Metadata-Version: 2.1
Name: zeblok-sdk
Version: 1.4.0
Summary: Zeblok Python SDK
Home-page: 
Author: Karan Pathak
Author-email: karan@dataturtles.com
Maintainer: Zeblok, Karan Pathak
Maintainer-email: zeblok@zeblok.com, karan.pathak@zeblok.com
Keywords: zeblok,python-sdk,zeblok-sdk
Classifier: Programming Language :: Python :: 3
Requires-Python: >=3.9
Description-Content-Type: text/markdown
License-File: LICENSE.md
Requires-Dist: boto3
Requires-Dist: requests
Requires-Dist: minio
Requires-Dist: azure-storage-blob

# Zeblok Python SDK

Zeblok-sdk will help integrate your MLOps workflows with the Zeblok Ai-MicroCloud platform.

## Components of the Python SDK

### Auth

- API Authentication
- DataLake Authentication

### Resources

- Plan
- Namespace

### Managed Service

- Microservice
- Orchestration-Addons
- Ai-API
- Ai-Pipeline
- DataLake
- DataSet
- Inference Hub
- Inference Chat

# Interface

<h3> Authentication </h3>

- API Authentication: `APIAuth(app_url, api_access_key,api_access_secret)`
- DataLake Authentication: `DataLake(api_auth, access_key, secret_key, bucket_name, blob_url, port)`

<h3> Plans </h3>

- Get all plans: `get_all()`
- Get a plan by id: `get_by_id(plan_id)`
- Validate a plan by id: `validate_id(plan_id)`
- Get filtered details of a plan: `get_filtered_details(plan_id, fields_req)`

<h3> Namespaces </h3>

- Get all namespaces: `get_all()`
- Get a namespace by id: `get_by_id(namespace_id)`
- Validate a namespace by id: `validate_id(namespace_id)`

<h3> MicroServices </h3>

- Get all microservices: `get_all()`
- Get a microservice by id: `get_by_id(microservice_id)`
- Validate a microservice by id: `validate_id(microservice_id)`
- Spawn a microservice: `spawn(display_name, microservice_id, plan_id, microservice_name, namespace_id, envs, ports, args, command)`

<h3> Orchestration-Addons </h3>

- Get all orchestrations: `get_all()`
- Get an orchestration by id: `get_by_id(orchestration_id)`
- Validate an orchestration by id: `validate_id(orchestration_id)`
- Spawn an orchestration: `spawn(orchestration_id, plan_id, namespace_id, orchestration_name, min_workers, max_workers)`

<h3> AI-APIs </h3>

- Get all AI-APIs with `deployed` state: `get_all(state=deployed)`
- Get all AI-APIs with `ready` state: `get_all(state=ready)`
- Validate an AI-API: `validate(image_name, state)`
- Create and Spawn an AI-API: `create_and_spawn(ai_api_name, model_folder_path, plan_id, namespace_id, ai_api_type)`
- Create an AI-API: `create(ai_api_name, model_folder_path, ai_api_type)`
- Spawn an AI-API: `spawn(image_name, namespace_id, plan_id)`

<h3> AI-Pipelines </h3>

- Get all AI-Pipelines with `created` state: `get_all(state=created)`
- Get all AI-Pipelines with `ready` state: `get_all(state=ready)`
- Validate an AI-Pipeline: `validate(image_name, state)`
- Create and Spawn an
  AI-API: `create_and_spawn(ai_pipeline_name, ai_pipeline_folder_path, caas_plan_id, ai_pipeline_plan_id, namespace_id)`
- Create an
  AI-Pipeline: `create(ai_pipeline_name, ai_pipeline_folder_path, caas_plan_id, ai_pipeline_plan_id, namespace_id)`
- Spawn an AI-Pipeline: `spawn(ai_pipeline_plan_id, namespace_id, ai_pipeline_image_name)`

<h3> DataLake </h3> 

- Check if a bucket exists: `bucket_exists()`
- Check if an object exists: `object_exists(object_name)`
- Upload an object: `upload_object(local_file_pathname, object_name)`
- Download an object: `download_object(object_name, local_dir, filename)`
- Get object PreSigned URL: `get_presigned_url(object_name)`
- Upload a folder: `upload_folder(folder_path)`

<h3> DataSet </h3>

- Get all DataSets: `get_all()`
- Get Dataset information by name: `get_by_name(dataset_name)`
- Create a DataSet: `create_dataset(dataset_name, dataset_description)`
- Upload files in a DataSet: `upload_dataset(dataset_id, filepaths)`

<h3> Inference Hub </h3>

- Get all inferences: `get_all()`
- Get an inference by id: `get_by_id(inference_id)`
- Validate an inference by id: `validate_id(inference_id)`
- Spawn an inference: `spawn(inference_name, inference_id, plan_id, namespace_id, inference_display_name, inference_model_image_name, inference_model_tag_id, resource_threshold, envs, ports, args, command, model_type, num_replicas, min_num_replicas, max_num_replicas, volume_path)`
- Get all spawned inferences: `get_all_spawned_inferences()`
- Get a spawned inference by id: `get_spawned_inference_by_id(spawned_inference_id)`
- Validate a spawned inference by id: `validate_spawned_inference_id(spawned_inference_id)`
- Get spawned inference ID by spawned inference pod name: `get_spawned_inference_id_by_pod_name(spawned_inference_pod_name)`

<h3> Inference Chat </h3>

- Chat with a spawned inference: `chat(prompt)`
- Get chats history for the current active chat session: `get_all()`


## Usage

Checkout the detailed usage of the SDK at [Usage.md](Usage.md#usage)

# Contact Zeblok

| **Team**           | **Email**          |
|--------------------|--------------------|
| **Technical Team** | support@zeblok.com |
| **Sales Team**     | sales@zeblok.com   |

