revenium-middleware-anthropic 0.2.23

A Python library that meters Anthropic usage to Revenium.

Revenium Middleware for Anthropic

A middleware library for metering and monitoring Anthropic API usage in Python applications.

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",
         "task_type": "summarize-customer-issue",
         "subscriber": {
             "id": "subscriberid-1234567890",
             "email": "[e-mail]",
             "credential": {
                 "name": "engineering-api-key",
                 "value": "sk-ant-api03-..."
             }
         },
         "organization_id": "acme-corp",
         "subscription_id": "startup-plan-Q1",
         "product_id": "saas-app-gold-tier",
         "agent": "support-agent",
    }
)
print(message.content)

Streaming Support

The middleware also supports Anthropic's streaming API. For streaming responses, use the usage_metadata parameter to provide metadata for analytics. The middleware will automatically track token usage and send metering data when the stream completes.

Example Code

View the examples directory for more code samples for both streaming and non-streaming AI calls.

️ Metadata Fields

The usage_metadata parameter supports the following fields:

Field	Description	Use Case
trace_id	Unique identifier for a conversation or session	Group multi-turn conversations into single event for performance & cost tracking
task_type	Classification of the AI operation by type of work	Track cost & performance by purpose (e.g., classification, summarization)
subscriber	Object containing subscriber information	Track cost & performance by individual users and their credentials
subscriber.id	The id of the subscriber from non-Revenium systems	Track cost & performance by individual users (if customers are anonymous or tracking by emails is not desired)
subscriber.email	The email address of the subscriber	Track cost & performance by individual users (if customer e-mail addresses are known)
subscriber.credential	Object containing credential information	Track cost & performance by API keys and credentials
subscriber.credential.name	An alias for an API key used by one or more users	Track cost & performance by individual API keys
subscriber.credential.value	The key value associated with the subscriber (i.e an API key)	Track cost & performance by API key value (normally used when the only identifier for a user is an API key)
organization_id	Customer or department ID from non-Revenium systems	Track cost & performance by customers or business units
subscription_id	Reference to a billing plan in non-Revenium systems	Track cost & performance by a specific subscription
product_id	Your product or feature making the AI call	Track cost & performance across different products
agent	Identifier for the specific AI agent	Track cost & performance performance by AI agent
response_quality_score	The quality of the AI response (0..1)	Track AI response quality

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 information
• INFO: General information (default)
• WARNING: Warning messages only
• ERROR: Error messages only
• CRITICAL: Critical error messages only

Contributing

See CONTRIBUTING.md

Security

See SECURITY.md

License

This project is licensed under the MIT License - see the LICENSE file for details.

Acknowledgments

• Built by the Revenium team