[-1], start=1):
+            name = msg.author_name or ("assistant" if msg.role == "assistant" else "user")
+            print(f"{'-' * 60}\n{i:02d} [{name}]\n{msg.text}")
+
+    """
+    Sample Output:
+
+    ===== Final Conversation =====
+    ------------------------------------------------------------
+    01 [user]
+    Write a tagline for a budget-friendly eBike.
+    ------------------------------------------------------------
+    02 [writer]
+    Ride farther, spend less—your affordable eBike adventure starts here.
+    ------------------------------------------------------------
+    03 [reviewer]
+    This tagline clearly communicates affordability and the benefit of extended travel, making it
+    appealing to budget-conscious consumers. It has a friendly and motivating tone, though it could
+    be slightly shorter for more punch. Overall, a strong and effective suggestion!
+    """
+
+
+if __name__ == "__main__":
+    asyncio.run(main())