A Python library that meters Anthropic usage to Revenium.
Project description
🤖 Revenium Middleware for Anthropic
A middleware library for metering and monitoring Anthropic API usage in Python applications. 🐍✨
✨ Features
- 📊 Precise Usage Tracking: Monitor tokens, costs, and request counts across all Anthropic API endpoints
- 🔌 Seamless Integration: Drop-in middleware that works with minimal code changes
- ⚙️ Flexible Configuration: Customize metering behavior to suit your application needs
📥 Installation
pip install revenium-middleware-anthropic
🔧 Usage
🔄 Zero-Config Integration
Simply export your REVENIUM_METERING_API_KEY and import the middleware. Your Anthropic calls will be metered automatically:
import anthropic
import revenium_middleware_anthropic
client = anthropic.Anthropic()
message = client.messages.create(
model="claude-3-7-sonnet-20250219",
max_tokens=20000,
temperature=1,
messages=[
{
"role": "user",
"content": [
{
"type": "text",
"text": "What is the meaning of life, the universe and everything?",
}
]
}
]
)
print(message.content)
The middleware automatically intercepts Anthropic API calls and sends metering data to Revenium without requiring any
changes to your existing code. Make sure to set the REVENIUM_METERING_API_KEY environment variable for authentication
with the Revenium service.
📈 Enhanced Tracking with Metadata
For more granular usage tracking and detailed reporting, add the usage_metadata parameter:
import anthropic
import revenium_middleware_anthropic
client = anthropic.Anthropic()
message = client.messages.create(
model="claude-3-7-sonnet-20250219",
max_tokens=20000,
temperature=1,
messages=[
{
"role": "user",
"content": [
{
"type": "text",
"text": "What is the meaning of life, the universe and everything?",
}
]
}
],
usage_metadata={
"trace_id": "conv-28a7e9d4-1c3b-4e5f-8a9b-7d1e3f2c1b4a",
"task_id": "chat-summary-af23c910",
"task_type": "text-classification",
"subscriber_identity": "customer-email@example.com",
"organization_id": "acme-corporation-12345",
"subscription_id": "startup-plan-quarterly-2025-Q1",
"product_id": "intelligent-document-processor-v3",
"source_id": "mobile-app-ios-v4.2",
"ai_provider_key_name": "anthropic-production-key1",
"agent": "customer-support-assistant-v2",
}
)
print(message.content)
🏷️ Metadata Fields
The usage_metadata parameter supports the following fields:
| Field | Description | Use Case |
|---|---|---|
trace_id |
Unique identifier for a conversation or session | Track multi-turn conversations |
task_id |
Identifier for a specific AI task | Group related API calls for a single task |
task_type |
Classification of the AI operation | Categorize usage by purpose (e.g., classification, summarization) |
subscriber_identity |
End-user identifier | Track usage by individual users |
organization_id |
Customer or department identifier | Allocate costs to business units |
subscription_id |
Reference to a billing plan | Associate usage with specific subscriptions |
product_id |
The product or feature using AI | Track usage across different products |
source_id |
Origin of the request | Monitor usage by platform or app version |
ai_provider_key_name |
Identifier for the API key used | Track usage by different API keys |
agent |
Identifier for the specific AI agent | Compare performance across different AI agents |
All metadata fields are optional. Adding them enables more detailed reporting and analytics in Revenium.
🔄 Compatibility
- 🐍 Python 3.8+
- 🤖 Anthropic Python SDK
🔍 Logging
This module uses Python's standard logging system. You can control the log level by setting the REVENIUM_LOG_LEVEL environment variable:
# Enable debug logging
export REVENIUM_LOG_LEVEL=DEBUG
# Or when running your script
REVENIUM_LOG_LEVEL=DEBUG python your_script.py
Available log levels:
DEBUG: Detailed debugging informationINFO: General information (default)WARNING: Warning messages onlyERROR: Error messages onlyCRITICAL: Critical error messages only
📚 Documentation
Full documentation is available at https://revenium-middleware-anthropic.readthedocs.io/
👥 Contributing
Contributions are welcome! Please check out our contributing guidelines for details.
- 🍴 Fork the repository
- 🌿 Create your feature branch (
git checkout -b feature/amazing-feature) - 💾 Commit your changes (
git commit -m 'Add some amazing feature') - 🚀 Push to the branch (
git push origin feature/amazing-feature) - 🔍 Open a Pull Request
📄 License
This project is licensed under the Apache Software License - see the LICENSE file for details.
🙏 Acknowledgments
- 🔥 Thanks to the Anthropic team for creating an excellent API
- 💖 Built with ❤️ by the Revenium team
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