neuron-explorer
Qwen3.5‑4B 전용 조향형 뉴런 탐색기, 모든 MLP 뉴런을 밀어 결과를 보관·탐색
직접 관리 인프라에서 자율 에이전트를 실행하고, Opengeni는 지속 실행·인간 승인·모델 선택을 지원하는 오픈소스 AI 플랫폼이다
Run autonomous agents on infrastructure you control. Opengeni is the open-source sovereign AI harness for durable execution, human approvals, and model choice.
개발 도구TypeScript · RustGitHub @Cloudgeni-ai온라인운영자 미확인
써 보셨어요? 한 번만 눌러 주세요. 로그인은 필요 없어요.
Open, self-hostable agentic runtime for organizations — durable, replayable agent sessions, human approvals, governed credentials and memory, running in managed sandboxes or on your own hardware. Apache-2.0.
저장소 README에서 가져옴
README 전체를 불러오는 중입니다. 아래는 저장된 발췌입니다.
Production-ready self-hostable agentic service.
Opengeni is a production-ready agentic service: it runs AI agents that do real work, keeps a session going for hours or days, records every step in a replayable event log, stops for a human when an action needs approval, and puts each session either in a managed sandbox or directly on a machine you own.README 전문 보기 ↗Opengeni is a production-ready agentic service: it runs AI agents that do real work, keeps a session going for hours or days, records every step in a replayable event log, stops for a human when an action needs approval, and puts each session either in a managed sandbox or directly on a machine you own.
Opengeni is not the agent; it is everything the agent needs around it. Give agents work from the web app and follow along, or call the same session API from your own product and let Opengeni hold the state, history, approvals, and outputs. It grew out of two years of running agents against production cloud infrastructure at Cloudgeni.
The fastest way is the managed service. Sign up at app.opengeni.ai, name your organization, connect a model (a ChatGPT/Codex or SuperGrok subscription, a provider key, or prepaid credits), and start your first session. Nothing to deploy. The quickstart walks through it.
Prefer to run it yourself? Everything is open source. Jump to Run it locally for a one-command dev stack, or to Self-host for production.
SessionConversation React component behind a packaged, tenant- and user-scoped proxy on your server. Your organization API key stays there.Repository changes land through the merge batcher: queued PRs are tested together on the combined tree and each lands as one squash commit. Main runs the full suite on a cadence and is the release gate.
For development, or to evaluate Opengeni before self-hosting. You need Bun at the exact version in .bun-version, Git, curl, Docker, rustup, a C compiler (Xcode Command Line Tools on macOS or build-essential on Debian/Ubuntu), and an OpenAI or Azure OpenAI key.
git clone https://github.com/Cloudgeni-ai/opengeni.git
cd opengeni
cp .env.example .env # add your model credentials
bun run dev
Open http://127.0.0.1:3000, describe a task, and watch the session run.
bun run dev installs dependencies, starts Postgres, NATS, Temporal, and object storage, runs migrations, and starts the API, workers, and web app. By default the agent runs commands directly on your machine (the local sandbox), not in an isolated container, so the API and web app listen only on 127.0.0.1. Set OPENGENI_SANDBOX_BACKEND=docker to run the agent in the local sandbox image instead. See Local development for manual startup, configuration, network exposure, and the native (no Docker) path.
Opengeni for macOS, Windows and Linux: your sessions, chat and inbox in a native window, with notifications and one click to let agents use the computer you're on.
# macOS
brew install --cask cloudgeni-ai/tap/opengeni
# macOS or Linux (deb, rpm or AppImage, picked for your system)
curl -fsSL https://<your-opengeni-server>/desktop/install.sh | sh
On Windows, download Opengeni-<version>-windows.exe from the newest desktop-v release. The web app's account menu has the same downloads under Desktop app. Every way of installing updates itself afterwards.
Let your coding agent do it. Install the Opengeni plugin, then ask your agent to add Opengeni to your product:
# Claude Code
claude plugin marketplace add Cloudgeni-ai/opengeni
claude plugin install opengeni@opengeni --scope user
# Codex (CLI, IDE, and the Codex app)
codex plugin marketplace add Cloudgeni-ai/opengeni
codex plugin add opengeni@opengeni
In Cursor, use Customize → From GitHub Repository with this repository. The plugin adds the Opengeni skills and connects your agent to your organization over MCP (sign in once in the browser). See the plugin guide.
