Mlflow Demo

MLflow 3 GenAI Demo

A comprehensive demonstration of **MLflow 3's GenAI capabilities** for observability and evaluating, monitoring, and improving GenAI application quality. This interactive demo showcases a sales email generation use case with end-to-end quality assessment workflows.

This interactive demo is deployed as a Databricks app in your Databricks workspace. There is a guided UI experience that's accompanied by Notebooks that show you how to do the end-to-end workflow of evaluating quality, iterating to improve quality, and monitoring quality in production.

**Learn more about MLflow 3:**

• Read the blog post
• View our website
• Get started via the documentation

Installing the demo

Choose your installation method:

🤖 Option A: Automated Setup (Recommended)

**Estimated time: 2 minutes user input + 15 minutes waiting for scripts to run**

The automated setup handles resource creation, configuration, and deployment for you using the Databricks Workspace SDK.

Prerequisites

• Databricks workspace access - Create one here if needed
• Install Python >=3.10.16

Run Automated Setup

The `./auto-setup.sh` script will run all the steps outlined in the [Manual Setup](#-option-b-manual-setup) workflow.

• 1. Install the Databricks CLI >= 0.262.0
  • Follow the installation guide
  • Verify installation: Run databricks --version to confirm it's installed
• 2. Install Python >= 3.10.16
• **3. A