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#

../../_images/login-1.png

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

../../_images/login-2.png

Token Management#

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

../../_images/pat.png

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

via CLI#

Login#

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.

jina auth logout

Token Management#

Create a new PAT#

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#

jina auth token list

Delete PAT#

jina auth token delete <name of PAT>

via Python API#

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

Login#

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#

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.

import hubble

hubble.get_token()

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

import hubble

hubble.get_token(interactive=True)

Mark a function as login required,

import hubble


@hubble.login_required
def foo():
    pass

Logout#

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:

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#

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#

import hubble

client = hubble.Client()

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