chore: import upstream snapshot with attribution

python/samples/02-agents/providers/amazon/README.md

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+# Bedrock Examples
+
+This folder contains examples demonstrating how to use AWS Bedrock models with the Agent Framework. The sample
+uses `BEDROCK_CHAT_MODEL`, `BEDROCK_REGION`, and AWS credentials (`AWS_ACCESS_KEY_ID`,
+`AWS_SECRET_ACCESS_KEY`, optional `AWS_SESSION_TOKEN`).
+
+## Examples
+
+| File | Description |
+|------|-------------|
+| [`bedrock_chat_client.py`](bedrock_chat_client.py) | Uses `BedrockChatClient` with a simple tool-enabled `Agent` to demonstrate direct Bedrock chat integration. |
+
+## Environment Variables
+
+- `BEDROCK_CHAT_MODEL`: Bedrock model ID (for example, `anthropic.claude-3-5-sonnet-20240620-v1:0`)
+- `BEDROCK_REGION`: AWS region (defaults to `us-east-1` if unset)
+- AWS credentials via standard variables (`AWS_ACCESS_KEY_ID`, `AWS_SECRET_ACCESS_KEY`, optional `AWS_SESSION_TOKEN`)

python/samples/02-agents/providers/amazon/bedrock_chat_client.py

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+# Copyright (c) Microsoft. All rights reserved.
+
+import asyncio
+from typing import Annotated
+
+from agent_framework import Agent, tool
+from agent_framework.amazon import BedrockChatClient, BedrockChatOptions
+from dotenv import load_dotenv
+from pydantic import Field
+
+# Load environment variables from .env file
+load_dotenv()
+
+"""
+Bedrock Chat Client Example
+
+This sample demonstrates using `BedrockChatClient` with an agent and a simple tool.
+
+Environment variables used:
+- `BEDROCK_CHAT_MODEL`
+- `BEDROCK_REGION` (defaults to `us-east-1` if unset)
+- AWS credentials via standard variables (`AWS_ACCESS_KEY_ID`, `AWS_SECRET_ACCESS_KEY`,
+  optional `AWS_SESSION_TOKEN`)
+"""
+
+
+# NOTE: approval_mode="never_require" is for sample brevity.
+# Use "always_require" in production; see samples/02-agents/tools/function_tool_with_approval.py
+# and samples/02-agents/tools/function_tool_with_approval_and_sessions.py.
+@tool(approval_mode="never_require")
+def get_weather(
+    city: Annotated[str, Field(description="The city to get the weather for.")],
+) -> dict[str, str]:
+    """Return a mock forecast for the requested city."""
+    normalized_city = city.strip() or "New York"
+    return {"city": normalized_city, "forecast": "72F and sunny"}
+
+
+async def main() -> None:
+    """Run a Bedrock-backed agent with one tool call."""
+    # 1. Create an agent with Bedrock chat client and one tool.
+    agent = Agent(
+        client=BedrockChatClient(),
+        instructions="You are a concise travel assistant.",
+        name="BedrockWeatherAgent",
+        tools=[get_weather],
+        default_options=BedrockChatOptions(tool_choice="auto"),
+    )
+
+    # 2. Run a query that uses the weather tool.
+    query = "Use the weather tool to check the forecast for New York."
+    print(f"User: {query}")
+    response = await agent.run(query)
+    print(f"Assistant: {response.text}")
+
+
+if __name__ == "__main__":
+    asyncio.run(main())
+
+
+"""
+Sample output:
+User: Use the weather tool to check the forecast for New York.
+Assistant: The forecast for New York is 72F and sunny.
+"""