MLflow OpenAI Flavor - Tutorials and Guides
Below, you will find a number of guides that focus on different ways that you can leverage the power of the openai library, leveraging MLflow's APIs for tracking and inference capabilities.
The diagram below shows the basic scope of the level of complexity that the tutorials cover.
Introductory Tutorial​
Advanced Tutorials​
In these tutorials, the topics cover applied interactions with OpenAI models, leveraging custom Python Models to enhance the functionality beyond what is possible with the basic prompt-based interaction from the introductory tutorial. If you're new to this flavor, please start with the Introductory Tutorial above, as it has information about environment configurations that you'll need to understand in order to get the notebooks in this section to work.
Learn how to leverage the ChatCompletions endpoint in the OpenAI flavor to create a useful text messaging screening tool within MLflow.
Learn how to leverage Custom Python Models with a useful Code Helper application that leverages OpenAI Models and MLflow.
Explore the application of embeddings with document comparison using an OpenAI model with MLflow.