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

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* Renamed create_agent to as_agent

* Override for as_agent

* Added override
This commit is contained in:
Dmytro Struk
2026-01-16 11:21:52 -08:00
committed by GitHub
Unverified
parent a151f10cc2
commit 5687e13221
163 changed files with 498 additions and 358 deletions
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python/samples/getting_started/workflows/_start-here/step2_agents_in_a_workflow.py
+2 -2
View File
@@ -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
+2 -2
View File
@@ -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
+1 -1
View File
@@ -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
+2 -2
View File
@@ -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
+2 -2
View File
@@ -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
+2 -2
View File
@@ -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
+2 -2
View File
@@ -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
+3 -3
View File
@@ -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
+2 -2
View File
@@ -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
+1 -1
View File
@@ -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
+4 -4
View File
@@ -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
+1 -1
View File
@@ -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
+2 -2
View File
@@ -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
+1 -1
View File
@@ -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
+3 -3
View File
@@ -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
+1 -1
View File
@@ -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
+3 -3
View File
@@ -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
+4 -4
View File
@@ -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
+1 -1
View File
@@ -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
+2 -2
View File
@@ -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
+3 -3
View File
@@ -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
+1 -1
View File
@@ -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
+2 -2
View File
@@ -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
+6 -6
View File
@@ -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
+7 -7
View File
@@ -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
+1 -1
View File
@@ -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],
python/samples/getting_started/workflows/declarative/function_tools/main.py
+1 -1
View File
@@ -59,7 +59,7 @@ def get_item_price(name: Annotated[str, Field(description="Menu item name")]) ->
async def main():
# Create agent with tools
chat_client = AzureOpenAIChatClient(credential=AzureCliCredential())
menu_agent = chat_client.create_agent(
menu_agent = chat_client.as_agent(
name="MenuAgent",
instructions="Answer questions about menu items, specials, and prices.",
tools=[get_menu, get_specials, get_item_price],
python/samples/getting_started/workflows/declarative/marketing/main.py
+3 -3
View File
@@ -52,15 +52,15 @@ async def main() -> None:
"""Run the marketing workflow with real Azure AI agents."""
chat_client = AzureOpenAIChatClient(credential=AzureCliCredential())
analyst_agent = chat_client.create_agent(
analyst_agent = chat_client.as_agent(
name="AnalystAgent",
instructions=ANALYST_INSTRUCTIONS,
)
writer_agent = chat_client.create_agent(
writer_agent = chat_client.as_agent(
name="WriterAgent",
instructions=WRITER_INSTRUCTIONS,
)
editor_agent = chat_client.create_agent(
editor_agent = chat_client.as_agent(
name="EditorAgent",
instructions=EDITOR_INSTRUCTIONS,
)
python/samples/getting_started/workflows/declarative/student_teacher/main.py
+2 -2
View File
@@ -55,12 +55,12 @@ async def main() -> None:
chat_client = AzureOpenAIChatClient(credential=AzureCliCredential())
# Create student and teacher agents
student_agent = chat_client.create_agent(
student_agent = chat_client.as_agent(
name="StudentAgent",
instructions=STUDENT_INSTRUCTIONS,
)
teacher_agent = chat_client.create_agent(
teacher_agent = chat_client.as_agent(
name="TeacherAgent",
instructions=TEACHER_INSTRUCTIONS,
)
python/samples/getting_started/workflows/human-in-the-loop/agents_with_approval_requests.py
+1 -1
View File
@@ -213,7 +213,7 @@ async def conclude_workflow(
def create_email_writer_agent() -> ChatAgent:
"""Create the Email Writer agent with tools that require approval."""
