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: