Designing Human Approval Nodes

# Example LangGraph approval node (conceptual)
from typing import TypedDict
from langgraph.types import interrupt

# Step 1: Define the graph state
class State(TypedDict):
    content: str
    approval: str

# Step 2: Pause and collect human approval
def review_node(state: State) -> dict:
    # `interrupt` sends the payload to the UI/human task system and returns the selected option.
    approval = interrupt({
        "question": "Do you approve this content?",
        "content": state["content"],
        "options": ["yes", "edit", "cancel"]
    })
    # Return the update to be merged into the graph state
    return {"approval": approval}

# Step 3: Route based on the human decision
def route_after_review(state: State) -> str:
    if state.get("approval") == "yes":
        return "proceed"
    elif state.get("approval") == "edit":
        return "modify"
    return "cancel"

# `builder` is an existing graph builder instance in your LangGraph setup.
# Map the routing function's outcomes to the next node IDs in the graph.
builder.add_conditional_edges(
    "review",                # node name where review happens
    route_after_review,      # routing function reading state
    {
        "proceed": "proceed",
        "modify": "modify",
        "cancel": "cancel"
    }
)