return OpenAIChatClient().create_agent(
return OpenAIChatClient().as_agent(
name="Email Writer",
instructions=("You are an excellent email assistant. You respond to incoming emails."),
# tools with `approval_mode="always_require"` will trigger approval requests
python/samples/getting_started/workflows/human-in-the-loop/concurrent_request_info.py
+3 -3
View File
@@ -99,7 +99,7 @@ async def main() -> None:
_chat_client = AzureOpenAIChatClient(credential=AzureCliCredential())
# Create agents that analyze from different perspectives
technical_analyst = _chat_client.create_agent(
technical_analyst = _chat_client.as_agent(
name="technical_analyst",
instructions=(
"You are a technical analyst. When given a topic, provide a technical "
@@ -108,7 +108,7 @@ async def main() -> None:
),
)
business_analyst = _chat_client.create_agent(
business_analyst = _chat_client.as_agent(
name="business_analyst",
instructions=(
"You are a business analyst. When given a topic, provide a business "
@@ -117,7 +117,7 @@ async def main() -> None:
),
)
user_experience_analyst = _chat_client.create_agent(
user_experience_analyst = _chat_client.as_agent(
name="ux_analyst",
instructions=(
"You are a UX analyst. When given a topic, provide a user experience "
python/samples/getting_started/workflows/human-in-the-loop/group_chat_request_info.py
+4 -4
View File
@@ -44,7 +44,7 @@ async def main() -> None:
chat_client = AzureOpenAIChatClient(credential=AzureCliCredential())
# Create agents for a group discussion
optimist = chat_client.create_agent(
optimist = chat_client.as_agent(
name="optimist",
instructions=(
"You are an optimistic team member. You see opportunities and potential "
@@ -53,7 +53,7 @@ async def main() -> None:
),
)
pragmatist = chat_client.create_agent(
pragmatist = chat_client.as_agent(
name="pragmatist",
instructions=(
"You are a pragmatic team member. You focus on practical implementation "
@@ -62,7 +62,7 @@ async def main() -> None:
),
)
creative = chat_client.create_agent(
creative = chat_client.as_agent(
name="creative",
instructions=(
"You are a creative team member. You propose innovative solutions and "
@@ -72,7 +72,7 @@ async def main() -> None:
)
# Orchestrator coordinates the discussion
orchestrator = chat_client.create_agent(
orchestrator = chat_client.as_agent(
name="orchestrator",
instructions=(
"You are a discussion manager coordinating a team conversation between participants. "
python/samples/getting_started/workflows/human-in-the-loop/guessing_game_with_human_input.py
+1 -1
View File
@@ -145,7 +145,7 @@ class TurnManager(Executor):
def create_guessing_agent() -> ChatAgent:
"""Create the guessing agent with instructions to guess a number between 1 and 10."""
return AzureOpenAIChatClient(credential=AzureCliCredential()).create_agent(
return AzureOpenAIChatClient(credential=AzureCliCredential()).as_agent(
name="GuessingAgent",
instructions=(
"You guess a number between 1 and 10. "
python/samples/getting_started/workflows/human-in-the-loop/sequential_request_info.py
+3 -3
View File
@@ -41,12 +41,12 @@ async def main() -> None:
chat_client = AzureOpenAIChatClient(credential=AzureCliCredential())
# Create agents for a sequential document review workflow
drafter = chat_client.create_agent(
drafter = chat_client.as_agent(
name="drafter",
instructions=("You are a document drafter. When given a topic, create a brief draft (2-3 sentences)."),
)
editor = chat_client.create_agent(
editor = chat_client.as_agent(
name="editor",
instructions=(
"You are an editor. Review the draft and make improvements. "
@@ -54,7 +54,7 @@ async def main() -> None:
),
)
finalizer = chat_client.create_agent(
finalizer = chat_client.as_agent(
name="finalizer",
instructions=(
"You are a finalizer. Take the edited content and create a polished final version. "
python/samples/getting_started/workflows/orchestration/concurrent_agents.py
+3 -3
View File
@@ -30,7 +30,7 @@ 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."
@@ -38,7 +38,7 @@ 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."
@@ -46,7 +46,7 @@ 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/orchestration/concurrent_custom_agent_executors.py
+3 -3
View File
@@ -40,7 +40,7 @@ class ResearcherExec(Executor):
agent: ChatAgent
def __init__(self, chat_client: AzureOpenAIChatClient, id: str = "researcher"):
self.agent = chat_client.create_agent(
self.agent = chat_client.as_agent(
instructions=(
"You're an expert market and product researcher. Given a prompt, provide concise, factual insights,"
" opportunities, and risks."
@@ -60,7 +60,7 @@ class MarketerExec(Executor):
agent: ChatAgent
def __init__(self, chat_client: AzureOpenAIChatClient, id: str = "marketer"):
self.agent = chat_client.create_agent(
self.agent = chat_client.as_agent(
instructions=(
"You're a creative marketing strategist. Craft compelling value propositions and target messaging"
" aligned to the prompt."
