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Merge branch 'feature/azure-ai-agents/1.0.3' of https://github.com/Azure/azure-sdk-for-python into feature/azure-ai-agents/1.0.3
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‎sdk/ai/azure-ai-agents/CHANGELOG.md‎

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# Release History
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## 1.0.3 (Unreleased)
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### Features Added
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- Added samples, [`sample_agents_auto_function_call.py`](https://github.com/Azure/azure-sdk-for-python/blob/main/sdk/ai/azure-ai-agents/samples/agents_tools/sample_agents_auto_function_call.py) and [`sample_agents_auto_function_call_async.py`](https://github.com/Azure/azure-sdk-for-python/blob/main/sdk/ai/azure-ai-agents/samples/agents_async/sample_agents_auto_function_call_async.py).
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## 1.0.2 (2025-07-01)
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### Bugs Fixed

‎sdk/ai/azure-ai-agents/README.md‎

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<!-- END SNIPPET -->
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Notice that if `enable_auto_function_calls` is called, the SDK will invoke the functions automatically during `create_and_process` or streaming. If you prefer to execute them manually, refer to [`sample_agents_stream_eventhandler_with_functions.py`](https://github.com/Azure/azure-sdk-for-python/blob/main/sdk/ai/azure-ai-agents/samples/agents_streaming/sample_agents_stream_eventhandler_with_functions.py) or
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[`sample_agents_functions.py`](https://github.com/Azure/azure-sdk-for-python/blob/main/sdk/ai/azure-ai-agents/samples/agents_tools/sample_agents_functions.py)
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When `enable_auto_function_calls` is called, the SDK will automatically invoke functions during both `create_and_process` and streaming workflows. This simplifies agent logic by handling function execution internally.
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- For examples of automatic function calls in action, refer to [`sample_agents_auto_function_call.py`](https://github.com/Azure/azure-sdk-for-python/blob/main/sdk/ai/azure-ai-agents/samples/agents_tools/sample_agents_auto_function_call.py) or [`sample_agents_auto_function_call_async.py`](https://github.com/Azure/azure-sdk-for-python/blob/main/sdk/ai/azure-ai-agents/samples/agents_async/sample_agents_auto_function_call_async.py).
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- If you prefer to manage function execution manually, refer to [`sample_agents_stream_eventhandler_with_functions.py`](https://github.com/Azure/azure-sdk-for-python/blob/main/sdk/ai/azure-ai-agents/samples/agents_streaming/sample_agents_stream_eventhandler_with_functions.py) or
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[`sample_agents_functions.py`](https://github.com/Azure/azure-sdk-for-python/blob/main/sdk/ai/azure-ai-agents/samples/agents_tools/sample_agents_functions.py).
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### Create Agent With Azure Function Call
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‎sdk/ai/azure-ai-agents/azure/ai/agents/_version.py‎

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# Changes may cause incorrect behavior and will be lost if the code is regenerated.
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# --------------------------------------------------------------------------
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VERSION = "1.0.2"
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VERSION = "1.0.3"

‎sdk/ai/azure-ai-agents/samples/agents_async/sample_agents_auto_function_call_async.py‎

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# ------------------------------------
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# Copyright (c) Microsoft Corporation.
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# Licensed under the MIT License.
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# ------------------------------------
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import asyncio
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"""
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DESCRIPTION:
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This sample demonstrates how to enable automatic function calls by calling `enable_auto_function_calls`
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using an asynchronous client.
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USAGE:
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python sample_agents_auto_function_call_async.py
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Before running the sample:
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pip install azure-ai-agents azure-identity
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Set these environment variables with your own values:
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1) PROJECT_ENDPOINT - The Azure AI Project endpoint, as found in the Overview
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page of your Azure AI Foundry portal.
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2) MODEL_DEPLOYMENT_NAME - The deployment name of the AI model, as found under the "Name" column in
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the "Models + endpoints" tab in your Azure AI Foundry project.
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"""
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import os, sys
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from azure.ai.projects.aio import AIProjectClient
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from azure.identity import DefaultAzureCredential
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from azure.ai.agents.models import AsyncFunctionTool, AsyncToolSet
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from utils.user_async_functions import user_async_functions
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async def main() -> None:
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project_client = AIProjectClient(
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endpoint=os.environ["PROJECT_ENDPOINT"],
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credential=DefaultAzureCredential(),
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)
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async with project_client:
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agents_client = project_client.agents
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# To enable tool calls executed automatically you can pass a functions in one of these types:
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# Set[Callable[..., Any]], _models.AsyncFunctionTool, or _models.AsyncToolSet
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# Example 1:
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# agents_client.enable_auto_function_calls(user_async_functions)
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# Example 2:
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# functions = AsyncFunctionTool(user_async_functions)
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# agents_client.enable_auto_function_calls(functions)
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# Example 3:
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# functions = AsyncFunctionTool(user_async_functions)
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# toolset = AsyncToolSet()
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# toolset.add(functions)
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# agents_client.enable_auto_function_calls(toolset)
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agents_client.enable_auto_function_calls(user_async_functions)
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# Notices that `enable_auto_function_calls` can be made at any time.
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functions = AsyncFunctionTool(user_async_functions)
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# Initialize agent.
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# Whether you would like the functions to be called automatically or not, it is required to pass functions as tools or toolset.
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agent = await agents_client.create_agent(
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model=os.environ["MODEL_DEPLOYMENT_NAME"],
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name="my-agent",
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instructions="You are a helpful agent",
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tools=functions.definitions,
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)
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print(f"Created agent, ID: {agent.id}")
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# Create thread for communication
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thread = await agents_client.threads.create()
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print(f"Created thread, ID: {thread.id}")
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# Create message to thread
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message = await agents_client.messages.create(
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thread_id=thread.id,
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role="user",
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content="Hello, send an email with the datetime and weather information in New York?",
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)
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print(f"Created message, ID: {message.id}")
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# Create and process agent run in thread with tools
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run = await agents_client.runs.create_and_process(thread_id=thread.id, agent_id=agent.id)
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print(f"Run finished with status: {run.status}")
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if run.status == "failed":
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print(f"Run failed: {run.last_error}")
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# Delete the agent when done
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await agents_client.delete_agent(agent.id)
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print("Deleted agent")
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# Fetch and log all messages
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messages = agents_client.messages.list(thread_id=thread.id)
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async for msg in messages:
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if msg.text_messages:
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last_text = msg.text_messages[-1]
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print(f"{msg.role}: {last_text.text.value}")
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if __name__ == "__main__":
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asyncio.run(main())

