Add MLflow to LLM Applications section

Signed-off-by: B-Step62 <yuki.watanabe@databricks.com>

README.md

@@ -331,6 +331,7 @@ If you're interested in the field of LLM, you may find the above list of milesto
 ## LLM Applications
 - [AdalFlow](https://github.com/SylphAI-Inc/AdalFlow) - AdalFlow: The library to build&auto-optimize LLM applications.
 - [dspy](https://github.com/stanfordnlp/dspy) - DSPy: The framework for programming—not prompting—foundation models.
+- [MLflow](https://mlflow.org/) - MLflow: An open-source framework for the end-to-end machine learning lifecycle, helping developers track experiments, evaluate models/prompts, deploy models, and add observability with tracing.
 - [YiVal](https://github.com/YiVal/YiVal) — Evaluate and Evolve: YiVal is an open-source GenAI-Ops tool for tuning and evaluating prompts, configurations, and model parameters using customizable datasets, evaluation methods, and improvement strategies.
 - [Guidance](https://github.com/microsoft/guidance) — A handy looking Python library from Microsoft that uses Handlebars templating to interleave generation, prompting, and logical control.
 - [LangChain](https://github.com/hwchase17/langchain) — A popular Python/JavaScript library for chaining sequences of language model prompts.