@@ -80,7 +80,7 @@ class LegalExec(Executor):
agent: ChatAgent
def __init__(self, chat_client: AzureOpenAIChatClient, id: str = "legal"):
self.agent = chat_client.create_agent(
self.agent = 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/orchestration/concurrent_custom_aggregator.py
+3 -3
View File
@@ -30,21 +30,21 @@ Prerequisites:
async def main() -> None:
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."
),
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."
),
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/orchestration/concurrent_participant_factory.py
+3 -3
View File
@@ -46,7 +46,7 @@ Prerequisites:
def create_researcher() -> ChatAgent:
"""Factory function to create a researcher agent instance."""
return AzureOpenAIChatClient(credential=AzureCliCredential()).create_agent(
return AzureOpenAIChatClient(credential=AzureCliCredential()).as_agent(
instructions=(
"You're an expert market and product researcher. Given a prompt, provide concise, factual insights,"
" opportunities, and risks."
@@ -57,7 +57,7 @@ def create_researcher() -> ChatAgent:
def create_marketer() -> ChatAgent:
"""Factory function to create a marketer agent instance."""
return AzureOpenAIChatClient(credential=AzureCliCredential()).create_agent(
return AzureOpenAIChatClient(credential=AzureCliCredential()).as_agent(
instructions=(
"You're a creative marketing strategist. Craft compelling value propositions and target messaging"
" aligned to the prompt."
@@ -68,7 +68,7 @@ def create_marketer() -> ChatAgent:
def create_legal() -> ChatAgent:
"""Factory function to create a legal/compliance agent instance."""
return AzureOpenAIChatClient(credential=AzureCliCredential()).create_agent(
return AzureOpenAIChatClient(credential=AzureCliCredential()).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/orchestration/handoff_autonomous.py
+3 -3
View File
@@ -44,7 +44,7 @@ def create_agents(
chat_client: AzureOpenAIChatClient,
) -> tuple[ChatAgent, ChatAgent, ChatAgent]:
"""Create coordinator and specialists for autonomous iteration."""
coordinator = chat_client.create_agent(
coordinator = chat_client.as_agent(
instructions=(
"You are a coordinator. You break down a user query into a research task and a summary task. "
"Assign the two tasks to the appropriate specialists, one after the other."
@@ -52,7 +52,7 @@ def create_agents(
name="coordinator",
)
research_agent = chat_client.create_agent(
research_agent = chat_client.as_agent(
instructions=(
"You are a research specialist that explores topics thoroughly using web search. "
"When given a research task, break it down into multiple aspects and explore each one. "
@@ -65,7 +65,7 @@ def create_agents(
tools=[HostedWebSearchTool()],
)
summary_agent = chat_client.create_agent(
summary_agent = chat_client.as_agent(
instructions=(
"You summarize research findings. Provide a concise, well-organized summary. When done, return "
"control to the coordinator."
python/samples/getting_started/workflows/orchestration/handoff_participant_factory.py
+4 -4
View File
@@ -67,7 +67,7 @@ def process_return(order_number: Annotated[str, "Order number to process return
def create_triage_agent() -> ChatAgent:
"""Factory function to create a triage agent instance."""
return AzureOpenAIChatClient(credential=AzureCliCredential()).create_agent(
return AzureOpenAIChatClient(credential=AzureCliCredential()).as_agent(
instructions=(
"You are frontline support triage. Route customer issues to the appropriate specialist agents "
"based on the problem described."
@@ -78,7 +78,7 @@ def create_triage_agent() -> ChatAgent:
def create_refund_agent() -> ChatAgent:
"""Factory function to create a refund agent instance."""
return AzureOpenAIChatClient(credential=AzureCliCredential()).create_agent(
return AzureOpenAIChatClient(credential=AzureCliCredential()).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
@@ -88,7 +88,7 @@ def create_refund_agent() -> ChatAgent:
def create_order_status_agent() -> ChatAgent:
"""Factory function to create an order status agent instance."""
