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https://github.com/qdrant/landing_page.git
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3215985d1d
* added a table of content * wide layout for docs, styles for the table of content * fixes for docs layout * wide footer at the docs section * added support for nested docs, added toggling groups of links, delimiters, external links * external link icon * added active state for nested links, styles for the external link icon * styles fix * remove doc sync * update directory structure and doc titles * fix outstanding links * fix more links for merge * Revert "fix more links for merge" This reverts commit 46c9ccaf1b7765f2cda8dc85d625fa6b4e3f5436. * Revert "fix outstanding links" This reverts commit 28e6380b74f1ab74690c8184551f186656d6d4e9. * fix remaining broken links * move how-to tutorials in the different page * split tutorials * fix link * upd github edit link * skip empty index pages --------- Co-authored-by: Andrey Vasnetsov <andrey@vasnetsov.com> Co-authored-by: David Sertic <62056091+davidmyriel@users.noreply.github.com>
20 lines
661 B
Markdown
20 lines
661 B
Markdown
---
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title: DocArray
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weight: 300
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---
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# DocArray
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You can use Qdrant natively in DocArray, where Qdrant serves as a high-performance document store to enable scalable vector search.
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DocArray is a library from Jina AI for nested, unstructured data in transit, including text, image, audio, video, 3D mesh, etc.
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It allows deep-learning engineers to efficiently process, embed, search, recommend, store, and transfer the data with a Pythonic API.
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To install DocArray with Qdrant support, please do
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```bash
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pip install "docarray[qdrant]"
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```
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More information can be found in [DocArray's documentations](https://docarray.jina.ai/advanced/document-store/qdrant/).
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