Metadata-Version: 2.4
Name: doopal
Version: 1.1.1
Summary: Python SDK for Doopal AI Governance Platform
Home-page: https://github.com/doopal-ai/doopal-governance
Author: Doopal Team
Author-email: info@doopal.com
Project-URL: Bug Reports, https://github.com/doopal-ai/doopal-governance/issues
Project-URL: Source, https://github.com/doopal-ai/doopal-governance
Project-URL: Documentation, https://docs.doopal.com
Keywords: ai governance llm security redaction policy enterprise compliance analytics monitoring rbac sso audit
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Classifier: Topic :: Internet :: WWW/HTTP :: HTTP Servers
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Requires-Python: >=3.8
Description-Content-Type: text/markdown
Requires-Dist: httpx>=0.24.0
Requires-Dist: pydantic>=2.0.0
Requires-Dist: asyncio
Provides-Extra: dev
Requires-Dist: pytest>=7.0.0; extra == "dev"
Requires-Dist: pytest-asyncio>=0.21.0; extra == "dev"
Requires-Dist: black>=23.0.0; extra == "dev"
Requires-Dist: isort>=5.12.0; extra == "dev"
Requires-Dist: mypy>=1.0.0; extra == "dev"
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# Doopal AI Governance Python SDK

The Doopal Python SDK provides a simple and powerful way to integrate AI governance, redaction, and policy enforcement into your Python applications. Route your LLM API calls through Doopal to ensure compliance, security, and cost control.

## Installation

```bash
pip install doopal
```

## Quick Start

### Async Usage (Recommended)

```python
import asyncio
from doopal_client import DoopalClient

async def main():
    async with DoopalClient(api_key="your-api-key") as client:
        response = await client.chat_completion(
            provider="openai",
            model="gpt-3.5-turbo",
            messages=[
                {"role": "user", "content": "Hello, how are you?"}
            ]
        )
        print(response.response)

asyncio.run(main())
```

### Synchronous Usage

```python
from doopal_client import DoopalSyncClient

client = DoopalSyncClient(api_key="your-api-key")

response = client.chat_completion(
    provider="openai",
    model="gpt-3.5-turbo",
    messages=[
        {"role": "user", "content": "Hello, how are you?"}
    ]
)

print(response.response)
client.close()
```

## Features

### Core AI Gateway
- **Multi-Provider Support**: Works with OpenAI, Anthropic, Azure OpenAI, Cohere, and more
- **Governance & Compliance**: Automatic policy enforcement and compliance checking
- **Content Redaction**: Sensitive data detection and redaction
- **Cost Control**: Budget management and usage tracking
- **Streaming Support**: Real-time streaming responses
- **Error Handling**: Comprehensive error handling with specific exception types
- **Async/Sync**: Both asynchronous and synchronous interfaces

### Enterprise Features (v1.1.0+)
- **Organization Management**: Multi-tenant organization administration
- **Role-Based Access Control (RBAC)**: User roles and permissions management
- **Single Sign-On (SSO)**: SAML/OIDC enterprise authentication
- **Advanced Analytics**: Compliance, threat detection, performance, and cost analytics
- **Audit Logging**: Comprehensive audit trails and compliance reporting
- **Security Monitoring**: Real-time threat detection and alerting
- **Policy Management**: Advanced policy creation, testing, and management
- **Provider Management**: AI provider configuration and monitoring
- **Comprehensive Health Checks**: Kubernetes-ready health, readiness, and liveness probes
- **Data Validation**: Structured data and PII validation capabilities

## Configuration

### Environment Variables

```bash
export DOOPAL_API_KEY="your-api-key"
export DOOPAL_BASE_URL="https://api.doopal.com"  # Optional
export DOOPAL_ORG_ID="your-org-id"  # Optional for multi-tenant setups
```

### Client Configuration

```python
client = DoopalClient(
    api_key="your-api-key",
    base_url="https://api.doopal.com",  # Default
    timeout=30,  # Request timeout in seconds
    max_retries=3,  # Maximum retry attempts
    organization_id="your-org-id"  # Optional
)
```

