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Releases: aryn-ai/sycamore

v0.1.29

09 Dec 22:52
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This Sycamore release contains small bug fixes and enhancements.

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Full Changelog: v0.1.28...v0.1.29

v0.1.28

05 Dec 23:24
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This release updates doc_ids from UUIDs to NanoIds, adds some document title functionality, and improves stability and performance.

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Full Changelog: v0.1.27...v0.1.28

v0.1.27

14 Nov 19:46
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This Sycamore release includes a variety of small bug fixes and improvements.

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Full Changelog: v0.1.26...v0.1.27

v0.1.26

08 Nov 00:02
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This release includes several stabliity and reliability improvements.

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Full Changelog: v0.1.25...v0.1.26

v0.1.25

18 Oct 23:23
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This Sycamore release includes numerous bug fixes for connectors and other transforms. It also includes support for Anthropic LLMs via Amazon Bedrock.

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Full Changelog: v0.1.24...v0.1.25

v0.1.24

14 Oct 19:52
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This Sycamore release includes several bug fixes in the Weaviate and DuckDB connectors and in several of the example notebooks. Thanks to @Dnaynu for contributing to the Sycamore documentation!

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Full Changelog: v0.1.23...v0.1.24

v0.1.23

10 Oct 22:34
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This is a small release that fixes a bug in the Weaviate writer and includes a few other bug fixes and documentation improvements.

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Full Changelog: v0.1.22...v0.1.23

v0.1.22

09 Oct 19:54
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This sycamore release includes support for Python 3.12, a connector for the Qdrant vector database, and many bug fixes and enhancements. Thanks to @Anush008 for contributing the Qdrant support!

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Full Changelog: v0.1.21...v0.1.22

v0.1.21

18 Sep 18:10
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This Sycamore release contains Aryn Partitioning Service client updates to support the new auto-threshold feature and add support for Microsoft Word (.doc and .docx) and Microsoft PowerPoint (.ppt and .pptx) files. It also contains a variety of bug fixes and stability improvements.

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Full Changelog: v0.1.20...v0.1.21

v0.1.20

06 Sep 18:39
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This release refactors Sycamore’s dependencies to use extras in order to conditionally pull in dependencies for connectors and local inference (e.g. creating vector embeddings). For example, if you want to use the OpenSearch connector, you will need to: pip install sycamore-ai[opensearch]. Or, if you want to run a local vector embedding model, you will need to: pip install sycamore-ai[local-inference]. To do both, you will need to: pip install sycamore-ai[opensearch,local-inference]

Also, this release includes performance and stability improvements.

What's Changed

New Contributors

Full Changelog: v0.1.19...v0.1.20