Python: [BREAKING] Renamed create_agent to as_agent (#3249)

* Renamed create_agent to as_agent

* Override for as_agent

* Added override

python/packages/azure-ai/agent_framework_azure_ai/_chat_client.py

@@ -4,18 +4,21 @@ import ast
 import json
 import re
 import sys
-from collections.abc import AsyncIterable, Mapping, MutableMapping, MutableSequence, Sequence
+from collections.abc import AsyncIterable, Callable, Mapping, MutableMapping, MutableSequence, Sequence
 from typing import Any, ClassVar, Generic, TypedDict
 
 from agent_framework import (
     AGENT_FRAMEWORK_USER_AGENT,
     BaseChatClient,
+    ChatAgent,
     ChatMessage,
+    ChatMessageStoreProtocol,
     ChatOptions,
     ChatResponse,
     ChatResponseUpdate,
     CitationAnnotation,
     Contents,
+    ContextProvider,
     DataContent,
     FunctionApprovalRequestContent,
     FunctionApprovalResponseContent,
@@ -23,6 +26,7 @@ from agent_framework import (
     FunctionResultContent,
     HostedFileContent,
     HostedMCPTool,
+    Middleware,
     Role,
     TextContent,
     TextSpanRegion,
@@ -1162,3 +1166,59 @@ class AzureAIAgentClient(BaseChatClient[TAzureAIAgentOptions], Generic[TAzureAIA
             The service URL for the chat client, or None if not set.
         """
         return self.agents_client._config.endpoint  # type: ignore
+
+    @override
+    def as_agent(
+        self,
+        *,
+        id: str | None = None,
+        name: str | None = None,
+        description: str | None = None,
+        instructions: str | None = None,
+        tools: ToolProtocol
+        | Callable[..., Any]
+        | MutableMapping[str, Any]
+        | Sequence[ToolProtocol | Callable[..., Any] | MutableMapping[str, Any]]
+        | None = None,
+        default_options: TAzureAIAgentOptions | None = None,
+        chat_message_store_factory: Callable[[], ChatMessageStoreProtocol] | None = None,
+        context_provider: ContextProvider | None = None,
+        middleware: Sequence[Middleware] | None = None,
+        **kwargs: Any,
+    ) -> ChatAgent[TAzureAIAgentOptions]:
+        """Convert this chat client to a ChatAgent.
+
+        This method creates a ChatAgent instance with this client pre-configured.
+        It does NOT create an agent on the Azure AI service - the actual agent
+        will be created on the server during the first invocation (run).
+
+        For creating and managing persistent agents on the server, use
+        :class:`~agent_framework_azure_ai.AzureAIAgentsProvider` instead.
+
+        Keyword Args:
+            id: The unique identifier for the agent. Will be created automatically if not provided.
+            name: The name of the agent.
+            description: A brief description of the agent's purpose.
+            instructions: Optional instructions for the agent.
+            tools: The tools to use for the request.
+            default_options: A TypedDict containing chat options.
+            chat_message_store_factory: Factory function to create an instance of ChatMessageStoreProtocol.
+            context_provider: Context providers to include during agent invocation.
+            middleware: List of middleware to intercept agent and function invocations.
+            kwargs: Any additional keyword arguments.
+
+        Returns:
+            A ChatAgent instance configured with this chat client.
+        """
+        return super().as_agent(
+            id=id,
+            name=name,
+            description=description,
+            instructions=instructions,
+            tools=tools,
+            default_options=default_options,
+            chat_message_store_factory=chat_message_store_factory,
+            context_provider=context_provider,
+            middleware=middleware,
+            **kwargs,
+        )

python/packages/azure-ai/agent_framework_azure_ai/_client.py

@@ -1,14 +1,19 @@
 # Copyright (c) Microsoft. All rights reserved.
 
 import sys
-from collections.abc import Mapping, MutableSequence
+from collections.abc import Callable, Mapping, MutableMapping, MutableSequence, Sequence
 from typing import TYPE_CHECKING, Any, ClassVar, Generic, TypedDict, TypeVar, cast
 
 from agent_framework import (
     AGENT_FRAMEWORK_USER_AGENT,
+    ChatAgent,
     ChatMessage,
+    ChatMessageStoreProtocol,
+    ContextProvider,
     HostedMCPTool,
+    Middleware,
     TextContent,
+    ToolProtocol,
     get_logger,
     use_chat_middleware,
     use_function_invocation,
@@ -511,3 +516,59 @@ class AzureAIClient(OpenAIBaseResponsesClient[TAzureAIClientOptions], Generic[TA
                         mcp["require_approval"] = {"never": {"tool_names": list(never_require_approvals)}}
 
         return mcp
+
+    @override
+    def as_agent(
+        self,
+        *,
+        id: str | None = None,
+        name: str | None = None,
+        description: str | None = None,
+        instructions: str | None = None,
+        tools: ToolProtocol
+        | Callable[..., Any]
+        | MutableMapping[str, Any]
+        | Sequence[ToolProtocol | Callable[..., Any] | MutableMapping[str, Any]]
+        | None = None,
+        default_options: TAzureAIClientOptions | None = None,
+        chat_message_store_factory: Callable[[], ChatMessageStoreProtocol] | None = None,
+        context_provider: ContextProvider | None = None,
+        middleware: Sequence[Middleware] | None = None,
+        **kwargs: Any,
+    ) -> ChatAgent[TAzureAIClientOptions]:
+        """Convert this chat client to a ChatAgent.
+
+        This method creates a ChatAgent instance with this client pre-configured.
+        It does NOT create an agent on the Azure AI service - the actual agent
+        will be created on the server during the first invocation (run).
+
+        For creating and managing persistent agents on the server, use
+        :class:`~agent_framework_azure_ai.AzureAIProjectAgentProvider` instead.
+
+        Keyword Args:
+            id: The unique identifier for the agent. Will be created automatically if not provided.
+            name: The name of the agent.
+            description: A brief description of the agent's purpose.
+            instructions: Optional instructions for the agent.
+            tools: The tools to use for the request.
+            default_options: A TypedDict containing chat options.
+            chat_message_store_factory: Factory function to create an instance of ChatMessageStoreProtocol.
+            context_provider: Context providers to include during agent invocation.
+            middleware: List of middleware to intercept agent and function invocations.
+            kwargs: Any additional keyword arguments.
+
+        Returns:
+            A ChatAgent instance configured with this chat client.
+        """
+        return super().as_agent(
+            id=id,
+            name=name,
+            description=description,
+            instructions=instructions,
+            tools=tools,
+            default_options=default_options,
+            chat_message_store_factory=chat_message_store_factory,
+            context_provider=context_provider,
+            middleware=middleware,
+            **kwargs,
+        )

python/packages/azurefunctions/agent_framework_azurefunctions/_app.py

@@ -104,13 +104,13 @@ class AgentFunctionApp(DFAppBase):
         from agent_framework.azure import AgentFunctionApp, AzureOpenAIChatClient
 
         # Create agents with unique names
-        weather_agent = AzureOpenAIChatClient(...).create_agent(
+        weather_agent = AzureOpenAIChatClient(...).as_agent(
             name="WeatherAgent",
             instructions="You are a helpful weather agent.",
             tools=[get_weather],
         )
 
-        math_agent = AzureOpenAIChatClient(...).create_agent(
+        math_agent = AzureOpenAIChatClient(...).as_agent(
             name="MathAgent",
             instructions="You are a helpful math assistant.",
             tools=[calculate],

python/packages/core/agent_framework/_clients.py

@@ -377,7 +377,7 @@ class BaseChatClient(SerializationMixin, ABC, Generic[TOptions_co]):
         """
         return "Unknown"
 
-    def create_agent(
+    def as_agent(
         self,
         *,
         id: str | None = None,
@@ -428,7 +428,7 @@ class BaseChatClient(SerializationMixin, ABC, Generic[TOptions_co]):
                 client = OpenAIChatClient(model_id="gpt-4")
 
                 # Create an agent using the convenience method
-                agent = client.create_agent(
+                agent = client.as_agent(
                     name="assistant",
                     instructions="You are a helpful assistant.",
                     default_options={"temperature": 0.7, "max_tokens": 500},

python/packages/core/agent_framework/_workflows/_handoff.py

@@ -710,9 +710,9 @@ class HandoffBuilder:
             from agent_framework.openai import OpenAIChatClient
 
             client = OpenAIChatClient()
-            triage = client.create_agent(instructions="...", name="triage_agent")
-            refund = client.create_agent(instructions="...", name="refund_agent")
-            billing = client.create_agent(instructions="...", name="billing_agent")
+            triage = client.as_agent(instructions="...", name="triage_agent")
+            refund = client.as_agent(instructions="...", name="refund_agent")
+            billing = client.as_agent(instructions="...", name="billing_agent")
 
             builder = HandoffBuilder().participants([triage, refund, billing])
             builder.with_start_agent(triage)

python/packages/core/agent_framework/openai/_assistants_client.py

@@ -9,8 +9,12 @@ from collections.abc import (
     Mapping,
     MutableMapping,
     MutableSequence,
+    Sequence,
 )
-from typing import Any, Generic, Literal, TypedDict, cast
+from typing import TYPE_CHECKING, Any, Generic, Literal, TypedDict, cast
+
+if TYPE_CHECKING:
+    from .._agents import ChatAgent
 
 from openai import AsyncOpenAI
 from openai.types.beta.threads import (
@@ -28,11 +32,14 @@ from openai.types.beta.threads.runs import RunStep
 from pydantic import ValidationError
 
