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

* Renamed create_agent to as_agent

* Override for as_agent

* Added override

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."
             ),

python/samples/getting_started/workflows/_start-here/step4_using_factories.py

@@ -59,7 +59,7 @@ async def reverse_text(text: str, ctx: WorkflowContext[str]) -> None:
 
 def create_agent() -> ChatAgent:
     """Factory function to create a Writer agent."""
-    return AzureOpenAIChatClient(credential=AzureCliCredential()).create_agent(
+    return AzureOpenAIChatClient(credential=AzureCliCredential()).as_agent(
         instructions=("You decode messages. Try to reconstruct the original message."),
         name="decoder",
     )

python/samples/getting_started/workflows/agents/azure_ai_agents_streaming.py

@@ -27,7 +27,7 @@ Prerequisites:
 
 
 def create_writer_agent(client: AzureAIAgentClient) -> ChatAgent:
-    return client.create_agent(
+    return client.as_agent(
         name="Writer",
         instructions=(
             "You are an excellent content writer. You create new content and edit contents based on the feedback."
@@ -36,7 +36,7 @@ def create_writer_agent(client: AzureAIAgentClient) -> ChatAgent:
 
 
 def create_reviewer_agent(client: AzureAIAgentClient) -> ChatAgent:
-    return client.create_agent(
+    return client.as_agent(
         name="Reviewer",
         instructions=(
             "You are an excellent content reviewer. "

python/samples/getting_started/workflows/agents/azure_chat_agents_function_bridge.py

@@ -87,7 +87,7 @@ async def enrich_with_references(
 
 
 def create_research_agent():
-    return AzureOpenAIChatClient(credential=AzureCliCredential()).create_agent(
+    return AzureOpenAIChatClient(credential=AzureCliCredential()).as_agent(
         name="research_agent",
         instructions=(
             "Produce a short, bullet-style briefing with two actionable ideas. Label the section as 'Initial Draft'."
@@ -96,7 +96,7 @@ def create_research_agent():
 
 
 def create_final_editor_agent():
-    return AzureOpenAIChatClient(credential=AzureCliCredential()).create_agent(
+    return AzureOpenAIChatClient(credential=AzureCliCredential()).as_agent(
         name="final_editor_agent",
         instructions=(
             "Use all conversation context (including external notes) to produce the final answer. "

python/samples/getting_started/workflows/agents/azure_chat_agents_streaming.py

@@ -27,7 +27,7 @@ Prerequisites:
 
 
 def create_writer_agent():
-    return AzureOpenAIChatClient(credential=AzureCliCredential()).create_agent(
+    return AzureOpenAIChatClient(credential=AzureCliCredential()).as_agent(
         instructions=(
             "You are an excellent content writer. You create new content and edit contents based on the feedback."
         ),
@@ -36,7 +36,7 @@ def create_writer_agent():
 
 
 def create_reviewer_agent():
-    return AzureOpenAIChatClient(credential=AzureCliCredential()).create_agent(
+    return AzureOpenAIChatClient(credential=AzureCliCredential()).as_agent(
         instructions=(
             "You are an excellent content reviewer."
             "Provide actionable feedback to the writer about the provided content."

python/samples/getting_started/workflows/agents/azure_chat_agents_tool_calls_with_feedback.py

@@ -168,7 +168,7 @@ class Coordinator(Executor):
 
 def create_writer_agent() -> ChatAgent:
     """Creates a writer agent with tools."""
-    return AzureOpenAIChatClient(credential=AzureCliCredential()).create_agent(
+    return AzureOpenAIChatClient(credential=AzureCliCredential()).as_agent(
         name="writer_agent",
         instructions=(
             "You are a marketing writer. Call the available tools before drafting copy so you are precise. "
@@ -182,7 +182,7 @@ def create_writer_agent() -> ChatAgent:
 
 def create_final_editor_agent() -> ChatAgent:
     """Creates a final editor agent."""
-    return AzureOpenAIChatClient(credential=AzureCliCredential()).create_agent(
+    return AzureOpenAIChatClient(credential=AzureCliCredential()).as_agent(
         name="final_editor_agent",
         instructions=(
             "You are an editor who polishes marketing copy after human approval. "

python/samples/getting_started/workflows/agents/concurrent_workflow_as_agent.py

@@ -28,7 +28,7 @@ async def main() -> None:
     # 1) Create three domain agents using AzureOpenAIChatClient
     chat_client = AzureOpenAIChatClient(credential=AzureCliCredential())
 
