Approval User Input

Approval + user input HITL: @approval + @tool(requires_user_input=True).

approval_user_input.py
"""
Approval User Input
=============================

Approval + user input HITL: @approval + @tool(requires_user_input=True).
"""

import os
import time

from agno.agent import Agent
from agno.approval import approval
from agno.db.sqlite import SqliteDb
from agno.models.openai import OpenAIResponses
from agno.tools import tool

DB_FILE = "tmp/approvals_test.db"


@approval
@tool(requires_user_input=True, user_input_fields=["recipient"])
def send_money(amount: float, recipient: str, note: str) -> str:
    """Send money to a recipient.

    Args:
        amount (float): The amount of money to send.
        recipient (str): The recipient to send money to (provided by user).
        note (str): A note to include with the transfer.

    Returns:
        str: Confirmation of the transfer.
    """
    return f"Sent ${amount} to {recipient}: {note}"


# ---------------------------------------------------------------------------
# Create Agent
# ---------------------------------------------------------------------------
db = SqliteDb(
    db_file=DB_FILE, session_table="agent_sessions", approvals_table="approvals"
)
agent = Agent(
    model=OpenAIResponses(id="gpt-5-mini"),
    tools=[send_money],
    markdown=True,
    db=db,
)

# ---------------------------------------------------------------------------
# Run Agent
# ---------------------------------------------------------------------------
if __name__ == "__main__":
    # Clean up from previous runs
    if os.path.exists(DB_FILE):
        os.remove(DB_FILE)
    os.makedirs("tmp", exist_ok=True)

    # Re-create after cleanup
    db = SqliteDb(
        db_file=DB_FILE, session_table="agent_sessions", approvals_table="approvals"
    )
    agent = Agent(
        model=OpenAIResponses(id="gpt-5-mini"),
        tools=[send_money],
        markdown=True,
        db=db,
    )

    # Step 1: Run - agent will pause
    print("--- Step 1: Running agent (expects pause) ---")
    run_response = agent.run("Send $50 to someone with the note 'lunch money'.")
    print(f"Run status: {run_response.status}")
    assert run_response.is_paused, f"Expected paused, got {run_response.status}"
    print("Agent paused as expected.")

    # Step 2: Check that an approval record was created in the DB
    print("\n--- Step 2: Checking approval record in DB ---")
    approvals_list, total = db.get_approvals(status="pending", approval_type="required")
    print(f"Pending approvals: {total}")
    assert total >= 1, f"Expected at least 1 pending approval, got {total}"
    approval_record = approvals_list[0]
    print(f"  Approval ID: {approval_record['id']}")
    print(f"  Run ID:      {approval_record['run_id']}")
    print(f"  Status:      {approval_record['status']}")
    print(f"  Source:      {approval_record['source_type']}")
    print(f"  Context:     {approval_record.get('context')}")

    # Step 3: Provide user input for recipient and confirm
    print("\n--- Step 3: Providing user input and confirming ---")
    for requirement in run_response.active_requirements:
        if requirement.needs_user_input:
            print(
                f"  Providing user input for tool: {requirement.tool_execution.tool_name}"
            )
            requirement.provide_user_input({"recipient": "Alice"})
        if requirement.needs_confirmation:
            print(f"  Confirming tool: {requirement.tool_execution.tool_name}")
            requirement.confirm()

    run_response = agent.continue_run(
        run_id=run_response.run_id,
        requirements=run_response.requirements,
    )
    print(f"Run status after continue: {run_response.status}")
    assert not run_response.is_paused, "Expected run to complete, but it's still paused"

    # Step 4: Resolve the approval record in the DB
    print("\n--- Step 4: Resolving approval in DB ---")
    resolved = db.update_approval(
        approval_record["id"],
        expected_status="pending",
        status="approved",
        resolved_by="test_user",
        resolved_at=int(time.time()),
    )
    assert resolved is not None, "Approval resolution failed (possible race condition)"
    print(f"  Resolved status: {resolved['status']}")
    print(f"  Resolved by:     {resolved['resolved_by']}")

    # Step 5: Verify no more pending approvals
    print("\n--- Step 5: Verifying no pending approvals ---")
    count = db.get_pending_approval_count()
    print(f"Remaining pending approvals: {count}")
    assert count == 0, f"Expected 0 pending approvals, got {count}"

    print("\n--- All checks passed! ---")
    print(f"\nAgent output (truncated): {str(run_response.content)[:200]}...")

These examples simulate approval decisions with fixed confirmations, rejections, user input, or external results. The deployment, email, payment, and scan demonstrations use placeholder actions. The Hacker News examples make real HTTP requests after confirmation. In an application, obtain the authorized user's decision before updating a requirement or approval record.

There are two continuation paths:

  • Explicit requirements: update the paused run's requirements and pass them to continue_run() or acontinue_run(). This supplies the decision directly; a pending database approval record does not gate that path. Keep its audit record in sync.
  • Database resolution: resolve the approval record first, then continue by run ID without supplying requirements. Required approvals are checked before execution. See Approval Post Hook for this pattern and its resolved approval metadata.

With @approval(type="audit"), records describe HITL resolution, including rejection and externally supplied results. A record does not establish that the tool body executed or that a real person supplied the decision.

Run the Example

Set up your virtual environment

uv venv --python 3.12
source .venv/bin/activate

Use a disposable example directory

This script deletes tmp/approvals_test.db if it exists, including its saved sessions and approvals. Save and run it in a separate disposable directory. If changing the database path, use a new file dedicated to this example.

Install dependencies

uv pip install -U agno openai sqlalchemy

Export your OpenAI API key

export OPENAI_API_KEY="your_openai_api_key_here"

Run the example

Save the code above as approval_user_input.py, then run:

python approval_user_input.py

Full source: cookbook/02_agents/11_approvals/approval_user_input.py