 from .._clients import BaseChatClient
-from .._middleware import use_chat_middleware
+from .._memory import ContextProvider
+from .._middleware import Middleware, use_chat_middleware
+from .._threads import ChatMessageStoreProtocol
 from .._tools import (
     AIFunction,
     HostedCodeInterpreterTool,
     HostedFileSearchTool,
+    ToolProtocol,
     use_function_invocation,
 )
 from .._types import (
@@ -761,3 +768,59 @@ class OpenAIAssistantsClient(
             self.assistant_name = agent_name
         if description and not self.assistant_description:
             self.assistant_description = description
+
+    @override
+    def as_agent(
+        self,
+        *,
+        id: str | None = None,
+        name: str | None = None,
+        description: str | None = None,
+        instructions: str | None = None,
+        tools: ToolProtocol
+        | Callable[..., Any]
+        | MutableMapping[str, Any]
+        | Sequence[ToolProtocol | Callable[..., Any] | MutableMapping[str, Any]]
+        | None = None,
+        default_options: TOpenAIAssistantsOptions | None = None,
+        chat_message_store_factory: Callable[[], ChatMessageStoreProtocol] | None = None,
+        context_provider: ContextProvider | None = None,
+        middleware: Sequence[Middleware] | None = None,
+        **kwargs: Any,
+    ) -> "ChatAgent[TOpenAIAssistantsOptions]":
+        """Convert this chat client to a ChatAgent.
+
+        This method creates a ChatAgent instance with this client pre-configured.
+        It does NOT create an assistant on the OpenAI service - the actual assistant
+        will be created on the server during the first invocation (run).
+
+        For creating and managing persistent assistants on the server, use
+        :class:`~agent_framework.openai.OpenAIAssistantProvider` instead.
+
+        Keyword Args:
+            id: The unique identifier for the agent. Will be created automatically if not provided.
+            name: The name of the agent.
+            description: A brief description of the agent's purpose.
+            instructions: Optional instructions for the agent.
+            tools: The tools to use for the request.
+            default_options: A TypedDict containing chat options.
+            chat_message_store_factory: Factory function to create an instance of ChatMessageStoreProtocol.
+            context_provider: Context providers to include during agent invocation.
+            middleware: List of middleware to intercept agent and function invocations.
+            kwargs: Any additional keyword arguments.
+
+        Returns:
+            A ChatAgent instance configured with this chat client.
+        """
+        return super().as_agent(
+            id=id,
+            name=name,
+            description=description,
+            instructions=instructions,
+            tools=tools,
+            default_options=default_options,
+            chat_message_store_factory=chat_message_store_factory,
+            context_provider=context_provider,
+            middleware=middleware,
+            **kwargs,
+        )

python/packages/declarative/agent_framework_declarative/_workflows/_factory.py

@@ -72,7 +72,7 @@ class WorkflowFactory:
 
             # Pre-register agents for InvokeAzureAgent actions
             chat_client = AzureOpenAIChatClient()
-            agent = chat_client.create_agent(name="MyAgent", instructions="You are helpful.")
+            agent = chat_client.as_agent(name="MyAgent", instructions="You are helpful.")
 
             factory = WorkflowFactory(agents={"MyAgent": agent})
             workflow = factory.create_workflow_from_yaml_path("workflow.yaml")
@@ -115,8 +115,8 @@ class WorkflowFactory:
                 # With pre-registered agents
                 client = AzureOpenAIChatClient()
                 agents = {
-                    "WriterAgent": client.create_agent(name="Writer", instructions="Write content."),
-                    "ReviewerAgent": client.create_agent(name="Reviewer", instructions="Review content."),
+                    "WriterAgent": client.as_agent(name="Writer", instructions="Write content."),
+                    "ReviewerAgent": client.as_agent(name="Reviewer", instructions="Review content."),
                 }
                 factory = WorkflowFactory(agents=agents)
 
@@ -533,14 +533,14 @@ class WorkflowFactory:
                     WorkflowFactory()
                     .register_agent(
                         "Writer",
-                        client.create_agent(
+                        client.as_agent(
                             name="Writer",
                             instructions="Write content.",
                         ),
                     )
                     .register_agent(
                         "Reviewer",
-                        client.create_agent(
+                        client.as_agent(
                             name="Reviewer",
                             instructions="Review content.",
                         ),

python/packages/foundry_local/agent_framework_foundry_local/_foundry_local_client.py

@@ -169,7 +169,7 @@ class FoundryLocalClient(OpenAIBaseChatClient[TFoundryLocalChatOptions], Generic
 
                 client = FoundryLocalClient(model_id="phi-4-mini")
 
-                agent = client.create_agent(
+                agent = client.as_agent(
                     name="LocalAgent",
                     instructions="You are a helpful agent.",
                     tools=get_weather,

python/packages/foundry_local/samples/foundry_local_agent.py

@@ -65,7 +65,7 @@ async def main() -> None:
             print(
                 f"- {model.alias} for {model.task} - id={model.id} - {(model.file_size_mb / 1000):.2f} GB - {model.license}"
             )
-    agent = client.create_agent(
+    agent = client.as_agent(
         name="LocalAgent",
         instructions="You are a helpful agent.",
         tools=get_weather,

python/packages/lab/gaia/samples/azure_ai_agent.py

@@ -49,7 +49,7 @@ async def create_gaia_agent() -> AsyncIterator[ChatAgent]:
     """
     async with (
         AzureCliCredential() as credential,
-        AzureAIAgentClient(credential=credential).create_agent(
+        AzureAIAgentClient(credential=credential).as_agent(
             name="GaiaAgent",
             instructions="Solve tasks to your best ability. Use Bing Search to find "
             "information and Code Interpreter to perform calculations and data analysis.",

python/packages/lab/gaia/samples/openai_agent.py

@@ -49,7 +49,7 @@ async def create_gaia_agent() -> AsyncIterator[ChatAgent]:
     """
     chat_client = OpenAIResponsesClient()
 
-    async with chat_client.create_agent(
+    async with chat_client.as_agent(
         name="GaiaAgent",
         instructions="Solve tasks to your best ability. Use Web Search to find "
         "information and Code Interpreter to perform calculations and data analysis.",

python/samples/autogen-migration/orchestrations/01_round_robin_group_chat.py

@@ -59,17 +59,17 @@ async def run_agent_framework() -> None:
     client = OpenAIChatClient(model_id="gpt-4.1-mini")
 
     # Create specialized agents
-    researcher = client.create_agent(
+    researcher = client.as_agent(
         name="researcher",
         instructions="You are a researcher. Provide facts and data about the topic.",
     )
 
-    writer = client.create_agent(
+    writer = client.as_agent(
         name="writer",
         instructions="You are a writer. Turn research into engaging content.",
     )
 
-    editor = client.create_agent(
+    editor = client.as_agent(
         name="editor",
         instructions="You are an editor. Review and finalize the content.",
     )
@@ -109,17 +109,17 @@ async def run_agent_framework_with_cycle() -> None:
     client = OpenAIChatClient(model_id="gpt-4.1-mini")
 
     # Create specialized agents
-    researcher = client.create_agent(
+    researcher = client.as_agent(
         name="researcher",
         instructions="You are a researcher. Provide facts and data about the topic.",
     )
 
-    writer = client.create_agent(
+    writer = client.as_agent(
         name="writer",
         instructions="You are a writer. Turn research into engaging content.",
     )
 
-    editor = client.create_agent(
+    editor = client.as_agent(
         name="editor",
         instructions="You are an editor. Review and finalize the content. End with APPROVED if satisfied.",
     )

python/samples/autogen-migration/orchestrations/02_selector_group_chat.py

@@ -65,19 +65,19 @@ async def run_agent_framework() -> None:
     client = OpenAIChatClient(model_id="gpt-4.1-mini")
 
     # Create specialized agents
-    python_expert = client.create_agent(
+    python_expert = client.as_agent(
         name="python_expert",
         instructions="You are a Python programming expert. Answer Python-related questions.",
         description="Expert in Python programming",
     )
 
-    javascript_expert = client.create_agent(
+    javascript_expert = client.as_agent(
         name="javascript_expert",
         instructions="You are a JavaScript programming expert. Answer JavaScript-related questions.",
         description="Expert in JavaScript programming",
     )
 
-    database_expert = client.create_agent(
+    database_expert = client.as_agent(
         name="database_expert",
         instructions="You are a database expert. Answer SQL and database-related questions.",
         description="Expert in databases and SQL",
@@ -87,7 +87,7 @@ async def run_agent_framework() -> None:
         GroupChatBuilder()
         .participants([python_expert, javascript_expert, database_expert])
         .set_manager(
-            manager=client.create_agent(
+            manager=client.as_agent(
                 name="selector_manager",
                 instructions="Based on the conversation, select the most appropriate expert to respond next.",
             ),

python/samples/autogen-migration/orchestrations/03_swarm.py

@@ -108,7 +108,7 @@ async def run_agent_framework() -> None:
     client = OpenAIChatClient(model_id="gpt-4.1-mini")
 
     # Create triage agent
-    triage_agent = client.create_agent(
+    triage_agent = client.as_agent(
         name="triage",
         instructions=(
             "You are a triage agent. Analyze the user's request and route to the appropriate specialist:\n"
@@ -119,14 +119,14 @@ async def run_agent_framework() -> None:
     )
 
     # Create billing specialist
-    billing_agent = client.create_agent(
+    billing_agent = client.as_agent(
         name="billing_agent",
         instructions="You are a billing specialist. Help with payment and billing questions. Provide clear assistance.",
         description="Handles billing and payment questions",
     )
 
     # Create technical support specialist
-    tech_support = client.create_agent(
+    tech_support = client.as_agent(
         name="technical_support",
         instructions="You are technical support. Help with technical issues. Provide clear assistance.",
         description="Handles technical support questions",

python/samples/autogen-migration/orchestrations/04_magentic_one.py

@@ -69,19 +69,19 @@ async def run_agent_framework() -> None:
     client = OpenAIChatClient(model_id="gpt-4.1-mini")
 
     # Create specialized agents
-    researcher = client.create_agent(
+    researcher = client.as_agent(
         name="researcher",
         instructions="You are a research analyst. Gather and analyze information.",
         description="Research analyst for data gathering",
     )
 
-    coder = client.create_agent(
+    coder = client.as_agent(
         name="coder",
         instructions="You are a programmer. Write code based on requirements.",
         description="Software developer for implementation",
     )
 
-    reviewer = client.create_agent(
+    reviewer = client.as_agent(
         name="reviewer",
         instructions="You are a code reviewer. Review code for quality and correctness.",
         description="Code reviewer for quality assurance",

python/samples/autogen-migration/single_agent/01_basic_assistant_agent.py

@@ -33,7 +33,7 @@ async def run_agent_framework() -> None:
 
     # AF constructs a lightweight ChatAgent backed by OpenAIChatClient
     client = OpenAIChatClient(model_id="gpt-4.1-mini")
-    agent = client.create_agent(
+    agent = client.as_agent(
         name="assistant",
         instructions="You are a helpful assistant. Answer in one sentence.",
     )

python/samples/autogen-migration/single_agent/02_assistant_agent_with_tool.py

@@ -65,7 +65,7 @@ async def run_agent_framework() -> None:
 
