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chore(prebuilt): critical renaming (#5971)

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* `create_react_agent` -> `create_agent`
* `agent` node -> `model` node
This commit is contained in:
Sydney Runkle
2025-08-20 09:15:42 -04:00
committed by GitHub
parent 20953b4728
commit f994d16b49
8 changed files with 96 additions and 102 deletions
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libs/langgraph/bench/react_agent.py
+2 -2
View File
@@ -10,7 +10,7 @@ from langchain_core.outputs import ChatGeneration, ChatResult
from langchain_core.tools import StructuredTool
from langgraph.checkpoint.base import BaseCheckpointSaver
from langgraph.prebuilt.chat_agent_executor import create_react_agent
from langgraph.prebuilt.chat_agent_executor import create_agent
from langgraph.pregel import Pregel
@@ -60,7 +60,7 @@ def react_agent(n_tools: int, checkpointer: Optional[BaseCheckpointSaver]) -> Pr
]
)
return create_react_agent(model, [tool], checkpointer=checkpointer)
return create_agent(model, [tool], checkpointer=checkpointer)
if __name__ == "__main__":
libs/langgraph/tests/test_large_cases.py
+2 -2
View File
@@ -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_react_agent
from langgraph.prebuilt.chat_agent_executor import create_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_react_agent(model, tools)
app = create_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
+2 -2
View File
@@ -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_react_agent
from langgraph.prebuilt.chat_agent_executor import create_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_react_agent(model, tools)
app = create_agent(model, tools)
assert await app.ainvoke(
{"messages": [HumanMessage(content="what is weather in sf")]}
libs/prebuilt/langgraph/prebuilt/__init__.py
+2 -2
View File
@@ -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_react_agent
from langgraph.prebuilt.chat_agent_executor import create_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_react_agent",
"create_agent",
"ToolNode",
"tools_condition",
"ValidationNode",
libs/prebuilt/langgraph/prebuilt/chat_agent_executor.py
+14 -18
View File
@@ -680,7 +680,7 @@ class _AgentBuilder(Generic[StructuredResponseT]):
def _get_entry_point(self) -> str:
"""Get the workflow entry point."""
return "pre_model_hook" if self.pre_model_hook else "agent"
return "pre_model_hook" if self.pre_model_hook else "model"
def _get_model_paths(self) -> list[str]:
"""Get possible edge destinations from model node."""
@@ -714,7 +714,7 @@ class _AgentBuilder(Generic[StructuredResponseT]):
# Add nodes
workflow.add_node(
"agent", self.create_model_node(), input_schema=self._get_input_schema()
"model", self.create_model_node(), input_schema=self._get_input_schema()
)
if self._tool_calling_enabled:
@@ -728,10 +728,10 @@ class _AgentBuilder(Generic[StructuredResponseT]):
# Add edges
if self.pre_model_hook:
workflow.add_edge("pre_model_hook", "agent")
workflow.add_edge("pre_model_hook", "model")
if self.post_model_hook:
workflow.add_edge("agent", "post_model_hook")
workflow.add_edge("model", "post_model_hook")
post_hook_paths = self._get_post_model_hook_paths()
if len(post_hook_paths) == 1:
# No need for a conditional edge if there's only one path
@@ -746,10 +746,10 @@ class _AgentBuilder(Generic[StructuredResponseT]):
model_paths = self._get_model_paths()
if len(model_paths) == 1:
# No need for a conditional edge if there's only one path
workflow.add_edge("agent", model_paths[0])
workflow.add_edge("model", model_paths[0])
else:
workflow.add_conditional_edges(
"agent",
"model",
self.create_model_router(),
path_map=model_paths,
)
@@ -771,7 +771,7 @@ class _AgentBuilder(Generic[StructuredResponseT]):
return workflow
def create_react_agent(
def create_agent(
model: Union[
str,
BaseChatModel,
@@ -796,7 +796,7 @@ def create_react_agent(
) -> CompiledStateGraph:
"""Creates an agent graph that calls tools in a loop until a stopping condition is met.
For more details on using `create_react_agent`, visit [Agents](https://langchain-ai.github.io/langgraph/agents/overview/) documentation.
For more details on using `create_agent`, visit [Agents](https://langchain-ai.github.io/langgraph/agents/overview/) documentation.
Args:
model: The language model for the agent. Supports static and dynamic
@@ -911,10 +911,10 @@ def create_react_agent(
store: An optional store object. This is used for persisting data
across multiple threads (e.g., multiple conversations / users).
interrupt_before: An optional list of node names to interrupt before.