‎sdk/ai/azure-ai-agents/samples/agents_tools/sample_agents_auto_function_call.py‎

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# ------------------------------------
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# Copyright (c) Microsoft Corporation.
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# Licensed under the MIT License.
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# ------------------------------------
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"""
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DESCRIPTION:
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This sample demonstrates how to enable automatic function calls by calling `enable_auto_function_calls`
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using a synchronous client.
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USAGE:
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python sample_agents_auto_function_call.py
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Before running the sample:
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pip install azure-ai-agents azure-identity
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Set these environment variables with your own values:
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1) PROJECT_ENDPOINT - The Azure AI Project endpoint, as found in the Overview
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page of your Azure AI Foundry portal.
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2) MODEL_DEPLOYMENT_NAME - The deployment name of the AI model, as found under the "Name" column in
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the "Models + endpoints" tab in your Azure AI Foundry project.
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"""
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import os, sys
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from azure.ai.projects import AIProjectClient
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from azure.identity import DefaultAzureCredential
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from azure.ai.agents.models import FunctionTool
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from samples.utils.user_functions import user_functions
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project_client = AIProjectClient(
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endpoint=os.environ["PROJECT_ENDPOINT"],
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credential=DefaultAzureCredential(),
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)
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with project_client:
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agents_client = project_client.agents
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agent = agents_client.create_agent(
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model=os.environ["MODEL_DEPLOYMENT_NAME"],
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name="my-agent",
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instructions="You are helpful agent",
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)
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# To enable tool calls executed automatically you can pass a functions in one of these types:
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# Set[Callable[..., Any]], _models.FunctionTool, or _models.ToolSet
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# Example 1:
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# agents_client.enable_auto_function_calls(user_functions)
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# Example 2:
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# functions = FunctionTool(user_functions)
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# agents_client.enable_auto_function_calls(functions)
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# Example 3:
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# functions = FunctionTool(user_functions)
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# toolset = ToolSet()
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# toolset.add(functions)
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# agents_client.enable_auto_function_calls(toolset)
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agents_client.enable_auto_function_calls(user_functions)
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# Notices that `enable_auto_function_calls` can be made at any time.
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functions = FunctionTool(user_functions)
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# Initialize agent.
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# Whether you would like the functions to be called automatically or not, it is required to pass functions as tools or toolset.
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agent = agents_client.create_agent(
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model=os.environ["MODEL_DEPLOYMENT_NAME"],
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name="my-agent",
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instructions="You are a helpful agent",
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tools=functions.definitions,
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)
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print(f"Created agent, ID: {agent.id}")
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# Create thread for communication
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thread = agents_client.threads.create()
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print(f"Created thread, ID: {thread.id}")
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# Create message to thread
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message = agents_client.messages.create(
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thread_id=thread.id,
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role="user",
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content="Hello, send an email with the datetime and weather information in New York?",
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)
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print(f"Created message, ID: {message.id}")
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# Create and process agent run in thread with tools
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run = agents_client.runs.create_and_process(thread_id=thread.id, agent_id=agent.id)
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print(f"Run finished with status: {run.status}")
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if run.status == "failed":
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print(f"Run failed: {run.last_error}")
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# Delete the agent when done
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agents_client.delete_agent(agent.id)
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print("Deleted agent")
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# Fetch and log all messages
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messages = agents_client.messages.list(thread_id=thread.id)
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for msg in messages:
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if msg.text_messages:
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last_text = msg.text_messages[-1]
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print(f"{msg.role}: {last_text.text.value}")

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