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Login & Token Management

docs/jina-ai-cloud/login.md

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Login & Token Management

To use Jina AI Cloud, you need to log in, either via a GitHub or Google account. This section describes how to log in Jina AI Cloud and manage the personal access token. You can do it via webpage, CLI or Python API.

via Webpage

Visit https://jina.ai and click on the "login" button.

Login

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After log in you can see your name and avatar in the top-right corner.

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Token Management

You can follow the GUI to create/delete personal access tokens for your Jina-serve applications.

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To use a token, set it as the environment variable JINA_AUTH_TOKEN.

via CLI

Login

shell
jina auth login

This will open browser automatically and login via 3rd party. Token will be saved locally.

Logout

If there is a valid token locally, this will disable that token and remove it from local config.

shell
jina auth logout

Token Management

Create a new PAT

shell
jina auth token create <name of PAT> -e <expiration days>

To use a token, set it as the environment variable JINA_AUTH_TOKEN.

List PATs

shell
jina auth token list

Delete PAT

shell
jina auth token delete <name of PAT>

via Python API

Installed along with Jina-serve, you can leverage the hubble package to manage login from Python

Login

python
import hubble

# Log in via browser or PAT. The token is saved locally.
# In Jupyter/Google Colab, interactive login is used automatically.
# To disable this feature, run `hubble.login(interactive=False)`.
hubble.login()

Check login status

python
import hubble

if hubble.is_logged_in():
    print('yeah')
else:
    print('no')

Get a personal access token

Notice that the token you got from this function is always valid. If the token is invalid or expired, the result is None.

python
import hubble

hubble.get_token()

If you are using inside an interactive environment, i.e. user can input via stdin:

python
import hubble

hubble.get_token(interactive=True)

Mark a function as login required,

python
import hubble


@hubble.login_required
def foo():
    pass

Logout

python
import hubble

# If there is a valid token locally,
# this will disable that token and remove it from local config.
hubble.logout()

Token management

After calling hubble.login(), you can use the client:

python
import hubble

client = hubble.Client(max_retries=None, jsonify=True)
# Get current user information.
response = client.get_user_info()
# Create a new personal access token for longer expiration period.
response = client.create_personal_access_token(name='my-pat', expiration_days=30)
# Query all personal access tokens.
response = client.list_personal_access_tokens()

Artifact management

python
import hubble
import io

client = hubble.Client(max_retries=None, jsonify=True)

# Upload artifact to Hubble Artifact Storage by providing path.
response = client.upload_artifact(f='~/Documents/my-model.onnx', is_public=False)

# Upload artifact to Hubble Artifact Storage by providing `io.BytesIO`
response = client.upload_artifact(
    f=io.BytesIO(b"some initial binary data: \x00\x01"), is_public=False
)

# Get current artifact information.
response = client.get_artifact_info(id='my-artifact-id')

# Download artifact to local directory.
response = client.download_artifact(id='my-artifact-id', f='my-local-filepath')
# Download artifact as an io.BytesIO object
response = client.download_artifact(id='my-artifact-id', f=io.BytesIO())

# Get list of artifacts.
response = client.list_artifacts(filter={'metaData.foo': 'bar'}, sort={'type': -1})

# Delete the artifact.
response = client.delete_artifact(id='my-artifact-id')

Error handling

python
import hubble

client = hubble.Client()

try:
    client.get_user_info()
except hubble.excepts.AuthenticationRequiredError:
    print('Please login first.')
except Exception:
    print('Unknown error')