Context

When using ChatGoogleGenerativeAI with LangGraph, you may encounter a BlockingError that prevents your application from running properly. This error occurs because LangGraph detects synchronous blocking calls that can degrade performance in ASGI web servers by tying up the event loop. The error typically appears when ChatGoogleGenerativeAI attempts to perform authentication operations that involve disk access.

Answer

To resolve this blocking error with ChatGoogleGenerativeAI, you need to initialize the model in the global context rather than within the active thread runtime. This prevents the authentication process from blocking the event loop during each request.

Solution: Move your ChatGoogleGenerativeAI initialization to the global scope of your application, outside of any function that gets called during request processing.

Instead of initializing the model inside your node function like this:

def your_node_function(state):
    model = ChatGoogleGenerativeAI(model="gemini-2.5-pro", api_key=os.environ.get("GOOGLE_API_KEY"), streaming=True)
    # rest of your code

Initialize it globally at the module level:

# At the top of your file, in global scope
model = ChatGoogleGenerativeAI(model="gemini-2.5-pro", api_key=os.environ.get("GOOGLE_API_KEY"), streaming=True)

def your_node_function(state):
    # Use the globally initialized model
    # rest of your code

Alternative workarounds if you cannot modify the initialization:

1. For development: Run your application with langgraph dev --allow-blocking

   Warning: The --allow-blocking flag may cause local deployments to freeze or hang (typically for 5-6 minutes after ToolCallEventMiddleware). If you experience hanging issues, try removing this flag and use the global initialization approach instead.

2. For deployment: Set the environment variable BG_JOB_ISOLATED_LOOPS=true

The global initialization approach is the recommended solution as it addresses the root cause by ensuring the authentication and setup operations happen once during application startup rather than during each request processing cycle.