     # Create agent with tool
     client = OpenAIChatClient(model_id="gpt-4.1-mini")
-    agent = client.create_agent(
+    agent = client.as_agent(
         name="assistant",
         instructions="You are a helpful assistant. Use available tools to answer questions.",
         tools=[get_weather],

python/samples/autogen-migration/single_agent/03_assistant_agent_thread_and_stream.py

@@ -40,7 +40,7 @@ async def run_agent_framework() -> None:
     from agent_framework.openai import OpenAIChatClient
 
     client = OpenAIChatClient(model_id="gpt-4.1-mini")
-    agent = client.create_agent(
+    agent = client.as_agent(
         name="assistant",
         instructions="You are a helpful math tutor.",
     )

python/samples/autogen-migration/single_agent/04_agent_as_tool.py

@@ -54,7 +54,7 @@ async def run_agent_framework() -> None:
     client = OpenAIChatClient(model_id="gpt-4.1-mini")
 
     # Create specialized writer agent
-    writer = client.create_agent(
+    writer = client.as_agent(
         name="writer",
         instructions="You are a creative writer. Write short, engaging content.",
     )
@@ -68,7 +68,7 @@ async def run_agent_framework() -> None:
     )
 
     # Create coordinator agent with writer tool
-    coordinator = client.create_agent(
+    coordinator = client.as_agent(
         name="coordinator",
         instructions="You coordinate with specialized agents. Delegate writing tasks to the writer agent.",
         tools=[writer_tool],

python/samples/demos/hosted_agents/agent_with_hosted_mcp/main.py

@@ -8,7 +8,7 @@ from azure.identity import DefaultAzureCredential
 
 def main():
     # Create an Agent using the Azure OpenAI Chat Client with a MCP Tool that connects to Microsoft Learn MCP
-    agent = AzureOpenAIChatClient(credential=DefaultAzureCredential()).create_agent(
+    agent = AzureOpenAIChatClient(credential=DefaultAzureCredential()).as_agent(
         name="DocsAgent",
         instructions="You are a helpful assistant that can help with microsoft documentation questions.",
         tools=HostedMCPTool(

python/samples/demos/hosted_agents/agent_with_text_search_rag/main.py

@@ -93,7 +93,7 @@ class TextSearchContextProvider(ContextProvider):
 
 def main():
     # Create an Agent using the Azure OpenAI Chat Client
-    agent = AzureOpenAIChatClient(credential=DefaultAzureCredential()).create_agent(
+    agent = AzureOpenAIChatClient(credential=DefaultAzureCredential()).as_agent(
         name="SupportSpecialist",
         instructions=(
             "You are a helpful support specialist for Contoso Outdoors. "

python/samples/demos/hosted_agents/agents_in_workflow/main.py

@@ -8,21 +8,21 @@ from azure.identity import DefaultAzureCredential  # pyright: ignore[reportUnkno
 
 def main():
     # Create agents
-    researcher = AzureOpenAIChatClient(credential=DefaultAzureCredential()).create_agent(
+    researcher = AzureOpenAIChatClient(credential=DefaultAzureCredential()).as_agent(
         instructions=(
             "You're an expert market and product researcher. "
             "Given a prompt, provide concise, factual insights, opportunities, and risks."
         ),
         name="researcher",
     )
-    marketer = AzureOpenAIChatClient(credential=DefaultAzureCredential()).create_agent(
+    marketer = AzureOpenAIChatClient(credential=DefaultAzureCredential()).as_agent(
         instructions=(
             "You're a creative marketing strategist. "
             "Craft compelling value propositions and target messaging aligned to the prompt."
         ),
         name="marketer",
     )
-    legal = AzureOpenAIChatClient(credential=DefaultAzureCredential()).create_agent(
+    legal = AzureOpenAIChatClient(credential=DefaultAzureCredential()).as_agent(
         instructions=(
             "You're a cautious legal/compliance reviewer. "
             "Highlight constraints, disclaimers, and policy concerns based on the prompt."

python/samples/demos/m365-agent/m365_agent_demo/app.py

@@ -93,7 +93,7 @@ def get_weather(
 
 def build_agent() -> ChatAgent:
     """Create and return the chat agent instance with weather tool registered."""
-    return OpenAIChatClient().create_agent(
+    return OpenAIChatClient().as_agent(
         name="WeatherAgent", instructions="You are a helpful weather agent.", tools=get_weather
     )
 

python/samples/demos/workflow_evaluation/create_workflow.py

@@ -78,7 +78,7 @@ class ResearchLead(Executor):
 
     def __init__(self, chat_client: AzureAIClient, id: str = "travel-planning-coordinator"):
         # store=True to preserve conversation history for evaluation
-        self.agent = chat_client.create_agent(
+        self.agent = chat_client.as_agent(
             id="travel-planning-coordinator",
             instructions=(
                 "You are the final coordinator. You will receive responses from multiple agents: "
@@ -220,7 +220,7 @@ async def _create_workflow(project_client, credential):
     travel_request_handler_client = AzureAIClient(
         project_client=project_client, credential=credential, agent_name="travel-request-handler"
     )
-    travel_request_handler = travel_request_handler_client.create_agent(
+    travel_request_handler = travel_request_handler_client.as_agent(
         id="travel-request-handler",
         instructions=(
             "You receive user travel queries and relay them to specialized agents. Extract key information: destination, dates, budget, and preferences. Pass this information forward clearly to the next agents."
@@ -233,7 +233,7 @@ async def _create_workflow(project_client, credential):
     hotel_search_client = AzureAIClient(
         project_client=project_client, credential=credential, agent_name="hotel-search-agent"
     )
-    hotel_search_agent = hotel_search_client.create_agent(
+    hotel_search_agent = hotel_search_client.as_agent(
         id="hotel-search-agent",
         instructions=(
             "You are a hotel search specialist. Your task is ONLY to search for and provide hotel information. Use search_hotels to find options, get_hotel_details for specifics, and check_availability to verify rooms. Output format: List hotel names, prices per night, total cost for the stay, locations, ratings, amenities, and addresses. IMPORTANT: Only provide hotel information without additional commentary."
@@ -247,7 +247,7 @@ async def _create_workflow(project_client, credential):
     flight_search_client = AzureAIClient(
         project_client=project_client, credential=credential, agent_name="flight-search-agent"
     )
-    flight_search_agent = flight_search_client.create_agent(
+    flight_search_agent = flight_search_client.as_agent(
         id="flight-search-agent",
         instructions=(
             "You are a flight search specialist. Your task is ONLY to search for and provide flight information. Use search_flights to find options, get_flight_details for specifics, and check_availability for seats. Output format: List flight numbers, airlines, departure/arrival times, prices, durations, and cabin class. IMPORTANT: Only provide flight information without additional commentary."
@@ -261,7 +261,7 @@ async def _create_workflow(project_client, credential):
     activity_search_client = AzureAIClient(
         project_client=project_client, credential=credential, agent_name="activity-search-agent"
     )
-    activity_search_agent = activity_search_client.create_agent(
+    activity_search_agent = activity_search_client.as_agent(
         id="activity-search-agent",
         instructions=(
             "You are an activities specialist. Your task is ONLY to search for and provide activity information. Use search_activities to find options for activities. Output format: List activity names, descriptions, prices, durations, ratings, and categories. IMPORTANT: Only provide activity information without additional commentary."
@@ -275,7 +275,7 @@ async def _create_workflow(project_client, credential):
     booking_confirmation_client = AzureAIClient(
         project_client=project_client, credential=credential, agent_name="booking-confirmation-agent"
     )
-    booking_confirmation_agent = booking_confirmation_client.create_agent(
+    booking_confirmation_agent = booking_confirmation_client.as_agent(
         id="booking-confirmation-agent",
         instructions=(
             "You confirm bookings. Use check_hotel_availability and check_flight_availability to verify slots, then confirm_booking to finalize. Provide ONLY: confirmation numbers, booking references, and confirmation status."
@@ -289,7 +289,7 @@ async def _create_workflow(project_client, credential):
     booking_payment_client = AzureAIClient(
         project_client=project_client, credential=credential, agent_name="booking-payment-agent"
     )
-    booking_payment_agent = booking_payment_client.create_agent(
+    booking_payment_agent = booking_payment_client.as_agent(
         id="booking-payment-agent",
         instructions=(
             "You process payments. Use validate_payment_method to verify payment, then process_payment to complete transactions. Provide ONLY: payment confirmation status, transaction IDs, and payment amounts."
@@ -303,7 +303,7 @@ async def _create_workflow(project_client, credential):
     booking_info_client = AzureAIClient(
         project_client=project_client, credential=credential, agent_name="booking-info-aggregation-agent"
     )
-    booking_info_aggregation_agent = booking_info_client.create_agent(
+    booking_info_aggregation_agent = booking_info_client.as_agent(
         id="booking-info-aggregation-agent",
         instructions=(
             "You aggregate hotel and flight search results. Receive options from search agents and organize them. Provide: top 2-3 hotel options with prices and top 2-3 flight options with prices in a structured format."

python/samples/getting_started/agents/anthropic/anthropic_advanced.py

@@ -17,7 +17,7 @@ This sample demonstrates using Anthropic with:
 
 async def main() -> None:
     """Example of streaming response (get results as they are generated)."""
-    agent = AnthropicClient[AnthropicChatOptions]().create_agent(
+    agent = AnthropicClient[AnthropicChatOptions]().as_agent(
         name="DocsAgent",
         instructions="You are a helpful agent for both Microsoft docs questions and general questions.",
         tools=[

python/samples/getting_started/agents/anthropic/anthropic_basic.py

@@ -26,7 +26,7 @@ async def non_streaming_example() -> None:
     print("=== Non-streaming Response Example ===")
 
     agent = AnthropicClient(
-    ).create_agent(
+    ).as_agent(
         name="WeatherAgent",
         instructions="You are a helpful weather agent.",
         tools=get_weather,
@@ -43,7 +43,7 @@ async def streaming_example() -> None:
     print("=== Streaming Response Example ===")
 
     agent = AnthropicClient(
-    ).create_agent(
+    ).as_agent(
         name="WeatherAgent",
         instructions="You are a helpful weather agent.",
         tools=get_weather,

python/samples/getting_started/agents/anthropic/anthropic_foundry.py

@@ -28,7 +28,7 @@ To use the Foundry integration ensure you have the following environment variabl
 
 async def main() -> None:
     """Example of streaming response (get results as they are generated)."""
-    agent = AnthropicClient(anthropic_client=AsyncAnthropicFoundry()).create_agent(
+    agent = AnthropicClient(anthropic_client=AsyncAnthropicFoundry()).as_agent(
         name="DocsAgent",
         instructions="You are a helpful agent for both Microsoft docs questions and general questions.",
         tools=[

python/samples/getting_started/agents/anthropic/anthropic_skills.py

@@ -31,7 +31,7 @@ async def main() -> None:
 
