Showing 5 open source projects for "search engine code"

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  • 1
    Qdrant

    Qdrant

    Vector Database for the next generation of AI applications

    Qdrant is a vector similarity engine & vector database. It deploys as an API service providing search for the nearest high-dimensional vectors. With Qdrant, embeddings or neural network encoders can be turned into full-fledged applications for matching, searching, recommending, and much more! Provides the OpenAPI v3 specification to generate a client library in almost any programming language.
    Downloads: 67 This Week
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  • 2
    Weaviate

    Weaviate

    Weaviate is a cloud-native, modular, real-time vector search engine

    Weaviate in a nutshell: Weaviate is a vector search engine and vector database. Weaviate uses machine learning to vectorize and store data, and to find answers to natural language queries. With Weaviate you can also bring your custom ML models to production scale. Weaviate in detail: Weaviate is a low-latency vector search engine with out-of-the-box support for different media types (text, images, etc.).
    Downloads: 1 This Week
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  • 3
    VectorDB

    VectorDB

    A Python vector database you just need, no more, no less

    ...It's a testament to effective Pythonic design without over-engineering, making it a lean yet powerful solution for all your needs. vectordb capitalizes on the powerful retrieval prowess of DocArray and the scalability, reliability, and serving capabilities of Jina. Here's the magic: DocArray serves as the engine driving vector search logic, while Jina guarantees efficient and scalable index serving. This synergy culminates in a robust, yet user-friendly vector database experience, that's vectordb for you.
    Downloads: 0 This Week
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  • 4
    NOW

    NOW

    No-code tool for creating a neural search solution in minutes

    One line to host them all. Bootstrap your multimodal search case in minutes. NOW gives the world access to multimodal neural search with just one command. NOW supports various formats for uploading your dataset to your search application. You may either choose a demo dataset hosted by NOW, or use your own custom dataset, to build an application. NOW can support your custom data in the form of a DocumentArray, as a path to a local folder, or S3 bucket. You can choose a demo dataset to get...
    Downloads: 0 This Week
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    MongoDB Atlas runs apps anywhere

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  • 5
    Aquila DB

    Aquila DB

    An easy to use Neural Search Engine

    Aquila DB is a Neural search engine. In other words, it is a database to index Latent Vectors generated by ML models along with JSON Metadata to perform k-NN retrieval. It is dead simple to set up, language-agnostic, and drop in addition to your Machine Learning Applications. Aquila DB, as of current features is a ready solution for Machine Learning engineers and Data scientists to build Neural Information Retrieval applications out of the box with minimal dependencies.
    Downloads: 0 This Week
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