Should be one of the following: "agent", "tools".
Should be one of the following: "model", "tools".
This is useful if you want to add a user confirmation or other interrupt before taking an action.
interrupt_after: An optional list of node names to interrupt after.
Should be one of the following: "agent", "tools".
Should be one of the following: "model", "tools".
This is useful if you want to return directly or run additional processing on an output.
debug: A flag indicating whether to enable debug mode.
name: An optional name for the CompiledStateGraph.
@@ -924,7 +924,7 @@ def create_react_agent(
Returns:
A CompiledStateGraph that can be used for chat interactions.
The "agent" node calls the language model with the messages list (after applying the prompt).
The "model" node calls the language model with the messages list (after applying the prompt).
If the resulting AIMessage contains `tool_calls`, the graph will then call the ["tools"][langgraph.prebuilt.tool_node.ToolNode].
The "tools" node executes the tools (1 tool per `tool_call`) and adds the responses to the messages list
as `ToolMessage` objects. The agent node then calls the language model again.
@@ -947,13 +947,13 @@ def create_react_agent(
Example:
```python
from langgraph.prebuilt import create_react_agent
from langgraph.prebuilt import create_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_react_agent(
graph = create_agent(
"anthropic:claude-3-7-sonnet-latest",
tools=[check_weather],
prompt="You are a helpful assistant",
@@ -1005,12 +1005,8 @@ def create_react_agent(
)
# Keep for backwards compatibility
create_tool_calling_executor = create_react_agent
__all__ = [
"create_react_agent",
"create_tool_calling_executor",
"create_agent",
"AgentState",
"AgentStatePydantic",
"AgentStateWithStructuredResponse",
libs/prebuilt/tests/__snapshots__/test_react_agent_graph.ambr
+21 -21
View File
@@ -2,18 +2,18 @@
# name: test_react_agent_graph_structure[None-None-tools0]
'''
graph TD;
__start__ --> agent;
agent --> __end__;
__start__ --> model;
model --> __end__;
'''
# ---
# name: test_react_agent_graph_structure[None-None-tools1]
'''
graph TD;
__start__ --> agent;
agent -.-> __end__;
agent -.-> tools;
tools --> agent;
__start__ --> model;
model -.-> __end__;
model -.-> tools;
tools --> model;
'''
# ---
@@ -21,8 +21,8 @@
'''
graph TD;
__start__ --> pre_model_hook;
pre_model_hook --> agent;
agent --> __end__;
pre_model_hook --> model;
model --> __end__;
'''
# ---
@@ -30,9 +30,9 @@
'''
graph TD;
__start__ --> pre_model_hook;
agent -.-> __end__;
agent -.-> tools;
pre_model_hook --> agent;
model -.-> __end__;
model -.-> tools;
pre_model_hook --> model;
tools --> pre_model_hook;
'''
@@ -40,8 +40,8 @@
# name: test_react_agent_graph_structure[post_model_hook-None-tools0]
'''
graph TD;
__start__ --> agent;
agent --> post_model_hook;
__start__ --> model;
model --> post_model_hook;
post_model_hook --> __end__;
'''
@@ -49,12 +49,12 @@
# name: test_react_agent_graph_structure[post_model_hook-None-tools1]
'''
graph TD;
__start__ --> agent;
agent --> post_model_hook;
__start__ --> model;
model --> post_model_hook;
post_model_hook -.-> __end__;
post_model_hook -.-> agent;
post_model_hook -.-> model;
post_model_hook -.-> tools;
tools --> agent;
tools --> model;
'''
# ---
@@ -62,8 +62,8 @@
'''
graph TD;
__start__ --> pre_model_hook;
agent --> post_model_hook;
pre_model_hook --> agent;
model --> post_model_hook;
pre_model_hook --> model;
post_model_hook --> __end__;
'''
@@ -72,11 +72,11 @@
'''
graph TD;
__start__ --> pre_model_hook;
agent --> post_model_hook;
model --> post_model_hook;
post_model_hook -.-> __end__;
post_model_hook -.-> pre_model_hook;
post_model_hook -.-> tools;
pre_model_hook --> agent;
pre_model_hook --> model;
tools --> pre_model_hook;
'''
libs/prebuilt/tests/test_react_agent.py
+51 -53
View File
@@ -28,7 +28,7 @@ from langgraph.graph import START, MessagesState, StateGraph
from langgraph.graph.message import REMOVE_ALL_MESSAGES
from langgraph.prebuilt import (
ToolNode,
create_react_agent,
create_agent,
)
from langgraph.prebuilt.chat_agent_executor import (
AgentState,
@@ -56,7 +56,7 @@ pytestmark = pytest.mark.anyio
def test_no_prompt(sync_checkpointer: BaseCheckpointSaver) -> None:
model = FakeToolCallingModel()
agent = create_react_agent(
agent = create_agent(
model,
[],
checkpointer=sync_checkpointer,
@@ -86,7 +86,7 @@ def test_no_prompt(sync_checkpointer: BaseCheckpointSaver) -> None:
async def test_no_prompt_async(async_checkpointer: BaseCheckpointSaver) -> None:
model = FakeToolCallingModel()
agent = create_react_agent(model, [], checkpointer=async_checkpointer)
agent = create_agent(model, [], checkpointer=async_checkpointer)
inputs = [HumanMessage("hi?")]