     # Create a agent with the pptx skill enabled
     # Skills also need the code interpreter tool to function
-    agent = client.create_agent(
+    agent = client.as_agent(
         name="DocsAgent",
         instructions="You are a helpful agent for creating powerpoint presentations.",
         tools=HostedCodeInterpreterTool(),

python/samples/getting_started/agents/azure_ai/azure_ai_provider_methods.py

@@ -145,49 +145,6 @@ async def get_agent_by_reference_example() -> None:
             )
 
 
-async def get_agent_by_details_example() -> None:
-    """Example of using provider.get_agent(details=...) with pre-fetched AgentDetails.
-
-    This method uses pre-fetched AgentDetails to get the latest version.
-    Use this when you already have AgentDetails from a previous API call.
-    """
-    print("=== provider.get_agent(details=...) Example ===")
-
-    async with (
-        AzureCliCredential() as credential,
-        AIProjectClient(endpoint=os.environ["AZURE_AI_PROJECT_ENDPOINT"], credential=credential) as project_client,
-    ):
-        # First, create an agent using the SDK directly
-        created_agent = await project_client.agents.create_version(
-            agent_name="TestAgentByDetails",
-            description="Test agent for get_agent by details example.",
-            definition=PromptAgentDefinition(
-                model=os.environ["AZURE_AI_MODEL_DEPLOYMENT_NAME"],
-                instructions="You are a helpful assistant. Always include an emoji in your response.",
-            ),
-        )
-
-        try:
-            # Fetch AgentDetails separately (simulating a previous API call)
-            agent_details = await project_client.agents.get(agent_name=created_agent.name)
-
-            # Get the agent using the pre-fetched details (sync - no HTTP call)
-            provider = AzureAIProjectAgentProvider(project_client=project_client)
-            agent = provider.as_agent(agent_details.versions.latest)
-
-            print(f"Retrieved agent: {agent.name} (from pre-fetched details)")
-
-            query = "How are you today?"
-            print(f"User: {query}")
-            result = await agent.run(query)
-            print(f"Agent: {result}\n")
-        finally:
-            # Clean up the agent
-            await project_client.agents.delete_version(
-                agent_name=created_agent.name, agent_version=created_agent.version
-            )
-
-
 async def multiple_agents_example() -> None:
     """Example of using a single provider to spawn multiple agents.
 
@@ -284,7 +241,6 @@ async def main() -> None:
     await create_agent_example()
     await get_agent_by_name_example()
     await get_agent_by_reference_example()
-    await get_agent_by_details_example()
     await as_agent_example()
     await multiple_agents_example()
 

python/samples/getting_started/agents/azure_openai/azure_assistants_basic.py

@@ -32,7 +32,7 @@ async def non_streaming_example() -> None:
     # and deleted after getting a response
     # For authentication, run `az login` command in terminal or replace AzureCliCredential with preferred
     # authentication option.
-    async with AzureOpenAIAssistantsClient(credential=AzureCliCredential()).create_agent(
+    async with AzureOpenAIAssistantsClient(credential=AzureCliCredential()).as_agent(
         instructions="You are a helpful weather agent.",
         tools=get_weather,
     ) as agent:
@@ -48,7 +48,7 @@ async def streaming_example() -> None:
 
     # Since no assistant ID is provided, the assistant will be automatically created
     # and deleted after getting a response
-    async with AzureOpenAIAssistantsClient(credential=AzureCliCredential()).create_agent(
+    async with AzureOpenAIAssistantsClient(credential=AzureCliCredential()).as_agent(
         instructions="You are a helpful weather agent.",
         tools=get_weather,
     ) as agent:

python/samples/getting_started/agents/azure_openai/azure_assistants_with_explicit_settings.py

@@ -34,7 +34,7 @@ async def main() -> None:
         endpoint=os.environ["AZURE_OPENAI_ENDPOINT"],
         deployment_name=os.environ["AZURE_OPENAI_CHAT_DEPLOYMENT_NAME"],
         credential=AzureCliCredential(),
-    ).create_agent(
+    ).as_agent(
         instructions="You are a helpful weather agent.",
         tools=get_weather,
     ) as agent:

python/samples/getting_started/agents/azure_openai/azure_chat_client_basic.py

@@ -31,7 +31,7 @@ async def non_streaming_example() -> None:
     # Create agent with Azure Chat Client
     # For authentication, run `az login` command in terminal or replace AzureCliCredential with preferred
     # authentication option.
-    agent = AzureOpenAIChatClient(credential=AzureCliCredential()).create_agent(
+    agent = AzureOpenAIChatClient(credential=AzureCliCredential()).as_agent(
         instructions="You are a helpful weather agent.",
         tools=get_weather,
     )
@@ -49,7 +49,7 @@ async def streaming_example() -> None:
     # Create agent with Azure Chat Client
     # For authentication, run `az login` command in terminal or replace AzureCliCredential with preferred
     # authentication option.
-    agent = AzureOpenAIChatClient(credential=AzureCliCredential()).create_agent(
+    agent = AzureOpenAIChatClient(credential=AzureCliCredential()).as_agent(
         instructions="You are a helpful weather agent.",
         tools=get_weather,
     )

python/samples/getting_started/agents/azure_openai/azure_chat_client_with_explicit_settings.py

@@ -34,7 +34,7 @@ async def main() -> None:
         deployment_name=os.environ["AZURE_OPENAI_CHAT_DEPLOYMENT_NAME"],
         endpoint=os.environ["AZURE_OPENAI_ENDPOINT"],
         credential=AzureCliCredential(),
-    ).create_agent(
+    ).as_agent(
         instructions="You are a helpful weather agent.",
         tools=get_weather,
     )

python/samples/getting_started/agents/azure_openai/azure_responses_client_basic.py

@@ -30,7 +30,7 @@ async def non_streaming_example() -> None:
 
     # For authentication, run `az login` command in terminal or replace AzureCliCredential with preferred
     # authentication option.
-    agent = AzureOpenAIResponsesClient(credential=AzureCliCredential()).create_agent(
+    agent = AzureOpenAIResponsesClient(credential=AzureCliCredential()).as_agent(
         instructions="You are a helpful weather agent.",
         tools=get_weather,
     )
@@ -47,7 +47,7 @@ async def streaming_example() -> None:
 
     # For authentication, run `az login` command in terminal or replace AzureCliCredential with preferred
     # authentication option.
-    agent = AzureOpenAIResponsesClient(credential=AzureCliCredential()).create_agent(
+    agent = AzureOpenAIResponsesClient(credential=AzureCliCredential()).as_agent(
         instructions="You are a helpful weather agent.",
         tools=get_weather,
     )

python/samples/getting_started/agents/azure_openai/azure_responses_client_image_analysis.py

@@ -18,7 +18,7 @@ async def main():
     print("=== Azure Responses Agent with Image Analysis ===")
 
     # 1. Create an Azure Responses agent with vision capabilities
-    agent = AzureOpenAIResponsesClient(credential=AzureCliCredential()).create_agent(
+    agent = AzureOpenAIResponsesClient(credential=AzureCliCredential()).as_agent(
         name="VisionAgent",
         instructions="You are a helpful agent that can analyze images.",
     )

python/samples/getting_started/agents/azure_openai/azure_responses_client_with_explicit_settings.py

@@ -34,7 +34,7 @@ async def main() -> None:
         deployment_name=os.environ["AZURE_OPENAI_RESPONSES_DEPLOYMENT_NAME"],
         endpoint=os.environ["AZURE_OPENAI_ENDPOINT"],
         credential=AzureCliCredential(),
-    ).create_agent(
+    ).as_agent(
         instructions="You are a helpful weather agent.",
         tools=get_weather,
     )

python/samples/getting_started/agents/azure_openai/azure_responses_client_with_local_mcp.py

@@ -37,7 +37,7 @@ async def main():
         credential=credential,
     )
 
-    agent: ChatAgent = responses_client.create_agent(
+    agent: ChatAgent = responses_client.as_agent(
         name="DocsAgent",
         instructions=("You are a helpful assistant that can help with Microsoft documentation questions."),
     )

python/samples/getting_started/agents/custom/custom_chat_client.py

@@ -125,7 +125,7 @@ async def main() -> None:
     print(f"Direct response: {direct_response.messages[0].text}")
 
     # Create an agent using the custom chat client
-    echo_agent = echo_client.create_agent(
+    echo_agent = echo_client.as_agent(
         name="EchoAgent",
         instructions="You are a helpful assistant that echoes back what users say.",
     )

python/samples/getting_started/agents/ollama/ollama_agent_basic.py

@@ -27,7 +27,7 @@ async def non_streaming_example() -> None:
     """Example of non-streaming response (get the complete result at once)."""
     print("=== Non-streaming Response Example ===")
 
-    agent = OllamaChatClient().create_agent(
+    agent = OllamaChatClient().as_agent(
         name="TimeAgent",
         instructions="You are a helpful time agent answer in one sentence.",
         tools=get_time,
@@ -43,7 +43,7 @@ async def streaming_example() -> None:
     """Example of streaming response (get results as they are generated)."""
     print("=== Streaming Response Example ===")
 
-    agent = OllamaChatClient().create_agent(
+    agent = OllamaChatClient().as_agent(
         name="TimeAgent",
         instructions="You are a helpful time agent answer in one sentence.",
         tools=get_time,

python/samples/getting_started/agents/ollama/ollama_agent_reasoning.py

@@ -21,7 +21,7 @@ https://ollama.com/
 async def reasoning_example() -> None:
     print("=== Response Reasoning Example ===")
 