## API Reference

### Chat Completions

```python
response = await client.chat_completion(
    provider="openai",
    model="gpt-3.5-turbo",
    messages=[
        {"role": "system", "content": "You are a helpful assistant."},
        {"role": "user", "content": "What is the capital of France?"}
    ],
    temperature=0.7,
    max_tokens=100,
    stream=False
)
```

### Streaming Chat Completions

```python
async for chunk in await client.chat_completion(
    provider="openai",
    model="gpt-3.5-turbo",
    messages=[{"role": "user", "content": "Tell me a story"}],
    stream=True
):
    print(chunk, end="")
```

### Text Completions

```python
response = await client.completion(
    provider="openai",
    model="gpt-3.5-turbo-instruct",
    prompt="The capital of France is",
    max_tokens=50
)
```

### Embeddings

```python
response = await client.embeddings(
    provider="openai",
    model="text-embedding-ada-002",
    input_text="Hello world"
)
```

### Usage Statistics

```python
stats = await client.get_usage_stats()
print(f"Total requests: {stats['total_requests']}")
print(f"Total cost: ${stats['total_cost']}")
```

### Health Check

```python
# Basic health check
health = await client.health_check()
print(f"Status: {health['status']}")

# Detailed health status (includes database, redis, etc.)
detailed_health = await client.get_detailed_health()
print(f"Database: {detailed_health['database']['status']}")
print(f"Redis: {detailed_health['redis']['status']}")

# Kubernetes readiness probe
readiness = await client.get_readiness_status()
print(f"Ready: {readiness['status']}")

# Kubernetes liveness probe
liveness = await client.get_liveness_status()
print(f"Live: {liveness['status']}")
```

### Enterprise Organization Management

```python
# Get organization information
org = await client.get_organization()
print(f"Organization: {org['name']}")

# Update organization settings
updated_org = await client.update_organization({
    'name': 'Acme Corp',
    'settings': {
        'enableAdvancedAnalytics': True,
        'complianceFrameworks': ['gdpr', 'hipaa']
    }
})

# Get user roles and permissions
roles = await client.get_user_roles()
print(f"User role: {roles['role']}")
print(f"Permissions: {roles['permissions']}")

# Get organization members
members = await client.get_organization_members()
print(f"{len(members)} members in organization")

# Invite new user
invitation = await client.invite_user({
    'email': 'user@company.com',
    'role': 'manager'
})

# Configure SSO
sso_config = await client.configure_sso({
    'provider': 'okta',
    'domain': 'company.okta.com',
    'clientId': 'your-client-id',
    'clientSecret': 'your-client-secret'
})
```

### Advanced Analytics

```python
# Compliance analytics
compliance_data = await client.get_compliance_analytics({
    'framework': 'gdpr',
    'startDate': '2024-01-01',
    'endDate': '2024-12-31'
})

# Threat detection analytics
threats = await client.get_threat_analytics({
    'severity': 'high',
    'timeframe': '24h'
})

# Performance analytics
performance = await client.get_performance_analytics({
    'metric': 'response_time',
    'aggregation': 'avg'
})

# Cost analytics
costs = await client.get_cost_analytics({
    'provider': 'openai',
    'groupBy': 'model'
})
```

### Compliance Reporting

```python
# Get compliance status
status = await client.get_compliance_status('gdpr')
print(f"GDPR compliance: {status['score']}%")

# Generate compliance report
report = await client.generate_compliance_report({
    'framework': 'hipaa',
    'format': 'pdf',
    'period': 'quarterly'
})

# Get compliance violations
violations = await client.get_compliance_violations({
    'severity': 'high',
    'status': 'open'
})
```

### Policy Management

```python
# Get all policies
policies = await client.get_policies()

# Create new policy
new_policy = await client.create_policy({
    'name': 'Content Safety Policy',
    'description': 'Prevent harmful content generation',
    'policyType': 'rego',
    'policyContent': 'package content.safety\n\ndefault allow = false...',
    'enabled': True,
    'priority': 1
})

# Update policy
updated_policy = await client.update_policy('policy-id', {
    'enabled': False,
    'priority': 2
})

# Delete policy
deleted = await client.delete_policy('policy-id')

# Test policy
test_result = await client.test_policy({
    'policyId': 'policy-id',
    'testInput': {
        'content': 'Test content',
        'user': {'role': 'user'}
    }
})
```

