tdapiclient - Teradata Third Party Analytics Integration Python Library

The tdapiclient Python library integrates the Python libraries from AWS SageMaker, Azure ML, and Google Vertex AI with Teradata. Users can train and score their models using teradataml DataFrame. tdapiclient will transparantly convert the teradataml DataFrame to an S3 address, Azure ML Dataset or Blob, or Vertex AI dataset to be used for training. The user can then provide another teradataml DataFrame as input for inference.

Users of tdapiclient can also deploy models trained in Azure ML, AWS SageMaker, or Vertex AI to a Teradata Vantage system for in-database scoring using BYOM functionality.

This library also provides API_Request, a method to call API_Request UDF, which can be used for obtaining OpenAI and Azure OpenAI text embeddings from large language models. This method can also be used for scoring models hosted in AWS, Azure, or Google Cloud Platform, equivalent to predicting in UDF mode through the tdapiclient predict method.

Teradata recommends downloading tdapiclient library from PyPi location : https://pypi.org/project/tdapiclient/.
Download from downloads.teradata.com location if your organization does not allow you to install directly from https://pypi.org/project/tdapiclient/.