Service
- Introduction To A Service
- Deploy your first Service
- Interacting With Your Service
- Configuring your service
- Update, Rollback, Promote
- Monitoring Your Service
Job
- Introduction To A Job
- Running your first Job
- Interacting With Your Job
- Monitor Your Job
- Configuring your Job
Workflow
Large Language Models (LLMs)
Workbenches: Notebooks and SSH
Volumes
Async Service
- Introduction to Async Service
- Deploy your first Async Service
- Configure async service
- Queue Integrations
- Monitor Your Async Service
Secret Management
ML Repository
- Introduction To ML Repo
- Experiment Tracking
- Create Tracing Project
Deploying On Your Own Cloud
- Modes Of Deployment
- Deploy Compute Plane
- Deploy Control Plane Only
- Advanced Configuration
- Integrations
- Deploy Truefoundry In An Air Gapped Environment
Experiment Tracking
Add Tags
Tags are labels for a run. A tag is represented by a string tag name and value.
Adding tags programmatically
from truefoundry.ml import get_client
client = get_client()
run = client.create_run(ml_repo="iris-demo", run_name="svm-model")
run.set_tags({"env": "development", "task": "classification"})
run.end()
How can I programmatically fetch the tags for a run?
You can use the get_tags
method. It returns a dictionary.
from truefoundry.ml import get_client
client = get_client()
run = client.get_run("run-id-of-the-run")
print(run.get_tags())
Adding tags with UI
You can view the tags from the dashboard and also create new tags.
Adding tags
Was this page helpful?
Assistant
Responses are generated using AI and may contain mistakes.