langgraph-human-in-the-loop

Pause graph execution for human review, approval, or validation, then resume with their input. Requires three components: a checkpointer (InMemorySaver or PostgresSaver), a thread ID in config, and JSON-serializable interrupt payloads interrupt(value) pauses and surfaces data; Command(resume=value) resumes and returns that value to the paused node All code before interrupt() re-executes on resume, so side effects must be idempotent (use upsert, not insert) Supports approval workflows, validation loops with re-prompting, and parallel interrupts resumed via ID-to-value mapping

INSTALLATION
npx skills add https://github.com/langchain-ai/langchain-skills --skill langgraph-human-in-the-loop
Run in your project or agent environment. Adjust flags if your CLI version differs.

SKILL.md

  • **interrupt(value)** — pauses execution, surfaces a value to the caller
  • **Command(resume=value)** — resumes execution, providing the value back to interrupt()
  • Checkpointer — required to save state while paused
  • Thread ID — required to identify which paused execution to resume

Requirements

Three things are required for interrupts to work:

  • Checkpointer — compile with checkpointer=InMemorySaver() (dev) or PostgresSaver (prod)
  • Thread ID — pass {"configurable": {"thread_id": "..."}} to every invoke/stream call
  • JSON-serializable payload — the value passed to interrupt() must be JSON-serializable

Basic Interrupt + Resume

interrupt(value) pauses the graph. The value surfaces in the result under __interrupt__. Command(resume=value) resumes — the resume value becomes the return value of interrupt().

Critical: when the graph resumes, the node restarts from the beginning — all code before interrupt() re-runs.

from langgraph.types import interrupt, Command

from langgraph.checkpoint.memory import InMemorySaver

from langgraph.graph import StateGraph, START, END

from typing_extensions import TypedDict

class State(TypedDict):

    approved: bool

def approval_node(state: State):

    # Pause and ask for approval

    approved = interrupt("Do you approve this action?")

    # When resumed, Command(resume=...) returns that value here

    return {"approved": approved}

checkpointer = InMemorySaver()

graph = (

    StateGraph(State)

    .add_node("approval", approval_node)

    .add_edge(START, "approval")

    .add_edge("approval", END)

    .compile(checkpointer=checkpointer)

)

config = {"configurable": {"thread_id": "thread-1"}}

# Initial run — hits interrupt and pauses

result = graph.invoke({"approved": False}, config)

print(result["__interrupt__"])

# [Interrupt(value='Do you approve this action?')]

# Resume with the human's response

result = graph.invoke(Command(resume=True), config)

print(result["approved"])  # True
import { interrupt, Command, MemorySaver, StateGraph, StateSchema, START, END } from "@langchain/langgraph";

import { z } from "zod";

const State = new StateSchema({

  approved: z.boolean().default(false),

});

const approvalNode = async (state: typeof State.State) => {

  // Pause and ask for approval

  const approved = interrupt("Do you approve this action?");

  // When resumed, Command({ resume }) returns that value here

  return { approved };

};

const checkpointer = new MemorySaver();

const graph = new StateGraph(State)

  .addNode("approval", approvalNode)

  .addEdge(START, "approval")

  .addEdge("approval", END)

  .compile({ checkpointer });

const config = { configurable: { thread_id: "thread-1" } };

// Initial run — hits interrupt and pauses

let result = await graph.invoke({ approved: false }, config);

console.log(result.__interrupt__);

// [{ value: 'Do you approve this action?', ... }]

// Resume with the human's response

result = await graph.invoke(new Command({ resume: true }), config);

console.log(result.approved);  // true

Approval Workflow

A common pattern: interrupt to show a draft, then route based on the human's decision.

from langgraph.types import interrupt, Command

from langgraph.graph import StateGraph, START, END

from typing import Literal

from typing_extensions import TypedDict

class EmailAgentState(TypedDict):

    email_content: str

    draft_response: str

    classification: dict

def human_review(state: EmailAgentState) -> Command[Literal["send_reply", "__end__"]]:

    """Pause for human review using interrupt and route based on decision."""

    classification = state.get("classification", {})

    # interrupt() must come first — any code before it will re-run on resume

    human_decision = interrupt({

        "email_id": state.get("email_content", ""),

        "draft_response": state.get("draft_response", ""),

        "urgency": classification.get("urgency"),

        "action": "Please review and approve/edit this response"

    })

    # Process the human's decision

    if human_decision.get("approved"):

        return Command(

            update={"draft_response": human_decision.get("edited_response", state.get("draft_response", ""))},

            goto="send_reply"

        )

    else:

