[BREAKING] Python: Remove workflow register factory methods. Update tests and samples (#3781)

* Remove workflow register factory methods. Update tests and samples

* Address Copilot feedback

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

@@ -3,6 +3,7 @@
 import asyncio
 
 from agent_framework import (
+    AgentExecutor,
     AgentExecutorRequest,
     AgentExecutorResponse,
     ChatMessageStore,
@@ -70,15 +71,12 @@ async def main() -> None:
         # Set the message store to store messages in memory.
         shared_thread.message_store = ChatMessageStore()
 
+        writer_executor = AgentExecutor(writer, agent_thread=shared_thread)
+        reviewer_executor = AgentExecutor(reviewer, agent_thread=shared_thread)
+
         workflow = (
-            WorkflowBuilder(start_executor="writer")
-            .register_agent(factory_func=lambda: writer, name="writer", agent_thread=shared_thread)
-            .register_agent(factory_func=lambda: reviewer, name="reviewer", agent_thread=shared_thread)
-            .register_executor(
-                factory_func=lambda: intercept_agent_response,
-                name="intercept_agent_response",
-            )
-            .add_chain(["writer", "intercept_agent_response", "reviewer"])
+            WorkflowBuilder(start_executor=writer_executor)
+            .add_chain([writer_executor, intercept_agent_response, reviewer_executor])
             .build()
         )
 

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

@@ -6,6 +6,7 @@ from dataclasses import dataclass, field
 from typing import Annotated
 
 from agent_framework import (
+    AgentExecutor,
     AgentExecutorRequest,
     AgentExecutorResponse,
     AgentResponse,
@@ -239,22 +240,20 @@ async def main() -> None:
     """Run the workflow and bridge human feedback between two agents."""
 
     # Build the workflow.
+    writer_agent = AgentExecutor(create_writer_agent())
+    final_editor_agent = AgentExecutor(create_final_editor_agent())
+    coordinator = Coordinator(
+        id="coordinator",
+        writer_id="writer_agent",
+        final_editor_id="final_editor_agent",
+    )
+
     workflow = (
-        WorkflowBuilder(start_executor="writer_agent")
-        .register_agent(create_writer_agent, name="writer_agent")
-        .register_agent(create_final_editor_agent, name="final_editor_agent")
-        .register_executor(
-            lambda: Coordinator(
-                id="coordinator",
-                writer_id="writer_agent",
-                final_editor_id="final_editor_agent",
-            ),
-            name="coordinator",
-        )
-        .add_edge("writer_agent", "coordinator")
-        .add_edge("coordinator", "writer_agent")
-        .add_edge("final_editor_agent", "coordinator")
-        .add_edge("coordinator", "final_editor_agent")
+        WorkflowBuilder(start_executor=writer_agent)
+        .add_edge(writer_agent, coordinator)
+        .add_edge(coordinator, writer_agent)
+        .add_edge(final_editor_agent, coordinator)
+        .add_edge(coordinator, final_editor_agent)
         .build()
     )
 

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

@@ -98,21 +98,16 @@ async def main() -> None:
     print("Building workflow with Worker-Reviewer cycle...")
     # Build a workflow with bidirectional communication between Worker and Reviewer,
     # and escalation paths for human review.
+    worker = Worker(
+        id="worker",
+        chat_client=AzureOpenAIChatClient(credential=AzureCliCredential()),
+    )
+    reviewer = ReviewerWithHumanInTheLoop(worker_id="worker")
+
     agent = (
-        WorkflowBuilder(start_executor="worker")
-        .register_executor(
-            lambda: Worker(
-                id="sub-worker",
-                chat_client=AzureOpenAIChatClient(credential=AzureCliCredential()),
-            ),
-            name="worker",
-        )
-        .register_executor(
-            lambda: ReviewerWithHumanInTheLoop(worker_id="sub-worker"),
-            name="reviewer",
-        )
-        .add_edge("worker", "reviewer")  # Worker sends requests to Reviewer
-        .add_edge("reviewer", "worker")  # Reviewer sends feedback to Worker
+        WorkflowBuilder(start_executor=worker)
+        .add_edge(worker, reviewer)  # Worker sends requests to Reviewer
+        .add_edge(reviewer, worker)  # Reviewer sends feedback to Worker
         .build()
         .as_agent()  # Convert workflow into an agent interface
     )

