revenium-middleware-openai 0.2.9

A Python library that meters OpenAI usage to Revenium.

🤖 Revenium Middleware for OpenAI

A middleware library for metering and monitoring OpenAI API usage in Python applications. 🐍✨

✨ Features

• 📊 Precise Usage Tracking: Monitor tokens, costs, and request counts across all OpenAI 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-openai

🔧 Usage

🔄 Zero-Config Integration

Simply export your REVENIUM_METERING_API_KEY and import the middleware. Your OpenAI calls will be metered automatically:

import openai
import revenium_middleware_openai

# Ensure REVENIUM_METERING_API_KEY environment variable is set

response = openai.chat.completions.create(
    model="gpt-4",  
    messages=[
        {"role": "system", "content": "You are a helpful assistant."},
        {
            "role": "user",
            "content": "What is the answer to life, the universe and everything?",
        },
    ],
    max_tokens=500,
)

print(response.choices[0].message.content)

The middleware automatically intercepts OpenAI 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 openai
import revenium_middleware_openai

response = openai.chat.completions.create(
    model="gpt-4",  # You can change this to other models like "gpt-3.5-turbo"
    messages=[
        {"role": "system", "content": "You are a helpful assistant."},
        {
            "role": "user",
            "content": "What is the meaning of life, the universe and everything?",
        },
    ],
    max_tokens=500,
    usage_metadata={
        "trace_id": "conv-28a7e9d4-1c3b-4e5f-8a9b-7d1e3f2c1b4a",
        "task_id": "chat-summary-af23c910",
        "task_type": "text-classification",
        "subscriber_identity": "[e-mail]",
        "organization_id": "acme-corporation-12345",
        "subscription_id": "startup-plan-quarterly-2025-Q1",
        "product_id": "intelligent-document-processor-v3",
        "ai_provider_key_name": "openai-production-key1",
        "agent": "customer-support-assistant-v2",
    },
)
print(response.choices[0].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_email	The email address of the subscriber	Track usage by individual users
subscriber_credential	The credential associated with the subscriber	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
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+
• 🤖 OpenAI Python SDK 1.0.0+
• 🌐 Works with all OpenAI models and endpoints

🔍 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

📚 Documentation

Full documentation is available at https://revenium-middleware-openai.readthedocs.io/

👥 Contributing

Contributions are welcome! Please check out our contributing guidelines for details.

1. 🍴 Fork the repository
2. 🌿 Create your feature branch (git checkout -b feature/amazing-feature)
3. 💾 Commit your changes (git commit -m 'Add some amazing feature')
4. 🚀 Push to the branch (git push origin feature/amazing-feature)
5. 🔍 Open a Pull Request

📄 License

This project is licensed under the Apache License 2.0 - see the LICENSE file for details.

🙏 Acknowledgments

• 🔥 Thanks to the OpenAI team for creating an excellent API
• 💖 Built with ❤️ by the Revenium team