Mona-openAI provides an easy and effective way for users to stay connected with the OpenAI usage with just one line of code. It is a great solution for its users to get instant tracking of their activities, whether making synchronous or asynchronous calls. An example usage in the form of coding boilerplate is provided in the ‘example_usage.py’ file. After making use of the ‘example_usage.py’, the help of Mona’s client is provided which will logs out the user information, parameters used, response from OpenAI server and custom analyses about the call.
The main function exposed in this package is ‘create’, which returns a class that wraps the originally used OpenAI endpoint class. Apart from OpenAI-based apps, this package supports a variety of other apps and processes. To configure the monitoring of details, the function requires a python dictionary in the argument including required keys. The package uses Mona SDK to export the data and therefore, can be customized with environment variables.
When Mona is used for logging purposes, it supports a more direct approach for logging, called the ‘get_rest_monitor’ function, which is quite simple and efficient. Moreover, it adds specific arguments like ‘create’ call to enable the monitoring of user’s activities.
Mona Labs is a company based in California that specializes in providing businesses with monitoring capability and helps them maintain high performance of their systems. Founder Alex Robinson and scientist Corey Beard have lead the team to become one of the leading companies in the industry. With years of experience in designing and developing monitoring and debugging solutions, Mona Labs is constantly evaluating and enhancing their services to offer the best product to customers. In the field of OpenAI usage monitoring, Mona-OpenAI is the most efficient product developed by the company. It is trusted by many users for its solid performance and useful features.
