Python: feat: Add create_handoff_tools() for Azure AI Agent Service compatibility

python/packages/core/agent_framework/orchestrations/__init__.py

@@ -17,6 +17,8 @@
     "HandoffBuilder",
     "HandoffConfiguration",
     "HandoffSentEvent",
+    "create_handoff_tools",
+    "get_handoff_tool_name",
     # Base orchestrator
     "BaseGroupChatOrchestrator",
     "GroupChatRequestMessage",

python/packages/core/agent_framework/orchestrations/__init__.pyi

@@ -21,6 +21,8 @@ from agent_framework_orchestrations import (
     HandoffBuilder,
     HandoffConfiguration,
     HandoffSentEvent,
+    create_handoff_tools,
+    get_handoff_tool_name,
     MagenticAgentExecutor,
     MagenticBuilder,
     MagenticContext,
@@ -74,4 +76,6 @@ __all__ = [
     "SequentialBuilder",
     "StandardMagenticManager",
     "__version__",
+    "create_handoff_tools",
+    "get_handoff_tool_name",
 ]

python/packages/orchestrations/agent_framework_orchestrations/__init__.py

@@ -39,6 +39,8 @@
     HandoffBuilder,
     HandoffConfiguration,
     HandoffSentEvent,
+    create_handoff_tools,
+    get_handoff_tool_name,
 )
 from ._magentic import (
     MAGENTIC_MANAGER_NAME,
@@ -107,4 +109,6 @@
     "__version__",
     "clean_conversation_for_handoff",
     "create_completion_message",
+    "create_handoff_tools",
+    "get_handoff_tool_name",
 ]

python/packages/orchestrations/agent_framework_orchestrations/_handoff.py

@@ -32,7 +32,7 @@
 import inspect
 import logging
 import sys
-from collections.abc import Awaitable, Callable, Sequence
+from collections.abc import Awaitable, Callable, Mapping, Sequence
 from dataclasses import dataclass
 from typing import Any, cast
 
@@ -116,6 +116,46 @@ def get_handoff_tool_name(target_id: str) -> str:
     return f"handoff_to_{target_id}"
 
 
+def create_handoff_tools(
+    target_agent_ids: Sequence[str],
+    descriptions: Mapping[str, str] | None = None,
+) -> list[FunctionTool[Any, Any]]:
+    """Create handoff tools for pre-registration with agents at creation time.
+
+    Use this function when working with services like Azure AI Agent Service
+    that require tools to be registered at agent creation time rather than
+    at request time. The returned tools can be passed directly to the agent
+    constructor.
+
+    Example::
+
+        # Create handoff tools for Azure AI Agent Service
+        handoff_tools = create_handoff_tools(["specialist", "escalation"])
+        agent = Agent(client=client, name="triage", default_options={"tools": handoff_tools})
+
+    Args:
+        target_agent_ids: Sequence of target agent IDs to create handoff tools for.
+        descriptions: Optional mapping from agent ID to a custom description for
+            the handoff tool. If not provided or if a given agent ID is not in the
+            mapping, the default description ``"Handoff to the <id> agent."`` is used.
+
+    Returns:
+        A list of :class:`FunctionTool` instances, one per target agent ID.
+    """
+    tools: list[FunctionTool[Any, Any]] = []
+    for target_id in target_agent_ids:
+        tool_name = get_handoff_tool_name(target_id)
+        doc = (descriptions or {}).get(target_id) or f"Handoff to the {target_id} agent."
+
+        @tool(name=tool_name, description=doc, approval_mode="never_require")
+        def _handoff_tool(context: str | None = None, _tid: str = target_id) -> str:
+            """Return a deterministic acknowledgement that encodes the target alias."""
+            return f"Handoff to {_tid}"
+
+        tools.append(_handoff_tool)
+    return tools
+
+
 HANDOFF_FUNCTION_RESULT_KEY = "handoff_to"
 
 
@@ -329,11 +369,12 @@ def _apply_auto_tools(self, agent: Agent, targets: Sequence[HandoffConfiguration
         for target in targets:
             handoff_tool = self._create_handoff_tool(target.target_id, target.description)
             if handoff_tool.name in existing_names:
-                raise ValueError(
-                    f"Agent '{resolve_agent_id(agent)}' already has a tool named '{handoff_tool.name}'. "
-                    f"Handoff tool name '{handoff_tool.name}' conflicts with existing tool."
-                    "Please rename the existing tool or modify the target agent ID to avoid conflicts."
+                logger.debug(
+                    "Agent '%s' already has a tool named '%s'; skipping auto-registration.",
+                    resolve_agent_id(agent),
+                    handoff_tool.name,
                 )
+                continue
             new_tools.append(handoff_tool)
 
         if new_tools:

python/packages/orchestrations/tests/test_handoff.py

@@ -20,7 +20,7 @@
 from agent_framework._clients import BaseChatClient
 from agent_framework._middleware import ChatMiddlewareLayer
 from agent_framework._tools import FunctionInvocationLayer
-from agent_framework.orchestrations import HandoffAgentUserRequest, HandoffBuilder
+from agent_framework.orchestrations import HandoffAgentUserRequest, HandoffBuilder, create_handoff_tools, get_handoff_tool_name
 
