Python: [BREAKING] Renamed AgentProtocol to SupportsAgentRun (#3717)

* Renamed AgentProtocol to AgentLike

* Resolved comments

* Renamed AgentLike to SupportsAgentRun

* Resolved comments

python/samples/getting_started/orchestrations/concurrent_agents.py

@@ -56,7 +56,7 @@ async def main() -> None:
     )
 
     # 2) Build a concurrent workflow
-    # Participants are either Agents (type of AgentProtocol) or Executors
+    # Participants are either Agents (type of SupportsAgentRun) or Executors
     workflow = ConcurrentBuilder().participants([researcher, marketer, legal]).build()
 
     # 3) Run with a single prompt and pretty-print the final combined messages

python/samples/getting_started/orchestrations/concurrent_custom_aggregator.py

@@ -80,7 +80,7 @@ async def main() -> None:
         return response.messages[-1].text if response.messages else ""
 
     # Build with a custom aggregator callback function
-    # - participants([...]) accepts AgentProtocol (agents) or Executor instances.
+    # - participants([...]) accepts SupportsAgentRun (agents) or Executor instances.
     #   Each participant becomes a parallel branch (fan-out) from an internal dispatcher.
     # - with_aggregator(...) overrides the default aggregator:
     #   • Default aggregator -> returns list[ChatMessage] (one user + one assistant per agent)

python/samples/getting_started/orchestrations/concurrent_participant_factory.py

@@ -122,7 +122,7 @@ async def run_workflow(workflow: Workflow, query: str) -> None:
 async def main() -> None:
     # Create a concurrent builder with participant factories and a custom aggregator
     # - register_participants([...]) accepts factory functions that return
-    #   AgentProtocol (agents) or Executor instances.
+    #   SupportsAgentRun (agents) or Executor instances.
     # - register_aggregator(...) takes a factory function that returns an Executor instance.
     concurrent_builder = (
         ConcurrentBuilder()

python/samples/getting_started/orchestrations/magentic.py

@@ -51,8 +51,6 @@ async def main() -> None:
             "You are a Researcher. You find information without additional computation or quantitative analysis."
         ),
         # This agent requires the gpt-4o-search-preview model to perform web searches.
-        # Feel free to explore with other agents that support web search, for example,
-        # the `OpenAIResponseAgent` or `AzureAgentProtocol` with bing grounding.
         chat_client=OpenAIChatClient(model_id="gpt-4o-search-preview"),
     )