return AzureOpenAIChatClient(credential=AzureCliCredential()).create_agent(
return AzureOpenAIChatClient(credential=AzureCliCredential()).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
@@ -98,7 +98,7 @@ def create_order_status_agent() -> ChatAgent:
def create_return_agent() -> ChatAgent:
"""Factory function to create a return agent instance."""
return AzureOpenAIChatClient(credential=AzureCliCredential()).create_agent(
return AzureOpenAIChatClient(credential=AzureCliCredential()).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/orchestration/handoff_simple.py
+4 -4
View File
@@ -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/orchestration/handoff_with_code_interpreter_file.py
+4 -4
View File
@@ -90,7 +90,7 @@ async def create_agents_v1(credential: AzureCliCredential) -> AsyncIterator[tupl
from agent_framework.azure import AzureAIAgentClient
async with AzureAIAgentClient(credential=credential) as client:
triage = client.create_agent(
triage = client.as_agent(
name="triage_agent",
instructions=(
"You are a triage agent. Route code-related requests to the code_specialist. "
@@ -99,7 +99,7 @@ async def create_agents_v1(credential: AzureCliCredential) -> AsyncIterator[tupl
),
)
code_specialist = client.create_agent(
code_specialist = client.as_agent(
name="code_specialist",
instructions=(
"You are a Python code specialist. Use the code interpreter to execute Python code "
@@ -124,12 +124,12 @@ async def create_agents_v2(credential: AzureCliCredential) -> AsyncIterator[tupl
AzureAIClient(credential=credential) as triage_client,
AzureAIClient(credential=credential) as code_client,
):
triage = triage_client.create_agent(
triage = triage_client.as_agent(
name="TriageAgent",
instructions="You are a triage agent. Your ONLY job is to route requests to the appropriate specialist.",
)
code_specialist = code_client.create_agent(
code_specialist = code_client.as_agent(
name="CodeSpecialist",
instructions=(
"You are a Python code specialist. You have access to a code interpreter tool. "
python/samples/getting_started/workflows/orchestration/sequential_agents.py
+2 -2
View File
@@ -31,12 +31,12 @@ 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/orchestration/sequential_custom_executors.py
+1 -1
View File
@@ -60,7 +60,7 @@ class Summarizer(Executor):
async def main() -> None:
# 1) Create a content agent
chat_client = AzureOpenAIChatClient(credential=AzureCliCredential())
content = chat_client.create_agent(
content = chat_client.as_agent(
instructions="Produce a concise paragraph answering the user's request.",
name="content",
)
python/samples/getting_started/workflows/orchestration/sequential_participant_factory.py
+1 -1
View File
@@ -50,7 +50,7 @@ class Accumulate(Executor):
def create_agent() -> ChatAgent:
return AzureOpenAIChatClient(credential=AzureCliCredential()).create_agent(
return AzureOpenAIChatClient(credential=AzureCliCredential()).as_agent(
instructions="Produce a concise paragraph answering the user's request.",
name="ContentProducer",
)
python/samples/getting_started/workflows/parallelism/fan_out_fan_in_edges.py
+3 -3
View File
@@ -94,7 +94,7 @@ class AggregateInsights(Executor):
def create_researcher_agent() -> ChatAgent:
"""Creates a research domain expert agent."""
return AzureOpenAIChatClient(credential=AzureCliCredential()).create_agent(
return AzureOpenAIChatClient(credential=AzureCliCredential()).as_agent(
instructions=(
"You're an expert market and product researcher. Given a prompt, provide concise, factual insights,"
" opportunities, and risks."
@@ -105,7 +105,7 @@ def create_researcher_agent() -> ChatAgent:
def create_marketer_agent() -> ChatAgent:
"""Creates a marketing domain expert agent."""
return AzureOpenAIChatClient(credential=AzureCliCredential()).create_agent(
return AzureOpenAIChatClient(credential=AzureCliCredential()).as_agent(
instructions=(
"You're a creative marketing strategist. Craft compelling value propositions and target messaging"
" aligned to the prompt."
@@ -116,7 +116,7 @@ def create_marketer_agent() -> ChatAgent:
def create_legal_agent() -> ChatAgent:
"""Creates a legal/compliance domain expert agent."""
return AzureOpenAIChatClient(credential=AzureCliCredential()).create_agent(
return AzureOpenAIChatClient(credential=AzureCliCredential()).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/state-management/shared_states_with_agents.py
+2 -2
View File
@@ -157,7 +157,7 @@ async def handle_spam(detection: DetectionResult, ctx: WorkflowContext[Never, st
def create_spam_detection_agent() -> ChatAgent:
"""Creates a 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. "
"Always return JSON with fields is_spam (bool) and reason (string)."
