Let us learn more on MLflow and RedisAI with the support of our Server management support services at Bobcares.

What is MLflow and RedisAI?

A plugin that connects RedisAI to the MLflow pipeline.

mlflow_redisai allows us to use mlflow to deploy the models developed and trained in the mlflow pipeline into RedisAI with no further user effort.

This plugin provides a few command line APIs, which are also accessible via mlflow’s python package, to help with the deployment process.

Support for MLflow and RedisAI

• Firstly, the community is not very active.
• Secondly, there are 6 outstanding problems and 0 closed issues. Issues are typically resolved in 195 days. There are 1 active and 0 closed pull requests.
• The developer community is divided on the issue.
• Finally, mlflow-redisai’s most recent version is 0.1.0.

When it comes to the quality, there are no issues or code smells in mlflow-redisai.

Security

• There have been no reported vulnerabilities in mlflow-redisai or its dependant libraries.
• The code analysis reveals 0 unsolved vulnerabilities. There are 0 security hotspots that require attention.

License

• The Apache-2.0 License governs the plugin. This is a Permissive license.
• Permissive licenses offer the fewest limitations and may be used in the majority of projects.

Reuse

• Firstly, mlflow-redisai versions are now available for download and installation.
• Secondly, the build file is now accessible. We may create the component from scratch.
• The instructions provide installation guidance, examples, and code snippets.
• There are 250 lines of code, 15 functions, and 4 files in all.
• Finally, it has a medium level of coding complexity. The intricacy of the code has a direct influence on its maintainability.

How to install the Plugin?

We simply need to install this package, which is accessible on pypi and we can install it with the following command line, to install and activate the plugin:

pip install mlflow_redisai

Installing this package registers the plugin in MLflow’s plugin registry using Python’s fantastic entrypoint mechanism.

This registry will be called whenever an MLflow script or command line parameter is executed.

Options for MLflow and RedisAI Plugin

This plugin allows us to connect with RedisAI deployments using MLflow using the parameters listed below.

All of these parameters are available via the command line and the Python API, albeit the predict command line option is currently unreliable.

If we are connecting to a non-local RedisAI instance or if the RedisAI instance requires non-standard connection parameters such as a username or password, see the connection parameters section.

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Conclusion

To sum up we have now seen more on the MLflow and RedisAI and how to set it up with the support of our tech support team.