-    researcher = chat_client.create_agent(
+    researcher = chat_client.as_agent(
         instructions=(
             "You're an expert market and product researcher. Given a prompt, provide concise, factual insights,"
             " opportunities, and risks."
@@ -36,7 +36,7 @@ async def main() -> None:
         name="researcher",
     )
 
-    marketer = chat_client.create_agent(
+    marketer = chat_client.as_agent(
         instructions=(
             "You're a creative marketing strategist. Craft compelling value propositions and target messaging"
             " aligned to the prompt."
@@ -44,7 +44,7 @@ async def main() -> None:
         name="marketer",
     )
 
-    legal = chat_client.create_agent(
+    legal = chat_client.as_agent(
         instructions=(
             "You're a cautious legal/compliance reviewer. Highlight constraints, disclaimers, and policy concerns"
             " based on the prompt."

python/samples/getting_started/workflows/agents/custom_agent_executors.py

@@ -43,7 +43,7 @@ class Writer(Executor):
 
     def __init__(self, id: str = "writer"):
         # Create a domain specific agent using your configured AzureOpenAIChatClient.
-        self.agent = AzureOpenAIChatClient(credential=AzureCliCredential()).create_agent(
+        self.agent = AzureOpenAIChatClient(credential=AzureCliCredential()).as_agent(
             instructions=(
                 "You are an excellent content writer. You create new content and edit contents based on the feedback."
             ),
@@ -85,7 +85,7 @@ class Reviewer(Executor):
 
     def __init__(self, id: str = "reviewer"):
         # Create a domain specific agent that evaluates and refines content.
-        self.agent = AzureOpenAIChatClient(credential=AzureCliCredential()).create_agent(
+        self.agent = AzureOpenAIChatClient(credential=AzureCliCredential()).as_agent(
             instructions=(
                 "You are an excellent content reviewer. You review the content and provide feedback to the writer."
             ),

python/samples/getting_started/workflows/agents/group_chat_workflow_as_agent.py

@@ -35,7 +35,7 @@ async def main() -> None:
     workflow = (
         GroupChatBuilder()
         .with_agent_orchestrator(
-            OpenAIChatClient().create_agent(
+            OpenAIChatClient().as_agent(
                 name="Orchestrator",
                 instructions="You coordinate a team conversation to solve the user's task.",
             )

python/samples/getting_started/workflows/agents/handoff_workflow_as_agent.py

@@ -66,7 +66,7 @@ def create_agents(chat_client: AzureOpenAIChatClient) -> tuple[ChatAgent, ChatAg
         Tuple of (triage_agent, refund_agent, order_agent, return_agent)
     """
     # Triage agent: Acts as the frontline dispatcher
-    triage_agent = chat_client.create_agent(
+    triage_agent = chat_client.as_agent(
         instructions=(
             "You are frontline support triage. Route customer issues to the appropriate specialist agents "
             "based on the problem described."
@@ -75,7 +75,7 @@ def create_agents(chat_client: AzureOpenAIChatClient) -> tuple[ChatAgent, ChatAg
     )
 
     # Refund specialist: Handles refund requests
-    refund_agent = chat_client.create_agent(
+    refund_agent = chat_client.as_agent(
         instructions="You process refund requests.",
         name="refund_agent",
         # In a real application, an agent can have multiple tools; here we keep it simple
@@ -83,7 +83,7 @@ def create_agents(chat_client: AzureOpenAIChatClient) -> tuple[ChatAgent, ChatAg
     )
 