### Provider Management

```python
# Get available providers
providers = await client.get_providers()

# Add new provider
new_provider = await client.add_provider({
    'name': 'OpenAI Production',
    'providerType': 'openai',
    'apiKey': 'sk-...',
    'modelConfigs': {
        'gpt-4': {
            'maxTokens': 4000,
            'temperature': 0.7,
            'costPerToken': 0.00003
        }
    },
    'rateLimits': {
        'requestsPerMinute': 3500,
        'tokensPerMinute': 90000
    }
})

# Update provider
updated_provider = await client.update_provider('provider-id', {
    'rateLimits': {
        'requestsPerMinute': 5000
    }
})
```

### Security & Monitoring

```python
# Get security threats
threats = await client.get_security_threats({
    'severity': 'high',
    'timeframe': '1h'
})

# Get observability metrics
metrics = await client.get_observability_metrics({
    'metric': 'request_rate',
    'timeframe': '5m'
})

# Get system alerts
alerts = await client.get_alerts({
    'status': 'active',
    'severity': 'critical'
})
```

### Integrations

```python
# Get available integrations
integrations = await client.get_integrations()

# Configure integration
configured_integration = await client.configure_integration({
    'type': 'slack',
    'config': {
        'webhookUrl': 'https://hooks.slack.com/...',
        'channel': '#ai-governance'
    }
})
```

### Data Validation

```python
# Validate structured data
validation = await client.validate_structured_data({
    'schema': {
        'type': 'object',
        'properties': {
            'name': {'type': 'string'},
            'age': {'type': 'number'}
        }
    },
    'data': {'name': 'John', 'age': 30}
})

# Validate PII detection
pii_validation = await client.validate_pii({
    'content': 'My email is john@example.com'
})
print(f"PII detected: {pii_validation['piiDetected']}")
```

### Audit Logging

```python
# Get audit logs
audit_logs = await client.get_audit_logs({
    'action': 'policy_violation',
    'startDate': '2024-01-01',
    'endDate': '2024-01-31',
    'userId': 'user123'
})

print(f"Found {len(audit_logs)} audit entries")
```

## Error Handling

The SDK provides specific exception types for different error scenarios:

```python
from doopal_client import DoopalError, PolicyViolationError, RedactionError

try:
    response = await client.chat_completion(
        provider="openai",
        model="gpt-3.5-turbo",
        messages=[{"role": "user", "content": "Sensitive content here"}]
    )
except PolicyViolationError as e:
    print(f"Policy violation: {e}")
except RedactionError as e:
    print(f"Content blocked: {e}")
except DoopalError as e:
    print(f"API error: {e}")
```

## Advanced Usage

### Custom Metadata

```python
response = await client.chat_completion(
    provider="openai",
    model="gpt-3.5-turbo",
    messages=[{"role": "user", "content": "Hello"}],
    metadata={
        "user_id": "user123",
        "session_id": "session456",
        "department": "engineering"
    }
)
```

### Multiple Providers

```python
# OpenAI
openai_response = await client.chat_completion(
    provider="openai",
    model="gpt-3.5-turbo",
    messages=[{"role": "user", "content": "Hello"}]
)

# Anthropic
anthropic_response = await client.chat_completion(
    provider="anthropic",
    model="claude-3-sonnet-20240229",
    messages=[{"role": "user", "content": "Hello"}]
)

# Azure OpenAI
azure_response = await client.chat_completion(
    provider="azure_openai",
    model="gpt-35-turbo",
    messages=[{"role": "user", "content": "Hello"}]
)
```

