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Some tool operations may be sensitive and require human approval before execution. Deep Agents support human-in-the-loop workflows through LangGraph’s interrupt capabilities. You can configure which tools require approval using the interrupt_on parameter.

Basic configuration

The interrupt_on parameter accepts a dictionary mapping tool names to interrupt configurations. Each tool can be configured with:
  • True: Enable interrupts with default behavior (approve, edit, reject allowed)
  • False: Disable interrupts for this tool
  • {"allowed_decisions": [...]}: Custom configuration with specific allowed decisions
from langchain.tools import tool
from deepagents import create_deep_agent
from langgraph.checkpoint.memory import MemorySaver

@tool
def delete_file(path: str) -> str:
    """Delete a file from the filesystem."""
    return f"Deleted {path}"

@tool
def read_file(path: str) -> str:
    """Read a file from the filesystem."""
    return f"Contents of {path}"

@tool
def send_email(to: str, subject: str, body: str) -> str:
    """Send an email."""
    return f"Sent email to {to}"

# Checkpointer is REQUIRED for human-in-the-loop
checkpointer = MemorySaver()

agent = create_deep_agent(
    model="claude-sonnet-4-6",
    tools=[delete_file, read_file, send_email],
    interrupt_on={
        "delete_file": True,  # Default: approve, edit, reject
        "read_file": False,   # No interrupts needed
        "send_email": {"allowed_decisions": ["approve", "reject"]},  # No editing
    },
    checkpointer=checkpointer  # Required!
)

Decision types

The allowed_decisions list controls what actions a human can take when reviewing a tool call:
  • "approve": Execute the tool with the original arguments as proposed by the agent
  • "edit": Modify the tool arguments before execution
  • "reject": Skip executing this tool call entirely
You can customize which decisions are available for each tool:
const interruptOn = {
  // Sensitive operations: allow all options
  delete_file: { allowedDecisions: ["approve", "edit", "reject"] },

  // Moderate risk: approval or rejection only
  write_file: { allowedDecisions: ["approve", "reject"] },

  // Must approve (no rejection allowed)
  critical_operation: { allowedDecisions: ["approve"] },
};

Handle interrupts

When an interrupt is triggered, the agent pauses execution and returns control. Check for interrupts in the result and handle them accordingly.
import { v4 as uuidv4 } from "uuid";
import { Command } from "@langchain/langgraph";

// Create config with thread_id for state persistence
const config = { configurable: { thread_id: uuidv4() } };

// Invoke the agent
let result = await agent.invoke({
  messages: [{ role: "user", content: "Delete the file temp.txt" }],
}, config);

// Check if execution was interrupted
if (result.__interrupt__) {
  // Extract interrupt information
  const interrupts = result.__interrupt__[0].value;
  const actionRequests = interrupts.actionRequests;
  const reviewConfigs = interrupts.reviewConfigs;

  // Create a lookup map from tool name to review config
  const configMap = Object.fromEntries(
    reviewConfigs.map((cfg) => [cfg.actionName, cfg])
  );

  // Display the pending actions to the user
  for (const action of actionRequests) {
    const reviewConfig = configMap[action.name];
    console.log(`Tool: ${action.name}`);
    console.log(`Arguments: ${JSON.stringify(action.args)}`);
    console.log(`Allowed decisions: ${reviewConfig.allowedDecisions}`);
  }

  // Get user decisions (one per actionRequest, in order)
  const decisions = [
    { type: "approve" }  // User approved the deletion
  ];

  // Resume execution with decisions
  result = await agent.invoke(
    new Command({ resume: { decisions } }),
    config  // Must use the same config!
  );
}

// Process final result
console.log(result.messages[result.messages.length - 1].content);

Multiple tool calls

When the agent calls multiple tools that require approval, all interrupts are batched together in a single interrupt. You must provide decisions for each one in order.
const config = { configurable: { thread_id: uuidv4() } };

let result = await agent.invoke({
  messages: [{
    role: "user",
    content: "Delete temp.txt and send an email to admin@example.com"
  }]
}, config);

if (result.__interrupt__) {
  const interrupts = result.__interrupt__[0].value;
  const actionRequests = interrupts.actionRequests;

  // Two tools need approval
  console.assert(actionRequests.length === 2);

  // Provide decisions in the same order as actionRequests
  const decisions = [
    { type: "approve" },  // First tool: delete_file
    { type: "reject" }    // Second tool: send_email
  ];

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

Edit tool arguments

When "edit" is in the allowed decisions, you can modify the tool arguments before execution:
if (result.__interrupt__) {
  const interrupts = result.__interrupt__[0].value;
  const actionRequest = interrupts.actionRequests[0];

  // Original args from the agent
  console.log(actionRequest.args);  // { to: "everyone@company.com", ... }

  // User decides to edit the recipient
  const decisions = [{
    type: "edit",
    editedAction: {
      name: actionRequest.name,  // Must include the tool name
      args: { to: "team@company.com", subject: "...", body: "..." }
    }
  }];

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

Subagent interrupts

When using subagents, you can use interrupts on tool calls and within tool calls.

