chore(prebuilt): revert back to create_react_agent (#6017)

libs/langgraph/tests/test_large_cases.py

@@ -21,7 +21,7 @@ from langgraph.checkpoint.memory import InMemorySaver
 from langgraph.constants import END, START
 from langgraph.graph import StateGraph
 from langgraph.graph.message import MessagesState, add_messages
-from langgraph.prebuilt.chat_agent_executor import create_agent
+from langgraph.prebuilt.chat_agent_executor import create_react_agent
 from langgraph.prebuilt.tool_node import ToolNode
 from langgraph.pregel import NodeBuilder, Pregel
 from langgraph.types import (
@@ -1301,7 +1301,7 @@ def test_prebuilt_tool_chat(snapshot: SnapshotAssertion) -> None:
         ]
     )
 
-    app = create_agent(model, tools)
+    app = create_react_agent(model, tools)
 
     assert json.dumps(app.get_input_jsonschema()) == snapshot
     assert json.dumps(app.get_output_jsonschema()) == snapshot

libs/langgraph/tests/test_large_cases_async.py

@@ -23,7 +23,7 @@ from langgraph.checkpoint.base import BaseCheckpointSaver
 from langgraph.constants import END, START
 from langgraph.graph.message import add_messages
 from langgraph.graph.state import StateGraph
-from langgraph.prebuilt.chat_agent_executor import create_agent
+from langgraph.prebuilt.chat_agent_executor import create_react_agent
 from langgraph.prebuilt.tool_node import ToolNode
 from langgraph.pregel import NodeBuilder, Pregel
 from langgraph.types import PregelTask, Send, StateSnapshot, StreamWriter
@@ -1059,7 +1059,7 @@ async def test_prebuilt_tool_chat() -> None:
 
     tools = [search_api]
 
-    app = create_agent(model, tools)
+    app = create_react_agent(model, tools)
 
     assert await app.ainvoke(
         {"messages": [HumanMessage(content="what is weather in sf")]}

libs/prebuilt/langgraph/prebuilt/__init__.py

@@ -1,6 +1,6 @@
 """langgraph.prebuilt exposes a higher-level API for creating and executing agents and tools."""
 
-from langgraph.prebuilt.chat_agent_executor import create_agent
+from langgraph.prebuilt.chat_agent_executor import create_react_agent
 from langgraph.prebuilt.tool_node import (
     InjectedState,
     InjectedStore,
@@ -10,7 +10,7 @@ from langgraph.prebuilt.tool_node import (
 from langgraph.prebuilt.tool_validator import ValidationNode
 
 __all__ = [
-    "create_agent",
+    "create_react_agent",
     "ToolNode",
     "tools_condition",
     "ValidationNode",

libs/prebuilt/langgraph/prebuilt/chat_agent_executor.py

@@ -899,7 +899,7 @@ def _supports_native_structured_output(
     )
 
 
-def create_agent(
+def create_react_agent(
     model: Union[
         str,
         BaseChatModel,
@@ -928,7 +928,7 @@ def create_agent(
 ) -> CompiledStateGraph:
     """Creates an agent graph that calls tools in a loop until a stopping condition is met.
 
-    For more details on using `create_agent`, visit [Agents](https://langchain-ai.github.io/langgraph/agents/overview/) documentation.
+    For more details on using `create_react_agent`, visit [Agents](https://langchain-ai.github.io/langgraph/agents/overview/) documentation.
 
     Args:
         model: The language model for the agent. Supports static and dynamic
@@ -1072,13 +1072,13 @@ def create_agent(
 
     Example:
         ```python
-        from langgraph.prebuilt import create_agent
+        from langgraph.prebuilt import create_react_agent
 
         def check_weather(location: str) -> str:
             '''Return the weather forecast for the specified location.'''
             return f"It's always sunny in {location}"
 
-        graph = create_agent(
+        graph = create_react_agent(
             "anthropic:claude-3-7-sonnet-latest",
             tools=[check_weather],
             prompt="You are a helpful assistant",
@@ -1132,6 +1132,6 @@ def create_agent(
 
