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langgraph logo
langgraph is a free, open-source software / service you can self-host or use without paying. Low-level orchestration framework for building stateful agents. Trusted by companies shaping the future of agents – including Klarna, Replit, Elastic, and more – LangGraph is a low-level orchestration framework for building, managing, and deploying long-running, stateful agents. pip install -U langgraph Tip If you're looking to quickly build agents, check out Deep Agents — a higher-level package built on LangGraph for agents that can plan, use subagents, and leverage file systems for complex tasks. For an equivalent JS/TS library, check out LangGraph.js and the JS docs . Why use LangGraph? LangGraph provides low-level supporting infrastructure for any long-running, stateful workflow or agent: Durable execution — Build agents that persist through failures and can run for extended periods, automatically resuming from exactly where they left off. Human-in-the-loop — Seamlessly incorporate human oversight by inspecting and modifying agent state at any point during execution. Comprehensive memory — Create truly stateful agents with both short-term working memory for ongoing reasoning and long-term persistent memory across sessions. Debugging with LangSmith — Gain deep visibility into complex agent behavior with visualization tools that trace execution paths, capture state transitions, and provide detailed runtime metrics. Production-ready deployment — Deploy sophisticated agent systems confidently with scalable infrastructure designed to handle the unique challenges of stateful, long-running workflows. Tip For developing, debugging, and deploying AI agents and LLM applications, see LangSmith . LangGraph ecosystem While LangGraph can be used standalone, it also integrates seamlessly with any LangChain product, giving developers a full suite of tools for building agents. To improve your LLM application development, pair LangGraph with: Deep Agents – Build agents that can plan, use subagents, and leverage file systems for complex tasks. LangChain – Provides integrations and composable components to streamline LLM application development. LangSmith – Helpful for agent evals and observability. Debug poor-performing LLM app runs, evaluate agent trajectories, gain visibility in production, and improve performance over time. LangSmith Deployment – Deploy and scale agents effortlessly with a purpose-built deployment platform for long-running, stateful workflows. Discover, reuse, configure, and share agents across teams – and iterate quickly with visual prototyping in LangSmith Studio . Documentation docs.langchain.com – Comprehensive documentation, including conceptual overviews and guides reference.langchain.com/python/langgraph – API reference docs for LangGraph packages LangGraph Quickstart – Get started building with LangGraph Chat LangChain – Chat with the LangChain documentation and get answers to your questions Discussions : Visit the LangChain Forum to connect with the community and share all of your technical questions, ideas, and feedback. Additional resources Guides – Quick, actionable code snippets for topics such as streaming, adding memory & persistence, and design patterns (e.g. branching, subgraphs, etc.). LangChain Academy – Learn the basics of LangGraph in our free, structured course. Case studies – Hear how industry leaders use LangGraph to ship AI applications at scale. Contributing Guide – Learn how to contribute to LangChain projects and find good first issues. Code of Conduct – Our community guidelines and standards for participation. Acknowledgements LangGraph is inspired by Pregel and Apache Beam . The public interface draws inspiration from NetworkX . LangGraph is built by LangChain Inc, the creators of LangChain, but can be used without LangChain.
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docusaurus logo
docusaurus is a free, open-source alternative to GitBook . Docusaurus Introduction Docusaurus is a project for building, deploying, and maintaining open source project websites easily. Short on time? Check out our 5-minute tutorial ⏱️ ! Tip : use docusaurus.new to test Docusaurus immediately in a playground. Simple to Start Docusaurus is built in a way so that it can get running in as little time as possible. We've built Docusaurus to handle the website build process so you can focus on your project. Localizable Docusaurus ships with localization support via CrowdIn. Empower and grow your international community by translating your documentation. Customizable While Docusaurus ships with the key pages and sections you need to get started, including a home page, a docs section, a blog , and additional support pages, it is also customizable to ensure you have a site that is uniquely yours . Installation Use the initialization CLI to create your site: npm init docusaurus@latest Read the docs for any further information. Contributing We've released Docusaurus because it helps us better scale and supports the many OSS projects at Meta. We hope that other organizations can benefit from the project. We are thankful for any contributions from the community. Code of Conduct Meta has adopted a Code of Conduct that we expect project participants to adhere to. Please read the full text so that you can understand what actions will and will not be tolerated. Contributing guide Read our contributing guide to learn about our development process, how to propose bugfixes and improvements, and how to build and test your changes to Docusaurus. Beginner-friendly bugs To help you get your feet wet and get you familiar with our contribution process, we have a list of beginner-friendly bugs that might contain smaller issues to tackle first. This is a great place to get started. Contact We have a few channels for contact: Discord : #general for those using Docusaurus. #contributors for those wanting to contribute to the Docusaurus core. @docusaurus X GitHub Issues Contributors This project exists thanks to all the people who contribute. [ Contribute ]. Backers Thank you to all our backers! 🙏 Become a backer Sponsors Support this project by becoming a sponsor. Your logo will show up here with a link to your website. Become a sponsor License Docusaurus is MIT licensed . The Docusaurus documentation (e.g., .md files in the /docs folder) is Creative Commons licensed . Special thanks BrowserStack supports us with free access for open source . Rocket Validator helps us find HTML markup and accessibility issues .
