Showing 4 open source projects for "unstructured data"

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  • 1
    Pimcore

    Pimcore

    Open Source Data & Experience Management Platform

    No matter if you're dealing with unstructured web documents or structured data for MDM/PIM, you define the UI design (web documents by a template and structured data with an intuitive graphical editor), Pimcore knows how to persist the data efficiently and optimized for fast access. Due to the framework approach, Pimcore is very flexible and adapts perfectly to your needs.
    Downloads: 9 This Week
    Last Update:
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  • 2
    skycaiji

    skycaiji

    Open source web scraping system for automated data collection tasks

    SkyCaiji is an open source web scraping and data collection system designed to gather information from websites through configurable extraction rules. It focuses on simplifying the process of building crawlers by allowing users to visually define scraping rules rather than writing complex code. It can collect structured or unstructured data from many types of webpages and automate the extraction process for large datasets.
    Downloads: 3 This Week
    Last Update:
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  • 3
    Relaticle

    Relaticle

    The Next-Generation Open-Source CRM Platform written with Laravel

    ...The interface lets you write plain text notes and tag or connect them dynamically, making it easier to uncover patterns and connections over time instead of losing insights in a long, unstructured list. Because it’s built with productivity and exploration in mind, Relaticle offers fast search, semantic context awareness, and the ability to zoom from high-level overviews down to specific node details. It also supports self-hosting so users retain full control over their data without relying on third-party servers or cloud subscriptions.
    Downloads: 8 This Week
    Last Update:
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  • 4
    LLPhant

    LLPhant

    A comprehensive PHP Generative AI Framework

    ...The framework focuses on usability by offering straightforward APIs for tasks like embeddings, question answering, and vector search, which are commonly required in real-world applications. It includes support for vector stores, enabling developers to build retrieval-augmented generation systems using structured or unstructured data. LLPhant also allows integration with external services and tools, making it possible to extend model capabilities beyond text generation into actionable workflows.
    Downloads: 0 This Week
    Last Update:
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