thread = {"configurable": {"thread_id": "123"}}
response = await agent.ainvoke({"messages": inputs}, thread, debug=True)
@@ -111,7 +111,7 @@ async def test_no_prompt_async(async_checkpointer: BaseCheckpointSaver) -> None:
def test_system_message_prompt():
prompt = SystemMessage(content="Foo")
agent = create_react_agent(FakeToolCallingModel(), [], prompt=prompt)
agent = create_agent(FakeToolCallingModel(), [], prompt=prompt)
inputs = [HumanMessage("hi?")]
response = agent.invoke({"messages": inputs})
expected_response = {
@@ -122,7 +122,7 @@ def test_system_message_prompt():
def test_string_prompt():
prompt = "Foo"
agent = create_react_agent(FakeToolCallingModel(), [], prompt=prompt)
agent = create_agent(FakeToolCallingModel(), [], prompt=prompt)
inputs = [HumanMessage("hi?")]
response = agent.invoke({"messages": inputs})
expected_response = {
@@ -136,7 +136,7 @@ def test_callable_prompt():
modified_message = f"Bar {state['messages'][-1].content}"
return [HumanMessage(content=modified_message)]
agent = create_react_agent(FakeToolCallingModel(), [], prompt=prompt)
agent = create_agent(FakeToolCallingModel(), [], prompt=prompt)
inputs = [HumanMessage("hi?")]
response = agent.invoke({"messages": inputs})
expected_response = {"messages": inputs + [AIMessage(content="Bar hi?", id="0")]}
@@ -148,7 +148,7 @@ async def test_callable_prompt_async():
modified_message = f"Bar {state['messages'][-1].content}"
return [HumanMessage(content=modified_message)]
agent = create_react_agent(FakeToolCallingModel(), [], prompt=prompt)
agent = create_agent(FakeToolCallingModel(), [], prompt=prompt)
inputs = [HumanMessage("hi?")]
response = await agent.ainvoke({"messages": inputs})
expected_response = {"messages": inputs + [AIMessage(content="Bar hi?", id="0")]}
@@ -160,7 +160,7 @@ def test_runnable_prompt():
lambda state: [HumanMessage(content=f"Baz {state['messages'][-1].content}")]
)
agent = create_react_agent(FakeToolCallingModel(), [], prompt=prompt)
agent = create_agent(FakeToolCallingModel(), [], prompt=prompt)
inputs = [HumanMessage("hi?")]
