Local Quantitative Glass Box AI Intelligence
git clone https://github.com/FantasyLab-ai/auroraResumen de Tools
<!-- mcp-name: io.github.FantasyLab-ai/aurora --> <div align="center"> <img src="docs/screenshots/aurora-mascot-wizard.png" alt="Aurora" width="200"/> # Aurora ### Glass-box quantitative intelligence. Local. Open. Cited. Aurora is the **verification cortex** for serious quantitative work — for humans analyzing hard data, and for AI systems that can't afford to hallucinate. > **Cloud LLMs guess. Aurora computes.** [](LICENSE) [](https://python.org) [](#) [](#) [](https://www.patreon.com/c/FantasyLab3DStudio) **[⬇️ Download the desktop app](#%EF%B8%8F-download-the-desktop-app)** · [Run from source](#-quickstart-60-seconds) · [Aurora Sentinel demos](#-aurora-sentinel--decision-contracts-in-the-room) · [See it in action](#see-aurora-in-action) · [Aurora Copilot](#-aurora-copilot--for-humans) · [Aurora Cortex (MCP + SDK)](#%EF%B8%8F-aurora-cortex--for-ai-systems) · [Roadmap](ROADMAP.md) · [FantasyLab.ai](https://fantasylab.ai) </div> --- ## ⬇️ Download the desktop app **The easiest way to run Aurora — no Python, no terminal, no setup.** Download the installer for your OS, double-click, and Aurora opens as a native app with the analysis backend bundled inside it. ### → [**Download the latest release**](https://github.com/FantasyLab-ai/aurora/releases/latest) Pick the file that matches your OS (filenames carry the version, e.g. `0.2.0`): | OS | File to download | Install | |---|---|---| | **Windows 10/11** | `Aurora_x.x.x_x64-setup.exe` **(recommended)** | Run the setup wizard. | | Windows 10/11 | `Aurora_x.x.x_x64_en-US.msi` | Alternative MSI installer (same app). | | **macOS** (Apple Silicon · M1/M2/M3/M4) | `Aurora_x.x.x_aarch64.dmg` | Open the `.dmg`, drag Aurora to Applications. | | **Linux** (Debian / Ubuntu / Mint) | `Aurora_x.x.x_amd64.deb` | `sudo apt install ./Aurora_x.x.x_amd64.deb` | | **Linux** (Fedora / RHEL / openSUSE) | `Aurora-x.x.x-1.x86_64.rpm` | `sudo dnf install ./Aurora-x.x.x-1.x86_64.rpm` | > `Aurora_aarch64.app.tar.gz` is an auto-updater artifact, **not** a download — > use the `.dmg` on macOS. There is currently no Intel-Mac (`x86_64`) or Linux > AppImage build; Intel-Mac users can [run from source](#-quickstart-60-seconds). On first launch Aurora bootstraps a small knowledge-bank seed, then runs **fully offline** — no API keys, no cloud, no telemetry. Drop a CSV on the window and watch it analyze. Aurora is **local-first: your data never leaves your machine** unless you explicitly share a single finding — see [PRIVACY.md](PRIVACY.md). > **Heads up on the "Unknown Publisher" warning.** Current releases are not yet > code-signed, so Windows SmartScreen may show *"Windows protected your PC"* and > macOS Gatekeeper may say *"unidentified developer."* This is expected for a > young open-source project. On Windows: **More info → Run anyway**. On macOS: > **right-click the app → Open**. Code-signing is on the roadmap. ### Desktop app — tips & known quirks A few things that are **expected behavior**, not bugs: - **First launch shows a welcome screen, not a run.** That's intentional — a fresh start is clean. Drop a CSV (or click a demo card) to begin; your past runs are always available under **Data → Bundles**. - **Give the backend a few seconds on first launch.** Aurora starts a local analysis server (`127.0.0.1:8001`) the first time you open it; the status dot reads "connecting…" for ~5–10 s before it goes live. If it lingers, the app is still warming up — it is not frozen. - **Big datasets take longer, and results land all at once.** A large file can spend a while in *"analyzing…"*. When it finishes you'll see *"analysis complete"* and the views populate. If the Overview looks momentarily empty right after completion, give it a few seconds or click another tab and back — the assembled state is still being fetched, and it will fill in. - **Re-running the same file is instant.** Identical data + settings reuse a cached analysis; the banner reads *"instant · cached."* That's a speed win, not a skipped run. - **Knowledge Bank starts small on a fresh install.