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4.2 KiB
Add custom authentication
!!! tip "Prerequisites"
This guide assumes familiarity with the following concepts:
* [**Authentication & Access Control**](../../concepts/auth.md)
* [**LangGraph Platform**](../../concepts/langgraph_platform.md)
For a more guided walkthrough, see [**setting up custom authentication**](../../tutorials/auth/getting_started.md) tutorial.
???+ note "Support by deployment type"
Custom auth is supported for all deployments in the **managed LangGraph Platform**, as well as **Enterprise** self-hosted plans. It is not supported for **Lite** self-hosted plans.
This guide shows how to add custom authentication to your LangGraph Platform application. This guide applies to both LangGraph Platform and self-hosted deployments. It does not apply to isolated usage of the LangGraph open source library in your own custom server.
1. Implement authentication
from langgraph_sdk import Auth
my_auth = Auth()
@my_auth.authenticate
async def authenticate(authorization: str) -> str:
token = authorization.split(" ", 1)[-1] # "Bearer <token>"
try:
# Verify token with your auth provider
user_id = await verify_token(token)
return user_id
except Exception:
raise Auth.exceptions.HTTPException(
status_code=401,
detail="Invalid token"
)
# Add authorization rules to actually control access to resources
@my_auth.on
async def add_owner(
ctx: Auth.types.AuthContext,
value: dict,
):
"""Add owner to resource metadata and filter by owner."""
filters = {"owner": ctx.user.identity}
metadata = value.setdefault("metadata", {})
metadata.update(filters)
return filters
# Assumes you organize information in store like (user_id, resource_type, resource_id)
@my_auth.on.store()
async def authorize_store(ctx: Auth.types.AuthContext, value: dict):
namespace: tuple = value["namespace"]
assert namespace[0] == ctx.user.identity, "Not authorized"
2. Update configuration
In your langgraph.json, add the path to your auth file:
{
"dependencies": ["."],
"graphs": {
"agent": "./agent.py:graph"
},
"env": ".env",
"auth": {
"path": "./auth.py:my_auth"
}
}
3. Connect from the client
Once you've set up authentication in your server, requests must include the the required authorization information based on your chosen scheme. Assuming you are using JWT token authentication, you could access your deployments using any of the following methods:
=== "Python Client"
```python
from langgraph_sdk import get_client
my_token = "your-token" # In practice, you would generate a signed token with your auth provider
client = get_client(
url="http://localhost:2024",
headers={"Authorization": f"Bearer {my_token}"}
)
threads = await client.threads.search()
```
=== "Python RemoteGraph"
```python
from langgraph.pregel.remote import RemoteGraph
my_token = "your-token" # In practice, you would generate a signed token with your auth provider
remote_graph = RemoteGraph(
"agent",
url="http://localhost:2024",
headers={"Authorization": f"Bearer {my_token}"}
)
threads = await remote_graph.ainvoke(...)
```
=== "JavaScript Client"
```javascript
import { Client } from "@langchain/langgraph-sdk";
const my_token = "your-token"; // In practice, you would generate a signed token with your auth provider
const client = new Client({
apiUrl: "http://localhost:2024",
defaultHeaders: { Authorization: `Bearer ${my_token}` },
});
const threads = await client.threads.search();
```
=== "JavaScript RemoteGraph"
```javascript
import { RemoteGraph } from "@langchain/langgraph/remote";
const my_token = "your-token"; // In practice, you would generate a signed token with your auth provider
const remoteGraph = new RemoteGraph({
graphId: "agent",
url: "http://localhost:2024",
headers: { Authorization: `Bearer ${my_token}` },
});
const threads = await remoteGraph.invoke(...);
```
=== "CURL"
```bash
curl -H "Authorization: Bearer ${your-token}" http://localhost:2024/threads
```