All 202 Dependencies
Every package MLflow depends on, ranked by repo health score.
MLflow is the largest open source AI engineering platform for agents, LLMs, and machine learning models. It 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 and support for 60+ frameworks, MLflow is trusted by organizations worldwide to ship AI to production with confidence.
Built on OpenTelemetry and designed for extensibility, MLflow supports Python, TypeScript, Java, and R. It provides a unified server, REST API, and web UI that integrates natively with LangChain, LangGraph, OpenAI Agents, DSPy, PydanticAI, CrewAI, LlamaIndex, AutoGen, Google ADK, Strands, and Apache Spark.
MLflow 3.x introduced a major pivot toward GenAI workflows: an integrated AI Gateway for multi-provider LLM routing, a prompt registry with versioning and Jinja2 templates, automated prompt optimization, LLM judge evaluation with the MemAlign optimizer, multi-turn conversation simulation for agent testing, distributed tracing across services, and built-in cost tracking across providers. Classical ML workflows — experiment tracking, model registry, deployment — remain fully supported alongside the new GenAI capabilities.
Deployment options include local servers, Docker, Kubernetes, and managed cloud platforms like AWS SageMaker and Azure ML, with a Databricks-managed option for enterprise teams who want fully managed infrastructure.