Skip to main content

AutoGPT Integration

Status

Integration Status: Planned Source Code: Not yet available Documentation: Conceptual

Overview

AutoGPT integration with OW-kai governance is currently in the planning phase. This integration would provide:

  • Pre-execution risk assessment for autonomous actions
  • Approval workflows for high-risk operations
  • Complete audit logging for compliance
  • Policy enforcement for AutoGPT agents

Planned Features

1. Autonomous Action Governance

# Conceptual - not yet implemented
from autogpt_ascend import AscendGovernancePlugin

plugin = AscendGovernancePlugin(
api_key="owkai_admin_key",
risk_threshold=70
)

2. Risk-Based Approval

# Low risk: Auto-approve
"read_file", "search_web"

# Medium risk: Evaluate
"write_file", "api_call"

# High risk: Require approval
"execute_command", "delete_data"

3. Audit Trail

# All AutoGPT actions logged with:
{
"agent_id": "autogpt-main",
"action_type": "file_write",
"risk_score": 45,
"decision": "approved",
"timestamp": "2025-12-04T10:30:00Z"
}

Current Alternatives

While native AutoGPT integration is planned, you can currently:

Option 1: Custom Agent Pattern

Use the Python SDK to wrap AutoGPT actions:

# See: integration-examples/python_sdk_example.py
from owkai import OWKAIClient, AuthorizedAgent

agent = AuthorizedAgent(
agent_id="autogpt-wrapper",
agent_name="AutoGPT Governed"
)

# Wrap AutoGPT actions with governance
decision = agent.request_authorization(
action_type="execute_command",
resource="system",
details={"command": "python script.py"}
)

Option 2: API Integration

Use direct REST API calls:

import requests

response = requests.post(
"https://pilot.owkai.app/api/v1/actions/submit",
headers={"Authorization": f"Bearer {api_key}"},
json={
"agent_id": "autogpt",
"action_type": "file_write",
"resource": "/data/output.txt"
}
)

Implementation Timeline

  • Phase 1: Requirements gathering (Q1 2025)
  • Phase 2: Plugin development (Q2 2025)
  • Phase 3: Beta testing (Q3 2025)
  • Phase 4: General availability (Q4 2025)

Providing Feedback

If you're interested in this integration:

  1. Review the Python SDK example
  2. Check the LangChain integration for similar patterns
  3. Contact us about beta testing

Next Steps