     # Order/shipping specialist: Resolves delivery issues
-    order_agent = chat_client.create_agent(
+    order_agent = chat_client.as_agent(
         instructions="You handle order and shipping inquiries.",
         name="order_agent",
         # In a real application, an agent can have multiple tools; here we keep it simple
@@ -91,7 +91,7 @@ def create_agents(chat_client: AzureOpenAIChatClient) -> tuple[ChatAgent, ChatAg
     )
 
     # Return specialist: Handles return requests
-    return_agent = chat_client.create_agent(
+    return_agent = chat_client.as_agent(
         instructions="You manage product return requests.",
         name="return_agent",
         # In a real application, an agent can have multiple tools; here we keep it simple

python/samples/getting_started/workflows/agents/mixed_agents_and_executors.py

@@ -82,7 +82,7 @@ def create_coding_agent(client: AzureAIAgentClient) -> ChatAgent:
     Returns:
         A ChatAgent configured with coding instructions and tools
     """
-    return client.create_agent(
+    return client.as_agent(
         name="CodingAgent",
         instructions=("You are a helpful assistant that can write and execute Python code to solve problems."),
         tools=HostedCodeInterpreterTool(),

python/samples/getting_started/workflows/agents/sequential_workflow_as_agent.py

@@ -29,12 +29,12 @@ async def main() -> None:
     # 1) Create agents
     chat_client = AzureOpenAIChatClient(credential=AzureCliCredential())
 
-    writer = chat_client.create_agent(
+    writer = chat_client.as_agent(
         instructions=("You are a concise copywriter. Provide a single, punchy marketing sentence based on the prompt."),
         name="writer",
     )
 
-    reviewer = chat_client.create_agent(
+    reviewer = chat_client.as_agent(
         instructions=("You are a thoughtful reviewer. Give brief feedback on the previous assistant message."),
         name="reviewer",
     )

python/samples/getting_started/workflows/agents/workflow_as_agent_kwargs.py

@@ -79,7 +79,7 @@ async def main() -> None:
     chat_client = OpenAIChatClient()
 
     # Create agent with tools that use kwargs
-    agent = chat_client.create_agent(
+    agent = chat_client.as_agent(
         name="assistant",
         instructions=(
             "You are a helpful assistant. Use the available tools to help users. "

python/samples/getting_started/workflows/agents/workflow_as_agent_with_thread.py

@@ -40,7 +40,7 @@ async def main() -> None:
 
     # Define factory functions for workflow participants
     def create_assistant() -> ChatAgent:
-        return chat_client.create_agent(
+        return chat_client.as_agent(
             name="assistant",
             instructions=(
                 "You are a helpful assistant. Answer questions based on the conversation "
@@ -49,7 +49,7 @@ async def main() -> None:
         )
 
     def create_summarizer() -> ChatAgent:
-        return chat_client.create_agent(
+        return chat_client.as_agent(
             name="summarizer",
             instructions=(
                 "You are a summarizer. After the assistant responds, provide a brief "
@@ -124,7 +124,7 @@ async def demonstrate_thread_serialization() -> None:
     chat_client = OpenAIChatClient()
 
     def create_assistant() -> ChatAgent:
-        return chat_client.create_agent(
+        return chat_client.as_agent(
             name="memory_assistant",
             instructions="You are a helpful assistant with good memory. Remember details from our conversation.",
         )

python/samples/getting_started/workflows/checkpoint/checkpoint_with_human_in_the_loop.py

@@ -178,7 +178,7 @@ def create_workflow(checkpoint_storage: FileCheckpointStorage) -> Workflow:
     workflow_builder = (
         WorkflowBuilder(max_iterations=6)
         .register_agent(
-            lambda: AzureOpenAIChatClient(credential=AzureCliCredential()).create_agent(
+            lambda: AzureOpenAIChatClient(credential=AzureCliCredential()).as_agent(
                 instructions="Write concise, warm release notes that sound human and helpful.",
                 # The agent name is stable across runs which keeps checkpoints deterministic.
                 name="writer",

python/samples/getting_started/workflows/checkpoint/handoff_with_tool_approval_checkpoint_resume.py

@@ -60,7 +60,7 @@ def submit_refund(refund_description: str, amount: str, order_id: str) -> str:
 def create_agents(client: AzureOpenAIChatClient) -> tuple[ChatAgent, ChatAgent, ChatAgent]:
     """Create a simple handoff scenario: triage, refund, and order specialists."""
 
