Tesfagabir Meharizghi a7000ee89e Callback handler for Amazon SageMaker Experiments (#8587) ... ## Description This PR implements a callback handler for SageMaker Experiments which is similar to that of mlflow. * When creating the callback handler, it takes the experiment's run object as an argument. All the callback outputs are then logged to the run object. * The output of each callback action (e.g., `on_llm_start`) is saved to S3 bucket as json file. * Optionally, you can also log additional information such as the LLM hyper-parameters to the same run object. * Once the callback object is no more needed, you will need to call the `flush_tracker()` method. This makes sure that any intermediate files are deleted. * A separate notebook example is provided to show how the callback is used. @3coins @agola11 --------- Co-authored-by: Tesfagabir Meharizghi <mehariz@amazon.com>		2023-08-01 13:47:08 -07:00
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_templates	Update Integrations links (#8206)	2023-07-24 21:20:32 -07:00
additional_resources	Link to use cases from tutorials (#8371)	2023-07-27 11:54:04 -07:00
ecosystem	use top nav docs (#8090)	2023-07-21 13:52:03 -07:00
guides	add example for memory (#8552)	2023-08-01 01:10:19 -07:00
integrations	Callback handler for Amazon SageMaker Experiments (#8587)	2023-08-01 13:47:08 -07:00
modules	updates some spelling mistakes (#8537)	2023-07-31 17:15:29 -07:00
use_cases	Fixed bug7445 where a duplicate restuld_id is added to the vectorstore. (#7573)	2023-07-31 18:00:01 -07:00