π CLI Reference
π οΈ CLI Quick Start
Go from zero to a running pipeline in 5 minutes using the FlowyML command line.
β‘ 5 Minutes π± Init βΆοΈ Run π₯οΈ Visualize
Full Reference
This page is a quick-start tutorial. For the complete list of every command, flag, and environment variable, see the CLI Reference.
Step 1 β Install FlowyML
Verify it worked:
Step 2 β Create a Project
This scaffolds everything you need:
my-project/
βββ flowyml.yaml # Stack & resource config
βββ requirements.txt # Python dependencies
βββ src/
βββ pipeline.py # Your first pipeline
Templates
Use --template ml or --template cv for pre-built ML or Computer Vision project structures.
Step 3 β Run Your Pipeline
You should see:
That's it!
Your pipeline ran locally with caching enabled by default. Run it again β cached steps are skipped automatically.
Step 4 β Launch the UI
Open http://localhost:8080 to see the DAG visualization, run history, and artifact inspector.
Stop it when you're done:
Step 5 β Pass Parameters
Override context values from the command line without changing code:
Step 6 β Try a Dry Run
See what would happen without actually executing:
Environment Variables
All FlowyML environment variables use the uppercase FLOWYML_ prefix:
| Variable | Default | Description |
|---|---|---|
FLOWYML_HOME |
~/.flowyml |
FlowyML home directory |
FLOWYML_ENV |
dev |
Environment name (dev, staging, prod) |
FLOWYML_UI_PORT |
8080 |
Default UI port |
FLOWYML_LOG_LEVEL |
INFO |
Logging level |
Handy Aliases
Add to your ~/.zshrc or ~/.bashrc:
π What's Next?
π Full CLI Reference
Every command, flag, and environment variable in one place.