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spacedrive logo
spacedrive is a free, open-source alternative to ExpanDrive . Spacedrive One file manager for all your devices and clouds. Powered by a Virtual Distributed File System, complete with apps for macOS, Windows, Linux, iOS and Android v2.spacedrive.com • Discord • Getting Started What is Spacedrive? Spacedrive is a cross-device data platform. Index files, emails, notes, and external sources. Search everything. Sync via P2P. Keep AI agents safe with built-in screening. Content identity — every file gets a BLAKE3 content hash. Same file on two devices produces the same hash. Spacedrive tracks redundancy and deduplication across all your machines. Cross-device — see all your files across all your devices in one place. Files on disconnected devices stay in the index and appear as offline. P2P sync — devices connect directly via Iroh/QUIC. No servers, no cloud, no single point of failure. Metadata syncs between devices. Files stay where they are. Cloud volumes — index S3, Google Drive, Dropbox, OneDrive, Azure, and GCS as first-class volumes alongside local storage. Nine views — grid, list, columns, media, size, recents, search, knowledge, and splat. QuickPreview for video, audio, code, documents, 3D, and images. Local-first — everything runs on your machine. No data leaves your device unless you choose to sync between your own devices. Is this a replacement for Finder or Explorer? No. Spacedrive sits above your OS file manager and adds capabilities Finder/Explorer lack: Portal across everything — search and browse files across local disks, external drives, NAS, cloud storage, and archived data sources from one interface. Operating surface for files — content identity, sidecars, derivative artifacts, rich metadata, sync, and cross-device awareness built into the core model. Embeddable and shareable — run it as a desktop app, headless server, hosted file service, or embed the interface and APIs into other products. AI-ready by design — indexing and analysis pipelines prepare data ahead of time instead of giving agents raw shell access. Safer access model — route AI and automation through structured APIs, permissions, and processing layers instead of direct file operations. You still use your OS for low-level file interactions. Spacedrive adds the cross-platform, cross-device, cloud-aware, and automation-friendly layer on top. Data Archival Spacedrive indexes external data sources via script-based adapters: Gmail, Apple Notes, Chrome bookmarks, Obsidian, Slack, GitHub, calendar events, contacts. Each source becomes a searchable repository alongside your files. Adapters are a folder with an adapter.toml manifest and a sync script in any language. If it reads stdin and prints lines, it works. Shipped adapters: Gmail, Apple Notes, Chrome Bookmarks, Chrome History, Safari History, Obsidian, OpenCode, Slack, macOS Contacts, macOS Calendar, GitHub. Spacebot Spacedrive integrates with Spacebot , an open source AI agent runtime. Spacebot runs as an optional separate process. Spacedrive provides the data, permission, and execution layer. Spacebot provides the intelligence. Each Spacebot instance pairs with one Spacedrive node as its home device. That node authenticates the agent, maintains the device graph, resolves permissions, and forwards operations to peer devices. Every device in your library can reach Spacebot through the paired node over P2P (Iroh/QUIC) without direct network access. One agent runtime serves your entire device fleet. When Spacebot spawns a worker, that worker can target any device in the library. File reads, shell commands, and operations proxy through Spacedrive to the target device. Talk to the agent from your phone while work executes on a server. Read files from a NAS, run commands on a workstation, report to a laptop — all in one task. Every operation passes through Spacedrive's permission system: which devices the agent can access, which paths are readable or writable, which operations are allowed, and which require human confirmation. The paired node resolves effective policy before forwarding. One security model, one audit surface across all devices and clouds. File System Intelligence Spacedrive adds intelligence to your filesystem by combining three layers: File intelligence — derivative data like OCR, transcripts, extracted metadata, thumbnails, previews, classifications, and sidecars. Directory intelligence — contextual knowledge attached to folders and subtrees ("active projects", "dormant