---
title: "LangGraph SDK"
description: "The CopilotKit LangGraph SDK for Python allows you to build and run LangGraph workflows with CopilotKit."
---
{
/*
* ATTENTION! DO NOT MODIFY THIS FILE!
* This page is auto-generated. If you want to make any changes to this page, changes must be made at:
* sdk-python/copilotkit/langgraph.py
*/
}
## copilotkit_customize_config
Customize the LangGraph configuration for use in CopilotKit.
To install the CopilotKit SDK, run:
```bash
pip install copilotkit
```
### Examples
Disable emitting messages and tool calls:
```python
from copilotkit.langgraph import copilotkit_customize_config
config = copilotkit_customize_config(
config,
emit_messages=False,
emit_tool_calls=False
)
```
To emit a tool call as streaming LangGraph state, pass the destination key in state,
the tool name and optionally the tool argument. (If you don't pass the argument name,
all arguments are emitted under the state key.)
```python
from copilotkit.langgraph import copilotkit_customize_config
config = copilotkit_customize_config(
config,
emit_intermediate_state=[
{
"state_key": "steps",
"tool": "SearchTool",
"tool_argument": "steps"
},
]
)
```
### Parameters
The LangChain/LangGraph configuration to customize. Pass None to make a new configuration.
Configure how messages are emitted. By default, all messages are emitted. Pass False to disable emitting messages.
Configure how tool calls are emitted. By default, all tool calls are emitted. Pass False to disable emitting tool calls. Pass a string or list of strings to emit only specific tool calls.
Lets you emit tool calls as streaming LangGraph state.
### Returns
The customized LangGraph configuration.
## copilotkit_exit
Exits the current agent after the run completes. Calling copilotkit_exit() will
not immediately stop the agent. Instead, it signals to CopilotKit to stop the agent after
the run completes.
### Examples
```python
from copilotkit.langgraph import copilotkit_exit
def my_node(state: Any):
await copilotkit_exit(config)
return state
```
### Parameters
The LangGraph configuration.
### Returns
Always return True.
## copilotkit_emit_state
Emits intermediate state to CopilotKit. Useful if you have a longer running node and you want to
update the user with the current state of the node.
### Examples
```python
from copilotkit.langgraph import copilotkit_emit_state
for i in range(10):
await some_long_running_operation(i)
await copilotkit_emit_state(config, {"progress": i})
```
### Parameters
The LangGraph configuration.
The state to emit (Must be JSON serializable).
### Returns
Always return True.
## copilotkit_emit_message
Manually emits a message to CopilotKit. Useful in longer running nodes to update the user.
Important: You still need to return the messages from the node.
### Examples
```python
from copilotkit.langgraph import copilotkit_emit_message
message = "Step 1 of 10 complete"
await copilotkit_emit_message(config, message)
# Return the message from the node
return {
"messages": [AIMessage(content=message)]
}
```
### Parameters
The LangGraph configuration.
The message to emit.
### Returns
Always return True.
## copilotkit_emit_tool_call
Manually emits a tool call to CopilotKit.
```python
from copilotkit.langgraph import copilotkit_emit_tool_call
await copilotkit_emit_tool_call(config, name="SearchTool", args={"steps": 10})
```
### Parameters
The LangGraph configuration.
The name of the tool to emit.
The arguments to emit.
### Returns
Always return True.