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​
Methods

Creates or updates an MLRepo entity based on the provided manifest.

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Parameters

​
manifest
MlRepoManifest
required
🔗 MlRepoManifestMLRepo manifest
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dry_run
typing.Optional[bool]
Validate the manifest and collaborators without persisting changes or updating artifact location in the database

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Returns

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GetMlRepoResponse
GetMlRepoResponse
🔗 GetMlRepoResponseReturns the created or updated MLRepo entity based on the provided manifest.

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Usage

from truefoundry import TrueFoundry

client = TrueFoundry(
    api_key="YOUR_API_KEY",
    base_url="https://yourhost.com/path/to/api",
)

client.ml_repos.create_or_update(
    manifest={"key": "value"},
    dry_run=False,
)
Get an ML Repo by its ID.

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Parameters

​
id
str
required

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Returns

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GetMlRepoResponse
GetMlRepoResponse
🔗 GetMlRepoResponseThe ML Repo data

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Usage

from truefoundry import TrueFoundry

client = TrueFoundry(
    api_key="YOUR_API_KEY",
    base_url="https://yourhost.com/path/to/api",
)

client.ml_repos.get(
    id="id_value",
)
Delete an ML Repo by its ID.

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Parameters

​
id
str
required

​
Returns

​
EmptyResponse
EmptyResponse
🔗 EmptyResponseEmpty response indicating successful deletion

​
Usage

from truefoundry import TrueFoundry

client = TrueFoundry(
    api_key="YOUR_API_KEY",
    base_url="https://yourhost.com/path/to/api",
)

client.ml_repos.delete(
    id="id_value",
)
List ML Repos with optional filtering by name.

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Parameters

​
name
typing.Optional[str]
Name of the ML Repo to filter by
​
limit
typing.Optional[int]
Maximum number of ML Repos to return
​
offset
typing.Optional[int]
Number of ML Repos to skip for pagination

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Returns

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SyncPager[MlRepo, ListMlReposResponse]
SyncPager[MlRepo, ListMlReposResponse]
🔗 ListMlReposResponseList of ML Repos matching the query with pagination information

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Usage

from truefoundry import TrueFoundry

client = TrueFoundry(
    api_key="YOUR_API_KEY",
    base_url="https://yourhost.com/path/to/api",
)

client.ml_repos.list(
    name="value",
    limit=10,
    offset=10,
)

# Iterate through results
for item in response:
    print(item.name)

# Or paginate page by page
for page in response.iter_pages():
    for item in page:
        print(item.name)