        # Rejection — human will handle directly

        return Command(update={}, goto=END)
import { interrupt, Command, END, GraphNode } from "@langchain/langgraph";

const humanReview: GraphNode<typeof EmailAgentState> = async (state) => {

  const classification = state.classification!;

  // interrupt() must come first — any code before it will re-run on resume

  const humanDecision = interrupt({

    emailId: state.emailContent,

    draftResponse: state.responseText,

    urgency: classification.urgency,

    action: "Please review and approve/edit this response",

  });

  // Process the human's decision

  if (humanDecision.approved) {

    return new Command({

      update: { responseText: humanDecision.editedResponse || state.responseText },

      goto: "sendReply",

    });

  } else {

    return new Command({ update: {}, goto: END });

  }

};

Validation Loop

Use interrupt() in a loop to validate human input and re-prompt if invalid.

from langgraph.types import interrupt

def get_age_node(state):

    prompt = "What is your age?"

    while True:

        answer = interrupt(prompt)

        # Validate the input

        if isinstance(answer, int) and answer > 0:

            break

        else:

            # Invalid input — ask again with a more specific prompt

            prompt = f"'{answer}' is not a valid age. Please enter a positive number."

    return {"age": answer}

Each Command(resume=...) call provides the next answer. If invalid, the loop re-interrupts with a clearer message.

config = {"configurable": {"thread_id": "form-1"}}

first = graph.invoke({"age": None}, config)

# __interrupt__: "What is your age?"

retry = graph.invoke(Command(resume="thirty"), config)

# __interrupt__: "'thirty' is not a valid age..."

final = graph.invoke(Command(resume=30), config)

print(final["age"])  # 30
import { interrupt } from "@langchain/langgraph";

const getAgeNode = (state: typeof State.State) => {

  let prompt = "What is your age?";

  while (true) {

    const answer = interrupt(prompt);

    // Validate the input

    if (typeof answer === "number" &#x26;&#x26; answer > 0) {

      return { age: answer };

    } else {

      // Invalid input — ask again with a more specific prompt

      prompt = `'${answer}' is not a valid age. Please enter a positive number.`;

    }

  }

};

Multiple Interrupts

When parallel branches each call interrupt(), resume all of them in a single invocation by mapping each interrupt ID to its resume value.

from typing import Annotated, TypedDict

import operator

from langgraph.checkpoint.memory import InMemorySaver

from langgraph.graph import START, END, StateGraph

from langgraph.types import Command, interrupt

class State(TypedDict):

    vals: Annotated[list[str], operator.add]

def node_a(state):

    answer = interrupt("question_a")

    return {"vals": [f"a:{answer}"]}

def node_b(state):

    answer = interrupt("question_b")

    return {"vals": [f"b:{answer}"]}

graph = (

    StateGraph(State)

    .add_node("a", node_a)

    .add_node("b", node_b)

    .add_edge(START, "a")

    .add_edge(START, "b")

    .add_edge("a", END)

    .add_edge("b", END)

    .compile(checkpointer=InMemorySaver())

)

config = {"configurable": {"thread_id": "1"}}

# Both parallel nodes hit interrupt() and pause

result = graph.invoke({"vals": []}, config)

# result["__interrupt__"] contains both Interrupt objects with IDs

# Resume all pending interrupts at once using a map of id -> value

resume_map = {

    i.id: f"answer for {i.value}"

    for i in result["__interrupt__"]

}

result = graph.invoke(Command(resume=resume_map), config)

# result["vals"] = ["a:answer for question_a", "b:answer for question_b"]
import { Command, END, MemorySaver, START, StateGraph, interrupt, isInterrupted, INTERRUPT, Annotation } from "@langchain/langgraph";

const State = Annotation.Root({

  vals: Annotation<string[]>({

    reducer: (left, right) => left.concat(Array.isArray(right) ? right : [right]),

    default: () => [],

  }),

});

function nodeA(_state: typeof State.State) {

  const answer = interrupt("question_a") as string;

  return { vals: [`a:${answer}`] };

}

function nodeB(_state: typeof State.State) {

  const answer = interrupt("question_b") as string;

  return { vals: [`b:${answer}`] };

}

const graph = new StateGraph(State)

  .addNode("a", nodeA)

  .addNode("b", nodeB)

  .addEdge(START, "a")

  .addEdge(START, "b")

  .addEdge("a", END)

  .addEdge("b", END)

  .compile({ checkpointer: new MemorySaver() });

const config = { configurable: { thread_id: "1" } };

const interruptedResult = await graph.invoke({ vals: [] }, config);

// Resume all pending interrupts at once

const resumeMap: Record<string, string> = {};

if (isInterrupted(interruptedResult)) {

  for (const i of interruptedResult[INTERRUPT]) {

    if (i.id != null) {

      resumeMap[i.id] = `answer for ${i.value}`;

    }

  }

}

const result = await graph.invoke(new Command({ resume: resumeMap }), config);

// result.vals = ["a:answer for question_a", "b:answer for question_b"]

User-fixable errors use interrupt() to pause and collect missing data — that's the pattern covered by this skill. For the full 4-tier error handling strategy (RetryPolicy, Command error loops, etc.), see the fundamentals skill.

