Approval Team
Team-level approval: member agent tool with @approval.
"""
Approval Team
=============================
Team-level approval: member agent tool with @approval.
"""
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.team.team import Team
from agno.tools import tool
DB_FILE = "tmp/approvals_team_test.db"
@approval
@tool(requires_confirmation=True)
def deploy_to_production(app_name: str, version: str) -> str:
"""Deploy an application to production.
Args:
app_name (str): Name of the application.
version (str): Version to deploy.
"""
return f"Successfully deployed {app_name} v{version} to production"
# ---------------------------------------------------------------------------
# Create Agent
# ---------------------------------------------------------------------------
db = SqliteDb(
db_file=DB_FILE, session_table="team_sessions", approvals_table="approvals"
)
deploy_agent = Agent(
name="Deploy Agent",
role="Handles deployments to production",
model=OpenAIResponses(id="gpt-5-mini"),
tools=[deploy_to_production],
)
team = Team(
name="DevOps Team",
members=[deploy_agent],
model=OpenAIResponses(id="gpt-5-mini"),
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="team_sessions", approvals_table="approvals"
)
deploy_agent = Agent(
name="Deploy Agent",
role="Handles deployments to production",
model=OpenAIResponses(id="gpt-5-mini"),
tools=[deploy_to_production],
)
team = Team(
name="DevOps Team",
members=[deploy_agent],
model=OpenAIResponses(id="gpt-5-mini"),
db=db,
)
# Step 1: Run - team will pause
print("--- Step 1: Running team (expects pause) ---")
response = team.run("Deploy the payments app version 2.1 to production")
print(f"Team run status: {response.status}")
assert response.is_paused, f"Expected paused, got {response.status}"
print("Team paused as expected.")
# Step 2: Check approval record
print("\n--- Step 2: Checking approval record in DB ---")
approvals_list, total = db.get_approvals(status="pending")
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" Source type: {approval_record['source_type']}")
print(f" Source name: {approval_record.get('source_name')}")
print(f" Context: {approval_record.get('context')}")
# Step 3: Confirm and continue
print("\n--- Step 3: Confirming and continuing ---")
for req in response.requirements:
if req.needs_confirmation:
print(
f" Confirming tool: {req.tool_execution.tool_name}({req.tool_execution.tool_args})"
)
req.confirm()
response = team.continue_run(response)
print(f"Team run status after continue: {response.status}")
# Step 4: Resolve approval in DB
print("\n--- Step 4: Resolving approval in DB ---")
resolved = db.update_approval(
approval_record["id"],
expected_status="pending",
status="approved",
resolved_by="devops_lead",
resolved_at=int(time.time()),
)
assert resolved is not None, "Approval resolution failed"
print(f" Resolved status: {resolved['status']}")
print(f" Resolved by: {resolved['resolved_by']}")
# Step 5: Verify
print("\n--- Step 5: Verifying no pending approvals ---")
count = db.get_pending_approval_count()
print(f"Remaining pending approvals: {count}")
assert count == 0
print("\n--- All checks passed! ---")
print(f"\nTeam output: {response.content}")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()oracontinue_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/activateUse a disposable example directory
This script deletes tmp/approvals_team_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 sqlalchemyExport your OpenAI API key
export OPENAI_API_KEY="your_openai_api_key_here"Run the example
Save the code above as approval_team.py, then run:
python approval_team.pyFull source: cookbook/02_agents/11_approvals/approval_team.py