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

@@ -186,18 +186,13 @@ async def main() -> None:
     print("=" * 50)
 
     print("Building workflow with Worker ↔ Reviewer cycle...")
+    worker = Worker(id="worker", chat_client=OpenAIChatClient(model_id="gpt-4.1-nano"))
+    reviewer = Reviewer(id="reviewer", chat_client=OpenAIChatClient(model_id="gpt-4.1"))
+
     agent = (
-        WorkflowBuilder(start_executor="worker")
-        .register_executor(
-            lambda: Worker(id="worker", chat_client=OpenAIChatClient(model_id="gpt-4.1-nano")),
-            name="worker",
-        )
-        .register_executor(
-            lambda: Reviewer(id="reviewer", chat_client=OpenAIChatClient(model_id="gpt-4.1")),
-            name="reviewer",
-        )
-        .add_edge("worker", "reviewer")  # Worker sends responses to Reviewer
-        .add_edge("reviewer", "worker")  # Reviewer provides feedback to Worker
+        WorkflowBuilder(start_executor=worker)
+        .add_edge(worker, reviewer)  # Worker sends responses to Reviewer
+        .add_edge(reviewer, worker)  # Reviewer provides feedback to Worker
         .build()
         .as_agent()  # Wrap workflow as an agent
     )

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

@@ -2,7 +2,7 @@
 
 import asyncio
 
-from agent_framework import AgentThread, ChatAgent, ChatMessageStore
+from agent_framework import AgentThread, ChatMessageStore
 from agent_framework.openai import OpenAIChatClient
 from agent_framework.orchestrations import SequentialBuilder
 
@@ -39,27 +39,24 @@ async def main() -> None:
     # Create a chat client
     chat_client = OpenAIChatClient()
 
-    # Define factory functions for workflow participants
-    def create_assistant() -> ChatAgent:
-        return chat_client.as_agent(
-            name="assistant",
-            instructions=(
-                "You are a helpful assistant. Answer questions based on the conversation "
-                "history. If the user asks about something mentioned earlier, reference it."
-            ),
-        )
+    assistant = chat_client.as_agent(
+        name="assistant",
+        instructions=(
+            "You are a helpful assistant. Answer questions based on the conversation "
+            "history. If the user asks about something mentioned earlier, reference it."
+        ),
+    )
 
-    def create_summarizer() -> ChatAgent:
-        return chat_client.as_agent(
-            name="summarizer",
-            instructions=(
-                "You are a summarizer. After the assistant responds, provide a brief "
-                "one-sentence summary of the key point from the conversation so far."
-            ),
-        )
+    summarizer = chat_client.as_agent(
+        name="summarizer",
+        instructions=(
+            "You are a summarizer. After the assistant responds, provide a brief "
+            "one-sentence summary of the key point from the conversation so far."
+        ),
+    )
 
     # Build a sequential workflow: assistant -> summarizer
-    workflow = SequentialBuilder(participant_factories=[create_assistant, create_summarizer]).build()
+    workflow = SequentialBuilder(participants=[assistant, summarizer]).build()
 
     # Wrap the workflow as an agent
     agent = workflow.as_agent(name="ConversationalWorkflowAgent")
@@ -124,13 +121,12 @@ async def demonstrate_thread_serialization() -> None:
     """
     chat_client = OpenAIChatClient()
 
-    def create_assistant() -> ChatAgent:
-        return chat_client.as_agent(
-            name="memory_assistant",
-            instructions="You are a helpful assistant with good memory. Remember details from our conversation.",
-        )
+    memory_assistant = chat_client.as_agent(
+        name="memory_assistant",
+        instructions="You are a helpful assistant with good memory. Remember details from our conversation.",
+    )
 
-    workflow = SequentialBuilder(participant_factories=[create_assistant]).build()
+    workflow = SequentialBuilder(participants=[memory_assistant]).build()
     agent = workflow.as_agent(name="MemoryWorkflowAgent")
 
     # Create initial thread and have a conversation