Продуктивность
Logseq
Logseq — a privacy-first platform for knowledge management: an outliner over your local Markdown files, with a graph, journals and spaced repetition built in
★ 45,3 тыс. звёздAGPL-3.0
Смотреть руководство →open-science — проект с открытым исходным кодом из категории «Продуктивность» от aipoch (aipoch/open-science на GitHub). У него 5 499 звёзд на GitHub и 510 форков, он распространяется по лицензии Apache-2.0 и последний раз обновлялся на GitHub 8 октября 2026.
A local-first, model-agnostic AI research workbench for reproducible scientific work.
Define the question and the evidence standard — for example, a systematic review with traceable sources.
Install via Homebrew on macOS, download a desktop build, or clone the repo to run from source.
Connect your model provider (the app is model-agnostic) and configure any Python/R environments and connectors.
Create a project, run a task with a skill such as literature-review, and review the report with its evidence trail.
Every report, table and figure can be traced back to its evidence, supporting reproducible research.
Ships agent skills (for example literature review) and supports MCP tools and connectors to extend the workbench.
Runs analysis code in app-managed or user-configured Python/R environments as part of a research task.
Works with the model provider you choose while projects and artifacts stay on your machine.
Work can be packaged as .science research packages for sharing and revisiting complete, evidenced results.
A CLI can initialize a profile, create projects, run tasks with approval profiles and download artifacts — no GUI required.
Clone Open Science if you want to run from source; macOS users can instead brew install --cask open-science.
git clone https://github.com/aipoch/open-science.git
cd open-scienceInstall dependencies and start the desktop app in development mode.
npm install
npm run devInitialize the CLI profile, create a project and run a task with a skill.
open-science init
open-science start --no-open
open-science run --project "Systematic review" --prompt-file ./task.md --skill literature-review --wait --jsonOpen Science is maintained by aipoch, with the product page at aipoch.com/open-science.
Yes — it is open source under the Apache-2.0 license. You pay for the model provider you connect.
It is model-agnostic: you connect a model provider of your choice, so you need an account or key for that provider (or a compatible local endpoint).
Chat assistants produce unverifiable text; Open Science executes inspectable tools, keeps artifacts, and traces every result back to evidence inside a local-first workbench.
Install the app (brew install --cask open-science on macOS), complete setup with your model provider, and create your first project.
Logseq — a privacy-first platform for knowledge management: an outliner over your local Markdown files, with a graph, journals and spaced repetition built in
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Другие проекты из категории «Продуктивность» с наибольшим числом звёзд в каталоге LibreAI — реалистичный список альтернатив, если open-science вам не подходит.
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Logseq — a privacy-first platform for knowledge management: an outliner over your local Markdown files, with a graph, journals and spaced repetition built in
Соседние проекты из категории «Продуктивность» в каталоге, ближайшие по числу звёзд к open-science — продолжайте изучать полку по обе стороны от него.
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Бесплатно и открыто — забирайте исходный код, ставьте звезду репозиторию и начинайте создавать.