 
 __all__ = [
-    "create_agent",
+    "create_react_agent",
     "AgentState",
 ]

libs/prebuilt/tests/test_react_agent.py

@@ -27,7 +27,7 @@ from langgraph.graph import START, MessagesState, StateGraph
 from langgraph.graph.message import REMOVE_ALL_MESSAGES
 from langgraph.prebuilt import (
     ToolNode,
-    create_agent,
+    create_react_agent,
 )
 from langgraph.prebuilt.chat_agent_executor import (
     AgentState,
@@ -53,7 +53,7 @@ pytestmark = pytest.mark.anyio
 def test_no_prompt(sync_checkpointer: BaseCheckpointSaver) -> None:
     model = FakeToolCallingModel()
 
-    agent = create_agent(
+    agent = create_react_agent(
         model,
         [],
         checkpointer=sync_checkpointer,
@@ -83,7 +83,7 @@ def test_no_prompt(sync_checkpointer: BaseCheckpointSaver) -> None:
 async def test_no_prompt_async(async_checkpointer: BaseCheckpointSaver) -> None:
     model = FakeToolCallingModel()
 
-    agent = create_agent(model, [], checkpointer=async_checkpointer)
+    agent = create_react_agent(model, [], checkpointer=async_checkpointer)
     inputs = [HumanMessage("hi?")]
     thread = {"configurable": {"thread_id": "123"}}
     response = await agent.ainvoke({"messages": inputs}, thread, debug=True)
@@ -108,7 +108,7 @@ async def test_no_prompt_async(async_checkpointer: BaseCheckpointSaver) -> None:
 
 def test_system_message_prompt():
     prompt = SystemMessage(content="Foo")
-    agent = create_agent(FakeToolCallingModel(), [], prompt=prompt)
+    agent = create_react_agent(FakeToolCallingModel(), [], prompt=prompt)
     inputs = [HumanMessage("hi?")]
     response = agent.invoke({"messages": inputs})
     expected_response = {
@@ -119,7 +119,7 @@ def test_system_message_prompt():
 
 def test_string_prompt():
     prompt = "Foo"
-    agent = create_agent(FakeToolCallingModel(), [], prompt=prompt)
+    agent = create_react_agent(FakeToolCallingModel(), [], prompt=prompt)
     inputs = [HumanMessage("hi?")]
     response = agent.invoke({"messages": inputs})
     expected_response = {
@@ -133,7 +133,7 @@ def test_callable_prompt():
         modified_message = f"Bar {state['messages'][-1].content}"
         return [HumanMessage(content=modified_message)]
 
-    agent = create_agent(FakeToolCallingModel(), [], prompt=prompt)
+    agent = create_react_agent(FakeToolCallingModel(), [], prompt=prompt)
     inputs = [HumanMessage("hi?")]
     response = agent.invoke({"messages": inputs})
     expected_response = {"messages": inputs + [AIMessage(content="Bar hi?", id="0")]}
@@ -145,7 +145,7 @@ async def test_callable_prompt_async():
         modified_message = f"Bar {state['messages'][-1].content}"
         return [HumanMessage(content=modified_message)]
 
-    agent = create_agent(FakeToolCallingModel(), [], prompt=prompt)
+    agent = create_react_agent(FakeToolCallingModel(), [], prompt=prompt)
     inputs = [HumanMessage("hi?")]
     response = await agent.ainvoke({"messages": inputs})
     expected_response = {"messages": inputs + [AIMessage(content="Bar hi?", id="0")]}
@@ -157,7 +157,7 @@ def test_runnable_prompt():
         lambda state: [HumanMessage(content=f"Baz {state['messages'][-1].content}")]
     )
 
-    agent = create_agent(FakeToolCallingModel(), [], prompt=prompt)
+    agent = create_react_agent(FakeToolCallingModel(), [], prompt=prompt)
     inputs = [HumanMessage("hi?")]
     response = agent.invoke({"messages": inputs})
     expected_response = {"messages": inputs + [AIMessage(content="Baz hi?", id="0")]}
@@ -184,7 +184,7 @@ def test_prompt_with_store():
     model = FakeToolCallingModel()
 
     # test state modifier that uses store works
-    agent = create_agent(
+    agent = create_react_agent(
         model,
         [add],
         prompt=prompt,
@@ -196,7 +196,7 @@ def test_prompt_with_store():
     assert response["messages"][-1].content == "User name is Alice-hi"
 
     # test state modifier that doesn't use store works
-    agent = create_agent(
+    agent = create_react_agent(
         model,
         [add],
         prompt=prompt_no_store,
@@ -234,14 +234,14 @@ async def test_prompt_with_store_async():
     model = FakeToolCallingModel()
 