-    agent = OllamaChatClient().create_agent(
+    agent = OllamaChatClient().as_agent(
         name="TimeAgent",
         instructions="You are a helpful agent answer in one sentence.",
         default_options={"think": True},  # Enable Reasoning on agent level

python/samples/getting_started/agents/ollama/ollama_with_openai_chat_client.py

@@ -36,7 +36,7 @@ async def non_streaming_example() -> None:
         api_key="ollama",  # Just a placeholder, Ollama doesn't require API key
         base_url=os.getenv("OLLAMA_ENDPOINT"),
         model_id=os.getenv("OLLAMA_MODEL"),
-    ).create_agent(
+    ).as_agent(
         name="WeatherAgent",
         instructions="You are a helpful weather agent.",
         tools=get_weather,
@@ -56,7 +56,7 @@ async def streaming_example() -> None:
         api_key="ollama",  # Just a placeholder, Ollama doesn't require API key
         base_url=os.getenv("OLLAMA_ENDPOINT"),
         model_id=os.getenv("OLLAMA_MODEL"),
-    ).create_agent(
+    ).as_agent(
         name="WeatherAgent",
         instructions="You are a helpful weather agent.",
         tools=get_weather,

python/samples/getting_started/agents/openai/openai_chat_client_basic.py

@@ -26,7 +26,7 @@ async def non_streaming_example() -> None:
     """Example of non-streaming response (get the complete result at once)."""
     print("=== Non-streaming Response Example ===")
 
-    agent = OpenAIChatClient().create_agent(
+    agent = OpenAIChatClient().as_agent(
         name="WeatherAgent",
         instructions="You are a helpful weather agent.",
         tools=get_weather,
@@ -42,7 +42,7 @@ async def streaming_example() -> None:
     """Example of streaming response (get results as they are generated)."""
     print("=== Streaming Response Example ===")
 
-    agent = OpenAIChatClient().create_agent(
+    agent = OpenAIChatClient().as_agent(
         name="WeatherAgent",
         instructions="You are a helpful weather agent.",
         tools=get_weather,

python/samples/getting_started/agents/openai/openai_chat_client_with_explicit_settings.py

@@ -30,7 +30,7 @@ async def main() -> None:
     agent = OpenAIChatClient(
         model_id=os.environ["OPENAI_CHAT_MODEL_ID"],
         api_key=os.environ["OPENAI_API_KEY"],
-    ).create_agent(
+    ).as_agent(
         instructions="You are a helpful weather agent.",
         tools=get_weather,
     )

python/samples/getting_started/agents/openai/openai_chat_client_with_local_mcp.py

@@ -55,7 +55,7 @@ async def mcp_tools_on_agent_level() -> None:
     # Tools are provided when creating the agent
     # The agent can use these tools for any query during its lifetime
     # The agent will connect to the MCP server through its context manager.
-    async with OpenAIChatClient().create_agent(
+    async with OpenAIChatClient().as_agent(
         name="DocsAgent",
         instructions="You are a helpful assistant that can help with microsoft documentation questions.",
         tools=MCPStreamableHTTPTool(  # Tools defined at agent creation

python/samples/getting_started/agents/openai/openai_chat_client_with_runtime_json_schema.py

@@ -32,7 +32,7 @@ runtime_schema = {
 async def non_streaming_example() -> None:
     print("=== Non-streaming runtime JSON schema example ===")
 
-    agent = OpenAIChatClient[OpenAIChatOptions]().create_agent(
+    agent = OpenAIChatClient[OpenAIChatOptions]().as_agent(
         name="RuntimeSchemaAgent",
         instructions="Return only JSON that matches the provided schema. Do not add commentary.",
     )
@@ -65,7 +65,7 @@ async def non_streaming_example() -> None:
 async def streaming_example() -> None:
     print("=== Streaming runtime JSON schema example ===")
 
-    agent = OpenAIChatClient().create_agent(
+    agent = OpenAIChatClient().as_agent(
         name="RuntimeSchemaAgent",
         instructions="Return only JSON that matches the provided schema. Do not add commentary.",
     )

python/samples/getting_started/agents/openai/openai_responses_client_image_analysis.py

@@ -17,7 +17,7 @@ async def main():
     print("=== OpenAI Responses Agent with Image Analysis ===")
 
     # 1. Create an OpenAI Responses agent with vision capabilities
-    agent = OpenAIResponsesClient().create_agent(
+    agent = OpenAIResponsesClient().as_agent(
         name="VisionAgent",
         instructions="You are a helpful agent that can analyze images.",
     )

python/samples/getting_started/agents/openai/openai_responses_client_image_generation.py

@@ -48,7 +48,7 @@ async def main() -> None:
     print("=== OpenAI Responses Image Generation Agent Example ===")
 
     # Create an agent with customized image generation options
-    agent = OpenAIResponsesClient().create_agent(
+    agent = OpenAIResponsesClient().as_agent(
         instructions="You are a helpful AI that can generate images.",
         tools=[
             HostedImageGenerationTool(

python/samples/getting_started/agents/openai/openai_responses_client_reasoning.py

@@ -19,7 +19,7 @@ In this case they are here: https://platform.openai.com/docs/api-reference/respo
 """
 
 
-agent = OpenAIResponsesClient[OpenAIResponsesOptions](model_id="gpt-5").create_agent(
+agent = OpenAIResponsesClient[OpenAIResponsesOptions](model_id="gpt-5").as_agent(
     name="MathHelper",
     instructions="You are a personal math tutor. When asked a math question, "
     "reason over how best to approach the problem and share your thought process.",

python/samples/getting_started/agents/openai/openai_responses_client_streaming_image_generation.py

@@ -42,7 +42,7 @@ async def main():
     print("=== OpenAI Streaming Image Generation Example ===\n")
 
     # Create agent with streaming image generation enabled
-    agent = OpenAIResponsesClient().create_agent(
+    agent = OpenAIResponsesClient().as_agent(
         instructions="You are a helpful agent that can generate images.",
         tools=[
             HostedImageGenerationTool(

python/samples/getting_started/agents/openai/openai_responses_client_with_explicit_settings.py

@@ -30,7 +30,7 @@ async def main() -> None:
     agent = OpenAIResponsesClient(
         model_id=os.environ["OPENAI_RESPONSES_MODEL_ID"],
         api_key=os.environ["OPENAI_API_KEY"],
-    ).create_agent(
+    ).as_agent(
         instructions="You are a helpful weather agent.",
         tools=get_weather,
     )

python/samples/getting_started/agents/openai/openai_responses_client_with_runtime_json_schema.py

@@ -32,7 +32,7 @@ runtime_schema = {
 async def non_streaming_example() -> None:
     print("=== Non-streaming runtime JSON schema example ===")
 
-    agent = OpenAIResponsesClient().create_agent(
+    agent = OpenAIResponsesClient().as_agent(
         name="RuntimeSchemaAgent",
         instructions="Return only JSON that matches the provided schema. Do not add commentary.",
     )
@@ -65,7 +65,7 @@ async def non_streaming_example() -> None:
 async def streaming_example() -> None:
     print("=== Streaming runtime JSON schema example ===")
 
-    agent = OpenAIResponsesClient().create_agent(
+    agent = OpenAIResponsesClient().as_agent(
         name="RuntimeSchemaAgent",
         instructions="Return only JSON that matches the provided schema. Do not add commentary.",
     )

python/samples/getting_started/agents/openai/openai_responses_client_with_structured_output.py

@@ -25,7 +25,7 @@ async def non_streaming_example() -> None:
     print("=== Non-streaming example ===")
 
     # Create an OpenAI Responses agent
-    agent = OpenAIResponsesClient().create_agent(
+    agent = OpenAIResponsesClient().as_agent(
         name="CityAgent",
         instructions="You are a helpful agent that describes cities in a structured format.",
     )
@@ -51,7 +51,7 @@ async def streaming_example() -> None:
     print("=== Streaming example ===")
 
     # Create an OpenAI Responses agent
-    agent = OpenAIResponsesClient().create_agent(
+    agent = OpenAIResponsesClient().as_agent(
         name="CityAgent",
         instructions="You are a helpful agent that describes cities in a structured format.",
     )

python/samples/getting_started/azure_functions/01_single_agent/function_app.py

@@ -16,7 +16,7 @@ from azure.identity import AzureCliCredential
 def _create_agent() -> Any:
     """Create the Joker agent."""
 
-    return AzureOpenAIChatClient(credential=AzureCliCredential()).create_agent(
+    return AzureOpenAIChatClient(credential=AzureCliCredential()).as_agent(
         name="Joker",
         instructions="You are good at telling jokes.",
     )

python/samples/getting_started/azure_functions/02_multi_agent/function_app.py

@@ -52,13 +52,13 @@ def calculate_tip(bill_amount: float, tip_percentage: float = 15.0) -> dict[str,
 # 1. Create multiple agents, each with its own instruction set and tools.
 chat_client = AzureOpenAIChatClient(credential=AzureCliCredential())
 
-weather_agent = chat_client.create_agent(
+weather_agent = chat_client.as_agent(
     name="WeatherAgent",
     instructions="You are a helpful weather assistant. Provide current weather information.",
     tools=[get_weather],
 )
 
-math_agent = chat_client.create_agent(
+math_agent = chat_client.as_agent(
     name="MathAgent",
     instructions="You are a helpful math assistant. Help users with calculations like tip calculations.",
     tools=[calculate_tip],

python/samples/getting_started/azure_functions/03_reliable_streaming/function_app.py

@@ -151,7 +151,7 @@ redis_callback = RedisStreamCallback()
 # Create the travel planner agent
 def create_travel_agent():
     """Create the TravelPlanner agent with tools."""
-    return AzureOpenAIChatClient(credential=AzureCliCredential()).create_agent(
+    return AzureOpenAIChatClient(credential=AzureCliCredential()).as_agent(
         name="TravelPlanner",
         instructions="""You are an expert travel planner who creates detailed, personalized travel itineraries.
 When asked to plan a trip, you should:

python/samples/getting_started/azure_functions/04_single_agent_orchestration_chaining/function_app.py

@@ -32,7 +32,7 @@ def _create_writer_agent() -> Any:
         "when given an improved sentence you polish it further."
     )
 
