client

Create and configure a LangGraphClient.

The client provides programmatic access to LangSmith Deployment. It supports both remote servers and local in-process connections (when running inside a LangGraph server).

Handle async requests to the LangGraph API.

Adds additional error messaging & content handling above the provided httpx client.

Top-level client for LangGraph API.

Client for managing assistants in LangGraph.

This class provides methods to interact with assistants, which are versioned configurations of your graph.

client = get_client(url="http://localhost:2024")
assistant = await client.assistants.get("assistant_id_123")

Client for managing recurrent runs (cron jobs) in LangGraph.

A run is a single invocation of an assistant with optional input, config, and context. This client allows scheduling recurring runs to occur automatically.

client = get_client(url="http://localhost:2024"))
cron_job = await client.crons.create_for_thread(
    thread_id="thread_123",
    assistant_id="asst_456",
    schedule="0 9 * * *",
    input={"message": "Daily update"}
)

Client for managing runs in LangGraph.

A run is a single assistant invocation with optional input, config, context, and metadata. This client manages runs, which can be stateful (on threads) or stateless.

client = get_client(url="http://localhost:2024")
run = await client.runs.create(assistant_id="asst_123", thread_id="thread_456", input={"query": "Hello"})

Client for interacting with the graph's shared storage.

The Store provides a key-value storage system for persisting data across graph executions, allowing for stateful operations and data sharing across threads.

client = get_client(url="http://localhost:2024")
await client.store.put_item(["users", "user123"], "mem-123451342", {"name": "Alice", "score": 100})

Client for managing threads in LangGraph.

A thread maintains the state of a graph across multiple interactions/invocations (aka runs). It accumulates and persists the graph's state, allowing for continuity between separate invocations of the graph.

client = get_client(url="http://localhost:2024"))
new_thread = await client.threads.create(metadata={"user_id": "123"})