     # test state modifier that uses store works
-    agent = create_agent(model, [add], prompt=prompt, store=in_memory_store)
+    agent = create_react_agent(model, [add], prompt=prompt, store=in_memory_store)
     response = await agent.ainvoke(
         {"messages": [("user", "hi")]}, {"configurable": {"user_id": "1"}}
     )
     assert response["messages"][-1].content == "User name is Alice-hi"
 
     # test state modifier that doesn't use store works
-    agent = create_agent(model, [add], prompt=prompt_no_store, store=in_memory_store)
+    agent = create_react_agent(model, [add], prompt=prompt_no_store, store=in_memory_store)
     response = await agent.ainvoke(
         {"messages": [("user", "hi")]}, {"configurable": {"user_id": "2"}}
     )
@@ -282,7 +282,7 @@ def test_model_with_tools(tool_style: str, include_builtin: bool) -> None:
         )
     # check valid agent constructor
     with pytest.raises(ValueError):
-        create_agent(
+        create_react_agent(
             model.bind_tools(tools),
             tools,
         )
@@ -431,7 +431,7 @@ def test_react_agent_with_structured_response() -> None:
     model = FakeToolCallingModel[WeatherResponse](
         tool_calls=tool_calls, structured_response=expected_structured_response
     )
-    agent = create_agent(
+    agent = create_react_agent(
         model,
         [get_weather],
         response_format=WeatherResponse,
@@ -491,7 +491,7 @@ def test_react_agent_update_state(
 
     tool_calls = [[{"args": {}, "id": "1", "name": "get_user_name"}]]
     model = FakeToolCallingModel(tool_calls=tool_calls)
-    agent = create_agent(
+    agent = create_react_agent(
         model,
         [get_user_name],
         state_schema=CustomState,
@@ -542,7 +542,7 @@ def test_react_agent_parallel_tool_calls(
         [],
     ]
     model = FakeToolCallingModel(tool_calls=tool_calls)
-    agent = create_agent(
+    agent = create_react_agent(
         model,
         [human_assistance, get_weather],
         checkpointer=sync_checkpointer,
@@ -606,7 +606,7 @@ def test_create_react_agent_inject_vars() -> None:
         "type": "tool_call",
     }
     model = FakeToolCallingModel(tool_calls=[[tool_call], []])
-    agent = create_agent(
+    agent = create_react_agent(
         model,
         ToolNode([tool1], handle_tool_errors=False),
         state_schema=AgentStateExtraKey,
@@ -646,7 +646,7 @@ async def test_return_direct() -> None:
         tool_calls=first_tool_call,
     )
     model = FakeToolCallingModel(tool_calls=[first_tool_call, []])
-    agent = create_agent(
+    agent = create_react_agent(
         model,
         [tool_return_direct, tool_normal],
     )
@@ -673,7 +673,7 @@ async def test_return_direct() -> None:
         ),
     ]
     model = FakeToolCallingModel(tool_calls=[second_tool_call, []])
-    agent = create_agent(model, [tool_return_direct, tool_normal])
+    agent = create_react_agent(model, [tool_return_direct, tool_normal])
     result = agent.invoke(
         {"messages": [HumanMessage(content="Test normal", id="hum1")]}
     )
@@ -702,7 +702,7 @@ async def test_return_direct() -> None:
         ),
     ]
     model = FakeToolCallingModel(tool_calls=[both_tool_calls, []])
-    agent = create_agent(model, [tool_return_direct, tool_normal])
+    agent = create_react_agent(model, [tool_return_direct, tool_normal])
     result = agent.invoke({"messages": [HumanMessage(content="Test both", id="hum2")]})
     assert result["messages"] == [
         HumanMessage(content="Test both", id="hum2"),
@@ -739,7 +739,7 @@ def test__get_state_args() -> None:
 
 def test_inspect_react() -> None:
     model = FakeToolCallingModel(tool_calls=[])
-    agent = create_agent(model, [])
+    agent = create_react_agent(model, [])
     inspect.getclosurevars(agent.nodes["model"].bound.func)
 
 
@@ -796,7 +796,7 @@ def test_react_with_subgraph_tools(
         ]
     )
     tool_node = ToolNode([addition, multiplication], handle_tool_errors=False)
-    agent = create_agent(
+    agent = create_react_agent(
         model,
         tool_node,
         checkpointer=sync_checkpointer,
@@ -846,7 +846,7 @@ def test_react_agent_subgraph_streaming_sync() -> None:
         ]
     )
 
