LangGraph Integration Blueprint

Guard high-risk LangGraph nodes before the graph advances.

Use Stacksona Gate at conditional edges, tool nodes, or interrupt points so a graph can pause, collect a reviewer decision, and resume with an audit trail.

Governance object: graph state + pending node transition.

Official docs ↗Graph API ↗

Where Stacksona sits

Graph state

planner output

Gate check

edge/node review

Reviewer

approve or reject

Decision id

stored in state

Route

approved branch

Execute

sensitive node

The useful integration point is the last safe moment before an external action, privileged read, or customer-visible response occurs.

Implementation steps

Use these steps as the first implementation pass. Start with one high-risk action, verify the reviewer workflow, then expand coverage.

Choose the gate nodePlace the check immediately before nodes that send messages, update records, call payment tools, modify files, or expose regulated data.
Build a compact review payloadInclude thread id, current node, proposed next node, tool name, arguments, user intent, and risk signals from graph state.
Pause instead of executingReturn a waiting state or route to a review branch when Gate says pending or rejected; only continue to the sensitive node when approved.
Persist the decisionWrite the Stacksona decision id back into graph state so downstream nodes and logs can reference the approval.

Recommended package

Use the Stacksona SDK or API wrapper

For Node.js or TypeScript guard services, start with the live SDK. For Python runtimes, call the same guard through your backend or a small HTTP wrapper.

npm i @stacksona/sdk

View SDK on npm

Approval payload to send

Keep the payload compact enough for a reviewer to decide quickly, but specific enough to explain exactly what the agent wants to do.

Field	What to include
agent	Stable name for the agent, crew, graph, or workflow that is asking for approval.
action	Human-readable verb such as `send_email`, `issue_refund`, or `execute_tool`.
risk	Use `low`, `medium`, or `high` so reviewers can triage quickly.
subject	The customer, ticket, repository, account, or data source affected by the action.
context	Small, reviewable facts: proposed arguments, policy signals, retrieved sources, role, task id, and links.

Conditional edge guard

starter pattern

def route_after_planning(state):
    action = state["proposed_action"]
    decision = gate_request({
        "agent": "refund-resolution-graph",
        "action": action["name"],
        "risk": action.get("risk", "medium"),
        "subject": state["ticket_id"],
        "context": {
            "thread_id": state["thread_id"],
            "current_node": "plan_action",
            "next_node": action["target_node"],
            "arguments": action["args"],
        },
    })

    state["stacksona_decision_id"] = decision["id"]
    if decision["status"] == "approved":
        return action["target_node"]
    return "wait_for_human_review"

Treat this as the shape of the guard. Replace gate_request, stacksona.gate.request, or run_tool with the SDK/API calls used in your runtime.

Practical guidance

Best gate points

Conditional edges, tool nodes, and any node that mutates external systems.

Resume strategy

Store the decision id in graph state, then resume from the review branch or approved edge.

Avoid

Do not gate every LLM thought; gate the concrete action boundary.

Try 14 Days Free View Integration Overview