aigc-compliance 1.0.2

Official Python SDK for AIGC Compliance API - AI content detection and watermarking

AIGC Compliance Python SDK

Official Python SDK for AIGC Compliance API - AI content detection and watermarking with EU GDPR and China Cybersecurity Law compliance.

🌟 Professional SDK | ⚡ High Performance | 🛡️ Enterprise Ready | 🌍 Global Compliance

🚀 Quick Start

Installation

pip install aigc-compliance

Basic Usage

from aigc_compliance import ComplianceClient

# Initialize client
client = ComplianceClient(api_key="your_api_key_here")

# Process image for AI detection and compliance
result = client.comply(
    file_path="image.jpg", 
    region="EU",
    watermark_position="bottom-right",
    include_base64=True
)

print(f"Compliant: {result['compliant']}")
print(f"AI Probability: {result['ai_probability']}")
print(f"Processing Time: {result['processing_time']}ms")

🌍 Compliance Regions

EU GDPR Compliance

result = client.comply(
    file_path="image.jpg",
    region="EU",
    watermark_position="bottom-right"
)
# Returns compliance result with EU GDPR metadata

China Cybersecurity Law Compliance

result = client.comply(
    file_path="image.jpg", 
    region="CN",
    watermark_position="top-left",
    logo_file="custom_logo.png",
    save_to_disk=True
)
# Returns compliance result with China Cybersecurity Law compliance

📖 Features

✅ Core Features (All Plans)

• AI Content Detection: Advanced ML models for AI-generated content identification
• Watermarking: Automatic watermark application with custom text and logos
• Multi-Region Compliance: EU GDPR and China Cybersecurity Law support
• Rate Limiting: Built-in rate limit handling with exponential backoff
• Error Handling: Comprehensive error types with detailed messages

🚀 Pro Features

• Custom Watermarks: Personalized watermark text and positioning
• Metadata Levels: Basic and detailed compliance metadata
• Legacy Support: /v1/tag endpoint for URL-based processing

🏢 Enterprise Features

• Batch Processing: Process up to 100 images in a single request
• Webhooks: Real-time notifications for completed processing
• Advanced Analytics: Detailed usage statistics and insights
• Custom Metadata: Attach additional metadata to processing requests

📚 API Reference

ComplianceClient

Constructor

ComplianceClient(
    api_key: str,
    base_url: Optional[str] = None,
    timeout: float = 30,
    max_retries: int = 3,
    user_agent: Optional[str] = None
)

Core Methods

comply()

Process image for AI detection and compliance watermarking.

def comply(
    file_path: str,
    region: str = "EU",
    watermark_position: str = "bottom-right",
    logo_file: Optional[str] = None,
    include_base64: bool = True,
    save_to_disk: bool = False,
    output_path: Optional[str] = None
) -> ComplianceResponse

Parameters:

• image: Image file (file object, bytes, or file path)
• region: Compliance region ("eu" for GDPR, "cn" for China)
• watermark_text: Custom watermark text
• watermark_logo: Whether to apply logo watermark
• metadata_level: Level of compliance metadata
• custom_metadata: Additional metadata (Enterprise only)

Returns:

{
    "is_ai_generated": bool,
    "confidence": float,
    "watermark_applied": bool,
    "processing_time_ms": int,
    "quota_remaining": int,
    "compliance_metadata": {
        "ai_generated_probability": float,
        "content_type": str,
        "processing_timestamp": str,
        "gdpr_compliant": bool,  # EU region
        # For China region (detailed):
        "cybersecurity_law_compliance": bool,
        "watermark_info": {...},
        "content_labeling": {...}
    }
}

tag() (Legacy)

Process image from URL (Pro/Enterprise only).

def tag(
    image_url: str,
    region: Literal["eu", "cn"] = "eu",
    watermark_text: Optional[str] = None,
    watermark_logo: bool = True,
    metadata_level: Literal["basic", "detailed"] = "basic",
) -> ComplianceResponse

batch_process() (Enterprise)

Process multiple images in batch.

def batch_process(
    items: List[BatchItem],
    region: Literal["eu", "cn"] = "eu",
    watermark_logo: bool = True,
    metadata_level: Literal["basic", "detailed"] = "basic",
) -> BatchResponse