-    agent = create_agent(
+    agent = create_react_agent(
         model,
         tools=[get_weather],
         prompt="You are a helpful travel assistant.",
@@ -935,7 +935,7 @@ async def test_react_agent_subgraph_streaming() -> None:
         ]
     )
 
-    agent = create_agent(
+    agent = create_react_agent(
         model,
         tools=[get_weather],
         prompt="You are a helpful travel assistant.",
@@ -1033,7 +1033,7 @@ def test_tool_node_node_interrupt(
         ]
     )
     config = {"configurable": {"thread_id": "1"}}
-    agent = create_agent(
+    agent = create_react_agent(
         model,
         [tool_interrupt, tool_normal],
         checkpointer=sync_checkpointer,
@@ -1085,7 +1085,7 @@ def test_dynamic_model_basic() -> None:
         else:
             return FakeToolCallingModel(tool_calls=[])
 
-    agent = create_agent(dynamic_model, [])
+    agent = create_react_agent(dynamic_model, [])
 
     result = agent.invoke({"messages": [HumanMessage("hello")]})
     assert len(result["messages"]) == 2
@@ -1123,7 +1123,7 @@ def test_dynamic_model_with_tools() -> None:
                 tool_calls=[[{"args": {"x": 1}, "id": "1", "name": "basic_tool"}], []]
             )
 
-    agent = create_agent(dynamic_model, [basic_tool, advanced_tool])
+    agent = create_react_agent(dynamic_model, [basic_tool, advanced_tool])
 
     # Test basic tool usage
     result = agent.invoke({"messages": [HumanMessage("basic request")]})
@@ -1156,7 +1156,7 @@ def test_dynamic_model_with_context() -> None:
         else:
             return FakeToolCallingModel(tool_calls=[])
 
-    agent = create_agent(dynamic_model, [], context_schema=Context)
+    agent = create_react_agent(dynamic_model, [], context_schema=Context)
 
     # Test with basic user
     result = agent.invoke(
@@ -1186,7 +1186,7 @@ def test_dynamic_model_with_state_schema() -> None:
         else:
             return FakeToolCallingModel(tool_calls=[])
 
-    agent = create_agent(dynamic_model, [], state_schema=CustomDynamicState)
+    agent = create_react_agent(dynamic_model, [], state_schema=CustomDynamicState)
 
     result = agent.invoke(
         {"messages": [HumanMessage("hello")], "model_preference": "advanced"}
@@ -1202,7 +1202,7 @@ def test_dynamic_model_with_prompt() -> None:
         return FakeToolCallingModel(tool_calls=[])
 
     # Test with string prompt
-    agent = create_agent(dynamic_model, [], prompt="system_msg")
+    agent = create_react_agent(dynamic_model, [], prompt="system_msg")
     result = agent.invoke({"messages": [HumanMessage("human_msg")]})
     assert result["messages"][-1].content == "system_msg-human_msg"
 
@@ -1211,7 +1211,7 @@ def test_dynamic_model_with_prompt() -> None:
         """Generate a dynamic system message based on state."""
         return [{"role": "system", "content": "system_msg"}] + list(state["messages"])
 
-    agent = create_agent(dynamic_model, [], prompt=dynamic_prompt)
+    agent = create_react_agent(dynamic_model, [], prompt=dynamic_prompt)
     result = agent.invoke({"messages": [HumanMessage("human_msg")]})
     assert result["messages"][-1].content == "system_msg-human_msg"
 
@@ -1222,7 +1222,7 @@ async def test_dynamic_model_async() -> None:
     def dynamic_model(state: AgentState, runtime: Runtime) -> BaseChatModel:
         return FakeToolCallingModel(tool_calls=[])
 
-    agent = create_agent(dynamic_model, [])
+    agent = create_react_agent(dynamic_model, [])
 
     result = await agent.ainvoke({"messages": [HumanMessage("hello async")]})
     assert len(result["messages"]) == 2
@@ -1250,7 +1250,7 @@ def test_dynamic_model_with_structured_response() -> None:
             ],
         )
 
-    agent = create_agent(dynamic_model, [], response_format=TestResponse)
+    agent = create_react_agent(dynamic_model, [], response_format=TestResponse)
 
     result = agent.invoke({"messages": [HumanMessage("hello")]})
     assert "structured_response" in result
@@ -1274,7 +1274,7 @@ def test_dynamic_model_with_checkpointer(sync_checkpointer):
             index=call_count,
         )
 