-    triage = client.create_agent(
+    triage = client.as_agent(
         name="triage_agent",
         instructions=(
             "You are a customer service triage agent. Listen to customer issues and determine "
@@ -69,7 +69,7 @@ def create_agents(client: AzureOpenAIChatClient) -> tuple[ChatAgent, ChatAgent,
         ),
     )
 
-    refund = client.create_agent(
+    refund = client.as_agent(
         name="refund_agent",
         instructions=(
             "You are a refund specialist. Help customers with refund requests. "
@@ -80,7 +80,7 @@ def create_agents(client: AzureOpenAIChatClient) -> tuple[ChatAgent, ChatAgent,
         tools=[submit_refund],
     )
 
-    order = client.create_agent(
+    order = client.as_agent(
         name="order_agent",
         instructions=(
             "You are an order tracking specialist. Help customers track their orders. "

python/samples/getting_started/workflows/checkpoint/workflow_as_agent_checkpoint.py

@@ -44,13 +44,13 @@ async def basic_checkpointing() -> None:
     chat_client = OpenAIChatClient()
 
     def create_assistant() -> ChatAgent:
-        return chat_client.create_agent(
+        return chat_client.as_agent(
             name="assistant",
             instructions="You are a helpful assistant. Keep responses brief.",
         )
 
     def create_reviewer() -> ChatAgent:
-        return chat_client.create_agent(
+        return chat_client.as_agent(
             name="reviewer",
             instructions="You are a reviewer. Provide a one-sentence summary of the assistant's response.",
         )
@@ -88,7 +88,7 @@ async def checkpointing_with_thread() -> None:
     chat_client = OpenAIChatClient()
 
     def create_assistant() -> ChatAgent:
-        return chat_client.create_agent(
+        return chat_client.as_agent(
             name="memory_assistant",
             instructions="You are a helpful assistant with good memory. Reference previous conversation when relevant.",
         )
@@ -132,7 +132,7 @@ async def streaming_with_checkpoints() -> None:
     chat_client = OpenAIChatClient()
 
     def create_assistant() -> ChatAgent:
-        return chat_client.create_agent(
+        return chat_client.as_agent(
             name="streaming_assistant",
             instructions="You are a helpful assistant.",
         )

python/samples/getting_started/workflows/composition/sub_workflow_kwargs.py

@@ -75,7 +75,7 @@ async def main() -> None:
     chat_client = OpenAIChatClient()
 
     # Create an agent with tools that use kwargs
-    inner_agent = chat_client.create_agent(
+    inner_agent = chat_client.as_agent(
         name="data_agent",
         instructions=(
             "You are a data access agent. Use the available tools to help users. "

python/samples/getting_started/workflows/control-flow/edge_condition.py

@@ -131,7 +131,7 @@ async def to_email_assistant_request(
 def create_spam_detector_agent() -> ChatAgent:
     """Helper to create a spam detection agent."""
     # AzureCliCredential uses your current az login. This avoids embedding secrets in code.
-    return AzureOpenAIChatClient(credential=AzureCliCredential()).create_agent(
+    return AzureOpenAIChatClient(credential=AzureCliCredential()).as_agent(
         instructions=(
             "You are a spam detection assistant that identifies spam emails. "
             "Always return JSON with fields is_spam (bool), reason (string), and email_content (string). "
@@ -145,7 +145,7 @@ def create_spam_detector_agent() -> ChatAgent:
 def create_email_assistant_agent() -> ChatAgent:
     """Helper to create an email assistant agent."""
     # AzureCliCredential uses your current az login. This avoids embedding secrets in code.
-    return AzureOpenAIChatClient(credential=AzureCliCredential()).create_agent(
+    return AzureOpenAIChatClient(credential=AzureCliCredential()).as_agent(
         instructions=(
             "You are an email assistant that helps users draft professional responses to emails. "
             "Your input may be a JSON object that includes 'email_content'; base your reply on that content. "

python/samples/getting_started/workflows/control-flow/multi_selection_edge_group.py