Side Effects Before Interrupt Must Be Idempotent

When the graph resumes, the node restarts from the beginning — ALL code before interrupt() re-runs. In subgraphs, BOTH the parent node and the subgraph node re-execute.

Do:

  • Use upsert (not insert) operations before interrupt()
  • Use check-before-create patterns
  • Place side effects after interrupt() when possible
  • Separate side effects into their own nodes

Don't:

  • Create new records before interrupt() — duplicates on each resume
  • Append to lists before interrupt() — duplicate entries on each resume
# GOOD: Upsert is idempotent — safe before interrupt

def node_a(state: State):

    db.upsert_user(user_id=state["user_id"], status="pending_approval")

    approved = interrupt("Approve this change?")

    return {"approved": approved}

# GOOD: Side effect AFTER interrupt — only runs once

def node_a(state: State):

    approved = interrupt("Approve this change?")

    if approved:

        db.create_audit_log(user_id=state["user_id"], action="approved")

    return {"approved": approved}

# BAD: Insert creates duplicates on each resume!

def node_a(state: State):

    audit_id = db.create_audit_log({  # Runs again on resume!

        "user_id": state["user_id"],

        "action": "pending_approval",

    })

    approved = interrupt("Approve this change?")

    return {"approved": approved}
// GOOD: Upsert is idempotent — safe before interrupt

const nodeA = async (state: typeof State.State) => {

  await db.upsertUser({ userId: state.userId, status: "pending_approval" });

  const approved = interrupt("Approve this change?");

  return { approved };

};

// GOOD: Side effect AFTER interrupt — only runs once

const nodeA = async (state: typeof State.State) => {

  const approved = interrupt("Approve this change?");

  if (approved) {

    await db.createAuditLog({ userId: state.userId, action: "approved" });

  }

  return { approved };

};

// BAD: Insert creates duplicates on each resume!

const nodeA = async (state: typeof State.State) => {

  await db.createAuditLog({  // Runs again on resume!

    userId: state.userId,

    action: "pending_approval",

  });

  const approved = interrupt("Approve this change?");

  return { approved };

};

Subgraph re-execution on resume

When a subgraph contains an interrupt(), resuming re-executes BOTH the parent node (that invoked the subgraph) AND the subgraph node (that called interrupt()):

def node_in_parent_graph(state: State):

    some_code()  # <-- Re-executes on resume

    subgraph_result = subgraph.invoke(some_input)

    # ...

def node_in_subgraph(state: State):

    some_other_code()  # <-- Also re-executes on resume

    result = interrupt("What's your name?")

    # ...
async function nodeInParentGraph(state: State) {

  someCode();  // <-- Re-executes on resume

  const subgraphResult = await subgraph.invoke(someInput);

  // ...

}

async function nodeInSubgraph(state: State) {

  someOtherCode();  // <-- Also re-executes on resume

  const result = interrupt("What's your name?");

  // ...

}

Command(resume) Warning

Command(resume=...) is the only Command pattern intended as input to invoke()/stream(). Do NOT pass Command(update=...) as input — it resumes from the latest checkpoint and the graph appears stuck. See the fundamentals skill for the full antipattern explanation.

Fixes

# WRONG

graph = builder.compile()

# CORRECT

graph = builder.compile(checkpointer=InMemorySaver())
// WRONG

const graph = builder.compile();

// CORRECT

const graph = builder.compile({ checkpointer: new MemorySaver() });
# WRONG

graph.invoke({"resume_data": "approve"}, config)

# CORRECT

graph.invoke(Command(resume="approve"), config)
// WRONG

await graph.invoke({ resumeData: "approve" }, config);

// CORRECT

await graph.invoke(new Command({ resume: "approve" }), config);
  • Use interrupts without a checkpointer — will fail
  • Resume without the same thread_id — creates a new thread instead of resuming
  • Pass Command(update=...) as invoke input — graph appears stuck (use plain dict)
  • Perform non-idempotent side effects before interrupt() — creates duplicates on resume
  • Assume code before interrupt() only runs once — it re-runs every resume
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