WeKnora

LLM Wiki is a cross-platform desktop application maintained by nash_su that turns imported documents into a persistent, organized, interlinked knowledge base. It uses a three-layer structure of immutable raw sources, LLM-generated wiki pages, and configuration rules, with ingest, query, and lint operations; generated pages use YAML frontmatter, source traceability, an index, an operation log, and [[wikilink]] cross-references. Its ingest pipeline first analyzes each source for entities, concepts, connections, contradictions, and recommended structure, then generates or updates wiki pages, summaries, indexes, research queries, and human-review items. SHA256 caching skips unchanged files, while a persistent queue supports serialized processing, retries, cancellation, and crash recovery. It accepts PDFs, Office documents, EPUB/MOBI, Org mode, images, media, web clips, and URL batches, with optional vision-based image captions and MinerU processing for complex PDFs. Retrieval combines tokenized keyword search, optional LanceDB vector search through OpenAI-compatible embedding endpoints, and graph expansion based on direct links, shared sources, Adamic-Adar similarity, and page-type affinity. The application also provides Louvain community detection, graph insights, deep research through Tavily, SerpApi, or SearXNG, a Rust tool-using chat agent, review workflows, Mermaid and KaTeX rendering, a Chrome web clipper, and project export/import. It includes a token-protected local HTTP API and MCP server for searching, reading files, traversing the graph, rescanning sources, and calling the backend agent. The application is built with Tauri v2, React, TypeScript, and Rust, has macOS, Windows, and Linux builds, and is licensed under GPL-3.0.

Alexandrie is a self-hosted, open-source knowledge base and wiki for teams and individuals, positioned as an alternative to Notion, Confluence, and Obsidian. It uses an extended CodeMirror 6 Markdown editor with support for LaTeX, custom containers, interactive checkboxes, snippets, speech-to-text, and embedded diagram creation. Notes are organized through multi-tenant teams, workspaces, categories, and nested documents, with full-text search, a command center, integrated Kanban boards, public links, and node- or workspace-level permissions ranging from no access to owner. It is distributed as an offline-first progressive web app with synchronization, OIDC/SSO support, Docker deployment, backup and restore pipelines, and S3-compatible media and backup storage.

Project NOMAD is an offline-first knowledge and education server from Crosstalk Solutions. It provides a browser-based Command Center and API that orchestrate containerized resources and applications through Docker on Debian-based systems, allowing the installation, configuration, and updating of an offline knowledge environment. Its capabilities include offline Wikipedia and reference libraries through Kiwix, Khan Academy courses and progress tracking through Kolibri, downloadable regional maps through ProtoMaps, CyberChef data tools, FlatNotes markdown notes, a one-click application catalog, and support for custom Docker containers. Its optional AI Assistant uses Ollama or an OpenAI-compatible server such as LM Studio or llama.cpp, with document uploads and semantic search implemented through Qdrant-based retrieval-augmented generation. An internet connection is required for installation and optional later downloads; the installed system is designed to operate offline and the project states that it has no built-in telemetry. It can be installed through a terminal-based script or Docker Compose, is licensed under Apache License 2.0, and does not currently include authentication, so the project advises against exposing an instance directly to the internet.

DeepTutor is an open-source, self-hostable AI tutoring platform developed by HKUDS for lifelong personalized tutoring. It provides a web application and command-line interface for interactive learning, problem solving, quiz generation, deep research, visualization, and mastery practice, with persistent memory and learning state shared across knowledge bases, books, notebooks, tutor personas, and other activities. The platform supports multi-agent problem solving, retrieval-augmented learning with source-traced and page-level citations, math animations, interactive visualizations, and tutor bots built from personal study materials. Its knowledge sources include personal documents, EPUBs and books with annotations, GitHub repositories, web search, and connected libraries; documented retrieval and ingestion options include GraphRAG, PageIndex, LightRAG, linked knowledge bases, Obsidian, and configurable parsing and vector backends. DeepTutor also includes courses, research workflows, an ecosystem of MCP services and tool or capability plugins, and integrations with connected coding agents and other partners. It can run locally or through Docker.