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CortexHub Python SDK - Policy-as-Code for AI Agents

Project description

CortexHub Python SDK

Runtime Governance for AI Agents - Policy enforcement, PII/secrets detection, complete audit trails with OpenTelemetry.

Installation

# Core SDK
pip install cortexhub

# With framework support (choose one or more)
pip install cortexhub[langgraph]      # LangGraph
pip install cortexhub[crewai]         # CrewAI
pip install cortexhub[openai-agents]  # OpenAI Agents SDK
pip install cortexhub[claude-agents]  # Claude Agent SDK

# All frameworks (for development)
pip install cortexhub[all]

Quick Start

from cortexhub import init, Framework

# Initialize CortexHub FIRST, before importing your framework
cortex = init(
    agent_id="customer_support_agent",
    framework=Framework.LANGGRAPH,  # or CREWAI, OPENAI_AGENTS, CLAUDE_AGENTS
)

# Now import and use your framework
from langgraph.prebuilt import create_react_agent

# Continue with your LangGraph setup...

Supported Frameworks

Framework Enum Value Install
LangGraph Framework.LANGGRAPH pip install cortexhub[langgraph]
CrewAI Framework.CREWAI pip install cortexhub[crewai]
OpenAI Agents Framework.OPENAI_AGENTS pip install cortexhub[openai-agents]
Claude Agents Framework.CLAUDE_AGENTS pip install cortexhub[claude-agents]

Configuration

# Required: API key for telemetry
export CORTEXHUB_API_KEY=ch_live_...

# Optional: Backend URL (defaults to production)
export CORTEXHUB_API_URL=https://api.cortexhub.ai

# Optional: provider keys for your framework or examples
export OPENAI_API_KEY=sk-...

Features

  • Policy Enforcement - Cedar-based policies, local evaluation
  • PII Detection - Presidio-powered, 50+ entity types, configurable
  • Secrets Detection - detect-secrets integration, 30+ secret types
  • Configurable Guardrails - Select specific PII/secret types to redact
  • Custom Patterns - Add company-specific regex patterns
  • OpenTelemetry - Industry-standard observability
  • Framework Adapters - Automatic interception for all major frameworks
  • Privacy Mode - Metadata-only by default, safe for production

Privacy Modes

# Production (default) - only metadata sent
cortex = init(agent_id="...", framework=..., privacy=True)
# Sends: tool names, arg schemas, PII types detected
# Never: raw values, prompts, responses

# Development - full data for testing policies  
cortex = init(agent_id="...", framework=..., privacy=False)
# Also sends: raw args, results, prompts (for policy testing)

Policy Enforcement

Policies are created in the CortexHub dashboard from detected risks. The SDK automatically fetches and enforces them:

from cortexhub.errors import PolicyViolationError, ApprovalRequiredError

# Policies are fetched automatically during init()
# If policies exist, enforcement mode is enabled

try:
    agent.run("Process a $10,000 refund")
except PolicyViolationError as e:
    print(f"Blocked by policy: {e.policy_name}")
    print(f"Reason: {e.reasoning}")
except ApprovalRequiredError as e:
    print(f"\n⏸️  APPROVAL REQUIRED")
    print(f"   Approval ID: {e.approval_id}")
    print(f"   Tool: {e.tool_name}")
    print(f"   Reason: {e.reason}")
    print(f"   Expires: {e.expires_at}")
    print(f"\n   Decision endpoint: {e.decision_endpoint}")
    print(f"   Configure a webhook to receive approval.decisioned event")

Guardrail Configuration

Guardrails detect PII and secrets in LLM prompts. Configure in the dashboard:

  1. Select types to redact: Choose specific PII types (email, phone, etc.)
  2. Add custom patterns: Regex for company-specific data (employee IDs, etc.)
  3. Choose action: Redact, block, or monitor only

The SDK applies your configuration automatically:

# With guardrail policy active:
# Input prompt: "Contact john@email.com about employee EMP-123456"
# After redaction: "Contact [REDACTED-EMAIL_ADDRESS] about employee [REDACTED-CUSTOM_EMPLOYEE_ID]"
# Only configured types are redacted

Examples

Examples live in the separate cortexhub-examples repository (the SDK package itself does not ship example scripts).

git clone git@github.com:cortexhub/cortexhub-examples.git
cd cortexhub-examples/langgraph  # or crewai, openai-agents, claude-agents

Important: Initialization Order

Always initialize CortexHub FIRST, before importing your framework:

# ✅ CORRECT
from cortexhub import init, Framework
cortex = init(agent_id="my_agent", framework=Framework.LANGGRAPH)

from langgraph.prebuilt import create_react_agent  # Import AFTER init

# ❌ WRONG
from langgraph.prebuilt import create_react_agent  # Framework imported first
from cortexhub import init, Framework
cortex = init(...)  # Too late!

This ensures:

  1. CortexHub sets up OpenTelemetry before frameworks that also use it
  2. Framework decorators/classes are properly wrapped

Architecture

Agent Decides → [CortexHub] → Agent Executes
                    │
              ┌─────┴─────┐
              │           │
         Policy      Guardrails
         Engine      (PII/Secrets)
              │           │
              └─────┬─────┘
                    │
              OpenTelemetry
               (to backend)

Development

cd python

# Install with all frameworks
uv sync --all-extras

# Run tests
uv run pytest

# Lint
uv run ruff check .

Links

License

MIT

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