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* 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>
27 lines
1.1 KiB
Markdown
27 lines
1.1 KiB
Markdown
---
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title: Qdrant Documentation
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weight: 10
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---
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# Overview
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Qdrant (read: quadrant ) is a vector similarity search engine. It provides a production-ready service with a convenient API to store, search, and manage points - vectors with an additional payload. Qdrant is tailored to extended filtering support. It makes it useful for all sorts of neural network or semantic-based matching, faceted search, and other applications.
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Qdrant is released under the open-source Apache License 2.0. Its source code is available on [GitHub](https://github.com/qdrant/qdrant).
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## Common uses
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Qdrant is ideal for deploying applications based on the matching of embeddings produced by neural network encoders.
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These can be:
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- Semantic search
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- Similar Image \ Audio \ Video search
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- Recommendation systems
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In addition to this documentation, you may be interested in looking at examples of projects made with Qdrant:
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- [Semantic Search for startups](https://demo.qdrant.tech/) + [Source Code](https://github.com/qdrant/qdrant_demo)
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- [Visual Food Discovery](https://food-discovery.qdrant.tech/)
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- [Step-by-Step tutorial on building neural search](/articles/neural-search-tutorial/)
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