response = agent.invoke({"messages": inputs})
expected_response = {"messages": inputs + [AIMessage(content="Baz hi?", id="0")]}
@@ -187,7 +187,7 @@ def test_prompt_with_store():
model = FakeToolCallingModel()
# test state modifier that uses store works
agent = create_react_agent(
agent = create_agent(
model,
[add],
prompt=prompt,
@@ -199,7 +199,7 @@ 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_react_agent(
agent = create_agent(
model,
[add],
prompt=prompt_no_store,
@@ -237,16 +237,14 @@ async def test_prompt_with_store_async():
model = FakeToolCallingModel()
# test state modifier that uses store works
agent = create_react_agent(model, [add], prompt=prompt, store=in_memory_store)
agent = create_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_react_agent(
model, [add], prompt=prompt_no_store, store=in_memory_store
)
agent = create_agent(model, [add], prompt=prompt_no_store, store=in_memory_store)
response = await agent.ainvoke(
{"messages": [("user", "hi")]}, {"configurable": {"user_id": "2"}}
)
@@ -287,7 +285,7 @@ def test_model_with_tools(tool_style: str, include_builtin: bool) -> None:
)
# check valid agent constructor
with pytest.raises(ValueError):
create_react_agent(
create_agent(
model.bind_tools(tools),
tools,
)
@@ -436,7 +434,7 @@ def test_react_agent_with_structured_response() -> None:
model = FakeToolCallingModel[WeatherResponse](
tool_calls=tool_calls, structured_response=expected_structured_response
)
agent = create_react_agent(
agent = create_agent(
model,
[get_weather],
response_format=WeatherResponse,
@@ -513,7 +511,7 @@ def test_react_agent_update_state(
tool_calls = [[{"args": {}, "id": "1", "name": "get_user_name"}]]
model = FakeToolCallingModel(tool_calls=tool_calls)
agent = create_react_agent(
agent = create_agent(
model,
[get_user_name],
state_schema=state_schema,
@@ -564,7 +562,7 @@ def test_react_agent_parallel_tool_calls(
[],
]
model = FakeToolCallingModel(tool_calls=tool_calls)
agent = create_react_agent(
agent = create_agent(
model,
[human_assistance, get_weather],
checkpointer=sync_checkpointer,
@@ -647,7 +645,7 @@ def test_create_react_agent_inject_vars(state_schema: StateSchemaType) -> None:
"type": "tool_call",
}
model = FakeToolCallingModel(tool_calls=[[tool_call], []])
agent = create_react_agent(
agent = create_agent(
model,
ToolNode([tool1], handle_tool_errors=False),
state_schema=state_schema,
@@ -687,7 +685,7 @@ async def test_return_direct() -> None:
tool_calls=first_tool_call,
)
model = FakeToolCallingModel(tool_calls=[first_tool_call, []])
agent = create_react_agent(
agent = create_agent(
model,
[tool_return_direct, tool_normal],
)
@@ -714,7 +712,7 @@ async def test_return_direct() -> None:
),
]
model = FakeToolCallingModel(tool_calls=[second_tool_call, []])
agent = create_react_agent(model, [tool_return_direct, tool_normal])
agent = create_agent(model, [tool_return_direct, tool_normal])
result = agent.invoke(
{"messages": [HumanMessage(content="Test normal", id="hum1")]}
)
@@ -743,7 +741,7 @@ async def test_return_direct() -> None:
),
]
model = FakeToolCallingModel(tool_calls=[both_tool_calls, []])
agent = create_react_agent(model, [tool_return_direct, tool_normal])
agent = create_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"),
@@ -780,8 +778,8 @@ def test__get_state_args() -> None:
def test_inspect_react() -> None:
model = FakeToolCallingModel(tool_calls=[])
agent = create_react_agent(model, [])
inspect.getclosurevars(agent.nodes["agent"].bound.func)
agent = create_agent(model, [])
inspect.getclosurevars(agent.nodes["model"].bound.func)
def test_react_with_subgraph_tools(
@@ -837,7 +835,7 @@ def test_react_with_subgraph_tools(
]
)
tool_node = ToolNode([addition, multiplication], handle_tool_errors=False)
agent = create_react_agent(
agent = create_agent(
model,
tool_node,
checkpointer=sync_checkpointer,
@@ -887,7 +885,7 @@ def test_react_agent_subgraph_streaming_sync() -> None:
]
)
agent = create_react_agent(
agent = create_agent(
model,
tools=[get_weather],
prompt="You are a helpful travel assistant.",
@@ -976,7 +974,7 @@ async def test_react_agent_subgraph_streaming() -> None:
]
)
agent = create_react_agent(
agent = create_agent(
model,
tools=[get_weather],
