diff --git a/python/samples/02-agents/chat_client/doubleword_chat_client.py b/python/samples/02-agents/chat_client/doubleword_chat_client.py
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+# Copyright (c) Microsoft. All rights reserved.
+
+"""
+Doubleword Chat Client Example
+
+This sample demonstrates how to use the Microsoft Agent Framework with
+Doubleword's OpenAI-compatible inference API. Doubleword is an AI model
+gateway providing unified routing, management, and security for inference
+across multiple model providers.
+
+Since Doubleword exposes an OpenAI-compatible API, you can use the built-in
+OpenAIChatCompletionClient with a custom base URL.
+
+Three execution modes are demonstrated:
+- main()       — realtime (priority tier)
+- main_async() — 1-hour async (flex tier, mid-tier cost)
+- main_batch() — 24-hour batch (deepest discount)
+
+Setup:
+    pip install agent-framework-openai
+    export DOUBLEWORD_API_KEY="your-api-key"
+
+Available models: https://docs.doubleword.ai/inference-api/models
+"""
+
+import asyncio
+import os
+
+from agent_framework import Message
+from agent_framework.openai import OpenAIChatCompletionClient
+
+
+async def main() -> None:
+    """Run a basic prompt using Doubleword's inference API."""
+    client = OpenAIChatCompletionClient(
+        model="Qwen/Qwen3.5-397B-A17B-FP8",
+        base_url="https://api.doubleword.ai/v1",
+        api_key=os.environ["DOUBLEWORD_API_KEY"],
+    )
+
+    message = Message("user", contents=["Explain the benefits of an AI model gateway in one paragraph."])
+    print(f"User: {message.text}")
+
+    response = await client.get_response([message], stream=False)
+    print(f"Assistant: {response}")
+
+
+async def main_async() -> None:
+    """Run requests on the 1-hour async (flex) tier using autobatcher.
+
+    Mid-tier cost between realtime and 24-hour batch — use when next-day
+    batch turnaround is too slow but realtime is too expensive.
+
+    Install: pip install autobatcher
+    See: https://pypi.org/project/autobatcher/
+    """
+    from autobatcher import AsyncOpenAI
+
+    client = OpenAIChatCompletionClient(
+        model="Qwen/Qwen3.5-397B-A17B-FP8",
+        async_client=AsyncOpenAI(
+            api_key=os.environ["DOUBLEWORD_API_KEY"],
+            base_url="https://api.doubleword.ai/v1",
+        ),
+    )
+
+    message = Message("user", contents=["Explain the benefits of an AI model gateway in one paragraph."])
+    print(f"User: {message.text}")
+
+    response = await client.get_response([message], stream=False)
+    print(f"Assistant: {response}")
+
+
+async def main_batch() -> None:
+    """Run batch requests at reduced cost using autobatcher.
+
+    24-hour batch tier — deepest discount (up to ~90% off realtime).
+
+    Install: pip install autobatcher
+    See: https://pypi.org/project/autobatcher/
+    """
+    from autobatcher import BatchOpenAI
+
+    client = OpenAIChatCompletionClient(
+        model="Qwen/Qwen3.5-397B-A17B-FP8",
+        async_client=BatchOpenAI(
+            api_key=os.environ["DOUBLEWORD_API_KEY"],
+            base_url="https://api.doubleword.ai/v1",
+        ),
+    )
+
+    message = Message("user", contents=["Explain the benefits of an AI model gateway in one paragraph."])
+    print(f"User: {message.text}")
+
+    response = await client.get_response([message], stream=False)
+    print(f"Assistant: {response}")
+
+
+if __name__ == "__main__":
+    asyncio.run(main())
+
+
+"""
+Sample output:
+User: Explain the benefits of an AI model gateway in one paragraph.
+Assistant: An AI model gateway provides a unified API layer that routes inference
+requests across multiple model providers, enabling organizations to ...
+"""