Example:

items = [
    {"id": "img1", "image": image1_bytes, "custom_metadata": {"source": "upload"}},
    {"id": "img2", "image": image2_bytes, "custom_metadata": {"source": "api"}},
]
result = client.batch_process(items, region="eu")

get_analytics() (Enterprise)

Get usage analytics and insights.

def get_analytics(
    period: Optional[str] = None,
    start_date: Optional[str] = None,
    end_date: Optional[str] = None,
) -> AnalyticsResponse

Webhook Management (Enterprise)

# Register webhook
webhook = client.register_webhook(
    url="https://your-app.com/webhooks/compliance",
    events=["compliance.completed", "batch.finished"],
    secret="your_webhook_secret"
)

# List webhooks
webhooks = client.list_webhooks()

# Delete webhook
client.delete_webhook(webhook_id="webhook_123")

🔧 Advanced Usage

Context Manager

with ComplianceClient(api_key="your_key") as client:
    result = client.comply(image, region="eu")
    # Client automatically closed

Error Handling

from aigc_compliance import (
    ComplianceClient,
    ComplianceAuthenticationError,
    ComplianceQuotaExceededError,
    ComplianceRateLimitError,
)

try:
    result = client.comply(image)
except ComplianceAuthenticationError:
    print("Invalid API key")
except ComplianceQuotaExceededError as e:
    print(f"Quota exceeded: {e.quota_used}/{e.quota_limit}")
except ComplianceRateLimitError as e:
    print(f"Rate limited. Retry after {e.retry_after}s")

Custom Configuration

client = ComplianceClient(
    api_key="your_key",
    base_url="https://custom-api.example.com",
    timeout=60,
    max_retries=5,
    user_agent="MyApp/1.0"
)

📊 Response Examples

Basic EU Response

{
  "is_ai_generated": true,
  "confidence": 0.95,
  "watermark_applied": true,
  "processing_time_ms": 1250,
  "quota_remaining": 245,
  "compliance_metadata": {
    "ai_generated_probability": 0.95,
    "content_type": "image/jpeg",
    "processing_timestamp": "2024-01-15T10:30:45Z",
    "gdpr_compliant": true
  }
}

Detailed China Response

{
  "is_ai_generated": true,
  "confidence": 0.97,
  "watermark_applied": true,
  "processing_time_ms": 1450,
  "quota_remaining": 244,
  "compliance_metadata": {
    "ai_generated_probability": 0.97,
    "content_type": "image/jpeg",
    "processing_timestamp": "2024-01-15T10:30:45Z",
    "cybersecurity_law_compliance": true,
    "watermark_info": {
      "text": "AI生成内容",
      "logo_applied": true,
      "position": "bottom-right",
      "transparency": 0.7
    },
    "content_labeling": {
      "category": "ai_generated",
      "compliance_level": "full",
      "regulatory_notes": "符合网络安全法要求"
    }
  }
}

🔐 Authentication

1. Get API Key: Sign up at AIGC Compliance Dashboard
2. Set API Key:

   # Method 1: Direct initialization
   client = ComplianceClient(api_key="sk_live_...")
   
   # Method 2: Environment variable
   import os
   client = ComplianceClient(api_key=os.getenv("AIGC_API_KEY"))
   

📈 Plans & Quotas

Plan	Monthly Quota	Features
Free	10 requests	Basic detection, EU watermarks
Starter	100 requests	Custom watermarks, both regions
Pro	1,000 requests	Legacy endpoints, detailed metadata
Enterprise	10,000+ requests	Batch processing, webhooks, analytics

🛠️ Development

Requirements

• Python 3.7+
• requests >= 2.25.0

Optional Dependencies

# Development tools
pip install aigc-compliance[dev]

Testing

import pytest
from aigc_compliance import ComplianceClient

def test_compliance_detection():
    client = ComplianceClient(api_key="test_key")
    # Add your test image
    with open("test_image.jpg", "rb") as f:
        result = client.comply(f)
    assert "is_ai_generated" in result

🔗 Links

• Dashboard: https://www.aigc-compliance.com/dashboard
• Documentation: https://www.aigc-compliance.com/docs
• API Status: https://status.aigc-compliance.com
• Support: [e-mail]

📄 License

MIT License - see LICENSE file for details.

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Need help? Check our comprehensive documentation or contact [e-mail].