Pausing the Agent for Input

Pause an agent run mid-tool, hand control to a custom React component, and resume with the user's answer.


Not supported on LangGraph (FastAPI)
LangGraph (FastAPI) doesn't support Human in the Loop: Interrupts. See the framework grid for which integrations support this feature.

What is this?#

useInterrupt lets your agent pause mid-run, hand control to the user through a custom React component, and resume with whatever the user returns. How that pause is implemented depends on the framework's runtime.

LangGraph ships a first-class interrupt() primitive that lets a running node suspend itself and hand control to the client. The run is frozen server-side until the client resolves the interrupt with a payload, at which point the node resumes as if interrupt() had simply returned that payload.

CopilotKit's useInterrupt is the frontend half of that contract: it subscribes to the paused run, renders whatever component you give it, and calls the agent back with the user's answer.

When should I use this?#

Reach for useInterrupt when the pause is a graph-enforced checkpoint where the code path must stop and wait for a human, not an LLM-initiated tool call. Typical cases:

  • A sensitive action (payments, irreversible writes) must be approved
  • A required piece of state isn't known and can only be collected from the user
  • The agent explicitly reaches an approval node in a longer workflow
  • You want the server-side contract to be interrupt(...) and resume with a payload

For LLM-initiated pauses where the model decides on the fly to ask the user, prefer useHumanInTheLoop.

The backend: interrupt() inside a tool#

Install the LangGraph Python SDK

uv add copilotkit
poetry add copilotkit
pip install copilotkit --extra-index-url https://copilotkit.gateway.scarf.sh/simple/
conda install copilotkit -c copilotkit-channel

Wire CopilotKit middleware into your graph

For useHumanInTheLoop tool-based HITL, the tool is defined entirely on the frontend and forwarded to the agent. CopilotKitMiddleware is what forwards it — drop it into your create_agent call.

frontend_tools.py
from langchain.agents import create_agent
from langchain_openai import ChatOpenAI
from copilotkit import CopilotKitMiddleware

graph = create_agent(
    model=ChatOpenAI(model="gpt-5.4"),
    tools=[],
    middleware=[CopilotKitMiddleware()],
    system_prompt="You are a helpful, concise assistant.",
)

For the useInterrupt graph-paused pattern, you'll also use LangGraph's native interrupt(...) primitive inside a graph node — no extra CopilotKit setup beyond the middleware above.

The example agent exposes a schedule_meeting tool. When the model calls it, the tool issues a langgraph.interrupt(...) with the meeting context. The run freezes here until the client resolves; the resolution becomes the return value of interrupt(), which the tool then turns into a final string for the model:

Not supported on LangGraph (FastAPI)
LangGraph (FastAPI) doesn't support Human in the Loop: Interrupts. See the framework grid for which integrations support this feature.

Two things to note:

  • The payload ({"topic": topic, "attendee": attendee}) is what the frontend receives as event.value. Keep it a plain, serializable object. It's the "pause-time context" the UI needs to render.
  • The return-side contract ({chosen_label, chosen_time} or {cancelled: true}) is entirely yours. The client can send anything as the resolve payload; the tool is the one that gives it meaning.

The frontend: useInterrupt render prop#

On the client you register a useInterrupt hook per agent. When the paused run arrives, its payload is handed to render as event.value, and resolve(...) is how you resume the run:

Not supported on LangGraph (FastAPI)
LangGraph (FastAPI) doesn't support Human in the Loop: Interrupts. See the framework grid for which integrations support this feature.

Whatever you pass to resolve is round-tripped back to the agent as the return value of the matching interrupt(...) call.

Key props#

  • agentId — must match a runtime-registered agent. If omitted, the hook assumes "default". A mismatch means the interrupt never fires.
  • render — receives { event, resolve }. event.value is the payload you passed to interrupt(...) on the server.
  • renderInChat — when true (as above), the picker appears inline in the chat transcript, between the paused assistant turn and the still-pending continuation.

Multiple interrupts? Add a type and gate with enabled#

If your graph issues more than one kind of interrupt (e.g. "ask" vs "approval"), tag each with a type field on the payload and install one useInterrupt per shape, each gated by an enabled predicate:

useInterrupt({
  agentId: "gen-ui-interrupt",
  enabled: ({ eventValue }) => eventValue.type === "ask",
  render: ({ event, resolve }) => (
    <AskCard question={event.value.content} onAnswer={resolve} />
  ),
});

useInterrupt({
  agentId: "gen-ui-interrupt",
  enabled: ({ eventValue }) => eventValue.type === "approval",
  render: ({ event, resolve }) => (
    <ApproveCard content={event.value.content} onAnswer={resolve} />
  ),
});

Preprocess with handler#

For cases where the interrupt can sometimes be resolved without user input (e.g. the current user already has permission), pass a handler that runs before render. The handler can call resolve(...) itself to short-circuit the UI, or return a value that render receives as result:

useInterrupt({
  agentId: "gen-ui-interrupt",
  handler: async ({ event, resolve }) => {
    const dept = await lookupUserDepartment();
    if (event.value.accessDepartment === dept || dept === "admin") {
      resolve({ code: "AUTH_BY_DEPARTMENT" });
      return; // skip render
    }
    return { dept };
  },
  render: ({ result, event, resolve }) => (
    <RequestAccessCard
      dept={result.dept}
      onRequest={() => resolve({ code: "REQUEST_AUTH" })}
      onCancel={() => resolve({ code: "CANCEL" })}
    />
  ),
});

Going further#