Checked other resources

• This is a bug, not a usage question. For questions, please use the LangChain Forum (https://forum.langchain.com/).
• I added a clear and detailed title that summarizes the issue.
• I read what a minimal reproducible example is (https://stackoverflow.com/help/minimal-reproducible-example).
• I included a self-contained, minimal example that demonstrates the issue INCLUDING all the relevant imports. The code run AS IS to reproduce the issue.

Example Code

from langchain.agents import create_agent
from langchain.tools import ToolRuntime, tool
from langchain_core.messages import ToolMessage, AIMessage, HumanMessage
from langgraph.types import Command

@tool(description="Request clarification from the user when intent is ambiguous.")
def clarify_user(
    question: str,
    runtime: ToolRuntime,
) -> Command:
    return Command(
        goto="__end__",
        update={
            "messages": [
                ToolMessage(
                    content="success",
                    tool_call_id=runtime.tool_call_id,
                    name="clarify_user"
                ),
                AIMessage(content=question)
            ],
            "awaiting_clarification": True,
        },
    )

agent = create_agent(
    model=your_chat_model,  # e.g., ChatOpenAI()
    tools=[clarify_user],
    system_prompt="For testing purposes, ALWAYS run clarify_user tool."
)

# This should terminate after clarify_user returns Command(goto="__end__")
result = agent.invoke({
    "messages": [HumanMessage(content="hello, run clarify_user tool please")]
})
print(result)

Error Message and Stack Trace (if applicable)

File ".../openai/_base_client.py", line 1047, in request
    raise self._make_status_error_from_response(err.response) from None
openai.BadRequestError: Error code: 400 - {
    'object': 'error', 
    'message': 'Expected last role User or Tool (or Assistant with prefix True) for serving but got assistant', 
    'type': 'invalid_request_message_order', 
    'param': None, 
    'code': '3230'
}

Description

Issue Body
Description
When using create_agent from LangGraph 1.0, returning a Command(goto="end", ...) from a tool does not terminate the graph as expected. Instead, the agent node is invoked again after the tool execution, which causes an OpenAI API error due to invalid message ordering.

Expected Behavior
Returning Command(goto="end", ...) from a tool should immediately terminate the graph and prevent further model nodes (LLM calls) .

Actual Behavior
The graph continues to the model/agent node after the tool returns the Command, causing an API error:

openai.BadRequestError: Error code: 400 - {'object': 'error', 'message': 'Expected last role User or Tool (or Assistant with prefix True) for serving but got assistant', 'type': 'invalid_request_message_order', 'param': None, 'code': '3230'}
This happens because:

The tool updates state with [ToolMessage, AIMessage]
The graph does not respect goto="end" and proceeds to call the model node
The model sees the last message is an AIMessage, which violates OpenAI's message ordering constraints
Reproduction
from langchain.agents import create_agent
from langchain.tools import ToolRuntime, tool
from langchain_core.messages import ToolMessage, AIMessage, HumanMessage
from langgraph.types import Command

@tool(description="Request clarification from the user when intent is ambiguous.")
def clarify_user(
question: str,
runtime: ToolRuntime,
) -> Command:
return Command(
goto="end",
update={
"messages": [
ToolMessage(
content="success",
tool_call_id=runtime.tool_call_id,
name="clarify_user"
),
AIMessage(content=question)
],
"awaiting_clarification": True,
},
)

agent = create_agent(
model=your_chat_model, # e.g., ChatOpenAI()
tools=[clarify_user],
system_prompt="For testing purposes, ALWAYS run clarify_user tool."
)

This should terminate after clarify_user returns Command(goto="end")

result = agent.invoke({
"messages": [HumanMessage(content="hello, run clarify_user tool please")]
})
print(result)
Error Traceback
File ".../openai/_base_client.py", line 1047, in request
raise self._make_status_error_from_response(err.response) from None
openai.BadRequestError: Error code: 400 - {
'object': 'error',
'message': 'Expected last role User or Tool (or Assistant with prefix True) for serving but got assistant',
'type': 'invalid_request_message_order',
'param': None,
'code': '3230'
}
Current Workaround
Using a before_model middleware to check if the last message is an AIMessage and manually jump to end:

from langchain.agents.middleware import AgentMiddleware

@jump_config(can_jump_to=["end"])
def before_model_check(state, config):
if state["messages"] and isinstance(state["messages"][-1], AIMessage):
return {"jump_to": "end"}
return None

Apply middleware to agent

This workaround is not ideal as it relies on message type inspection rather than proper Command handling.

Environment
langgraph version: 1.0.x (please specify exact version)
langchain version: >1.0
Python version: 3.12
OS: macOS
Questions
Is Command(goto="end") supposed to work when returned from a tool inside create_agent?
If so, is this a bug in the prebuilt agent's edge routing logic?
If not, what is the recommended pattern for terminating an agent graph early from within a tool?

System Info

System Information

OS: Darwin
OS Version: Darwin Kernel Version 23.6.0: Wed May 14 13:52:22 PDT 2025; root:xnu-10063.141.1.705.2~2/RELEASE_ARM64_T6000
Python Version: 3.12.7 (main, Oct 16 2024, 07:12:08) [Clang 18.1.8 ]

Package Information

langchain_core: 1.1.0
langchain: 1.1.0
langchain_community: 0.4.1
langsmith: 0.4.49
langchain_anthropic: 1.2.0
langchain_classic: 1.0.0
langchain_mcp_adapters: 0.1.14
langchain_openai: 1.1.0
langchain_text_splitters: 1.0.0
langgraph_api: 0.5.27
langgraph_cli: 0.4.7
langgraph_runtime_inmem: 0.19.0
langgraph_sdk: 0.2.10

Optional packages not installed

langserve

Other Dependencies

aiohttp: 3.13.2
anthropic: 0.75.0
blockbuster: 1.5.25
click: 8.3.1
cloudpickle: 3.1.2
cryptography: 44.0.3
dataclasses-json: 0.6.7
grpcio: 1.76.0
grpcio-tools: 1.75.1
httpx: 0.28.1
httpx-sse: 0.4.3
jsonpatch: 1.33
jsonschema-rs: 0.29.1
langgraph: 1.0.4
langgraph-checkpoint: 3.0.1
mcp: 1.22.0
numpy: 2.3.5
openai: 1.109.1
opentelemetry-api: 1.38.0
opentelemetry-exporter-otlp-proto-http: 1.38.0
opentelemetry-sdk: 1.38.0
orjson: 3.11.4
packaging: 25.0
protobuf: 6.33.1
pydantic: 2.12.5
pydantic-settings: 2.12.0
pyjwt: 2.10.1
pytest: 9.0.1
python-dotenv: 1.2.1
pyyaml: 6.0.3
PyYAML: 6.0.3
requests: 2.32.5
requests-toolbelt: 1.0.0
rich: 14.2.0
sqlalchemy: 2.0.44
SQLAlchemy: 2.0.44
sse-starlette: 2.1.3
starlette: 0.50.0
structlog: 25.5.0
tenacity: 9.1.2
tiktoken: 0.12.0
truststore: 0.10.4
typing-extensions: 4.15.0
uvicorn: 0.38.0
watchfiles: 1.1.1
zstandard: 0.25.0