-    return AzureOpenAIChatClient(credential=AzureCliCredential()).create_agent(
+    return AzureOpenAIChatClient(credential=AzureCliCredential()).as_agent(
         name=WRITER_AGENT_NAME,
         instructions=instructions,
     )

python/samples/getting_started/azure_functions/05_multi_agent_orchestration_concurrency/function_app.py

@@ -29,12 +29,12 @@ CHEMIST_AGENT_NAME = "ChemistAgent"
 def _create_agents() -> list[Any]:
     chat_client = AzureOpenAIChatClient(credential=AzureCliCredential())
 
-    physicist = chat_client.create_agent(
+    physicist = chat_client.as_agent(
         name=PHYSICIST_AGENT_NAME,
         instructions="You are an expert in physics. You answer questions from a physics perspective.",
     )
 
-    chemist = chat_client.create_agent(
+    chemist = chat_client.as_agent(
         name=CHEMIST_AGENT_NAME,
         instructions="You are an expert in chemistry. You answer questions from a chemistry perspective.",
     )

python/samples/getting_started/azure_functions/06_multi_agent_orchestration_conditionals/function_app.py

@@ -45,12 +45,12 @@ class EmailPayload(BaseModel):
 def _create_agents() -> list[Any]:
     chat_client = AzureOpenAIChatClient(credential=AzureCliCredential())
 
-    spam_agent = chat_client.create_agent(
+    spam_agent = chat_client.as_agent(
         name=SPAM_AGENT_NAME,
         instructions="You are a spam detection assistant that identifies spam emails.",
     )
 
-    email_agent = chat_client.create_agent(
+    email_agent = chat_client.as_agent(
         name=EMAIL_AGENT_NAME,
         instructions="You are an email assistant that helps users draft responses to emails with professionalism.",
     )

python/samples/getting_started/azure_functions/07_single_agent_orchestration_hitl/function_app.py

@@ -51,7 +51,7 @@ def _create_writer_agent() -> Any:
         "Return your response as JSON with 'title' and 'content' fields."
     )
 
-    return AzureOpenAIChatClient(credential=AzureCliCredential()).create_agent(
+    return AzureOpenAIChatClient(credential=AzureCliCredential()).as_agent(
         name=WRITER_AGENT_NAME,
         instructions=instructions,
     )

python/samples/getting_started/azure_functions/08_mcp_server/README.md

@@ -145,17 +145,17 @@ from agent_framework.azure import AgentFunctionApp, AzureOpenAIChatClient
 chat_client = AzureOpenAIChatClient()
 
 # Define agents with different roles
-joker_agent = chat_client.create_agent(
+joker_agent = chat_client.as_agent(
     name="Joker",
     instructions="You are good at telling jokes.",
 )
 
-stock_agent = chat_client.create_agent(
+stock_agent = chat_client.as_agent(
     name="StockAdvisor",
     instructions="Check stock prices.",
 )
 
-plant_agent = chat_client.create_agent(
+plant_agent = chat_client.as_agent(
     name="PlantAdvisor",
     instructions="Recommend plants.",
     description="Get plant recommendations.",

python/samples/getting_started/azure_functions/08_mcp_server/function_app.py

@@ -30,19 +30,19 @@ chat_client = AzureOpenAIChatClient()
 
 # Define three AI agents with different roles
 # Agent 1: Joker - HTTP trigger only (default)
-agent1 = chat_client.create_agent(
+agent1 = chat_client.as_agent(
     name="Joker",
     instructions="You are good at telling jokes.",
 )
 
 # Agent 2: StockAdvisor - MCP tool trigger only
-agent2 = chat_client.create_agent(
+agent2 = chat_client.as_agent(
     name="StockAdvisor",
     instructions="Check stock prices.",
 )
 
 # Agent 3: PlantAdvisor - Both HTTP and MCP tool triggers
-agent3 = chat_client.create_agent(
+agent3 = chat_client.as_agent(
     name="PlantAdvisor",
     instructions="Recommend plants.",
     description="Get plant recommendations.",

python/samples/getting_started/context_providers/mem0/mem0_basic.py

@@ -32,7 +32,7 @@ async def main() -> None:
     # For Mem0 authentication, set Mem0 API key via "api_key" parameter or MEM0_API_KEY environment variable.
     async with (
         AzureCliCredential() as credential,
-        AzureAIAgentClient(credential=credential).create_agent(
+        AzureAIAgentClient(credential=credential).as_agent(
             name="FriendlyAssistant",
             instructions="You are a friendly assistant.",
             tools=retrieve_company_report,

python/samples/getting_started/context_providers/mem0/mem0_oss.py

@@ -35,7 +35,7 @@ async def main() -> None:
     local_mem0_client = AsyncMemory()
     async with (
         AzureCliCredential() as credential,
-        AzureAIAgentClient(credential=credential).create_agent(
+        AzureAIAgentClient(credential=credential).as_agent(
             name="FriendlyAssistant",
             instructions="You are a friendly assistant.",
             tools=retrieve_company_report,

python/samples/getting_started/context_providers/mem0/mem0_threads.py

@@ -27,7 +27,7 @@ async def example_global_thread_scope() -> None:
 
     async with (
         AzureCliCredential() as credential,
-        AzureAIAgentClient(credential=credential).create_agent(
+        AzureAIAgentClient(credential=credential).as_agent(
             name="GlobalMemoryAssistant",
             instructions="You are an assistant that remembers user preferences across conversations.",
             tools=get_user_preferences,
@@ -65,7 +65,7 @@ async def example_per_operation_thread_scope() -> None:
 
     async with (
         AzureCliCredential() as credential,
-        AzureAIAgentClient(credential=credential).create_agent(
+        AzureAIAgentClient(credential=credential).as_agent(
             name="ScopedMemoryAssistant",
             instructions="You are an assistant with thread-scoped memory.",
             tools=get_user_preferences,
@@ -113,14 +113,14 @@ async def example_multiple_agents() -> None:
 
     async with (
         AzureCliCredential() as credential,
-        AzureAIAgentClient(credential=credential).create_agent(
+        AzureAIAgentClient(credential=credential).as_agent(
             name="PersonalAssistant",
             instructions="You are a personal assistant that helps with personal tasks.",
             context_provider=Mem0Provider(
                 agent_id=agent_id_1,
             ),
         ) as personal_agent,
-        AzureAIAgentClient(credential=credential).create_agent(
+        AzureAIAgentClient(credential=credential).as_agent(
             name="WorkAssistant",
             instructions="You are a work assistant that helps with professional tasks.",
             context_provider=Mem0Provider(

python/samples/getting_started/context_providers/redis/azure_redis_conversation.py

@@ -77,7 +77,7 @@ async def main() -> None:
     client = OpenAIChatClient()
 
     # Create agent with Azure Redis store
-    agent = client.create_agent(
+    agent = client.as_agent(
         name="AzureRedisAssistant",
         instructions="You are a helpful assistant.",
         chat_message_store_factory=chat_message_store_factory,

python/samples/getting_started/context_providers/redis/redis_basics.py

@@ -178,7 +178,7 @@ async def main() -> None:
     client = OpenAIChatClient(model_id=os.getenv("OPENAI_CHAT_MODEL_ID"), api_key=os.getenv("OPENAI_API_KEY"))
     # Create agent wired to the Redis context provider. The provider automatically
     # persists conversational details and surfaces relevant context on each turn.
-    agent = client.create_agent(
+    agent = client.as_agent(
         name="MemoryEnhancedAssistant",
         instructions=(
             "You are a helpful assistant. Personalize replies using provided context. "
@@ -220,7 +220,7 @@ async def main() -> None:
     # Create agent exposing the flight search tool. Tool outputs are captured by the
     # provider and become retrievable context for later turns.
     client = OpenAIChatClient(model_id=os.getenv("OPENAI_CHAT_MODEL_ID"), api_key=os.getenv("OPENAI_API_KEY"))
-    agent = client.create_agent(
+    agent = client.as_agent(
         name="MemoryEnhancedAssistant",
         instructions=(
             "You are a helpful assistant. Personalize replies using provided context. "

python/samples/getting_started/context_providers/redis/redis_conversation.py

@@ -63,7 +63,7 @@ async def main() -> None:
     client = OpenAIChatClient(model_id=os.getenv("OPENAI_CHAT_MODEL_ID"), api_key=os.getenv("OPENAI_API_KEY"))
     # Create agent wired to the Redis context provider. The provider automatically
     # persists conversational details and surfaces relevant context on each turn.
-    agent = client.create_agent(
+    agent = client.as_agent(
         name="MemoryEnhancedAssistant",
         instructions=(
             "You are a helpful assistant. Personalize replies using provided context. "

python/samples/getting_started/context_providers/redis/redis_threads.py

@@ -63,7 +63,7 @@ async def example_global_thread_scope() -> None:
         scope_to_per_operation_thread_id=False,  # Share memories across all threads
     )
 
-    agent = client.create_agent(
+    agent = client.as_agent(
         name="GlobalMemoryAssistant",
         instructions=(
             "You are a helpful assistant. Personalize replies using provided context. "
@@ -125,7 +125,7 @@ async def example_per_operation_thread_scope() -> None:
         vector_distance_metric="cosine",
     )
 
-    agent = client.create_agent(
+    agent = client.as_agent(
         name="ScopedMemoryAssistant",
         instructions="You are an assistant with thread-scoped memory.",
         context_provider=provider,
@@ -190,7 +190,7 @@ async def example_multiple_agents() -> None:
         vector_distance_metric="cosine",
     )
 
-    personal_agent = client.create_agent(
+    personal_agent = client.as_agent(
         name="PersonalAssistant",
         instructions="You are a personal assistant that helps with personal tasks.",
         context_provider=personal_provider,
@@ -208,7 +208,7 @@ async def example_multiple_agents() -> None:
         vector_distance_metric="cosine",
     )
 
-    work_agent = client.create_agent(
+    work_agent = client.as_agent(
         name="WorkAssistant",
         instructions="You are a work assistant that helps with professional tasks.",
         context_provider=work_provider,

python/samples/getting_started/devui/workflow_agents/workflow.py

@@ -62,7 +62,7 @@ def is_approved(message: Any) -> bool:
 chat_client = AzureOpenAIChatClient(api_key=os.environ.get("AZURE_OPENAI_API_KEY", ""))
 