## Response Format

All responses include governance and redaction information:

```python
{
    "response": "The generated text response",
    "provider": "openai",
    "model": "gpt-3.5-turbo",
    "usage": {
        "prompt_tokens": 10,
        "completion_tokens": 20,
        "total_tokens": 30
    },
    "metadata": {
        "request_id": "req_123",
        "processing_time": 1.5,
        "policies_applied": ["content_filter", "rate_limit"],
        "cost": 0.0001
    },
    "redacted_content": [
        "email@example.com was redacted",
        "SSN 123-45-6789 was blocked"
    ]
}
```

## Enterprise Integration Examples

### Multi-Tenant Setup

```python
# Initialize client with organization context
client = DoopalClient(
    api_key='your-api-key',
    base_url='https://api.your-domain.com',
    organization_id='org-123'  # Important for multi-tenant deployments
)

# All subsequent calls will be scoped to this organization
org_data = await client.get_organization()
compliance = await client.get_compliance_status('gdpr')
```

### Production Monitoring

```python
import asyncio
from datetime import datetime

# Health monitoring for production deployments
health_checks = {
    'basic': await client.health_check(),
    'detailed': await client.get_detailed_health(),
    'ready': await client.get_readiness_status(),
    'live': await client.get_liveness_status()
}

print('Production health status:', health_checks)

# Real-time threat monitoring
async def monitor_threats():
    while True:
        threats = await client.get_security_threats({'timeframe': '5m'})
        if threats:
            print(f"{len(threats)} security threats detected!")
        await asyncio.sleep(30)  # Check every 30 seconds

# Run monitoring in background
asyncio.create_task(monitor_threats())
```

### Compliance Automation

```python
# Automated compliance reporting
compliance_report = await client.generate_compliance_report({
    'framework': 'sox',
    'format': 'json',
    'period': 'monthly',
    'includeViolations': True,
    'includeRemediation': True
})

# Send to compliance team
print(f"Generated SOX report: {compliance_report['reportId']}")
```

### Enterprise Policy Management

```python
# Bulk policy management for enterprise deployments
policies_config = [
    {
        'name': 'GDPR Data Protection',
        'description': 'Ensure GDPR compliance for EU data',
        'policyType': 'rego',
        'policyContent': open('policies/gdpr.rego').read(),
        'enabled': True,
        'priority': 1
    },
    {
        'name': 'HIPAA Healthcare Data',
        'description': 'Protect healthcare information',
        'policyType': 'rego', 
        'policyContent': open('policies/hipaa.rego').read(),
        'enabled': True,
        'priority': 2
    }
]

# Deploy policies
for policy_config in policies_config:
    policy = await client.create_policy(policy_config)
    print(f"Created policy: {policy['id']}")
    
    # Test policy
    test_result = await client.test_policy({
        'policyId': policy['id'],
        'testInput': {'content': 'Test healthcare data: Patient ID 12345'}
    })
    print(f"Policy test result: {test_result['allowed']}")
```

## Development

### Running Tests

```bash
pip install -e ".[dev]"
pytest
```

### Code Formatting

```bash
black .
isort .
```

### Type Checking

```bash
mypy .
```

## Changelog

### v1.1.0 (Latest)
- ✨ Added enterprise organization management
- ✨ Implemented RBAC and user management  
- ✨ Added advanced compliance analytics
- ✨ Comprehensive health checks for Kubernetes
- ✨ Security threat detection and monitoring
- ✨ Policy management and testing capabilities
- ✨ Provider management and configuration
- ✨ Audit logging and compliance reporting
- ✨ Integration management
- ✨ Structured data and PII validation
- 🔧 Updated to support all B2B enterprise features
- 🔧 Enhanced async/sync method coverage

### v1.0.0
- 🎉 Initial release
- ✨ Basic chat completions and embeddings
- ✨ Multi-provider support
- ✨ Content redaction and policy enforcement
- ✨ Streaming support
- ✨ OpenAI-compatible endpoints
- ✨ Async/sync interfaces

## Support

- Documentation: https://docs.doopal.com
- GitHub Issues: https://github.com/doopal-ai/doopal/issues
- Email: info@doopal.com
- Enterprise Support: info@doopal.com
- Customer Success: info@doopal.com

## License

MIT License - see LICENSE file for details.
