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Python SDK for AgentGuard - AI Agent governance and monitoring platform

Project description

AgentGuard Python SDK

Python SDK for integrating with AgentGuard - AI Agent governance and monitoring platform.

Features

  • Zero Code Changes - Drop-in replacement for OpenAI client
  • Unified Client - One client for all features (LLM + Approvals)
  • Transparent Proxy - All requests routed through AgentGuard
  • Integrated Approval Management - Built-in approval status query and submission
  • Business API Interception - Monitor all API calls
  • Cost Tracking - Automatic cost monitoring
  • Policy Enforcement - Apply governance policies
  • Approval Workflows - Handle high-risk operations

Installation

pip install agentguard-zhx

Quick Start

Basic Usage

from agentguard import AgentGuardOpenAI

# Initialize client
client = AgentGuardOpenAI(
    agentguard_url="http://localhost:8080",
    agent_api_key="ag_xxx"
)

# Use standard OpenAI API
response = client.chat.completions.create(
    model="gpt-4",
    messages=[{"role": "user", "content": "Hello"}]
)

print(response.choices[0].message.content)

Approval Status Query

Query approval status using integrated approval management:

from agentguard import AgentGuardOpenAI

# One client for everything
client = AgentGuardOpenAI(
    agentguard_url="http://localhost:8080",
    agent_api_key="ag_xxx"
)

# LLM calls
response = client.chat.completions.create(...)

# Approval management (integrated)
status = client.approvals.get_status("approval_id")

if status.is_approved:
    print("Approved:", status.execution_result)
elif status.is_rejected:
    print("Rejected:", status.remark)

# Submit approval reason
client.approvals.submit_reason("approval_id", "Need to delete test data")

Environment Variables

# Set environment variables
export AGENTGUARD_URL="http://localhost:8080"
export AGENTGUARD_API_KEY="ag_xxx"

# Use without explicit configuration
from agentguard import AgentGuardOpenAI

client = AgentGuardOpenAI()  # Loads from environment

Business API Interception

from agentguard import enable_agentguard
import requests

# Enable global interception
enable_agentguard(
    agentguard_url="http://localhost:8080",
    agent_api_key="ag_xxx",
    intercept_patterns=[r"https://api\.example\.com/.*"]
)

# All matching requests go through AgentGuard
response = requests.get("https://api.example.com/data")

Configuration

AgentGuardConfig

from agentguard import AgentGuardConfig, AgentGuardOpenAI

config = AgentGuardConfig(
    agentguard_url="http://localhost:8080",
    agent_api_key="ag_xxx"
)

client = AgentGuardOpenAI(config=config)

Examples

See the examples/ directory for more examples:

  • basic_usage.py - Basic OpenAI integration
  • approval_polling.py - Query approval status
  • business_api.py - Business API interception

API Reference

AgentGuardOpenAI

Drop-in replacement for OpenAI client with integrated approval management.

Parameters:

  • agentguard_url (str): AgentGuard server URL
  • agent_api_key (str): AgentGuard API key
  • config (AgentGuardConfig, optional): Configuration object

Integrated Approval Management:

Access via client.approvals:

  • get_status(approval_id) - Query approval status by ID
  • submit_reason(approval_id, reason) - Submit approval reason/justification

Returns: ApprovalStatusResponse with:

  • status - ApprovalStatus enum (PENDING/APPROVED/REJECTED/EXPIRED)
  • execution_result - Result if approved and executed
  • remark - Rejection reason if rejected
  • is_pending, is_approved, is_rejected, is_expired - Helper properties

enable_agentguard()

Enable global request interception for the requests library.

Parameters:

  • agentguard_url (str): AgentGuard server URL
  • agent_api_key (str): AgentGuard API key
  • intercept_patterns (List[str], optional): URL patterns to intercept (regex)

Development

# Install development dependencies
pip install -e ".[dev]"

# Run tests
pytest

# Format code
black agentguard/

# Lint code
ruff check agentguard/

License

MIT License

Support

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