Showing 4 open source projects for "document management system php"

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    Rocketnotes

    Rocketnotes

    AI-powered markdown editor - leverage LLMs with your documents

    ...The system is designed with productivity workflows in mind, allowing users to build interconnected notes and maintain organized collections of information. By combining note management with AI-assisted writing and summarization tools, the platform aims to help users process large volumes of information more efficiently.
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    LLM TLDR

    LLM TLDR

    95% token savings. 155x faster queries. 16 languages

    LLM TLDR is a tool that leverages large language models (LLMs) to generate concise, coherent summaries (TL;DRs) of long documents, articles, or text files, helping users quickly understand large amounts of content without reading every word. It integrates with LLM APIs to handle input texts of varying lengths and complexity, applying techniques like chunking, context management, and multi-pass summarization to preserve accuracy even when the source is very large. The system supports both...
    Downloads: 0 This Week
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  • 3
    nashsu LLM Wiki

    nashsu LLM Wiki

    LLM Wiki is a cross-platform desktop application

    nashsu LLM Wiki is a project designed to create a structured, navigable knowledge base powered by large language models, enabling users to explore information in a wiki-like format. It likely transforms raw data or documents into interconnected pages that can be dynamically generated and summarized by AI. The system emphasizes discoverability, allowing users to navigate topics through links and relationships rather than static search results. It may include mechanisms for content generation,...
    Downloads: 0 This Week
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  • 4
    Canopy

    Canopy

    Retrieval Augmented Generation (RAG) framework

    Canopy is an open-source retrieval-augmented generation (RAG) framework developed by Pinecone to simplify the process of building applications that combine large language models with external knowledge sources. The system provides a complete pipeline for transforming raw text data into searchable embeddings, storing them in a vector database, and retrieving relevant context for language model responses. It is designed to handle many of the complex components required for a RAG workflow, including document chunking, embedding generation, prompt construction, and chat history management.
    Downloads: 0 This Week
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