CrewAI

Gate sensitive CrewAI crew actions behind human approval before they execute.

Install

pip install cheqpoint

pip install cheqpoint

Create a Cheqpoint approval tool

Python

from crewai import Agent, Task, Crew
from crewai_tools import tool
from cheqpoint import CheqpointClient

client = CheqpointClient(api_key=os.environ["CHEQPOINT_API_KEY"])

@tool("request_human_approval")
def request_human_approval(action: str, summary: str, details: dict) -> str:
    """Request human approval before executing a sensitive action."""
    result = client.checkpoint(
        action=action,
        summary=summary,
        details=details,
        risk_level="high",
    )
    if result["status"] == "APPROVED":
        return f"Approved. Note: {result.get('decisionNote', '')}"
    raise ValueError(f"Rejected: {result.get('decisionNote', 'No reason given')}")

from crewai import Agent, Task, Crew
from crewai_tools import tool
from cheqpoint import CheqpointClient

client = CheqpointClient(api_key=os.environ["CHEQPOINT_API_KEY"])

@tool("request_human_approval")
def request_human_approval(action: str, summary: str, details: dict) -> str:
    """Request human approval before executing a sensitive action."""
    result = client.checkpoint(
        action=action,
        summary=summary,
        details=details,
        risk_level="high",
    )
    if result["status"] == "APPROVED":
        return f"Approved. Note: {result.get('decisionNote', '')}"
    raise ValueError(f"Rejected: {result.get('decisionNote', 'No reason given')}")

Wire into a CrewAI agent

Python

finance_agent = Agent(
    role="Finance Manager",
    goal="Process customer refunds within policy",
    backstory="You are a careful finance agent that always gets approval for large refunds.",
    tools=[request_human_approval],
    verbose=True,
)

approve_task = Task(
    description="Approve the £750 refund for order #98765 if within policy.",
    agent=finance_agent,
    expected_output="Confirmation that refund was approved or reason for rejection.",
)

crew = Crew(agents=[finance_agent], tasks=[approve_task])
result = crew.kickoff()
print(result)

finance_agent = Agent(
    role="Finance Manager",
    goal="Process customer refunds within policy",
    backstory="You are a careful finance agent that always gets approval for large refunds.",
    tools=[request_human_approval],
    verbose=True,
)

approve_task = Task(
    description="Approve the £750 refund for order #98765 if within policy.",
    agent=finance_agent,
    expected_output="Confirmation that refund was approved or reason for rejection.",
)

crew = Crew(agents=[finance_agent], tasks=[approve_task])
result = crew.kickoff()
print(result)