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Getting Started with LangGraph

OpenBox integrates with LangGraph by wrapping your compiled graph — your agents, nodes, and state machines stay exactly as they are while every action is governed, scored, and auditable.

One Code Change​

The entire integration is a single function call wrapping your compiled graph:

agent.py
import os
from langgraph.graph import StateGraph, START, END, MessagesState
from openbox_langgraph import create_openbox_graph_handler  # Added import

graph = StateGraph(MessagesState)
graph.add_node("agent", call_model)
graph.add_node("tools", tool_node)
graph.add_edge(START, "agent")
graph.add_conditional_edges("agent", should_continue, {"tools": "tools", END: END})
graph.add_edge("tools", "agent")

app = graph.compile()

# Wrap with OpenBox governance
governed = create_openbox_graph_handler(
    graph=app,
    api_url=os.getenv("OPENBOX_URL"),
    api_key=os.getenv("OPENBOX_API_KEY"),
    agent_did=os.getenv("OPENBOX_AGENT_DID"),
    agent_private_key=os.getenv("OPENBOX_AGENT_PRIVATE_KEY"),
    agent_name="MyAgent",
)

result = await governed.ainvoke({"messages": [("user", "Hello")]})

Newly created OpenBox agents require DID signing by default. If Require signing is disabled for the agent, omit agent_did and agent_private_key. See Agent DID Identity for the required environment variables.

Choose Your Path​

LangGraph 101​

Get the LangGraph concepts that matter for OpenBox before you wire governance into a real graph.

I already use LangGraph​

Add the trust layer to your existing agent in 5 minutes. Install the SDK, wrap your graph, and your agent is governed.

Show me the SDK reference​

Explore the full API reference, configuration options, error handling, and 3-layer governance architecture.

What OpenBox Captures​

From a single integration point, OpenBox captures:

  • Root graph lifecycle events for governed graph invocations
  • User prompt signals before graph execution
  • Tool, subagent, and LLM activity lifecycle events
  • HTTP, database, and traced-function telemetry, with optional lower-level file telemetry
  • Governance decisions, approvals, and guardrail outcomes

What To Expect In The UI​

After integration, OpenBox gives you:

  • A run timeline for graph, tool, subagent, and LLM activity
  • Policy and guardrail decisions on governed boundaries
  • Session replay with runtime context
  • Model and token usage when the model provider returns usage metadata
  • Tool health metrics for graphs that actually execute tools

Next Steps​

  1. Read LangGraph 101 if you want the conceptual model first.
  2. Use Wrap an Existing Graph if you already have LangGraph in production.
  3. Continue to the LangGraph Developer Guide for configuration, event semantics, telemetry, and troubleshooting.