Or wire it yourself — one server route and one component:
// app/api/opengeni/[...path]/route.ts (server only; the key stays here)
import { Opengeni } from "@opengeni/sdk/chat";
import { createSessionProxyRoute } from "@opengeni/sdk/next";
const og = new Opengeni({ apiKey: process.env.OPENGENI_API_KEY! });
export const { GET, POST, PUT, PATCH, DELETE } = createSessionProxyRoute(og, {
resolve: async (request) => {
const me = await authenticate(request); // your product's own auth
if (!me) return new Response("Unauthorized", { status: 401 });
return { user: me.id, tenant: me.teamId }; // workspaces and members are created on first use
},
createSession: (input) => input,
});
// Browser
import { OpenGeniChat } from "@opengeni/react";
import "@opengeni/react/compiled.css";
<OpenGeniChat baseUrl="/api/opengeni" />;
Follow Embed manually for the details, then the TypeScript SDK and React components. Northstar support is a runnable SaaS embed with a product MCP server.
"Agent" is one word for at least ten different jobs. A model is a function from tokens to tokens: it forgets everything between calls, has no idea what it is allowed to do, and has no obligation to keep working until the job is done. Everything above it exists to turn that into work that finishes, can be trusted with real systems, and can be explained afterwards.
Opengeni is built as those layers.
┌───────────────┐ ┌───────────────────────────────────────────────────────┐
│ │ │ 10 SURFACES console · embedded UI · Slack · │
│ 8 GOVERNANCE │ │ voice · SDK · API │
│ │ ├───────────────────────────────────────────────────────┤
│ identity │ │ 9 KNOWLEDGE scoped retrieval · reviewed │
│ tenancy │ │ learning · never mixed with chat │
│ permissions │ ├───────────────────────────────────────────────────────┤
│ secrets │ │ 7 DURABLE STATE sessions · turns · goals · │
│ approvals │ │ & ORCHESTRATION recovery · human-in-the-loop │
│ audit │ ├───────────────────────────────────────────────────────┤
│ │ │ 6 COMPUTE sandboxes · browsers · │
│ + │ │ your own machines │
│ │ ├───────────────────────────────────────────────────────┤
│ OBSERVABILITY │ │ 5 TOOLS one gateway · MCP · connections · │
│ & COST │ │ credentials outside the prompt │
│ │ ├───────────────────────────────────────────────────────┤
│ every call │ │ 4 AGENT LOOP cache-stable prompt · gradual │
│ records what │ │ tool disclosure · exact history │
│ it cost and │ ├───────────────────────────────────────────────────────┤
│ who pays │ │ 3 MODEL ROUTING allowed models · fallback · │
│ │ │ capacity waits · billing │
│ │ ├───────────────────────────────────────────────────────┤
│ │ │ 1-2 INFERENCE any provider · any wire format · │
│ │ │ swappable mid-conversation │
└───────────────┘ └───────────────────────────────────────────────────────┘
Rent the edges, own the middle. Models, provider APIs, and the raw compute box change too fast to own, so every one of them is a swappable boundary. Durable state, governance, and knowledge are where your workflows, permissions, audit record, and institutional memory actually live, so they sit in a Postgres database you operate, export, and can leave with.
| I want to... | Read |
|---|---|
| Start on the managed service | Quickstart |
| Run it locally | Local development |
| Deploy to production | Self-host · Deployment guide |
| Add agents to my product | Product integration · SDK reference |
| Run sessions on my own hardware | Connect a machine · Connected Machines |
| Call the HTTP API directly | HTTP API overview |
| Configure models and providers | Model providers |
| Give agents repository access | GitHub App |
| Understand goals, approvals, memory | Goals · Human input · |
The public product docs live at docs.opengeni.ai, and the thinking behind the layers above is on the Opengeni blog. The Cloudgeni Infrastructure Agents Guide covers patterns for infrastructure-focused agents.
Bun · Hono · React and Vite · Temporal · Postgres with pgvector · NATS · OpenAI Agents SDK · a Rust agent and relay for Connected Machines
Do not expose a production deployment without a deliberate access mode, tested database role posture, rate limits, and a reviewed sandbox credential policy. See the security boundary and report vulnerabilities through SECURITY.md.
Contributions are welcome. Read CONTRIBUTING.md for setup, checks, and the pull request workflow, and AGENTS.md if you work on Opengeni itself.
bun run typecheck
bun test
Apache-2.0. Optional curated Skills under packages/runtime/src/curated_skill_library carry their own provenance and license metadata; HashiCorp-derived Terraform guidance is MPL-2.0 and is never mounted by default.
| Understand the internals | Architecture · Run lifecycle · Docs map |
| See what is planned | Roadmap |