-    agent = create_agent(dynamic_model, [], checkpointer=sync_checkpointer)
+    agent = create_react_agent(dynamic_model, [], checkpointer=sync_checkpointer)
     config = {"configurable": {"thread_id": "test_dynamic"}}
 
     # First call
@@ -1313,7 +1313,7 @@ def test_dynamic_model_state_dependent_tools() -> None:
                 tool_calls=[[{"args": {"x": 1}, "id": "1", "name": "tool_a"}], []]
             )
 
-    agent = create_agent(dynamic_model, [tool_a, tool_b])
+    agent = create_react_agent(dynamic_model, [tool_a, tool_b])
 
     # Ask to use tool B
     result = agent.invoke({"messages": [HumanMessage("use_b please")]})
@@ -1336,7 +1336,7 @@ def test_dynamic_model_error_handling() -> None:
             raise ValueError("Dynamic model failed")
         return FakeToolCallingModel(tool_calls=[])
 
-    agent = create_agent(failing_dynamic_model, [])
+    agent = create_react_agent(failing_dynamic_model, [])
 
     # Normal operation should work
     result = agent.invoke({"messages": [HumanMessage("hello")]})
@@ -1351,13 +1351,13 @@ def test_dynamic_model_vs_static_model_behavior():
     """Test that dynamic and static models produce equivalent results when configured the same."""
     # Static model
     static_model = FakeToolCallingModel(tool_calls=[])
-    static_agent = create_agent(static_model, [])
+    static_agent = create_react_agent(static_model, [])
 
     # Dynamic model returning the same model
     def dynamic_model(state, runtime: Runtime):
         return FakeToolCallingModel(tool_calls=[])
 
-    dynamic_agent = create_agent(dynamic_model, [])
+    dynamic_agent = create_react_agent(dynamic_model, [])
 
     input_msg = {"messages": [HumanMessage("test message")]}
 
@@ -1382,7 +1382,7 @@ def test_dynamic_model_receives_correct_state():
         received_states.append(state)
         return FakeToolCallingModel(tool_calls=[])
 
-    agent = create_agent(dynamic_model, [], state_schema=CustomAgentState)
+    agent = create_react_agent(dynamic_model, [], state_schema=CustomAgentState)
 
     # Test with initial state
     input_state = {"messages": [HumanMessage("hello")], "custom_field": "test_value"}
@@ -1413,7 +1413,7 @@ async def test_dynamic_model_receives_correct_state_async():
         received_states.append(state)
         return FakeToolCallingModel(tool_calls=[])
 
-    agent = create_agent(dynamic_model, [], state_schema=CustomAgentStateAsync)
+    agent = create_react_agent(dynamic_model, [], state_schema=CustomAgentStateAsync)
 
     # Test with initial state
     input_state = {
@@ -1443,7 +1443,7 @@ def test_pre_model_hook() -> None:
     def pre_model_hook(state: AgentState):
         return {"llm_input_messages": [HumanMessage("Hello!")]}
 
-    agent = create_agent(model, [], pre_model_hook=pre_model_hook)
+    agent = create_react_agent(model, [], pre_model_hook=pre_model_hook)
     assert "pre_model_hook" in agent.nodes
     result = agent.invoke({"messages": [HumanMessage("hi?")]})
     assert result == {
@@ -1459,7 +1459,7 @@ def test_pre_model_hook() -> None:
             "messages": [RemoveMessage(id=REMOVE_ALL_MESSAGES), HumanMessage("Hello!")]
         }
 
-    agent = create_agent(model, [], pre_model_hook=pre_model_hook)
+    agent = create_react_agent(model, [], pre_model_hook=pre_model_hook)
     result = agent.invoke({"messages": [HumanMessage("hi?")]})
     assert result == {
         "messages": [
@@ -1478,7 +1478,7 @@ def test_post_model_hook() -> None:
     def post_model_hook(state: FlagState) -> dict[str, bool]:
         return {"flag": True}
 
-    pmh_agent = create_agent(
+    pmh_agent = create_react_agent(
         model, [], post_model_hook=post_model_hook, state_schema=FlagState
     )
 
@@ -1528,7 +1528,7 @@ def test_post_model_hook_with_structured_output() -> None:
         return {"flag": True}
 
     model = FakeToolCallingModel(tool_calls=tool_calls)
-    agent = create_agent(
+    agent = create_react_agent(
         model,
         [get_weather],
         response_format=WeatherResponse,
@@ -1546,7 +1546,7 @@ def test_post_model_hook_with_structured_output() -> None:
 