@@ -183,7 +183,7 @@ async def database_access(analysis: AnalysisResult, ctx: WorkflowContext[Never,
 
 def create_email_analysis_agent() -> ChatAgent:
     """Creates the email analysis agent."""
-    return AzureOpenAIChatClient(credential=AzureCliCredential()).create_agent(
+    return AzureOpenAIChatClient(credential=AzureCliCredential()).as_agent(
         instructions=(
             "You are a spam detection assistant that identifies spam emails. "
             "Always return JSON with fields 'spam_decision' (one of NotSpam, Spam, Uncertain) "
@@ -196,7 +196,7 @@ def create_email_analysis_agent() -> ChatAgent:
 
 def create_email_assistant_agent() -> ChatAgent:
     """Creates the email assistant agent."""
-    return AzureOpenAIChatClient(credential=AzureCliCredential()).create_agent(
+    return AzureOpenAIChatClient(credential=AzureCliCredential()).as_agent(
         instructions=("You are an email assistant that helps users draft responses to emails with professionalism."),
         name="email_assistant_agent",
         default_options={"response_format": EmailResponse},
@@ -205,7 +205,7 @@ def create_email_assistant_agent() -> ChatAgent:
 
 def create_email_summary_agent() -> ChatAgent:
     """Creates the email summary agent."""
-    return AzureOpenAIChatClient(credential=AzureCliCredential()).create_agent(
+    return AzureOpenAIChatClient(credential=AzureCliCredential()).as_agent(
         instructions=("You are an assistant that helps users summarize emails."),
         name="email_summary_agent",
         default_options={"response_format": EmailSummaryModel},

python/samples/getting_started/workflows/control-flow/simple_loop.py

@@ -117,7 +117,7 @@ class ParseJudgeResponse(Executor):
 
 def create_judge_agent() -> ChatAgent:
     """Create a judge agent that evaluates guesses."""
-    return AzureOpenAIChatClient(credential=AzureCliCredential()).create_agent(
+    return AzureOpenAIChatClient(credential=AzureCliCredential()).as_agent(
         instructions=("You strictly respond with one of: MATCHED, ABOVE, BELOW based on the given target and guess."),
         name="judge_agent",
     )

python/samples/getting_started/workflows/control-flow/switch_case_edge_group.py

@@ -154,7 +154,7 @@ async def handle_uncertain(detection: DetectionResult, ctx: WorkflowContext[Neve
 
 def create_spam_detection_agent() -> ChatAgent:
     """Create and return the spam detection agent."""
-    return AzureOpenAIChatClient(credential=AzureCliCredential()).create_agent(
+    return AzureOpenAIChatClient(credential=AzureCliCredential()).as_agent(
         instructions=(
             "You are a spam detection assistant that identifies spam emails. "
             "Be less confident in your assessments. "
@@ -168,7 +168,7 @@ def create_spam_detection_agent() -> ChatAgent:
 
 def create_email_assistant_agent() -> ChatAgent:
     """Create and return the email assistant agent."""
-    return AzureOpenAIChatClient(credential=AzureCliCredential()).create_agent(
+    return AzureOpenAIChatClient(credential=AzureCliCredential()).as_agent(
         instructions=("You are an email assistant that helps users draft responses to emails with professionalism."),
         name="email_assistant_agent",
         default_options={"response_format": EmailResponse},

python/samples/getting_started/workflows/declarative/customer_support/main.py

@@ -168,40 +168,40 @@ async def main() -> None:
     chat_client = AzureOpenAIChatClient(credential=AzureCliCredential())
 
