Manage Providers Using Jupyter Notebook Integration

Introduction

The ZEDEDA Edge AI Client (zededa-eip-client) is a Python package that provides programmatic access to ZEDEDA Edge Inference Services. You can use it to manage providers, browse models, trigger imports, and monitor jobs from a Jupyter Notebook, a Python script, or any other Python environment. This article covers provider management using the client. For console-based provider management, see Manage Providers.

Prerequisites

Python 3.8 or later.
Access to ZEDEDA Edge Inference Services with a valid organization ID.
Credentials for the provider types you want to add (API tokens, access keys, or service principal details).

Install the Client

Install the zededa-eip-client package from PyPI:

pip install zededa-eip-client

Authenticate

Authenticate with ZEDEDA Edge Inference Services before making any API calls. Pass your organization ID to the login function:

from zededa_eip_client import login

login(organization_id="your-organization-id")

After authentication, initialize the client:

from zededa_eip_client.client import ZededaEIPClient

client = ZededaEIPClient()

List Providers

Retrieve all providers configured in your organization:

providers = client.list_external_providers()
for provider in providers:
    print(provider["name"], provider["type"], provider["status"])

Each provider entry includes the provider name, type, connection status, and configuration details.

Create a Provider

Use create_external_provider to add a new provider. The required fields vary by provider type. The following examples cover seven of the nine supported provider types. Qualcomm AI Hub and Local (file upload) providers are also supported.

HuggingFace

client.create_external_provider(
    name="my-huggingface",
    provider_type="huggingface",
    credentials={"token": "hf_your_access_token"},
)

NVIDIA NGC

client.create_external_provider(
    name="my-ngc",
    provider_type="nvidia_ngc",
    credentials={"api_key": "your-ngc-api-key"},
)

Azure ML

client.create_external_provider(
    name="my-azure-ml",
    provider_type="azure",
    credentials={
        "tenant_id": "your-tenant-id",
        "client_id": "your-client-id",
        "client_secret": "your-client-secret",
    },
    configuration={
        "subscription_id": "your-subscription-id",
        "resource_group": "your-resource-group",
        "workspace_name": "your-workspace",
    },
)

Azure Blob

client.create_external_provider(
    name="my-blob",
    provider_type="blob",
    credentials={"account_key": "your-account-key"},
    configuration={
        "storage_account": "your-storage-account",
        "container": "your-container",
    },
)

MLflow

client.create_external_provider(
    name="my-mlflow",
    provider_type="mlflow",
    url="https://your-mlflow-server",
    credentials={
        "username": "your-username",
        "password": "your-password",
    },
)

Amazon S3

client.create_external_provider(
    name="my-s3",
    provider_type="s3",
    credentials={
        "access_key": "your-access-key-id",
        "secret_key": "your-secret-access-key",
        "session_token": "optional-session-token",
    },
    configuration={
        "region": "us-east-1",
        "bucket": "your-bucket-name",
    },
)

AWS SageMaker

client.create_external_provider(
    name="my-sagemaker",
    provider_type="sagemaker",
    credentials={
        "access_key": "your-access-key-id",
        "secret_key": "your-secret-access-key",
    },
    configuration={"region": "us-east-1"},
)

Update a Provider

Use update_external_provider to modify an existing provider’s credentials or configuration. Pass the provider ID and only the fields you want to change:

client.update_external_provider(
    provider_id="your-provider-id",
    credentials={"token": "hf_new_access_token"},
)

Test a Provider Connection

Use test_provider_connection to verify that ZEDEDA Edge Inference Services can reach the provider with its current credentials:

result = client.test_provider_connection(provider_id="your-provider-id")
print(result)

The response indicates whether the connection succeeded or failed. Only Super Admin can run a connection test. A failed test sets the provider to an error state, and imports from it are blocked until a test passes.

Browse a Provider

Use browse_provider to list models or files available in a provider. Browsing is supported for all provider types. The search query is supported only for Hugging Face, MLflow, NVIDIA NGC, and Qualcomm AI Hub providers. For other provider types, omit query or the request fails.

items = client.browse_provider(
    provider_id="your-provider-id",
    path="/",        # directory path within the provider
    query="llama",   # optional search query
)
for item in items:
    print(item["name"], item["type"])

Import a Model from a Provider

Use import_model_from_external_provider to start an import job that fetches a model from the provider into your ZEDEDA Edge Inference Services model library:

job = client.import_model_from_external_provider(
    provider_id="your-provider-id",
    model_path="meta-llama/Llama-3-8b",
    model_name="llama-3-8b",
    version="1.0",
)
print("Import job started:", job["id"])

The method returns a job object containing the job ID. You can use this ID to monitor import progress in the Infrastructure Monitor Jobs page, or by polling the job status programmatically.

Delete a Provider

Use delete_external_provider to remove a provider from your organization:

client.delete_external_provider(provider_id="your-provider-id")

Deleting a provider does not remove any models that were already imported from it.

​Introduction

​Prerequisites

​Install the Client

​Authenticate

​List Providers

​Create a Provider

​HuggingFace

​NVIDIA NGC

​Azure ML

​Azure Blob

​MLflow

​Amazon S3

​AWS SageMaker

​Update a Provider

​Test a Provider Connection

​Browse a Provider

​Import a Model from a Provider

​Delete a Provider

​In This Section