     # Reset the state of the model
     model = FakeToolCallingModel(tool_calls=tool_calls)
-    agent = create_agent(
+    agent = create_react_agent(
         model,
         [get_weather],
         response_format=WeatherResponse,
@@ -1646,7 +1646,7 @@ def test_create_react_agent_inject_vars_with_post_model_hook() -> None:
         return {"foo": 2}
 
     model = FakeToolCallingModel(tool_calls=[[tool_call], []])
-    agent = create_agent(
+    agent = create_react_agent(
         model,
         ToolNode([tool1], handle_tool_errors=False),
         state_schema=AgentStateExtraKey,
@@ -1681,7 +1681,7 @@ def test_response_format_using_tool_choice() -> None:
 
     expected_structured_response = WeatherResponse(temperature=75)
     model = FakeToolCallingModel(tool_calls=tool_calls)
-    agent = create_agent(
+    agent = create_react_agent(
         model,
         [get_weather],
         response_format=WeatherResponse,

libs/prebuilt/tests/test_react_agent_graph.py

@@ -4,7 +4,7 @@ import pytest
 from pydantic import BaseModel
 from syrupy import SnapshotAssertion
 
-from langgraph.prebuilt import create_agent
+from langgraph.prebuilt import create_react_agent
 from tests.model import FakeToolCallingModel
 
 model = FakeToolCallingModel()
@@ -40,7 +40,7 @@ def test_react_agent_graph_structure(
     pre_model_hook: Union[Callable, None],
     post_model_hook: Union[Callable, None],
 ) -> None:
-    agent = create_agent(
+    agent = create_react_agent(
         model,
         tools=tools,
         pre_model_hook=pre_model_hook,

libs/prebuilt/tests/test_response_format.py

@@ -8,7 +8,7 @@ from langchain_core.messages import HumanMessage
 from pydantic import BaseModel, Field
 from typing_extensions import TypedDict
 
-from langgraph.prebuilt import create_agent
+from langgraph.prebuilt import create_react_agent
 from langgraph.prebuilt.responses import (
     MultipleStructuredOutputsError,
     NativeOutput,
@@ -120,7 +120,7 @@ class TestResponseFormatAsModel:
 
         model = FakeToolCallingModel(tool_calls=tool_calls)
 
-        agent = create_agent(model, [get_weather], response_format=WeatherBaseModel)
+        agent = create_react_agent(model, [get_weather], response_format=WeatherBaseModel)
         response = agent.invoke({"messages": [HumanMessage("What's the weather?")]})
 
         assert response["structured_response"] == EXPECTED_WEATHER_PYDANTIC
@@ -141,7 +141,7 @@ class TestResponseFormatAsModel:
 
         model = FakeToolCallingModel(tool_calls=tool_calls)
 
-        agent = create_agent(model, [get_weather], response_format=WeatherDataclass)
+        agent = create_react_agent(model, [get_weather], response_format=WeatherDataclass)
         response = agent.invoke({"messages": [HumanMessage("What's the weather?")]})
 
         assert response["structured_response"] == EXPECTED_WEATHER_DATACLASS
@@ -162,7 +162,7 @@ class TestResponseFormatAsModel:
 
         model = FakeToolCallingModel(tool_calls=tool_calls)
 
-        agent = create_agent(model, [get_weather], response_format=WeatherTypedDict)
+        agent = create_react_agent(model, [get_weather], response_format=WeatherTypedDict)
         response = agent.invoke({"messages": [HumanMessage("What's the weather?")]})
 
         assert response["structured_response"] == EXPECTED_WEATHER_DICT
@@ -183,7 +183,7 @@ class TestResponseFormatAsModel:
 
         model = FakeToolCallingModel(tool_calls=tool_calls)
 
-        agent = create_agent(model, [get_weather], response_format=weather_json_schema)
+        agent = create_react_agent(model, [get_weather], response_format=weather_json_schema)
         response = agent.invoke({"messages": [HumanMessage("What's the weather?")]})
 
         assert response["structured_response"] == EXPECTED_WEATHER_DICT
@@ -206,7 +206,7 @@ class TestResponseFormatAsToolOutput:
 
         model = FakeToolCallingModel(tool_calls=tool_calls)
 
