Showing 3 open source projects for "document library semantic search"

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  • 1
    Haystack

    Haystack

    Haystack is an open source NLP framework to interact with your data

    Apply the latest NLP technology to your own data with the use of Haystack's pipeline architecture. Implement production-ready semantic search, question answering, summarization and document ranking for a wide range of NLP applications. Evaluate components and fine-tune models. Ask questions in natural language and find granular answers in your documents using the latest QA models with the help of Haystack pipelines. Perform semantic search and retrieve ranked documents according to meaning, not just keywords! ...
    Downloads: 8 This Week
    Last Update:
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  • 2
    Cherche

    Cherche

    Neural Search

    Search is fully compatible with the collaborative filtering library Implicit. It is advantageous if you have a history associated with users and you want to retrieve / re-rank documents based on user preferences.
    Downloads: 3 This Week
    Last Update:
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  • 3
    Vector AI

    Vector AI

    A platform for building vector based applications

    Vector AI is a framework designed to make the process of building production-grade vector-based applications as quick and easily as possible. Create, store, manipulate, search and analyze vectors alongside json documents to power applications such as neural search, semantic search, personalized recommendations etc. Image2Vec, Audio2Vec, etc (Any data can be turned into vectors through machine learning). Store your vectors alongside documents without having to do a db lookup for metadata...
    Downloads: 1 This Week
    Last Update:
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