 # Create Writer agent - generates content
-writer = chat_client.create_agent(
+writer = chat_client.as_agent(
     name="Writer",
     instructions=(
         "You are an excellent content writer. "
@@ -72,7 +72,7 @@ writer = chat_client.create_agent(
 )
 
 # Create Reviewer agent - evaluates and provides structured feedback
-reviewer = chat_client.create_agent(
+reviewer = chat_client.as_agent(
     name="Reviewer",
     instructions=(
         "You are an expert content reviewer. "
@@ -90,7 +90,7 @@ reviewer = chat_client.create_agent(
 )
 
 # Create Editor agent - improves content based on feedback
-editor = chat_client.create_agent(
+editor = chat_client.as_agent(
     name="Editor",
     instructions=(
         "You are a skilled editor. "
@@ -101,7 +101,7 @@ editor = chat_client.create_agent(
 )
 
 # Create Publisher agent - formats content for publication
-publisher = chat_client.create_agent(
+publisher = chat_client.as_agent(
     name="Publisher",
     instructions=(
         "You are a publishing agent. "
@@ -111,7 +111,7 @@ publisher = chat_client.create_agent(
 )
 
 # Create Summarizer agent - creates final publication report
-summarizer = chat_client.create_agent(
+summarizer = chat_client.as_agent(
     name="Summarizer",
     instructions=(
         "You are a summarizer agent. "

python/samples/getting_started/evaluation/red_teaming/README.md

@@ -113,7 +113,7 @@ async def main() -> None:
     credential = AzureCliCredential()
 
     # 2. Create agent inline
-    agent = AzureOpenAIChatClient(credential=credential).create_agent(
+    agent = AzureOpenAIChatClient(credential=credential).as_agent(
         model="gpt-4o",
         instructions="You are a helpful financial advisor..."
     )

python/samples/getting_started/evaluation/red_teaming/red_team_agent_sample.py

@@ -41,7 +41,7 @@ async def main() -> None:
     # Create the agent
     # Constructor automatically reads from environment variables:
     # AZURE_OPENAI_ENDPOINT, AZURE_OPENAI_DEPLOYMENT_NAME, AZURE_OPENAI_API_KEY
-    agent = AzureOpenAIChatClient(credential=credential).create_agent(
+    agent = AzureOpenAIChatClient(credential=credential).as_agent(
         name="FinancialAdvisor",
         instructions="""You are a professional financial advisor assistant.
 

python/samples/getting_started/evaluation/self_reflection/self_reflection.py

@@ -275,7 +275,7 @@ async def run_self_reflection_batch(
     agent = AzureOpenAIChatClient(
         credential=AzureCliCredential(),
         deployment_name=agent_model,
-    ).create_agent(
+    ).as_agent(
         instructions="You are a helpful agent.",
     )
 

python/samples/getting_started/mcp/agent_as_mcp_server.py

@@ -48,7 +48,7 @@ def get_item_price(
 async def run() -> None:
     # Define an agent
     # Agent's name and description provide better context for AI model
-    agent = OpenAIResponsesClient().create_agent(
+    agent = OpenAIResponsesClient().as_agent(
         name="RestaurantAgent",
         description="Answer questions about the menu.",
         tools=[get_specials, get_item_price],

python/samples/getting_started/middleware/agent_and_run_level_middleware.py

@@ -166,7 +166,7 @@ async def main() -> None:
     # authentication option.
     async with (
         AzureCliCredential() as credential,
-        AzureAIAgentClient(credential=credential).create_agent(
+        AzureAIAgentClient(credential=credential).as_agent(
             name="WeatherAgent",
             instructions="You are a helpful weather assistant.",
             tools=get_weather,

python/samples/getting_started/middleware/chat_middleware.py

@@ -142,7 +142,7 @@ async def class_based_chat_middleware() -> None:
     # authentication option.
     async with (
         AzureCliCredential() as credential,
-        AzureAIAgentClient(credential=credential).create_agent(
+        AzureAIAgentClient(credential=credential).as_agent(
             name="EnhancedChatAgent",
             instructions="You are a helpful AI assistant.",
             # Register class-based middleware at agent level (applies to all runs)
@@ -164,7 +164,7 @@ async def function_based_chat_middleware() -> None:
 
     async with (
         AzureCliCredential() as credential,
-        AzureAIAgentClient(credential=credential).create_agent(
+        AzureAIAgentClient(credential=credential).as_agent(
             name="FunctionMiddlewareAgent",
             instructions="You are a helpful AI assistant.",
             # Register function-based middleware at agent level
@@ -194,7 +194,7 @@ async def run_level_middleware() -> None:
 
     async with (
         AzureCliCredential() as credential,
-        AzureAIAgentClient(credential=credential).create_agent(
+        AzureAIAgentClient(credential=credential).as_agent(
             name="RunLevelAgent",
             instructions="You are a helpful AI assistant.",
             tools=get_weather,

python/samples/getting_started/middleware/class_based_middleware.py

@@ -99,7 +99,7 @@ async def main() -> None:
     # authentication option.
     async with (
         AzureCliCredential() as credential,
-        AzureAIAgentClient(credential=credential).create_agent(
+        AzureAIAgentClient(credential=credential).as_agent(
             name="WeatherAgent",
             instructions="You are a helpful weather assistant.",
             tools=get_weather,

python/samples/getting_started/middleware/decorator_middleware.py

@@ -70,7 +70,7 @@ async def main() -> None:
     # authentication option.
     async with (
         AzureCliCredential() as credential,
-        AzureAIAgentClient(credential=credential).create_agent(
+        AzureAIAgentClient(credential=credential).as_agent(
             name="TimeAgent",
             instructions="You are a helpful time assistant. Call get_current_time when asked about time.",
             tools=get_current_time,

python/samples/getting_started/middleware/exception_handling_with_middleware.py

@@ -58,7 +58,7 @@ async def main() -> None:
     # authentication option.
     async with (
         AzureCliCredential() as credential,
-        AzureAIAgentClient(credential=credential).create_agent(
+        AzureAIAgentClient(credential=credential).as_agent(
             name="DataAgent",
             instructions="You are a helpful data assistant. Use the data service tool to fetch information for users.",
             tools=unstable_data_service,

python/samples/getting_started/middleware/function_based_middleware.py

@@ -83,7 +83,7 @@ async def main() -> None:
     # authentication option.
     async with (
         AzureCliCredential() as credential,
-        AzureAIAgentClient(credential=credential).create_agent(
+        AzureAIAgentClient(credential=credential).as_agent(
             name="WeatherAgent",
             instructions="You are a helpful weather assistant.",
             tools=get_weather,

python/samples/getting_started/middleware/middleware_termination.py

@@ -110,7 +110,7 @@ async def pre_termination_middleware() -> None:
     print("\n--- Example 1: Pre-termination Middleware ---")
     async with (
         AzureCliCredential() as credential,
-        AzureAIAgentClient(credential=credential).create_agent(
+        AzureAIAgentClient(credential=credential).as_agent(
             name="WeatherAgent",
             instructions="You are a helpful weather assistant.",
             tools=get_weather,
@@ -137,7 +137,7 @@ async def post_termination_middleware() -> None:
     print("\n--- Example 2: Post-termination Middleware ---")
     async with (
         AzureCliCredential() as credential,
-        AzureAIAgentClient(credential=credential).create_agent(
+        AzureAIAgentClient(credential=credential).as_agent(
             name="WeatherAgent",
             instructions="You are a helpful weather assistant.",
             tools=get_weather,

python/samples/getting_started/middleware/override_result_with_middleware.py

@@ -83,7 +83,7 @@ async def main() -> None:
     # authentication option.
     async with (
         AzureCliCredential() as credential,
-        AzureAIAgentClient(credential=credential).create_agent(
+        AzureAIAgentClient(credential=credential).as_agent(
             name="WeatherAgent",
             instructions="You are a helpful weather assistant. Use the weather tool to get current conditions.",
             tools=get_weather,

python/samples/getting_started/middleware/runtime_context_delegation.py

@@ -147,7 +147,7 @@ async def pattern_1_single_agent_with_closure() -> None:
     client = OpenAIChatClient(model_id="gpt-4o-mini")
 
     # Create agent with both tools and shared context via middleware
-    communication_agent = client.create_agent(
+    communication_agent = client.as_agent(
         name="communication_agent",
         instructions=(
             "You are a communication assistant that can send emails and notifications. "
@@ -294,14 +294,14 @@ async def pattern_2_hierarchical_with_kwargs_propagation() -> None:
     client = OpenAIChatClient(model_id="gpt-4o-mini")
 
     # Create specialized sub-agents
-    email_agent = client.create_agent(
+    email_agent = client.as_agent(
         name="email_agent",
         instructions="You send emails using the send_email_v2 tool.",
         tools=[send_email_v2],
         middleware=[email_kwargs_tracker],
     )
 
-    sms_agent = client.create_agent(
+    sms_agent = client.as_agent(
         name="sms_agent",
         instructions="You send SMS messages using the send_sms tool.",
         tools=[send_sms],
@@ -309,7 +309,7 @@ async def pattern_2_hierarchical_with_kwargs_propagation() -> None:
     )
 
     # Create coordinator that delegates to sub-agents
-    coordinator = client.create_agent(
+    coordinator = client.as_agent(
         name="coordinator",
         instructions=(
             "You coordinate communication tasks. "
@@ -396,7 +396,7 @@ async def pattern_3_hierarchical_with_middleware() -> None:
     client = OpenAIChatClient(model_id="gpt-4o-mini")
 
     # Sub-agent with validation middleware
-    protected_agent = client.create_agent(
+    protected_agent = client.as_agent(
         name="protected_agent",
         instructions="You perform protected operations that require authentication.",
         tools=[protected_operation],
@@ -404,7 +404,7 @@ async def pattern_3_hierarchical_with_middleware() -> None:
     )
 
     # Coordinator delegates to protected agent
-    coordinator = client.create_agent(
+    coordinator = client.as_agent(
         name="coordinator",
         instructions="You coordinate protected operations. Delegate to protected_executor.",
         tools=[

python/samples/getting_started/middleware/shared_state_middleware.py

@@ -93,7 +93,7 @@ async def main() -> None:
     # authentication option.
     async with (
         AzureCliCredential() as credential,
-        AzureAIAgentClient(credential=credential).create_agent(
+        AzureAIAgentClient(credential=credential).as_agent(
             name="UtilityAgent",
             instructions="You are a helpful assistant that can provide weather information and current time.",
             tools=[get_weather, get_time],

python/samples/getting_started/middleware/thread_behavior_middleware.py

@@ -70,7 +70,7 @@ async def main() -> None:
 
     # For authentication, run `az login` command in terminal or replace AzureCliCredential with preferred
     # authentication option.
-    agent = AzureOpenAIChatClient(credential=AzureCliCredential()).create_agent(
+    agent = AzureOpenAIChatClient(credential=AzureCliCredential()).as_agent(
         name="WeatherAgent",
         instructions="You are a helpful weather assistant.",
         tools=get_weather,

python/samples/getting_started/minimal_sample.py

@@ -15,7 +15,7 @@ def get_weather(
     return f"The weather in {location} is {conditions[randint(0, 3)]} with a high of {randint(10, 30)}°C."
 
