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Project Jupyter is an open-source web-based interactive computing platform centered on notebooks and computational kernels. JupyterLab provides a configurable interface for notebooks, code, and data, while the classic Jupyter Notebook offers a document-oriented web application for creating and sharing computational documents. Notebooks combine executable code with narrative text, equations, visualizations, and rich outputs, and use a JSON-based document format; kernels run code in a selected programming language and communicate with the notebook through a JSON-based interactive computing protocol over ZeroMQ and WebSockets. Jupyter supports more than 40 languages, including Python, R, Julia, and Scala, and includes JupyterHub for centrally deployed multi-user environments and Voilà for turning notebooks into stand-alone web applications.

PI-Desktop is a local-first desktop workspace for AI coding agents, built with Electron, a Rust host core, and the pi Agent Harness. It lets users open local projects, connect cloud or local models through providers such as OpenAI-compatible APIs, manage projects and long-running sessions, and review file changes and command output. Its architecture separates the React renderer, Electron desktop orchestration, Rust-managed permissions, filesystem access, SQLite persistence and secrets, and a pi Agent sidecar responsible for the agent loop, model interaction, and streaming. Agent, Plan, and Goal modes provide different approval boundaries; agents can read and edit files, run commands, and delegate exploration, implementation, research, testing, or review to background Subagents. The workspace supports MCP servers, Skills, installable Plugins, model and provider switching, session imports, notifications, context checkpoints, and a plugin marketplace. Conversations are stored locally as JSONL with a SQLite index, settings and logs remain on the machine, credentials use the operating-system keychain, and model requests go directly to the configured provider or endpoint. Plugin processes are permission-gated and isolated from the renderer, but plugins remain user-trusted code rather than a complete operating-system sandbox. It is an early-preview cross-platform application distributed for macOS, Windows, and Linux under the GNU Lesser General Public License v3.0.

LibreChat is an open-source, self-hosted AI chat platform that provides a ChatGPT-inspired interface for connecting to major AI providers and custom OpenAI-compatible endpoints. It supports model switching, multimodal file interactions, web search, speech-to-text and text-to-speech, image generation, conversation search, presets, branching, resumable streams, and a sandboxed Code Interpreter for languages including Python, JavaScript/TypeScript, Go, C/C++, Java, PHP, Rust, and Fortran. Its agent system supports no-code custom assistants, community-shared agents, MCP servers, tools, file search, code execution, reusable SKILL.md instruction bundles, subagents, and an Agent Management API. Agents can optionally use attached workspaces to inspect, search, edit, and run commands in bounded environments. The platform also provides generative UI artifacts, including React, HTML, and Mermaid content, plus custom actions and integrations with providers such as Anthropic, AWS Bedrock, OpenAI, Azure OpenAI, Google, Vertex AI, Ollama, Groq, Mistral, OpenRouter, and others. LibreChat includes multi-user authentication through OAuth2, LDAP, and email login; browser-based administration of users, groups, roles, and configuration; role-based permissions; observability through OpenTelemetry and Langfuse; Redis-backed synchronization for scaled deployments; and Docker Compose deployment options. It is built in public and intended for local or cloud self-hosting.

Codeman is a self-hosted web dashboard for running and monitoring AI coding agents. It launches Claude Code, OpenCode, Codex, Antigravity, Gemini, Pi, or Grok in persistent tmux sessions, with an optional plain shell, and streams their terminals to a browser. Sessions persist across restarts and network drops; idle detection can re-prompt agents, resume them after usage limits reset, and run scheduled jobs, while live floating windows show background agents and subagents. The dashboard is designed for touch devices and includes local echo, QR login, swipe navigation, and push notifications. It can run locally, in Docker, or over SSH, is MIT licensed, runs on the user's machine by default, and states that it has no telemetry.

Agent Deck is an open-source terminal dashboard for running and monitoring multiple AI coding agents in parallel. It displays each session’s status, active tool, working directory, and last prompt in real time, with Vim-style keyboard navigation for creating, focusing, closing, and renaming panes. It supports Claude Code and OpenCode through automatically installed hooks and runs as the single-binary `dot-agent-deck`, with native embedded terminal panes and no external terminal multiplexer required. The dashboard runs inside terminals including Ghostty, iTerm2, Alacritty, Kitty, and WezTerm, while preserving the agent clients’ existing shortcuts, skills, and configurations. Per-project TOML configuration can pair an agent with side panes for test runs, log tails, or `kubectl` watches. macOS and Linux installation is available through Homebrew, Nix, prebuilt binaries, or source builds; Windows use is currently through WSL. The project is distributed under the MIT license.