gradientai 1.0.0.dev7

Gradient AI API

gradientai-python-sdk

Interface for interacting with Gradient AI.

The gradientai-python-sdk library provides convenient access to the Gradient AI from applications written in the Python language. It includes a pre-defined set of classes for API resources that initialize themselves dynamically from API responses.

You can find usage examples for the Gradient AI Python library in our API reference and SDK quickstart. We also offer an example project in Python.

Requirements

Python 3.7+

Installation

You don't need this source code unless you want to modify the package. If you just want to use the package, just run:

pip install gradientai

Then import the package:

import gradientai

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 parameter for being able to make the call. Gradient uses
# access tokens, which can be generated by going to https://auth.gradient.ai/select-workspace and selecting
# "Access tokens" under the profile drop-down.

# Configure Bearer authorization: AccessToken
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_gradient_workspace_id = 'x_gradient_workspace_id_example' # str | 
    complete_model_body_params = gradientai.CompleteModelBodyParams() # CompleteModelBodyParams | 

    try:
        # Complete model
        api_response = api_instance.complete_model(id, x_gradient_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://github.com/Preemo-Inc/gradientai-python-sdk/blob/main/

Class	Method	HTTP request	Description
ModelsApi	complete_model	POST /models/{id}/complete	Complete model
ModelsApi	create_model	POST /models	Create model
ModelsApi	delete_model	DELETE /models/{id}	Delete model.
ModelsApi	fine_tune_model	POST /models/{id}/fine-tune	Fine-tune model
ModelsApi	get_model	GET /models/{id}	Describe model
ModelsApi	list_models	GET /models	List available models

Documentation For Models

• BaseModel
• CompleteModelBodyParams
• CompleteModelError
• CompleteModelSuccess
• CreateModelError
• CreateModelRequestBody
• CreateModelRequestBodyInitialHyperparameters
• CreateModelRequestBodyInitialHyperparametersLoraHyperparameters
• CreateModelRequestBodyInitialHyperparametersTrainingArguments
• CreateModelRequestBodyModel
• CreateModelSuccess
• DeleteModelError
• FineTuneModelError
• FineTuneModelRequestBody
• FineTuneModelRequestBodySamplesInner
• FineTuneModelRequestBodySamplesInnerFineTuningParameters
• FineTuneModelSuccess
• GetModelError
• GetModelSuccess
• ListModelsError
• ListModelsSuccess
• ListModelsSuccessModelsInner
• ModelAdapter

Documentation For Authorization

Authentication schemes defined for the API:

AccessToken

• Type: Bearer authentication

Author

[e-mail]