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text,source
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"---
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draft: false
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title: Food Discovery
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short_description: Qdrant Food Discovery Demo recommends more similar meals based on how they look
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description: This demo uses data from Delivery Service. Users may like or dislike the photo of a dish, and the app will recommend more similar meals based on how they look. It's also possible to choose to view results from the restaurants within the delivery radius.
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preview_image: /demo/food-discovery-demo.png
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link: https://food-discovery.qdrant.tech/
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weight: 2
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sitemapExclude: True
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---
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",demo/demo-2.md
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"---
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draft: false
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title: E-commerce products categorization
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short_description: E-commerce products categorization demo from Qdrant vector database
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description: This demo shows how you can use vector database in e-commerce. Enter the name of the product and the application will understand which category it belongs to, based on the multi-language model. The dots represent clusters of products.
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preview_image: /demo/products_categorization_demo.jpg
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link: https://qdrant.to/extreme-classification-demo
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weight: 3
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sitemapExclude: True
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---
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",demo/demo-3.md
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"---
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draft: false
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title: Startup Search
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short_description: Qdrant Startup Search. This demo uses short descriptions of startups to perform a semantic search
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description: This demo uses short descriptions of startups to perform a semantic search. Each startup description converted into a vector using a pre-trained SentenceTransformer model and uploaded to the Qdrant vector search engine. Demo service processes text input with the same model and uses its output to query Qdrant for similar vectors. You can turn neural search on and off to compare the result with regular full-text search.
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preview_image: /demo/startup_search_demo.jpg
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link: https://qdrant.to/semantic-search-demo
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weight: 1
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sitemapExclude: True
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---
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",demo/demo-1.md
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"---
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page_title: Vector Search Demos and Examples
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description: Interactive examples and demos of vector search based applications developed with Qdrant vector search engine.
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title: Vector Search Demos
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section_title: Interactive Live Examples
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---",demo/_index.md
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"---
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title: Examples
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weight: 25
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# If the index.md file is empty, the link to the section will be hidden from the sidebar
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is_empty: false
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---
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# Sample Use Cases
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Our Notebooks offer complex instructions that are supported with a throrough explanation. Follow along by trying out the code and get the most out of each example.
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| Example | Description | Stack |
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|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|-------------------------------------------------------------------------------------------------|----------------------------|
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| [Intro to Semantic Search and Recommendations Systems](https://githubtocolab.com/qdrant/examples/blob/master/qdrant_101_getting_started/getting_started.ipynb) | Learn how to get started building semantic search and recommendation systems. | Qdrant |
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| [Search and Recommend Newspaper Articles](https://githubtocolab.com/qdrant/examples/blob/master/qdrant_101_text_data/qdrant_and_text_data.ipynb) | Work with text data to develop a semantic search and a recommendation engine for news articles. | Qdrant |
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| [Recommendation System for Songs](https://githubtocolab.com/qdrant/examples/blob/master/qdrant_101_audio_data/03_qdrant_101_audio.ipynb) | Use Qdrant to develop a music recommendation engine based on audio embeddings. | Qdrant |
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| [Image Comparison System for Skin Conditions](https://colab.research.google.com/github/qdrant/examples/blob/master/qdrant_101_image_data/04_qdrant_101_cv.ipynb) | Use Qdrant to compare challenging images with labels representing different skin diseases. | Qdrant |
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| [Question and Answer System with LlamaIndex](https://githubtocolab.com/qdrant/examples/blob/master/llama_index_recency/Qdrant%20and%20LlamaIndex%20%E2%80%94%20A%20new%20way%20to%20keep%20your%20Q%26A%20systems%20up-to-date.ipynb) | Combine Qdrant and LlamaIndex to create a self-updating Q&A system. | Qdrant, LlamaIndex, Cohere |
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| [Extractive QA System](https://githubtocolab.com/qdrant/examples/blob/master/extractive_qa/extractive-question-answering.ipynb) | Extract answers directly from context to generate highly relevant answers. | Qdrant |
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| [Ecommerce Reverse Image Search](https://githubtocolab.com/qdrant/examples/blob/master/ecommerce_reverse_image_search/ecommerce-reverse-image-search.ipynb) | Accept images as search queries to receive semantically appropriate answers. | Qdrant |
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| [Basic RAG](https://githubtocolab.com/qdrant/examples/blob/master/rag-openai-qdrant/rag-openai-qdrant.ipynb) | Basic RAG pipeline with Qdrant and OpenAI SDKs | OpenAI, Qdrant, FastEmbed |
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",documentation/examples.md
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"---
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title: Release notes
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weight: 42
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type: external-link
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external_url: https://github.com/qdrant/qdrant/releases
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sitemapExclude: True
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---
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",documentation/release-notes.md
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"---
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title: Benchmarks
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weight: 33
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draft: true
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---
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",documentation/benchmarks.md
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"---
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title: Community links
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weight: 42
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---
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# Community Contributions
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Though we do not officially maintain this content, we still feel that is is valuable and thank our dedicated contributors.
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| Link | Description | Stack |
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|------|------------------------------|--------|
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| [Pinecone to Qdrant Migration](https://github.com/NirantK/qdrant_tools) | Complete python toolset that supports migration between two products. | Qdrant, Pinecone |
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| [LlamaIndex Support for Qdrant](https://gpt-index.readthedocs.io/en/latest/examples/vector_stores/QdrantIndexDemo.html) | Documentation on common integrations with LlamaIndex. | Qdrant, LlamaIndex |
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| [Geo.Rocks Semantic Search Tutorial](https://geo.rocks/post/qdrant-transformers-js-semantic-search/) | Create a fully working semantic search stack with a built in search API and a minimal stack. | Qdrant, HuggingFace, SentenceTransformers, transformers.js |
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",documentation/community-links.md
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