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Source channel @githubtrending · Post #14827 · Jun 12

#typescript#desktop#docx#electron#html#languages#libreoffice#linux#macos#markdown#nodejs#office#offline#pandoc#pdf#productivity#windows#zettlr Zettlr is a free, open-source app that helps you write, organize, and publish your notes and documents using simple Markdown files. It works on Windows, macOS, and Linux, and lets you manage your notes with features like workspaces, tags, and powerful search, so you can quickly find what you need. Zettlr supports easy citations with reference managers like Zotero, offers code highlighting, dark mode, and flexible export options to PDF, Word, or LaTeX, making it ideal for students, researchers, and writers who want a privacy-focused, distraction-free way to work with their ideas and publish their work[1][3][5]. The benefit is that you can focus on your content, not formatting, and easily turn your notes into professional documents. https://github.com/Zettlr/Zettlr

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@githubtrending · Post #15523 · 02/25/2026, 12:30 PM

#typescript#agent#agentic#agentic_framework#agentic_workflow#ai#ai_agents#bytedance#deep_research#harness#langchain#langgraph#langmanus#llm#multi_agent#nodejs#podcast#python#superagent#typescript DeerFlow 2.0 is an open-source super agent harness that orchestrates multiple sub-agents, memory systems, and sandboxed execution environments to accomplish complex tasks. Built on LangGraph and LangChain, it combines research, coding, and content creation capabilities with extensible skills and tools. The platform features isolated Docker containers for safe execution, long-term memory that learns your preferences, and the ability to spawn sub-agents that work in parallel on different task angles. You benefit from dramatically reduced research and automation time—tasks that typically take hours complete in minutes—while maintaining full transparency and control over agent decisions through human-in-the-loop collaboration. Whether you need deep research reports, data analysis, slide decks, or custom workflows, DeerFlow handles multi-step complexity without requiring extensive coding knowledge. https://github.com/bytedance/deer-flow