MLflow
Open-source platform for the machine learning and GenAI lifecycle, including tracing of LLM and agent calls.
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About MLflow
MLflow is an open-source platform for managing the machine learning and AI application lifecycle. It helps developers debug, evaluate, monitor, and optimize AI applications built with large language models, agents, and machine learning models. The platform provides observability through production-grade tracing compatible with any LLM provider and agent framework, systematic evaluation capabilities with built-in metrics and custom options, and prompt management with versioning and optimization features.
MLflow also includes an AI Gateway that offers a unified API for multiple LLM providers, along with experiment tracking and model registry functionality for the full machine learning workflow. The platform is developed by mlflow and distributed under the Apache 2.0 license. It is written in Python and designed to serve teams of all sizes working on AI engineering projects.
Checked 19 October 2026.
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- Run your own LLM proxy to track token usage: LiteLLM in front of Claude Code and Codex
A local LiteLLM proxy logs one row per agent request with tokens, cost, key and session. Setup in about 15 minutes, tested on LiteLLM 1.106.0, October 2026.