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Choreo setup

Before running the Fine-Tune Pipeline, you need to ensure the MLFlow server running in Choreo as well as the MLFLow database is running in choreo.

MLFlow database setup

Already have a database running?

If you already have a database running in Choreo, you can skip this step.

1. Deploy the database in Choreo

  • Go to Choreo
  • Go to your organization
  • Go to Resources > Databases
  • Create a new database
  • Choose PostgreSQL as the database type
  • Deploy the database

2. Power on the database

  • Go to the database you just created
  • Click on Power On Servicec to start the database
  • Copy the configuration details (host, port, username, password, database name)

MLFlow server setup

1. Deploy the server in Choreo

Already have a server running?

If you already have an MLFlow server running in Choreo, you can skip this step.

  • Go to Choreo
  • Create a project under your organization
  • Deploy the MLFlow server within the project as a web application component
  • Use this GitHub repository as the source: MLFlow Server

2. Configure the MLFlow server

  • Go to the MLFlow server component
  • Go to DevOps > Configs & Secrets
  • Create a new configuration with the details you found in the MLflow database setup:
    DATABASE = "your-database-name"
    USER = "your-database-username"
    PASSWORD = "your-database-password"
    HOST = "your-database-host"
    PORT = "your-database-port"

3. Add storage mounts

  • Go to DevOps > Storage
  • Create a new storage mount with in-memory type
  • Add mount path as mlruns

4. Configure container entrypoint

  • Go to DevOps > Containers
  • Set the command to ["mlflow", "run"]
  • Set the arguments to ["--backend-store-uri", "postgresql+psycopg2://$(USER):$(PASSWORD)@$(HOST):$(PORT)/$(DATABASE)", "--host", "0.0.0.0", "--port", "5000"]

5. Start the MLFlow server

  • Go to Build and build the latest
  • Go to 'Deploy' and deploy the latest build
  • Go to the web app url in the Deploy tab and ensure the server is running.

🚀 Great. Now you can move into fine tuning.

Next Steps

With your environment set up, you're ready to:

  1. Run your first fine-tuning job
  2. Explore configuration options
  3. Learn about advanced features