LangGraph

What is supported

LangGraph 1.0 and later. Onecortex recognises a compiled graph: the result of StateGraph(...).compile(), and anything that returns one, such as LangChain’s create_agent. An uncompiled StateGraph is not recognised.

A complete agent

agent.yml

apiVersion: v1
runtime: python3.12
entrypoint: agent.py:graph
dependencies: requirements.txt

requirements.txt

langgraph>=1.0
langchain>=1.0
langchain-openai>=1.0

agent.py

from langchain.chat_models import init_chat_model
from langchain_core.runnables import RunnableConfig
from langgraph.graph import START, MessagesState, StateGraph

# Reads OPENAI_API_KEY, which you add as a secret on the agent's Config tab.
model = init_chat_model("openai:gpt-5")


def respond(state: MessagesState, config: RunnableConfig) -> dict:
    return {"messages": [model.invoke(state["messages"])]}


builder = StateGraph(MessagesState)
builder.add_node("respond", respond)
builder.add_edge(START, "respond")
graph = builder.compile()

Add OPENAI_API_KEY as a secret on the agent’s Config tab, then deploy. Any model works: this one is an example. See Configuration and secrets.

A complete LangGraph example

support-triage: A support graph with a tool node and a checkpointer, on the oldest supported LangGraph. It runs with no model key.

The prompt and the reply

The prompt arrives as the graph’s input state, {"messages": [{"role": "user", "content": prompt}]}, so a graph on MessagesState works unchanged. The reply is the text of the last message. A graph whose state has no messages answers with its final state as text.

Events it reports

Events	From
`text`	The model’s streamed tokens
`tool_call_start`, `tool_call_args`, `tool_call_end`	Each tool call the model makes, as it forms
`tool_result`	Each tool’s reply, with `isError` when the tool failed
`step_start`, `step_end`	Each node, by its name
`done` or `error`	The end of the run: always exactly one

See Streaming and events.

The caller’s fields

Under config["configurable"]["onecortex"], in any node that takes a config argument:

def respond(state: MessagesState, config: RunnableConfig) -> dict:
    params = config["configurable"]["onecortex"]["params"]
    model_name = params.get("model", "gpt-5")
    ...

Sessions: thread_id is set from the session, so the same sessionId always reaches the same thread. Compile the graph with a checkpointer and it remembers the conversation for as long as the session’s instance runs. Onecortex does not add a checkpointer for you: for memory that outlasts an instance, compile with one backed by your own database. See Sessions.

Known limits

Only the compiled graph is recognised. Export builder.compile(), not builder.
Onecortex adds no checkpointer, and an in memory one lasts only as long as the session’s instance.

Troubleshooting

You see	Do this
`Onecortex could not determine how to invoke the object at your entrypoint (type: StateGraph)`	You exported the builder. Export `builder.compile()`.
The agent forgets the previous message	Send the same `sessionId` on each call, and compile with a checkpointer.

Get started

Build your agent

Frameworks

Deploy

Call your agent

Observe

Production

Organizations

Resources

What is supported

A complete agent

A complete LangGraph example

The prompt and the reply

Events it reports

The caller’s fields

Known limits

Troubleshooting

​What is supported

​A complete agent

A complete LangGraph example

​The prompt and the reply

​Events it reports

​The caller’s fields

​Known limits

​Troubleshooting

What is supported

A complete agent

The prompt and the reply

Events it reports

The caller’s fields

Known limits

Troubleshooting