@@ -170,7 +170,7 @@ def create_spam_detection_agent() -> ChatAgent:
def create_email_assistant_agent() -> ChatAgent:
"""Creates an 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. "
"Return JSON with a single field 'response' containing the drafted reply."
python/samples/getting_started/workflows/state-management/workflow_kwargs.py
+1 -1
View File
@@ -73,7 +73,7 @@ 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/tool-approval/concurrent_builder_tool_approval.py
+2 -2
View File
@@ -104,7 +104,7 @@ async def main() -> None:
# 3. Create two agents focused on different stocks but with the same tool sets
chat_client = OpenAIChatClient()
microsoft_agent = chat_client.create_agent(
microsoft_agent = chat_client.as_agent(
name="MicrosoftAgent",
instructions=(
"You are a personal trading assistant focused on Microsoft (MSFT). "
@@ -113,7 +113,7 @@ async def main() -> None:
tools=[get_stock_price, get_market_sentiment, get_portfolio_balance, execute_trade],
)
google_agent = chat_client.create_agent(
google_agent = chat_client.as_agent(
name="GoogleAgent",
instructions=(
"You are a personal trading assistant focused on Google (GOOGL). "
python/samples/getting_started/workflows/tool-approval/group_chat_builder_tool_approval.py
+2 -2
View File
@@ -96,7 +96,7 @@ async def main() -> None:
# 3. Create specialized agents
chat_client = OpenAIChatClient()
qa_engineer = chat_client.create_agent(
qa_engineer = chat_client.as_agent(
name="QAEngineer",
instructions=(
"You are a QA engineer responsible for running tests before deployment. "
@@ -105,7 +105,7 @@ async def main() -> None:
tools=[run_tests],
)
devops_engineer = chat_client.create_agent(
devops_engineer = chat_client.as_agent(
name="DevOpsEngineer",
instructions=(
"You are a DevOps engineer responsible for deployments. First check staging "
python/samples/getting_started/workflows/tool-approval/sequential_builder_tool_approval.py
+1 -1
View File
@@ -67,7 +67,7 @@ def get_database_schema() -> str:
async def main() -> None:
# 2. Create the agent with tools (approval mode is set per-tool via decorator)
chat_client = OpenAIChatClient()
database_agent = chat_client.create_agent(
database_agent = chat_client.as_agent(
name="DatabaseAgent",
instructions=(
"You are a database assistant. You can view the database schema and execute "
python/samples/getting_started/workflows/visualization/concurrent_with_visualization.py
+3 -3
View File
@@ -88,7 +88,7 @@ class AggregateInsights(Executor):
def create_researcher_agent() -> ChatAgent:
"""Creates a research domain expert agent."""
return AzureOpenAIChatClient(credential=AzureCliCredential()).create_agent(
return AzureOpenAIChatClient(credential=AzureCliCredential()).as_agent(
instructions=(
"You're an expert market and product researcher. Given a prompt, provide concise, factual insights,"
" opportunities, and risks."
@@ -99,7 +99,7 @@ def create_researcher_agent() -> ChatAgent:
def create_marketer_agent() -> ChatAgent:
"""Creates a marketing domain expert agent."""
return AzureOpenAIChatClient(credential=AzureCliCredential()).create_agent(
return AzureOpenAIChatClient(credential=AzureCliCredential()).as_agent(
instructions=(
"You're a creative marketing strategist. Craft compelling value propositions and target messaging"
" aligned to the prompt."
@@ -110,7 +110,7 @@ def create_marketer_agent() -> ChatAgent:
def create_legal_agent() -> ChatAgent:
"""Creates a legal domain expert agent."""
return AzureOpenAIChatClient(credential=AzureCliCredential()).create_agent(
return AzureOpenAIChatClient(credential=AzureCliCredential()).as_agent(
instructions=(
"You're a cautious legal/compliance reviewer. Highlight constraints, disclaimers, and policy concerns"
" based on the prompt."