archives", etc). Access intelligence — permissions and policy that apply across devices and clouds, routing agents through structured access instead of raw shell commands. When an agent navigates through Spacedrive, it receives the file listing, subtree context, effective permissions, and summaries. Users can explain how they organize their system. Agents can add attributed notes. Jobs generate summaries from structure and activity. The intelligence stays attached to the filesystem, not buried in temporary session memory. Safety Screening When enabled, every record passes through a safety pipeline before becoming searchable: Prompt Guard 2 — local classifier detects prompt injection in emails, messages, and documents before they enter the index. Trust tiers — authored content (your notes) gets balanced screening, external content (email inbox) gets strict screening. Quarantine system — flagged records excluded from AI agent queries, reviewable in desktop app. Content fencing — search results include trust metadata so agents know what's safe vs untrusted. No other local data tool screens indexed content before exposing it to AI. Architecture The core is built on four principles: Virtual Distributed Filesystem (VDFS) — files and folders become first-class objects with rich metadata, independent of physical location. Every file gets a universal address ( SdPath ) that works across devices. Content Identity System — adaptive hashing (BLAKE3 with strategic sampling for large files) creates a unique fingerprint for every piece of content. Enables deduplication, redundancy tracking, and content-based operations. Transactional Actions — every file operation can be previewed before execution. See space savings, conflicts, and estimated time, then approve or cancel. Operations become durable jobs that survive network interruptions and device restarts. Leaderless Sync — peer-to-peer synchronization without central coordinators. Device-specific data uses state replication. Shared metadata uses an HLC-ordered log with deterministic conflict resolution. The implementation is a single Rust crate with CQRS/DDD architecture. Every operation (file copy, tag create, search query) is a registered action or query with type-safe input/output that auto-generates TypeScript types for the frontend. Component Technology Language Rust Async runtime Tokio Database SQLite (SeaORM + sqlx) P2P Iroh (QUIC, hole-punching, local discovery) Content hashing BLAKE3 Vector search LanceDB + FastEmbed Cloud storage OpenDAL Cryptography Ed25519, X25519, ChaCha20-Poly1305, AES-GCM Media FFmpeg, libheif, Pdfium, Whisper Desktop Tauri 2 Mobile React Native + Expo Frontend React 19, Vite, TanStack Query, Tailwind CSS v4 Design system SpaceUI (shared component library) Type generation Specta spacedrive/ ├── core/ # Rust engine (CQRS/DDD) ├── apps/ │ ├── tauri/ # Desktop app (macOS, Windows, Linux) │ ├── mobile/ # React Native (iOS, Android) │ ├── cli/ # CLI and daemon │ ├── server/ # Headless server │ └── web/ # Browser client ├── packages/ │ ├── interface/ # Shared React UI │ ├── ts-client/ # Auto-generated TypeScript client │ ├── ui/ # Component library │ └── assets/ # Icons, images, SVGs ├── crates/ # Standalone Rust crates (ffmpeg, crypto, etc.) ├── adapters/ # Script-based data source adapters └── schemas/ # TOML data type schemas Getting Started Requires Rust 1.81+, Bun 1.3+, just , and Python 3.9+ (for adapters). git clone https://github.com/spacedriveapp/spacedrive cd spacedrive just setup # bun install + native deps + cargo config just dev-desktop # launch the desktop app (auto-starts daemon) just test # run all workspace tests Privacy & Security Spacedrive is local-first. Your data stays on your devices. End-to-End Encryption — all P2P traffic encrypted via QUIC/TLS At-Rest Encryption — libraries can be encrypted on disk (SQLCipher) No Telemetry — zero tracking or analytics Self-Hostable — run your own relay servers Data Sovereignty — you control where your data lives Optional cloud integration is available for backup and remote access, but it's never required. The cloud service runs unmodified Spacedrive core as a standard P2P device—no special privileges. Contributing Join Discord to chat with developers and community Contributing Guide Adapter Guide — write a data source adapter SpaceUI — shared design system (clone alongside Spacedrive to work on UI) License FSL-1.1-ALv2 — Functional Source License , converting to Apache 2.0 after two years.
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