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7c2dae8855
* Fix sample bugs: incorrect API params, wrong client types, and invalid options - typed_options.py: Fix AnthropicClient model->model_id, wrap raw strings in Message objects for get_response(), fix reasoning_effort->reasoning dict, fix budget_tokens minimum (1024), use OpenAIChatClient not FoundryChatClient, remove unused import - client_reasoning.py: Fix deprecated model_id to model param - client_with_hosted_mcp.py: Remove invalid store=True kwarg from Agent.run() - code_defined_skill.py: Fix precision kwarg to use function_invocation_kwargs - Various other samples: Fix deprecated API usage and incorrect params Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Address PR review comments - client_with_hosted_mcp.py: Fix remaining store=True kwarg on line 68 to use options dict - client_with_session.py: Change store=True to store=False to match in-memory persistence demo intent - typed_options.py: Remove non-existent import and model key from docstring example Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * new sample fixes --------- Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
79 lines
2.3 KiB
Python
79 lines
2.3 KiB
Python
# Copyright (c) Microsoft. All rights reserved.
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import asyncio
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from random import randint
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from typing import Annotated
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from agent_framework import Agent, tool
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from agent_framework.anthropic import AnthropicClient
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from dotenv import load_dotenv
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# Load environment variables from .env file
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load_dotenv()
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"""
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Anthropic Chat Agent Example
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This sample demonstrates using Anthropic with an agent and a single custom tool.
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"""
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# NOTE: approval_mode="never_require" is for sample brevity. Use "always_require" in production;
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# see samples/02-agents/tools/function_tool_with_approval.py
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# and samples/02-agents/tools/function_tool_with_approval_and_sessions.py.
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@tool(approval_mode="never_require")
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def get_weather(
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location: Annotated[str, "The location to get the weather for."],
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) -> str:
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"""Get the weather for a given location."""
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conditions = ["sunny", "cloudy", "rainy", "stormy"]
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return f"The weather in {location} is {conditions[randint(0, 3)]} with a high of {randint(10, 30)}°C."
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async def non_streaming_example() -> None:
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"""Example of non-streaming response (get the complete result at once)."""
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print("=== Non-streaming Response Example ===")
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agent = Agent(
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client=AnthropicClient(model_id="claude-sonnet-4-5-20250929"),
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name="WeatherAgent",
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instructions="You are a helpful weather agent.",
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tools=get_weather,
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)
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query = "What's the weather like in Seattle?"
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print(f"User: {query}")
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result = await agent.run(query)
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print(f"Result: {result}\n")
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async def streaming_example() -> None:
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"""Example of streaming response (get results as they are generated)."""
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print("=== Streaming Response Example ===")
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agent = Agent(
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client=AnthropicClient(model_id="claude-sonnet-4-5-20250929"),
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name="WeatherAgent",
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instructions="You are a helpful weather agent.",
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tools=get_weather,
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)
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query = "What's the weather like in Portland and in Paris?"
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print(f"User: {query}")
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print("Agent: ", end="", flush=True)
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async for chunk in agent.run(query, stream=True):
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if chunk.text:
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print(chunk.text, end="", flush=True)
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print("\n")
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async def main() -> None:
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print("=== Anthropic Example ===")
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await streaming_example()
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await non_streaming_example()
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if __name__ == "__main__":
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asyncio.run(main())
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