Gradient AI API
Project description
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
Project details
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