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MLflow

Open source AI engineering platform for agents, LLMs, and ML models. Debug, evaluate, monitor, and optimize production-quality AI applications.

★ 27,068 GitHub Apache-2.0 mlflowllmevaluationmonitoringagentsai-engineeringmlopstracingmodel-registry LLM & Chat

Overview

MLflow is the open source AI engineering platform designed for teams building with agents, LLMs, and ML models. It provides a comprehensive suite of tools for debugging complex agent workflows, evaluating model performance across multiple providers including OpenAI, Anthropic, Google, and open-source models like Llama and DeepSeek, monitoring production deployments with tracing and drift detection, and optimizing prompts through systematic experimentation. With over 27,000 GitHub stars, MLflow supports the full AI development lifecycle from experimentation to production. Key features include AI Gateway for unified API access, Prompt Engineering Studio for iterative prompt development, Tracing for end-to-end workflow visualization, Model Registry for version management, and Evaluation framework for comparing models and prompts across metrics. MLflow integrates with popular frameworks like LangChain, LlamaIndex, and OpenAI Agents SDK, making it the standard platform for teams serious about AI quality and reliability.

Requirements

Min vCPU
2
Min RAM
4096 MB
Min Disk
10 GB
Rec vCPU
4
Rec RAM
8192 MB
Rec Disk
20 GB

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Affiliate disclosure

Docker Compose

# Generated by Run This Ai — docker-compose.yml
services:
  mlflow:
    image: burakince/mlflow:latest
    restart: unless-stopped
    ports:
      - 8080:8080
    volumes:
      - ./data/mlflow:/data

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Guides & articles

Getting Started with MLflow: Debug, Trace, and Evaluate Your AI Applications

Step-by-step tutorial for setting up MLflow with Docker, enabling tracing for OpenAI calls, evaluating models side-by-side, and using the AI Gateway. Real examples.

Jul 17, 2026

MLflow: Open-Source AI Engineering Platform for LLMs and Agents

Explore MLflow, the open-source AI engineering platform for debugging, evaluating, monitoring, and optimizing LLMs and AI agents. 27K GitHub stars, Apache-2.0.

Jul 17, 2026