-        agent = create_agent(
+        agent = create_react_agent(
             model, [get_weather], response_format=ToolOutput(WeatherBaseModel)
         )
         response = agent.invoke({"messages": [HumanMessage("What's the weather?")]})
@@ -229,7 +229,7 @@ class TestResponseFormatAsToolOutput:
 
         model = FakeToolCallingModel(tool_calls=tool_calls)
 
-        agent = create_agent(
+        agent = create_react_agent(
             model, [get_weather], response_format=ToolOutput(WeatherDataclass)
         )
         response = agent.invoke({"messages": [HumanMessage("What's the weather?")]})
@@ -252,7 +252,7 @@ class TestResponseFormatAsToolOutput:
 
         model = FakeToolCallingModel(tool_calls=tool_calls)
 
-        agent = create_agent(
+        agent = create_react_agent(
             model, [get_weather], response_format=ToolOutput(WeatherTypedDict)
         )
         response = agent.invoke({"messages": [HumanMessage("What's the weather?")]})
@@ -275,7 +275,7 @@ class TestResponseFormatAsToolOutput:
 
         model = FakeToolCallingModel(tool_calls=tool_calls)
 
-        agent = create_agent(
+        agent = create_react_agent(
             model, [get_weather], response_format=ToolOutput(weather_json_schema)
         )
         response = agent.invoke({"messages": [HumanMessage("What's the weather?")]})
@@ -298,7 +298,7 @@ class TestResponseFormatAsToolOutput:
 
         model = FakeToolCallingModel(tool_calls=tool_calls)
 
-        agent = create_agent(
+        agent = create_react_agent(
             model,
             [get_weather, get_location],
             response_format=ToolOutput(
@@ -324,7 +324,7 @@ class TestResponseFormatAsToolOutput:
 
         model_location = FakeToolCallingModel(tool_calls=tool_calls_location)
 
-        agent_location = create_agent(
+        agent_location = create_react_agent(
             model_location,
             [get_weather, get_location],
             response_format=ToolOutput(
@@ -356,7 +356,7 @@ class TestResponseFormatAsToolOutput:
             tool_calls=tool_calls
         )
 
-        agent = create_agent(
+        agent = create_react_agent(
             model,
             [get_weather, get_location],
             response_format=ToolOutput(Union[WeatherBaseModel, LocationResponse]),
@@ -380,7 +380,7 @@ class TestResponseFormatAsToolOutput:
 
         model_location = FakeToolCallingModel(tool_calls=tool_calls_location)
 
-        agent_location = create_agent(
+        agent_location = create_react_agent(
             model_location,
             [get_weather, get_location],
             response_format=ToolOutput(Union[WeatherBaseModel, LocationResponse]),
@@ -411,7 +411,7 @@ class TestResponseFormatAsToolOutput:
 
         model = FakeToolCallingModel(tool_calls=tool_calls)
 
-        agent = create_agent(
+        agent = create_react_agent(
             model,
             [],
             response_format=ToolOutput(
@@ -452,7 +452,7 @@ class TestResponseFormatAsToolOutput:
 
         model = FakeToolCallingModel(tool_calls=tool_calls)
 
-        agent = create_agent(
+        agent = create_react_agent(
             model,
             [],
             response_format=ToolOutput(
@@ -481,7 +481,7 @@ class TestResponseFormatAsToolOutput:
 
         model = FakeToolCallingModel(tool_calls=tool_calls)
 
-        agent = create_agent(
+        agent = create_react_agent(
             model,
             [],
             response_format=ToolOutput(
@@ -517,7 +517,7 @@ class TestResponseFormatAsToolOutput:
 
         model = FakeToolCallingModel(tool_calls=tool_calls)
 
-        agent = create_agent(
+        agent = create_react_agent(
             model,
             [],
             response_format=ToolOutput(
@@ -563,7 +563,7 @@ class TestResponseFormatAsToolOutput:
                 return "Custom error: Multiple outputs not allowed"
             return "Custom error"
 
-        agent = create_agent(
+        agent = create_react_agent(
             model,
             [],
             response_format=ToolOutput(
@@ -607,7 +607,7 @@ class TestResponseFormatAsToolOutput:
 
         model = FakeToolCallingModel(tool_calls=tool_calls)
 
-        agent = create_agent(
+        agent = create_react_agent(
             model,
             [],
             response_format=ToolOutput(
@@ -637,7 +637,7 @@ class TestResponseFormatAsNativeOutput:
             tool_calls=tool_calls, structured_response=EXPECTED_WEATHER_PYDANTIC
         )
 