     # Create agents with structured outputs
-    self_service_agent = chat_client.create_agent(
+    self_service_agent = chat_client.as_agent(
         name="SelfServiceAgent",
         instructions=SELF_SERVICE_INSTRUCTIONS,
         default_options={"response_format": SelfServiceResponse},
     )
 
-    ticketing_agent = chat_client.create_agent(
+    ticketing_agent = chat_client.as_agent(
         name="TicketingAgent",
         instructions=TICKETING_INSTRUCTIONS,
         tools=plugin.get_functions(),
         default_options={"response_format": TicketingResponse},
     )
 
-    routing_agent = chat_client.create_agent(
+    routing_agent = chat_client.as_agent(
         name="TicketRoutingAgent",
         instructions=TICKET_ROUTING_INSTRUCTIONS,
         tools=[plugin.get_ticket],
         default_options={"response_format": RoutingResponse},
     )
 
-    windows_support_agent = chat_client.create_agent(
+    windows_support_agent = chat_client.as_agent(
         name="WindowsSupportAgent",
         instructions=WINDOWS_SUPPORT_INSTRUCTIONS,
         tools=[plugin.get_ticket],
         default_options={"response_format": SupportResponse},
     )
 
-    resolution_agent = chat_client.create_agent(
+    resolution_agent = chat_client.as_agent(
         name="TicketResolutionAgent",
         instructions=RESOLUTION_INSTRUCTIONS,
         tools=[plugin.resolve_ticket],
     )
 
-    escalation_agent = chat_client.create_agent(
+    escalation_agent = chat_client.as_agent(
         name="TicketEscalationAgent",
         instructions=ESCALATION_INSTRUCTIONS,
         tools=[plugin.get_ticket, plugin.send_notification],

python/samples/getting_started/workflows/declarative/deep_research/main.py

@@ -126,38 +126,38 @@ async def main() -> None:
     chat_client = AzureOpenAIChatClient(credential=AzureCliCredential())
 
     # Create agents
-    research_agent = chat_client.create_agent(
+    research_agent = chat_client.as_agent(
         name="ResearchAgent",
         instructions=RESEARCH_INSTRUCTIONS,
     )
 
-    planner_agent = chat_client.create_agent(
+    planner_agent = chat_client.as_agent(
         name="PlannerAgent",
         instructions=PLANNER_INSTRUCTIONS,
     )
 
-    manager_agent = chat_client.create_agent(
+    manager_agent = chat_client.as_agent(
         name="ManagerAgent",
         instructions=MANAGER_INSTRUCTIONS,
         default_options={"response_format": ManagerResponse},
     )
 
-    summary_agent = chat_client.create_agent(
+    summary_agent = chat_client.as_agent(
         name="SummaryAgent",
         instructions=SUMMARY_INSTRUCTIONS,
     )
 
-    knowledge_agent = chat_client.create_agent(
+    knowledge_agent = chat_client.as_agent(
         name="KnowledgeAgent",
         instructions=KNOWLEDGE_INSTRUCTIONS,
     )
 
-    coder_agent = chat_client.create_agent(
+    coder_agent = chat_client.as_agent(
         name="CoderAgent",
         instructions=CODER_INSTRUCTIONS,
     )
 
-    weather_agent = chat_client.create_agent(
+    weather_agent = chat_client.as_agent(
         name="WeatherAgent",
         instructions=WEATHER_INSTRUCTIONS,
     )

python/samples/getting_started/workflows/declarative/function_tools/README.md

@@ -73,7 +73,7 @@ Session Complete
 ```python
 # Create the agent with tools
 chat_client = AzureOpenAIChatClient(credential=AzureCliCredential())
-menu_agent = chat_client.create_agent(
+menu_agent = chat_client.as_agent(
     name="MenuAgent",
     instructions="You are a helpful restaurant menu assistant...",
     tools=[get_menu, get_specials, get_item_price],