Interrupts on tool calls

Each subagent can have its own interrupt_on configuration that overrides the main agent’s settings:
const agent = createDeepAgent({
  tools: [deleteFile, readFile],
  interruptOn: {
    delete_file: true,
    read_file: false,
  },
  subagents: [{
    name: "file-manager",
    description: "Manages file operations",
    systemPrompt: "You are a file management assistant.",
    tools: [deleteFile, readFile],
    interruptOn: {
      // Override: require approval for reads in this subagent
      delete_file: true,
      read_file: true,  // Different from main agent!
    }
  }],
  checkpointer
});
When a subagent triggers an interrupt, the handling is the same—check for interrupts on the result and resume with Command.

Interrupts within tool calls

Subagent tools can call interrupt() directly to pause execution and await approval:
import { createAgent, tool } from "langchain";
import { ChatOpenAI } from "@langchain/openai";
import { HumanMessage } from "@langchain/core/messages";
import { MemorySaver, Command, interrupt } from "@langchain/langgraph";
import { createDeepAgent } from "deepagents";
import { z } from "zod";

const requestApproval = tool(
  async ({ actionDescription }: { actionDescription: string }) => {
    const approval = interrupt({
      type: "approval_request",
      action: actionDescription,
      message: `Please approve or reject: ${actionDescription}`,
    }) as { approved?: boolean; reason?: string };

    if (approval.approved) {
      return `Action '${actionDescription}' was APPROVED. Proceeding...`;
    } else {
      return `Action '${actionDescription}' was REJECTED. Reason: ${
        approval.reason || "No reason provided"
      }`;
    }
  },
  {
    name: "request_approval",
    description: "Request human approval before proceeding with an action.",
    schema: z.object({
      actionDescription: z
        .string()
        .describe("The action that requires approval"),
    }),
  }
);

async function main() {
  const checkpointer = new MemorySaver();
  const model = new ChatOpenAI({
    model: "gpt-4o-mini",
    maxTokens: 4096,
  });

  const compiledSubagent = createAgent({
    model: model,
    tools: [requestApproval],
    name: "approval-agent",
  });

  const parentAgent = await createDeepAgent({
    checkpointer: checkpointer,
    subagents: [
      {
        name: "approval-agent",
        description: "An agent that can request approvals",
        runnable: compiledSubagent as any,
      },
    ],
  });

  const threadId = "test_interrupt_directly";
  const config = { configurable: { thread_id: threadId } };

  console.log("Invoking agent - sub-agent will use request_approval tool...");

  let result = await parentAgent.invoke(
    {
      messages: [
        new HumanMessage({
          content:
            "Use the task tool to launch the approval-agent sub-agent. " +
            "Tell it to use the request_approval tool to request approval for 'deploying to production'.",
        }),
      ],
    },
    config
  );

  if (result.__interrupt__) {
    const interruptValue = result.__interrupt__[0].value as {
      type?: string;
      action?: string;
      message?: string;
    };
    console.log("\nInterrupt received!");
    console.log(`  Type: ${interruptValue.type}`);
    console.log(`  Action: ${interruptValue.action}`);
    console.log(`  Message: ${interruptValue.message}`);

    console.log("\nResuming with Command(resume={'approved': true})...");
    const result2 = await parentAgent.invoke(
      new Command({ resume: { approved: true } }),
      config
    );

    if (!result2.__interrupt__) {
      console.log("\nExecution completed!");
      // Find the tool response
      const toolMsgs = result2.messages?.filter((m) => m.type === "tool") || [];
      if (toolMsgs.length > 0) {
        const lastToolMsg = toolMsgs[toolMsgs.length - 1];
        console.log(`  Tool result: ${lastToolMsg.content}`);
      }
    } else {
      console.log("\nAnother interrupt occurred");
    }
  } else {
    console.log(
      "\n  No interrupt - the model may not have called request_approval"
    );
  }
}

main().catch(console.error);
When run, this produces the following output:
Invoking agent - sub-agent will use request_approval tool...

Interrupt received!
  Type: approval_request
  Action: deploying to production
  Message: Please approve or reject: deploying to production

Resuming with Command(resume={'approved': true})...

Execution completed!
  Tool result: Approval for "deploying to production" has been granted. You can proceed with the deployment.

Best practices

Always use a checkpointer

Human-in-the-loop requires a checkpointer to persist agent state between the interrupt and resume:

Use the same thread ID

When resuming, you must use the same config with the same thread_id:

Match decision order to actions

The decisions list must match the order of action_requests:

Tailor configurations by risk

Configure different tools based on their risk level: