The open source AI engineering platform for agents, LLMs, and ML models.
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MLflow maintains a significant public presence on GitHub, emphasizing its role as an open source AI engineering platform. The organization features a wide range of repositories primarily written in Python, TypeScript, Go, HTML, and Rust. Notable projects include the core mlflow repository, mlflow-example, and mlflow-export-import, which cater to various aspects of AI model management.
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Public repositories
mlflow
The open source AI engineering platform for agents, LLMs, and ML models. MLflow enables teams of all sizes to debug, evaluate, monitor, and optimize production-quality AI applications while controlling costs and managing access to models and data.
mlflow-example
An example MLflow project
mlflow-export-import
No description provided for this repository.
mlflow-torchserve
Plugin for deploying MLflow models to TorchServe
mlflow-apps
MLflow App Library
mlp-regression-template
Example repo to kickstart integration with mlflow pipelines.
mlflow-go-backend
Repository for the Go-based MLflow Tracking Server
recipes-regression-template
Template repo for kickstarting recipes for regression use case
skills
No description provided for this repository.
recipes-examples
Example repo to kickstart integration with mlflow recipes.
recipes-classification-template
Template repo for kickstarting recipes for classification use case
mlflow-website
No description provided for this repository.
mlp-regression-example
No description provided for this repository.
mlflow-typescript-examples
Examples on how to build full-stack Node.js applications with MLflow Tracing SDK.
rfcs
A repository to store RFCs (design doc, decision log, etc) for MLflow development
mlflow-n8n-nodes
n8n.io node for MLflow
dev
A fork of the mlflow/mlflow repository for testing automation jobs
mlflow-legacy-website
No description provided for this repository.
uv
An extremely fast Python package and project manager, written in Rust.
mlflow-repo-status
No description provided for this repository.
Frequently asked questions
What does mlflow build on GitHub?
MLflow builds a variety of tools and libraries on GitHub, focusing on AI engineering for agents, LLMs, and ML models. Key repositories include mlflow, mlflow-example, and mlflow-torchserve, which facilitate different facets of AI model tracking and deployment.
Which programming languages does mlflow use?
MLflow predominantly utilizes Python for its core projects, along with TypeScript, Go, HTML, and Rust for specific functionalities. This diverse language usage allows the organization to develop robust tools for AI model management.
Are mlflow's repositories public?
Yes, all of mlflow's repositories are public on GitHub. This openness allows developers and researchers to access, contribute to, and utilize a wide range of tools focused on AI engineering and model management.
Is this exposure intended?
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