Showing 4 open source projects for "markdown"

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    Reor Project

    Reor Project

    Private & local AI personal knowledge management app

    Reor is an AI-powered desktop note-taking app: it automatically links related notes, answers questions on your notes, provides semantic search and can generate AI flashcards. Everything is stored locally and you can edit your notes with an Obsidian-like markdown editor. The hypothesis of the project is that AI tools for thought should run models locally by default. Reor stands on the shoulders of the giants Ollama, Transformers.js & LanceDB to enable both LLMs and embedding models to run locally.
    Downloads: 0 This Week
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  • 2
    Eigenfocus

    Eigenfocus

    Self-Hosted - Project Management, Planning and Time Tracker

    Eigenfocus is an AI-powered personal knowledge management system that uses embeddings and semantic search to help users organize and retrieve ideas across documents. Designed for researchers and creatives, it enables deep linking between notes and supports querying based on meaning rather than keywords.
    Downloads: 1 This Week
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  • 3
    QMD

    QMD

    mini cli search engine for your docs, knowledge bases, etc.

    QMD is a powerful and lightweight command-line tool that acts as an on-device search engine for your personal knowledge base, allowing you to index and search files like Markdown notes, meeting transcripts, technical documentation, and other text collections without depending on cloud services. Designed to keep all search activity local, it combines classic full-text search techniques with modern semantic features such as vector similarity and hybrid ranking so that queries return not just literal matches but conceptually relevant results. ...
    Downloads: 1 This Week
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  • 4
    trimwise

    trimwise

    Query-aware prompt compression for high-signal LLM prompts.

    Trimwise is an extractive Python library for the step between collecting text and assembling a prompt. Give it a document, a maximum size, and optionally the task you care about. It selects useful fragments from across the document, returns them in source order, and guarantees that the measured result stays within your token, word, or character limit. This is especially useful when an agent has several sources but cannot place every source in the context window. Instead of taking the...
    Downloads: 0 This Week
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