prompt="You are a helpful travel assistant.",
@@ -1074,7 +1072,7 @@ def test_tool_node_node_interrupt(
]
)
config = {"configurable": {"thread_id": "1"}}
agent = create_react_agent(
agent = create_agent(
model,
[tool_interrupt, tool_normal],
checkpointer=sync_checkpointer,
@@ -1126,7 +1124,7 @@ def test_dynamic_model_basic() -> None:
else:
return FakeToolCallingModel(tool_calls=[])
agent = create_react_agent(dynamic_model, [])
agent = create_agent(dynamic_model, [])
result = agent.invoke({"messages": [HumanMessage("hello")]})
assert len(result["messages"]) == 2
@@ -1164,7 +1162,7 @@ def test_dynamic_model_with_tools() -> None:
tool_calls=[[{"args": {"x": 1}, "id": "1", "name": "basic_tool"}], []]
)
agent = create_react_agent(dynamic_model, [basic_tool, advanced_tool])
agent = create_agent(dynamic_model, [basic_tool, advanced_tool])
# Test basic tool usage
result = agent.invoke({"messages": [HumanMessage("basic request")]})
@@ -1197,7 +1195,7 @@ def test_dynamic_model_with_context() -> None:
else:
return FakeToolCallingModel(tool_calls=[])
agent = create_react_agent(dynamic_model, [], context_schema=Context)
agent = create_agent(dynamic_model, [], context_schema=Context)
# Test with basic user
result = agent.invoke(
@@ -1227,7 +1225,7 @@ def test_dynamic_model_with_state_schema() -> None:
else:
return FakeToolCallingModel(tool_calls=[])
agent = create_react_agent(dynamic_model, [], state_schema=CustomDynamicState)
agent = create_agent(dynamic_model, [], state_schema=CustomDynamicState)
result = agent.invoke(
{"messages": [HumanMessage("hello")], "model_preference": "advanced"}
@@ -1243,7 +1241,7 @@ def test_dynamic_model_with_prompt() -> None:
return FakeToolCallingModel(tool_calls=[])
# Test with string prompt
agent = create_react_agent(dynamic_model, [], prompt="system_msg")
agent = create_agent(dynamic_model, [], prompt="system_msg")
result = agent.invoke({"messages": [HumanMessage("human_msg")]})
assert result["messages"][-1].content == "system_msg-human_msg"
@@ -1252,7 +1250,7 @@ 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_react_agent(dynamic_model, [], prompt=dynamic_prompt)
agent = create_agent(dynamic_model, [], prompt=dynamic_prompt)
result = agent.invoke({"messages": [HumanMessage("human_msg")]})
assert result["messages"][-1].content == "system_msg-human_msg"
@@ -1263,7 +1261,7 @@ async def test_dynamic_model_async() -> None:
def dynamic_model(state: AgentState, runtime: Runtime) -> BaseChatModel:
return FakeToolCallingModel(tool_calls=[])
agent = create_react_agent(dynamic_model, [])
agent = create_agent(dynamic_model, [])
result = await agent.ainvoke({"messages": [HumanMessage("hello async")]})
assert len(result["messages"]) == 2
@@ -1291,7 +1289,7 @@ def test_dynamic_model_with_structured_response() -> None:
],
)
agent = create_react_agent(dynamic_model, [], response_format=TestResponse)
agent = create_agent(dynamic_model, [], response_format=TestResponse)
result = agent.invoke({"messages": [HumanMessage("hello")]})
assert "structured_response" in result
@@ -1315,7 +1313,7 @@ def test_dynamic_model_with_checkpointer(sync_checkpointer):
index=call_count,
)
agent = create_react_agent(dynamic_model, [], checkpointer=sync_checkpointer)
agent = create_agent(dynamic_model, [], checkpointer=sync_checkpointer)
config = {"configurable": {"thread_id": "test_dynamic"}}
# First call
@@ -1354,7 +1352,7 @@ def test_dynamic_model_state_dependent_tools() -> None:
tool_calls=[[{"args": {"x": 1}, "id": "1", "name": "tool_a"}], []]
)
agent = create_react_agent(dynamic_model, [tool_a, tool_b])
agent = create_agent(dynamic_model, [tool_a, tool_b])
# Ask to use tool B
result = agent.invoke({"messages": [HumanMessage("use_b please")]})
@@ -1377,7 +1375,7 @@ def test_dynamic_model_error_handling() -> None:
raise ValueError("Dynamic model failed")
return FakeToolCallingModel(tool_calls=[])
agent = create_react_agent(failing_dynamic_model, [])
agent = create_agent(failing_dynamic_model, [])
# Normal operation should work
result = agent.invoke({"messages": [HumanMessage("hello")]})
@@ -1392,13 +1390,13 @@ 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_react_agent(static_model, [])
static_agent = create_agent(static_model, [])
