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feat: Add OpenSearch Binary & Byte data_type support #17476

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christopher-learningpool

Description

This PR adds support for byte and binary vector storage in the OpenSearch vector store integration, leveraging OpenSearch 2.17's new vector capabilities. This enhancement enables more efficient vector storage by supporting 8-bit integers (-128 to 127) instead of only floats, significantly reducing storage requirements while maintaining search quality.

Fixes #17271

New Package?

Did I fill in the tool.llamahub section in the pyproject.toml and provide a detailed README.md for my new integration or package?

  • Yes
  • No

Version Bump?

Did I bump the version in the pyproject.toml file of the package I am updating? (Except for the llama-index-core package)

  • Yes
  • No

Type of Change

Please delete options that are not relevant.

  • New feature (non-breaking change which adds functionality)

How Has This Been Tested?

Your pull-request will likely not be merged unless it is covered by some form of impactful unit testing.

  • I added new unit tests to cover this change

Added comprehensive test suite including:

  • Initialisation tests for different vector types and configurations
  • Validation tests for engine and space type requirements
  • Functionality tests for both synchronous and asynchronous operations
  • Tests covering the full range of byte values (-128 to 127)
  • Tests ensuring binary vector dimension requirements
  • Tests for both lucene and faiss engines with byte vectors

Suggested Checklist:

  • I have performed a self-review of my own code
  • I have commented my code, particularly in hard-to-understand areas
  • I have made corresponding changes to the documentation
  • I have added Google Colab support for the newly added notebooks.
  • My changes generate no new warnings
  • I have added tests that prove my fix is effective or that my feature works
  • New and existing unit tests pass locally with my changes
  • I ran make format; make lint to appease the lint gods

@dosubot dosubot bot added the size:L This PR changes 100-499 lines, ignoring generated files. label Jan 10, 2025
@@ -269,7 +269,7 @@ class BaseNode(BaseComponent):
id_: str = Field(
default_factory=lambda: str(uuid.uuid4()), description="Unique ID of the node."
)
embedding: Optional[List[float]] = Field(
embedding: Optional[List[Union[float, int]]] = Field(
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not 100% sure how I feel about changing this. But I guess it makes sense. This will likely cause some mypy errors? Lets see the linting output

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It's a low-level change that I wasn't expecting to change. Any other changes to the core schema would be a more considerable breaking change if we wanted to add an embedding_type field and switch based on that.

Do you have any thoughts on how we should proceed? I suspect we'll see more need to add byte or binary support in the future.

@logan-markewich
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logan-markewich commented Jan 17, 2025

Not sure whats up with tests... investigating

UPDATE: fixed the testing weirdness

UPDATE: jk still weird

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[Feature Request]: OpenSearch Byte Vector Support
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