gradientai 1.0.0.dev3

Gradient AI API

gradientai-python-sdk

Interface for interacting with Gradient AI.

This Python package is automatically generated by the OpenAPI Generator project:

• API version: 1.0.0
• Package version: 1.0.0-dev.3
• Build package: org.openapitools.codegen.languages.PythonClientCodegen

Requirements.

Python 3.7+

Installation & Usage

pip install

If the python package is hosted on a repository, you can install directly using:

pip install git+https://github.com/Preemo-Inc/gradientai-python-sdk.git

(you may need to run pip with root permission: sudo pip install git+https://github.com/Preemo-Inc/gradientai-python-sdk.git)

Then import the package:

import gradientai

Setuptools

Install via Setuptools.

python setup.py install --user

(or sudo python setup.py install to install the package for all users)

Then import the package:

import gradientai

Tests

Execute pytest to run the tests.

Getting Started

Please follow the installation procedure and then run the following:

import time
import gradientai
from gradientai.rest import ApiException
from pprint import pprint

# Defining the host is optional and defaults to https://api.gradient.ai/api
# See configuration.py for a list of all supported configuration parameters.
configuration = gradientai.Configuration(
    host = "https://api.gradient.ai/api"
)

# The client must configure the authentication and authorization parameters
# in accordance with the API server security policy.
# Examples for each auth method are provided below, use the example that
# satisfies your auth use case.

# Configure Bearer authorization (JWT): bearerAuth
configuration = gradientai.Configuration(
    access_token = os.environ["BEARER_TOKEN"]
)


# Enter a context with an instance of the API client
with gradientai.ApiClient(configuration) as api_client:
    # Create an instance of the API class
    api_instance = gradientai.ModelsApi(api_client)
    id = 'id_example' # str | 
    x_preemo_workspace_id = 'x_preemo_workspace_id_example' # str | 
    complete_model_body_params = gradientai.CompleteModelBodyParams() # CompleteModelBodyParams | 

    try:
        # Complete model
        api_response = api_instance.complete_model(id, x_preemo_workspace_id, complete_model_body_params)
        print("The response of ModelsApi->complete_model:\n")
        pprint(api_response)
    except ApiException as e:
        print("Exception when calling ModelsApi->complete_model: %s\n" % e)

Documentation for API Endpoints

All URIs are relative to https://api.gradient.ai/api

Class	Method	HTTP request	Description
ModelsApi	complete_model	POST /models/{id}/completions	Complete model
ModelsApi	create_model	POST /models	Create model
ModelsApi	delete_model	DELETE /models/{id}	Delete model.
ModelsApi	get_model	GET /models/{id}	Describe model
ModelsApi	list_models	GET /models	List available models
ModelsApi	train_model	PUT /models/{id}	Train model

Documentation For Models

• CompleteModelBodyParams
• CompleteModelError
• CompleteModelSuccess
• CreateModelError
• CreateModelRequestBody
• CreateModelRequestBodyInitialHyperparameters
• CreateModelRequestBodyInitialHyperparametersLoraHyperparameters
• CreateModelRequestBodyInitialHyperparametersTrainingArguments
• CreateModelRequestBodyModel
• CreateModelSuccess
• DeleteModelError
• GetModelError
• GetModelSuccess
• ListModelsError
• ListModelsSuccess
• ListModelsSuccessModelsInner
• ListModelsSuccessModelsInnerOneOf
• ListModelsSuccessModelsInnerOneOf1
• TrainModelError
• TrainModelRequestBody
• TrainModelRequestBodySamplesInner
• TrainModelRequestBodySamplesInnerFineTuningParameters
• TrainModelSuccess

Documentation For Authorization

Authentication schemes defined for the API:

bearerAuth

• Type: Bearer authentication (JWT)

Author