npx skills add ...
npx skills add langchain-ai/langchain-skills --skill langgraph-human-in-the-loop
npx skills add langchain-ai/langchain-skills --skill langgraph-human-in-the-loop
INVOKE THIS SKILL when implementing human-in-the-loop patterns, pausing for approval, or handling errors in LangGraph. Covers interrupt(), Command(resume=...), approval/validation workflows, and the 4-tier error handling strategy.
interrupt(value) — pauses execution, surfaces a value to the callerCommand(resume=value) — resumes execution, providing the value back to interrupt()Three things are required for interrupts to work:
checkpointer=InMemorySaver() (dev) or PostgresSaver (prod){"configurable": {"thread_id": "..."}} to every invoke/stream callinterrupt() must be JSON-serializableinterrupt(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.
A common pattern: interrupt to show a draft, then route based on the human's decision.
Interrupt for human review, then route to send or end based on the decision.Use interrupt() in a loop to validate human input and re-prompt if invalid.
Each Command(resume=...) call provides the next answer. If invalid, the loop re-interrupts with a clearer message.
When parallel branches each call interrupt(), resume all of them in a single invocation by mapping each interrupt ID to its resume value.
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.
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:
interrupt()interrupt() when possibleDon't:
interrupt() — duplicates on each resumeinterrupt() — duplicate entries on each resumeWhen a subgraph contains an interrupt(), resuming re-executes BOTH the parent node (that invoked the subgraph) AND the subgraph node (that called interrupt()):
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.
Command(update=...) as invoke input — graph appears stuck (use plain dict)interrupt() — creates duplicates on resumeinterrupt() only runs once — it re-runs every resumeimport { 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); // truefrom 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 });
}
};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}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"]) # 30import { 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" && answer > 0) {
return { age: answer };
} else {
// Invalid input — ask again with a more specific prompt
prompt = `'${answer}' is not a valid age. Please enter a positive number.`;
}
}
};from typing import Annotated, TypedDict
import operator
from langgraph.checkpoint.memory import InMemorySaver
from langgraph.graph import START, END, StateGraph
from langgraph.types import Command, interrupt
class State(TypedDict):
vals: Annotated[list[str], operator.add]
def node_a(state):
answer = interrupt("question_a")
return {"vals": [f"a:{answer}"]}
def node_b(state):
answer = interrupt("question_b")
return {"vals": [f"b:{answer}"]}
graph = (
StateGraph(State)
.add_node("a", node_a)
.add_node("b", node_b)
.add_edge(START, "a")
.add_edge(START, "b")
.add_edge("a", END)
.add_edge("b", END)
.compile(checkpointer=InMemorySaver())
)
config = {"configurable": {"thread_id": "1"}}
# Both parallel nodes hit interrupt() and pause
result = graph.invoke({"vals": []}, config)
# result["__interrupt__"] contains both Interrupt objects with IDs
# Resume all pending interrupts at once using a map of id -> value
resume_map = {
i.id: f"answer for {i.value}"
for i in result["__interrupt__"]
}
result = graph.invoke(Command(resume=resume_map), config)
# result["vals"] = ["a:answer for question_a", "b:answer for question_b"]import { Command, END, MemorySaver, START, StateGraph, interrupt, isInterrupted, INTERRUPT, Annotation } from "@langchain/langgraph";
const State = Annotation.Root({
vals: Annotation<string[]>({
reducer: (left, right) => left.concat(Array.isArray(right) ? right : [right]),
default: () => [],
}),
});
function nodeA(_state: typeof State.State) {
const answer = interrupt("question_a") as string;
return { vals: [`a:${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"]# 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 };
};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?");
// ...
}# 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);