Metadata-Version: 2.1
Name: konan-sdk
Version: 1.1.0
Summary: Python SDK for Konan's API
Home-page: https://github.com/SynapseAnalytics/konan-sdk
License: MIT
Author: Synapse Analytics
Requires-Python: >=3.7,<4.0
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Requires-Dist: PyJWT[crypto] (>=2.1.0,<3.0.0)
Requires-Dist: fastapi (>=0.70,<0.71)
Requires-Dist: fastapi-utils (>=0.2.1,<0.3.0)
Requires-Dist: loguru (>=0.5.3,<0.6.0)
Requires-Dist: pydantic (>=1.8.2,<2.0.0)
Requires-Dist: requests (>=2.26.0,<3.0.0)
Project-URL: Documentation, https://docs.konan.ai
Project-URL: Konan Website, https://konan.ai
Project-URL: Repository, https://github.com/SynapseAnalytics/konan-sdk
Description-Content-Type: text/markdown

### Getting Started

```Python
from konan_sdk.sdk import KonanSDK

if __name__ == '__main__':
    # Initialize the SDK. Set verbose to True if you want verbose logging.
    sdk = KonanSDK(verbose=False)

    # Login user your valid konan credentials
    user = sdk.login("<email>", "<password>")

    # Define the input data to be passed to your model
    input_data = {"feature_1": 1, "feature_2": "abc", }

    # Run the prediction
    prediction_uuid, ml_output = sdk.predict("<deployment_uuid>", input_data)

    # Print the returned output
    print(prediction_uuid, ml_output)
```
