Commit 577a6f8
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[ML] Integrate SageMaker with OpenAI Embeddings (elastic#126856) (elastic#127610)
Integrating with SageMaker.
Current design:
- SageMaker accepts any byte payload, which can be text, csv, or json. `api` represents the structure of the payload that we will send, for example `openai`, `elastic`, `common`, probably `cohere` or `huggingface` as well.
- `api` implementations are extensions of `SageMakerSchemaPayload`, which supports:
- "extra" service and task settings specific to the payload structure, so `cohere` would require `embedding_type` and `openai` would require `dimensions` in the `service_settings`
- conversion logic from model, service settings, task settings, and input to `SdkBytes`
- conversion logic from responding `SdkBytes` to `InferenceServiceResults`
- Everything else is tunneling, there are a number of base `service_settings` and `task_settings` that are independent of the api format that we will store and set
- We let the SDK do the bulk of the work in terms of connection details, rate limiting, retries, etc.1 parent 686a9e4 commit 577a6f8
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lines changed- docs/changelog
- gradle
- server/src/main/java/org/elasticsearch
- common
- x-pack/plugin/inference
- qa/inference-service-tests/src/javaRestTest/java/org/elasticsearch/xpack/inference
- src
- main/java
- org/elasticsearch/xpack/inference
- common/amazon
- external/http
- services/sagemaker
- model
- schema
- openai
- test/java/org/elasticsearch/xpack/inference/services
- sagemaker
- model
- schema
- openai
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