Get Ml Repo
Get a ml repo by id Args: id: Unique identifier of the ml repo to get user_info: Authenticated user information
Returns: GetMLRepoResponse: The ml repo
curl --request GET \
--url https://{controlPlaneURL}/api/ml/v1/ml-repos/{id} \
--header 'Authorization: Bearer <token>'{
"data": {
"tenant_name": "truefoundry",
"manifest": {
"name": "devtest-finetuning-test-420",
"type": "ml-repo",
"description": "This is a test MLRepo for fine-tuning experiments.",
"collaborators": [
{
"role_id": "mlf-project-admin",
"subject": "user:user1@example.com"
},
{
"role_id": "mlf-project-admin",
"subject": "team:teamb"
}
],
"storage_integration_fqn": "truefoundry:aws:aws-4:blob-storage:devtest-test-1"
},
"created_by_subject": {
"subjectId": "cm1xxxp",
"subjectSlug": "test-user@truefoundry.com",
"subjectType": "user",
"subjectDisplayName": "Test User"
},
"created_at": "2023-11-07T05:31:56Z",
"id": "420",
"num_runs": 10,
"artifact_type_counts": {},
"datasets_count": 10
}
}Authorizations
Bearer authentication header of the form Bearer <token>, where <token> is your auth token.
Path Parameters
Response
ML Repo
Tenant Name
"truefoundry"
+label=MLRepo +usage=MLRepo is a repository ML training runs that log params, metrics, plots, images and versioned entities like artifacts, models, prompts, tools, agents
+value=ml-repo
ml-repo +label=Name +icon=fa-desktop:#black +usage=Name of the ML Repo. +message=Alphanumeric word, may contain '-' with a maximum length of 100 characters +sort=1
+label=Storage Integration +icon=hard-drive +usage=Storage Integration to store artifacts and models. A storage integration represents a connected blob storage like AWS S3 / Azure Blob Storage / Google Cloud Storage. +message=Select the storage-integration where you want to save your artifacts and models View Docs +sort=4
+label=Collaborators +sort=5 +usage=Users and Teams that have access to MLRepo +uiType=Collaborators
+label=Description +icon=fa-desktop:#black +usage=Description for the ML Repo. +message=Description can be maximum 500 characters +sort=2 +placeholder=MLRepo to track text-classification experiments and models +uiProps={"descriptionInline":true}
{
"name": "devtest-finetuning-test-420",
"type": "ml-repo",
"description": "This is a test MLRepo for fine-tuning experiments.",
"collaborators": [
{
"role_id": "mlf-project-admin",
"subject": "user:user1@example.com"
},
{
"role_id": "mlf-project-admin",
"subject": "team:teamb"
}
],
"storage_integration_fqn": "truefoundry:aws:aws-4:blob-storage:devtest-test-1"
}
Subject ID
Subject type
user, team, serviceaccount Subject slug
Subject display name
{
"subjectId": "cm1xxxp",
"subjectSlug": "test-user@truefoundry.com",
"subjectType": "user",
"subjectDisplayName": "Test User"
}
Created At
Experiment Id
"420"
Number of runs
10
Number of datasets
10
curl --request GET \
--url https://{controlPlaneURL}/api/ml/v1/ml-repos/{id} \
--header 'Authorization: Bearer <token>'{
"data": {
"tenant_name": "truefoundry",
"manifest": {
"name": "devtest-finetuning-test-420",
"type": "ml-repo",
"description": "This is a test MLRepo for fine-tuning experiments.",
"collaborators": [
{
"role_id": "mlf-project-admin",
"subject": "user:user1@example.com"
},
{
"role_id": "mlf-project-admin",
"subject": "team:teamb"
}
],
"storage_integration_fqn": "truefoundry:aws:aws-4:blob-storage:devtest-test-1"
},
"created_by_subject": {
"subjectId": "cm1xxxp",
"subjectSlug": "test-user@truefoundry.com",
"subjectType": "user",
"subjectDisplayName": "Test User"
},
"created_at": "2023-11-07T05:31:56Z",
"id": "420",
"num_runs": 10,
"artifact_type_counts": {},
"datasets_count": 10
}
}