Python: Adding USearch memory connector #2358
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shawncal
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This is exciting! We are also working on C# bindings for USearch to allow broader integration with SK 🤗 cc @dluc |
Fix: removing cast to `str` due to patch in USearch
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@microsoft-github-policy-service agree |
Refactor: method naming Docs: update to fit changes
Docs: clarification
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awesome, thank you @ashvardanian - I'll take a look asap (FYI, there's a quick git conflict to fix when you have a chance) |
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Hey, @dluc! @AleksandrKent has updated the poetry file. It seems to be the only collision. But it will re-appear as soon as you have any other dependency updates, so we should try merging this sooner. Please let us know if anything has to be polished. |
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dluc
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python/semantic_kernel/connectors/memory/usearch/usearch_memory_store.py
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### Motivation and Context The integration of [USearch](https://github.com/unum-cloud/usearch) as a memory connector to Semantic Kernel (SK). ### Description The USearch `Index` does not natively have the ability to store different collections, and it only stores embeddings without other attributes like `MemoryRecord`. The `USearchMemoryStore` class encapsulates these capabilities. It uses the USearch `Index` to store a collection of embeddings under unique IDs, with original collection names mapped to those IDs. Other `MemoryRecord ` attributes are stored in a `pyarrow.Table`, which is mapped to each collection. It's important to note the current behavior when a user removes a record or upserts a new one with an existing ID: the old row is not removed from the `pyarrow.Table`. This is done for performance reasons but could lead to the table growing in size. By default, `USearchMemoryStore` operates as an in-memory store. To enable persistence, you must set the persist mode with calling appropriate `__init__ `, supplying a path to the directory for the persist files. For each collection, two files will be created: `{collection_name}.usearch` and `{collection_name}.parquet`. Changes will only be dumped to the disk when `close_async` is called. Due to the interface provided by the base class `MemoryStoreBase`, this happens implicitly when using a context manager, or it may be called explicitly. Since collection names are used to store files on disk, all names are converted to lowercase. To ensure efficient use of memory, you should call `close_async`. --------- Co-authored-by: Abby Harrison <[email protected]> Co-authored-by: Abby Harrison <[email protected]> Co-authored-by: Devis Lucato <[email protected]>
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Motivation and Context
The integration of USearch as a memory connector to Semantic Kernel (SK).
Description
The USearch
Indexdoes not natively have the ability to store different collections, and it only stores embeddings without other attributes likeMemoryRecord.The
USearchMemoryStoreclass encapsulates these capabilities. It uses the USearchIndexto store a collection of embeddings under unique IDs, with original collection names mapped to those IDs. OtherMemoryRecordattributes are stored in apyarrow.Table, which is mapped to each collection.It's important to note the current behavior when a user removes a record or upserts a new one with an existing ID: the old row is not removed from the
pyarrow.Table. This is done for performance reasons but could lead to the table growing in size.By default,
USearchMemoryStoreoperates as an in-memory store. To enable persistence, you must set the persist mode with calling appropriate__init__, supplying a path to the directory for the persist files. For each collection, two files will be created:{collection_name}.usearchand{collection_name}.parquet. Changes will only be dumped to the disk whenclose_asyncis called. Due to the interface provided by the base classMemoryStoreBase, this happens implicitly when using a context manager, or it may be called explicitly.Since collection names are used to store files on disk, all names are converted to lowercase.
To ensure efficient use of memory, you should call
close_async.Contribution Checklist