 
 class MockChatClient(ChatMiddlewareLayer[Any], FunctionInvocationLayer[Any], BaseChatClient[Any]):
@@ -364,3 +364,105 @@ def test_handoff_builder_accepts_all_instances_in_add_handoff():
     assert "triage" in workflow.executors
     assert "specialist_a" in workflow.executors
     assert "specialist_b" in workflow.executors
+
+
+def test_create_handoff_tools_creates_correct_tools():
+    """Test that create_handoff_tools creates tools with correct names and default descriptions."""
+    target_ids = ["specialist", "escalation"]
+    tools = create_handoff_tools(target_ids)
+
+    assert len(tools) == 2
+    assert tools[0].name == "handoff_to_specialist"
+    assert tools[1].name == "handoff_to_escalation"
+    assert tools[0].description == "Handoff to the specialist agent."
+    assert tools[1].description == "Handoff to the escalation agent."
+
+
+def test_create_handoff_tools_with_custom_descriptions():
+    """Test that create_handoff_tools uses custom descriptions when provided."""
+    target_ids = ["billing", "tech"]
+    descriptions = {
+        "billing": "Transfer the customer to the billing department.",
+        "tech": "Transfer the customer to technical support.",
+    }
+    tools = create_handoff_tools(target_ids, descriptions=descriptions)
+
+    assert len(tools) == 2
+    assert tools[0].name == "handoff_to_billing"
+    assert tools[1].name == "handoff_to_tech"
+    assert tools[0].description == "Transfer the customer to the billing department."
+    assert tools[1].description == "Transfer the customer to technical support."
+
+
+def test_create_handoff_tools_empty():
+    """Test that create_handoff_tools returns empty list for empty input."""
+    tools = create_handoff_tools([])
+    assert tools == []
+
+
+async def test_pre_registered_tools_no_conflict():
+    """Test that pre-registered handoff tools do not raise ValueError when building a workflow.
+
+    This verifies the Azure AI Agent Service compatibility fix: when a user creates
+    handoff tools upfront and attaches them to the agent, _apply_auto_tools should
+    skip the duplicates instead of raising.
+    """
+    pre_registered_tools = create_handoff_tools(["specialist"])
+    mock_client = MockChatClient(name="triage")
+    agent = Agent(
+        client=mock_client,
+        name="triage",
+        id="triage",
+        default_options={"tools": pre_registered_tools},  # type: ignore
+    )
+
+    specialist = MockHandoffAgent(name="specialist")
+    # This should NOT raise ValueError for duplicate tool names
+    workflow = (
+        HandoffBuilder(participants=[agent, specialist])
+        .with_start_agent(agent)
+        .add_handoff(agent, [specialist])
+        .build()
+    )
+
+    assert "triage" in workflow.executors
+    assert "specialist" in workflow.executors
+
+
+def test_get_handoff_tool_name():
+    """Test that get_handoff_tool_name returns the expected format."""
+    assert get_handoff_tool_name("specialist") == "handoff_to_specialist"
+    assert get_handoff_tool_name("billing_agent") == "handoff_to_billing_agent"
+
+
+async def test_mesh_topology_with_pre_registered_tools():
+    """Test that pre-registered tools work in a mesh topology where each agent can route to all others."""
+    # Create agents with pre-registered handoff tools (Azure AI Agent Service pattern)
+    mock_client_a = MockChatClient(name="agent_a", handoff_to="agent_b")
+    tools_a = create_handoff_tools(["agent_b", "agent_c"])
+    agent_a = Agent(
+        client=mock_client_a,
+        name="agent_a",
+        id="agent_a",
+        default_options={"tools": tools_a},  # type: ignore
+    )
+
+    agent_b = MockHandoffAgent(name="agent_b")
+    agent_c = MockHandoffAgent(name="agent_c")
+
+    workflow = (
+        HandoffBuilder(participants=[agent_a, agent_b, agent_c])
+        .with_start_agent(agent_a)
+        .build()
+    )
+
+    assert "agent_a" in workflow.executors
+    assert "agent_b" in workflow.executors
+    assert "agent_c" in workflow.executors
+
+    # Run the workflow to verify it works end-to-end
+    events = await _drain(workflow.run("Test message", stream=True))
+    # agent_a should hand off to agent_b, which has no further handoff
+    # so it should request user input
+    requests = [ev for ev in events if ev.type == "request_info"]
+    assert requests

python/samples/getting_started/workflows/README.md

@@ -46,6 +46,7 @@ Once comfortable with these, explore the rest of the samples below.
 | Workflow as Agent with Thread          | [agents/workflow_as_agent_with_thread.py](./agents/workflow_as_agent_with_thread.py)                           | Use AgentThread to maintain conversation history across workflow-as-agent invocations                |
 | Workflow as Agent kwargs               | [agents/workflow_as_agent_kwargs.py](./agents/workflow_as_agent_kwargs.py)                                     | Pass custom context (data, user tokens) via kwargs through workflow.as_agent() to @ai_function tools |
 | Handoff Workflow as Agent              | [agents/handoff_workflow_as_agent.py](./agents/handoff_workflow_as_agent.py)                                   | Use a HandoffBuilder workflow as an agent with HITL via FunctionCallContent/FunctionResultContent    |
+| Azure AI Handoff (Pre-Registered Tools) | [agents/handoff_with_azure_ai_agents.py](./agents/handoff_with_azure_ai_agents.py)                           | Use create_handoff_tools() to pre-register handoff tools at agent creation time for Azure AI Agent Service |
 
 ### checkpoint