-        agent = create_agent(
+        agent = create_react_agent(
             model, [get_weather], response_format=NativeOutput(WeatherBaseModel)
         )
         response = agent.invoke({"messages": [HumanMessage("What's the weather?")]})
@@ -655,7 +655,7 @@ class TestResponseFormatAsNativeOutput:
             tool_calls=tool_calls, structured_response=EXPECTED_WEATHER_DATACLASS
         )
 
-        agent = create_agent(
+        agent = create_react_agent(
             model, [get_weather], response_format=NativeOutput(WeatherDataclass)
         )
         response = agent.invoke(
@@ -675,7 +675,7 @@ class TestResponseFormatAsNativeOutput:
             tool_calls=tool_calls, structured_response=EXPECTED_WEATHER_DICT
         )
 
-        agent = create_agent(
+        agent = create_react_agent(
             model, [get_weather], response_format=NativeOutput(WeatherTypedDict)
         )
         response = agent.invoke({"messages": [HumanMessage("What's the weather?")]})
@@ -693,7 +693,7 @@ class TestResponseFormatAsNativeOutput:
             tool_calls=tool_calls, structured_response=EXPECTED_WEATHER_DICT
         )
 
-        agent = create_agent(
+        agent = create_react_agent(
             model, [get_weather], response_format=NativeOutput(weather_json_schema)
         )
         response = agent.invoke({"messages": [HumanMessage("What's the weather?")]})
@@ -719,7 +719,7 @@ def test_union_of_types() -> None:
         tool_calls=tool_calls, structured_response=EXPECTED_WEATHER_PYDANTIC
     )
 
-    agent = create_agent(
+    agent = create_react_agent(
         model,
         [get_weather, get_location],
         response_format=ToolOutput(Union[WeatherBaseModel, LocationResponse]),
@@ -736,7 +736,7 @@ def test_union_of_types() -> None:
 def test_inference_to_native_output() -> None:
     """Test that native output is inferred when a model supports it."""
     model = ChatOpenAI(model="gpt-5")
-    agent = create_agent(
+    agent = create_react_agent(
         model,
         prompt="You are a helpful weather assistant. Please call the get_weather tool, then use the WeatherReport tool to generate the final response.",
         tools=[get_weather],
@@ -763,7 +763,7 @@ def test_inference_to_native_output() -> None:
 def test_inference_to_tool_output() -> None:
     """Test that tool output is inferred when a model supports it."""
     model = ChatOpenAI(model="gpt-4")
-    agent = create_agent(
+    agent = create_react_agent(
         model,
         prompt="You are a helpful weather assistant. Please call the get_weather tool, then use the WeatherReport tool to generate the final response.",
         tools=[get_weather],

libs/prebuilt/tests/test_responses_spec.py

@@ -9,7 +9,7 @@ from langchain_core.messages import HumanMessage
 from langchain_core.tools import tool
 from pydantic import BaseModel, create_model
 
-from langgraph.prebuilt import create_agent
+from langgraph.prebuilt import create_react_agent
 from langgraph.prebuilt.responses import ToolOutput
 from tests.utils import BaseSchema, load_spec
 
@@ -129,7 +129,7 @@ def test_responses_integration_matrix(case: TestCase) -> None:
             http_client=http_client,
         )
 
-        agent = create_agent(
+        agent = create_react_agent(
             model,
             tools=[role_tool["tool"], dept_tool["tool"]],
             prompt=AGENT_PROMPT,

libs/prebuilt/tests/test_return_direct_spec.py

@@ -7,7 +7,7 @@ import pytest
 from langchain_core.messages import HumanMessage
 from langchain_core.tools import tool
 
-from langgraph.prebuilt import create_agent
+from langgraph.prebuilt import create_react_agent
 from langgraph.prebuilt.responses import ToolOutput
 from tests.utils import BaseSchema, load_spec
 
@@ -79,14 +79,14 @@ def test_return_direct_integration_matrix(case: TestCase) -> None:
     )
 
     if case.response_format:
-        agent = create_agent(
+        agent = create_react_agent(
             model,
             tools=[poll_tool["tool"]],
             prompt=AGENT_PROMPT,
             response_format=ToolOutput(case.response_format),
         )
     else:
-        agent = create_agent(
+        agent = create_react_agent(
             model,
             tools=[poll_tool["tool"]],
             prompt=AGENT_PROMPT,