mlflow

MLflow is an open source platform for the complete machine learning lifecycle

mlflow Permissive license Copyright 2018 Databricks, Inc. All rights reserved. Apache License Version 2.0, January 2004 http://www.apache.org/licenses/ TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION 1.… (full text in the JSON record) Active ★ 27,502 v3.15.1 released 2026-08-03

Install

mlflow on PyPI

pip

pip install mlflow

uv

uv add mlflow

poetry

poetry add mlflow

Package facts

License	Copyright 2018 Databricks, Inc. All rights reserved. Apache License Version 2.0, January 2004 http://www.apache.org/licenses/ TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION 1.… (full text in the JSON record) (permissive)
Python support	supports the current Python release (>=3.10)
Install friction	low — pure-Python wheel
Runtime dependencies	20 — mlflow-skinny, mlflow-tracing, Flask-CORS, Flask, aiohttp, alembic, cryptography, docker, graphene, gunicorn, huey, matplotlib, numpy, pandas, pyarrow, scikit-learn, scipy, skops, sqlalchemy, waitress
Maintenance	actively maintained — 10 days since the last release
Last repo commit	2026-08-13
First released	2018-06-04
Popularity	one of the top 1,000 most-downloaded packages on PyPI (30-day window, as of 2026-08-13)
Known vulnerabilities	none known (OSV.dev, checked 2026-08-13)

Evidence: mlflow-3.15.1-py3-none-any.whl

Keywords: mlflow, ai, databricks

Development Status :: 5 - Production/StableIntended Audience :: DevelopersIntended Audience :: End Users/DesktopIntended Audience :: Information TechnologyIntended Audience :: Science/ResearchLicense :: OSI Approved :: Apache Software LicenseOperating System :: OS IndependentProgramming Language :: Python :: 3.10Topic :: Scientific/Engineering :: Artificial IntelligenceTopic :: Software Development :: Libraries :: Python Modules

About mlflow

from the package's own PyPI description — quoted content, verbatim

<h1 align="center" style="border-bottom: none"> <a href="https://mlflow.org/"> <img alt="MLflow logo" src="https://raw.githubusercontent.com/mlflow/mlflow/refs/heads/master/assets/logo.svg" width="200" /> </a> </h1> <h2 align="center" style="border-bottom: none">The Open Source AI Engineering Platform for Agents, LLMs & Models</h2>

MLflow is the largest 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. With over 60 million monthly downloads, thousands of organizations rely on MLflow each day to ship AI to production with confidence.

MLflow's comprehensive feature set for agents and LLM applications includes production-grade observability, evaluation, [prompt...

Read as markdown · JSON record · Source repository · Docs

AI interpretation — verify before relying

AI-generated interpretation of the package facts above; every digit, version, license, or vulnerability id it cites is grounded in the facts already shown on this page

MLflow is an open-source AI engineering platform for building, debugging, evaluating, and deploying LLM applications, AI agents, and ML models with integrated observability, evaluation, prompt management, and model tracking.

Low friction install with a pure-Python wheel. Active maintenance (latest release 2026-08-03, 10 days old) and strong community signal (27502 GitHub stars). Requires Python 3.10+. The 20 runtime dependencies span data science (numpy, pandas, scikit-learn), web frameworks (Flask, aiohttp), and infrastructure (Docker, SQLAlchemy), reflecting a comprehensive ML platform.

Apache License 2.0 (permissive) allows commercial use, modification, and redistribution with minimal restrictions. You must include a copy of the license and note any changes made, but there are no copyleft obligations.

Usage

pip install mlflow

import mlflow
mlflow.set_tracking_uri("http://localhost:5000")
mlflow.openai.autolog()

Requires Python 3.10 or later. MLflow server typically runs on localhost:5000; ensure the port is available or configure an alternative tracking URI.

Verdict: MLflow is a mature, actively maintained platform (Production/Stable status, 27502 stars, zero known vulnerabilities) with low install friction and permissive licensing. Its 20 runtime dependencies reflect a full-featured ML/AI stack. Ideal for teams shipping LLM applications and ML models to production with comprehensive observability, evaluation, and governance built in.

Needs verification

Whether the full 20-dependency install is required for basic use cases or if lighter entry points are recommended for specific workflows.
Performance and resource overhead of the MLflow server in production environments at scale.
Specific capabilities and integrations mentioned in the description excerpt beyond what the fact sheet confirms.

llm observability and tracingml experiment tracking and model registryai agent evaluation and monitoringprompt management and optimizationmodel deployment and lifecycle managementproduction ai application debuggingmlops platformai gateway and cost control