# Dynamic model returning the same model
def dynamic_model(state, runtime: Runtime):
return FakeToolCallingModel(tool_calls=[])
dynamic_agent = create_react_agent(dynamic_model, [])
dynamic_agent = create_agent(dynamic_model, [])
input_msg = {"messages": [HumanMessage("test message")]}
@@ -1423,7 +1421,7 @@ def test_dynamic_model_receives_correct_state():
received_states.append(state)
return FakeToolCallingModel(tool_calls=[])
agent = create_react_agent(dynamic_model, [], state_schema=CustomAgentState)
agent = create_agent(dynamic_model, [], state_schema=CustomAgentState)
# Test with initial state
input_state = {"messages": [HumanMessage("hello")], "custom_field": "test_value"}
@@ -1454,7 +1452,7 @@ async def test_dynamic_model_receives_correct_state_async():
received_states.append(state)
return FakeToolCallingModel(tool_calls=[])
agent = create_react_agent(dynamic_model, [], state_schema=CustomAgentStateAsync)
agent = create_agent(dynamic_model, [], state_schema=CustomAgentStateAsync)
# Test with initial state
input_state = {
@@ -1483,7 +1481,7 @@ def test_pre_model_hook() -> None:
def pre_model_hook(state: AgentState):
return {"llm_input_messages": [HumanMessage("Hello!")]}
agent = create_react_agent(model, [], pre_model_hook=pre_model_hook)
agent = create_agent(model, [], pre_model_hook=pre_model_hook)
assert "pre_model_hook" in agent.nodes
result = agent.invoke({"messages": [HumanMessage("hi?")]})
assert result == {
@@ -1499,7 +1497,7 @@ def test_pre_model_hook() -> None:
"messages": [RemoveMessage(id=REMOVE_ALL_MESSAGES), HumanMessage("Hello!")]
}
agent = create_react_agent(model, [], pre_model_hook=pre_model_hook)
agent = create_agent(model, [], pre_model_hook=pre_model_hook)
result = agent.invoke({"messages": [HumanMessage("hi?")]})
assert result == {
"messages": [
@@ -1518,7 +1516,7 @@ def test_post_model_hook() -> None:
def post_model_hook(state: FlagState) -> dict[str, bool]:
return {"flag": True}
pmh_agent = create_react_agent(
pmh_agent = create_agent(
model, [], post_model_hook=post_model_hook, state_schema=FlagState
)
@@ -1530,7 +1528,7 @@ def test_post_model_hook() -> None:
events = list(pmh_agent.stream({"messages": [HumanMessage("hi?")], "flag": False}))
assert events == [
{
"agent": {
"model": {
"messages": [
AIMessage(
content="hi?",
@@ -1568,7 +1566,7 @@ def test_post_model_hook_with_structured_output() -> None:
return {"flag": True}
model = FakeToolCallingModel(tool_calls=tool_calls)
agent = create_react_agent(
agent = create_agent(
model,
[get_weather],
response_format=WeatherResponse,
@@ -1586,7 +1584,7 @@ def test_post_model_hook_with_structured_output() -> None:
# Reset the state of the model
model = FakeToolCallingModel(tool_calls=tool_calls)
agent = create_react_agent(
agent = create_agent(
model,
[get_weather],
response_format=WeatherResponse,
@@ -1599,7 +1597,7 @@ def test_post_model_hook_with_structured_output() -> None:
)
assert events == [
{
"agent": {
"model": {
"messages": [
AIMessage(
content="What's the weather?",
@@ -1631,7 +1629,7 @@ def test_post_model_hook_with_structured_output() -> None:
}
},
{
"agent": {
"model": {
"messages": [
AIMessage(
content="What's the weather?-What's the weather?-The weather is sunny and 75°F.",
@@ -1703,7 +1701,7 @@ def test_create_react_agent_inject_vars_with_post_model_hook(
return {"foo": 2}
model = FakeToolCallingModel(tool_calls=[[tool_call], []])
agent = create_react_agent(
agent = create_agent(
model,
ToolNode([tool1], handle_tool_errors=False),
state_schema=state_schema,
@@ -1738,7 +1736,7 @@ def test_response_format_using_tool_choice() -> None:
expected_structured_response = WeatherResponse(temperature=75)
model = FakeToolCallingModel(tool_calls=tool_calls)
agent = create_react_agent(
agent = create_agent(
model,
[get_weather],
response_format=WeatherResponse,
libs/prebuilt/tests/test_react_agent_graph.py
+2 -2
View File
@@ -4,7 +4,7 @@ import pytest
from pydantic import BaseModel
from syrupy import SnapshotAssertion
from langgraph.prebuilt import create_react_agent
from langgraph.prebuilt import create_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_react_agent(
agent = create_agent(
model,
tools=tools,
pre_model_hook=pre_model_hook,