 
-agent = OpenAIChatClient().create_agent(
+agent = OpenAIChatClient().as_agent(
     name="WeatherAgent", instructions="You are a helpful weather agent.", tools=get_weather
 )
 print(asyncio.run(agent.run("What's the weather like in Seattle?")))

python/samples/getting_started/threads/custom_chat_message_store_thread.py

@@ -58,7 +58,7 @@ async def main() -> None:
 
     # OpenAI Chat Client is used as an example here,
     # other chat clients can be used as well.
-    agent = OpenAIChatClient().create_agent(
+    agent = OpenAIChatClient().as_agent(
         name="CustomBot",
         instructions="You are a helpful assistant that remembers our conversation.",
         # Use custom chat message store.

python/samples/getting_started/threads/redis_chat_message_store_thread.py

@@ -33,7 +33,7 @@ async def example_manual_memory_store() -> None:
     thread = AgentThread(message_store=redis_store)
 
     # Create agent
-    agent = OpenAIChatClient().create_agent(
+    agent = OpenAIChatClient().as_agent(
         name="RedisBot",
         instructions="You are a helpful assistant that remembers our conversation using Redis.",
     )
@@ -76,7 +76,7 @@ async def example_user_session_management() -> None:
         )
 
     # Create agent with factory pattern
-    agent = OpenAIChatClient().create_agent(
+    agent = OpenAIChatClient().as_agent(
         name="SessionBot",
         instructions="You are a helpful assistant. Keep track of user preferences.",
         chat_message_store_factory=create_user_session_store,
@@ -129,7 +129,7 @@ async def example_conversation_persistence() -> None:
     )
 
     thread1 = AgentThread(message_store=store1)
-    agent = OpenAIChatClient().create_agent(
+    agent = OpenAIChatClient().as_agent(
         name="PersistentBot",
         instructions="You are a helpful assistant. Remember our conversation history.",
     )
@@ -189,7 +189,7 @@ async def example_thread_serialization() -> None:
 
     original_thread = AgentThread(message_store=original_store)
 
-    agent = OpenAIChatClient().create_agent(
+    agent = OpenAIChatClient().as_agent(
         name="SerializationBot",
         instructions="You are a helpful assistant.",
     )
@@ -241,7 +241,7 @@ async def example_message_limits() -> None:
     )
 
     thread = AgentThread(message_store=store)
-    agent = OpenAIChatClient().create_agent(
+    agent = OpenAIChatClient().as_agent(
         name="LimitBot",
         instructions="You are a helpful assistant with limited memory.",
     )

python/samples/getting_started/threads/suspend_resume_thread.py

@@ -22,7 +22,7 @@ async def suspend_resume_service_managed_thread() -> None:
     # AzureAIAgentClient supports service-managed threads.
     async with (
         AzureCliCredential() as credential,
-        AzureAIAgentClient(credential=credential).create_agent(
+        AzureAIAgentClient(credential=credential).as_agent(
             name="MemoryBot", instructions="You are a helpful assistant that remembers our conversation."
         ) as agent,
     ):
@@ -55,7 +55,7 @@ async def suspend_resume_in_memory_thread() -> None:
 
     # OpenAI Chat Client is used as an example here,
     # other chat clients can be used as well.
-    agent = OpenAIChatClient().create_agent(
+    agent = OpenAIChatClient().as_agent(
         name="MemoryBot", instructions="You are a helpful assistant that remembers our conversation."
     )
 

python/samples/getting_started/tools/README.md

@@ -80,7 +80,7 @@ class MyTools:
 
 # Create instance and use methods as tools
 tools = MyTools(mode="safe")
-agent = client.create_agent(tools=tools.process)
+agent = client.as_agent(tools=tools.process)
 
 # Change behavior dynamically
 tools.mode = "normal"

python/samples/getting_started/tools/ai_function_declaration_only.py

@@ -19,7 +19,7 @@ async def main():
         description="Get the current time in ISO 8601 format.",
     )
 
-    agent = OpenAIResponsesClient().create_agent(
+    agent = OpenAIResponsesClient().as_agent(
         name="DeclarationOnlyToolAgent",
         instructions="You are a helpful agent that uses tools.",
         tools=function_declaration,

python/samples/getting_started/tools/ai_function_from_dict_with_dependency_injection.py

@@ -57,7 +57,7 @@ async def main() -> None:
     # - "func": the parameter name that will receive the injected function
     tool = AIFunction.from_dict(definition, dependencies={"ai_function": {"name:add_numbers": {"func": func}}})
 
-    agent = OpenAIResponsesClient().create_agent(
+    agent = OpenAIResponsesClient().as_agent(
         name="FunctionToolAgent", instructions="You are a helpful assistant.", tools=tool
     )
     response = await agent.run("What is 5 + 3?")

python/samples/getting_started/tools/ai_function_recover_from_failures.py

@@ -36,7 +36,7 @@ def safe_divide(
 
 async def main():
     # tools = Tools()
-    agent = OpenAIResponsesClient().create_agent(
+    agent = OpenAIResponsesClient().as_agent(
         name="ToolAgent",
         instructions="Use the provided tools.",
         tools=[greet, safe_divide],

python/samples/getting_started/tools/ai_function_with_kwargs.py

@@ -36,7 +36,7 @@ def get_weather(
 
 
 async def main() -> None:
-    agent = OpenAIResponsesClient().create_agent(
+    agent = OpenAIResponsesClient().as_agent(
         name="WeatherAgent",
         instructions="You are a helpful weather assistant.",
         tools=[get_weather],

python/samples/getting_started/tools/ai_function_with_max_exceptions.py

@@ -31,7 +31,7 @@ def safe_divide(
 
 async def main():
     # tools = Tools()
-    agent = OpenAIResponsesClient().create_agent(
+    agent = OpenAIResponsesClient().as_agent(
         name="ToolAgent",
         instructions="Use the provided tools.",
         tools=[safe_divide],

python/samples/getting_started/tools/ai_function_with_max_invocations.py

@@ -20,7 +20,7 @@ def unicorn_function(times: Annotated[int, "The number of unicorns to return."])
 
 async def main():
     # tools = Tools()
-    agent = OpenAIResponsesClient().create_agent(
+    agent = OpenAIResponsesClient().as_agent(
         name="ToolAgent",
         instructions="Use the provided tools.",
         tools=[unicorn_function],

python/samples/getting_started/tools/ai_function_with_thread_injection.py

@@ -35,7 +35,7 @@ async def get_weather(
 
 
 async def main() -> None:
-    agent = OpenAIChatClient().create_agent(
+    agent = OpenAIChatClient().as_agent(
         name="WeatherAgent", instructions="You are a helpful weather assistant.", tools=[get_weather]
     )
 

python/samples/getting_started/tools/ai_functions_in_class.py

@@ -45,7 +45,7 @@ async def main():
     # Applying the ai_function decorator to one of the methods of the class
     add_function = ai_function(description="Add two numbers.")(tools.add)
 
-    agent = OpenAIResponsesClient().create_agent(
+    agent = OpenAIResponsesClient().as_agent(
         name="ToolAgent",
         instructions="Use the provided tools.",
     )

python/samples/getting_started/tools/function_invocation_configuration.py

@@ -27,7 +27,7 @@ async def main():
         client.function_invocation_configuration.max_iterations = 40
         print(f"Function invocation configured as: \n{client.function_invocation_configuration.to_json(indent=2)}")
 
-    agent = client.create_agent(name="ToolAgent", instructions="Use the provided tools.", tools=add)
+    agent = client.as_agent(name="ToolAgent", instructions="Use the provided tools.", tools=add)
 
     print("=" * 60)
     print("Call add(239847293, 29834)")

python/samples/getting_started/workflows/_start-here/step2_agents_in_a_workflow.py

@@ -28,14 +28,14 @@ async def main():
     """Build and run a simple two node agent workflow: Writer then Reviewer."""
     # Create the Azure chat client. AzureCliCredential uses your current az login.
     chat_client = AzureOpenAIChatClient(credential=AzureCliCredential())
-    writer_agent = chat_client.create_agent(
+    writer_agent = chat_client.as_agent(
         instructions=(
             "You are an excellent content writer. You create new content and edit contents based on the feedback."
         ),
         name="writer",
     )
 
-    reviewer_agent = chat_client.create_agent(
+    reviewer_agent = chat_client.as_agent(
         instructions=(
             "You are an excellent content reviewer."
             "Provide actionable feedback to the writer about the provided content."

python/samples/getting_started/workflows/_start-here/step3_streaming.py

@@ -52,7 +52,7 @@ class Writer(Executor):
 
     def __init__(self, chat_client: AzureOpenAIChatClient, id: str = "writer"):
         # Create a domain specific agent using your configured AzureOpenAIChatClient.
-        self.agent = chat_client.create_agent(
+        self.agent = chat_client.as_agent(
             instructions=(
                 "You are an excellent content writer. You create new content and edit contents based on the feedback."
             ),
@@ -89,7 +89,7 @@ class Reviewer(Executor):
 
     def __init__(self, chat_client: AzureOpenAIChatClient, id: str = "reviewer"):
         # Create a domain specific agent that evaluates and refines content.
-        self.agent = chat_client.create_agent(
+        self.agent = chat_client.as_agent(
             instructions=(
                 "You are an excellent content reviewer. You review the content and provide feedback to the writer."
             ),