** The bundled app ships with a seed bank that grows over time; the large multi-thousand-entry bank you may see in screenshots is built up on a machine that's been ingesting data for a while. Citations still work against whatever is local. Want to build it yourself or run from source? Keep reading. --- ## ⚡ Quickstart (60 seconds) ```bash # 1. Clone + create a virtualenv git clone https://github.com/FantasyLab-ai/aurora.git cd aurora python -m venv .venv # Windows: .\.venv\Scripts\Activate.ps1 # macOS / Linux: source .venv/bin/activate # 2. Install pip install -r requirements.txt # 3. Run the Studio python studio_api.py ``` Open <http://127.0.0.1:8000>. Click **▶ Try a demo** for an instant smoke test, or drop your own CSV / Parquet / JSON / XLSX. > First run will download a small knowledge-bank seed (~50 MB). After that, Aurora runs **fully offline** — no API keys, no cloud, no telemetry. **Optional extras** (only if you need them): ```bash pip install cryptography # Ed25519 bundle signing pip install mcp # MCP server for LLM agents (Claude Desktop, Cursor, etc.) pip install -r requirements-dev.txt # contributor / test extras ``` For the optional Vite + TypeScript frontend build (developers only), see [§ Optional frontend build](#optional-enhanced-frontend-build). --- ## 🖥️ The desktop app A native, installable app — frameless window, sidebar navigation, drag-and-drop any file onto it. Built with Tauri 2, with Aurora's **full analysis backend bundled inside the installer**, so it runs with zero setup: no Python, no venv, no terminal. > **Most people should just [download it](#%EF%B8%8F-download-the-desktop-app).** > The rest of this section is for developers who want to build it from > source or hack on the UI. ### What it does | Surface | Behavior | |---|---| | Frameless window | Rounded card on transparent OS background; `aurora ◆` titlebar with min/max/close | | Sidebar (left) | Workspace · Data · Full Studio sections + live "aurora: online / offline" status dot | | Tab strip (top) | Overview / Findings / Data with one shared sliding underline | | **Drag & drop ANY file** | CSV, TSV, JSON, JSONL, Parquet, XLSX — drop anywhere on the window, or click to browse | | Overview | Stat cards (Findings · Methods · Anomalies · Regimes) + **Aurora's narrative** in plain English | | Findings | Severity-filtered card grid; **click a card for the full evidence panel** | | Methods | Per-run method tally with share-bars | | Datasets | Bundled fixtures + demo datasets — **click any card to run it** | | Bundles | Past runs — every signed `.aurora.json` on disk, status-coded | | Aurora Studio sidebar | Full legacy UI in an iframe — every feature still reachable | ### Build it from source / develop The desktop app lives in [`desktop/`](desktop/). To build the installer yourself (PyInstaller backend + Tauri shell) or run the UI in hot-reload dev mode, see **[`desktop/README.md`](desktop/README.md)** — it covers the prerequisites (Node, Rust), the one-command launcher (`launch.ps1`), the installer build (`build_installer.ps1`), and the Windows Smart App Control caveat. A `git tag vX.Y.Z` push triggers the cross-platform release CI. --- ## 🚨 Aurora Sentinel — Decision Contracts in the room Aurora ships a complete **demo rig** under [`demos/`](demos/) that turns a Decision Contract trip into something tangible — a Discord ping, a Slack alert, an OBS overlay card, a smart-plug flipping in your room. Five "I gave my local AI X and watch what it caught" videos, all built on the same scaffolding. | # | Demo | Hero shot | What it shows | |---|---|---|---| | 1 | **Aurora Alarm** | A physical light flips when the data breaks | The closed loop is real — software → cited reason → real-world consequence | | 2 | **Community Sentinel** | A Discord embed lands with method + row + |z|σ | Drop-in for any Discord community; cited anomalies, no cloud | | 3 | **The Save** | A Slack ping arrives at the regime shift | The "human watching dashboards would have slept through this" demo | | 4 | **Verification Cortex** | An agent calls Aurora's MCP and acts on a *verified* number | Sells the agent-builder use case; no more confidently-wrong z-scores | | 5 | **Rediscover the Law** | Aurora derives `y = ½·a·t²` from a falling-ball video | The flagship hook — a free local AI rediscovers gravity, cited to SINDy | **Quickstart for the demos** (after the install above): ```bash # Generate the synthetic datasets one time: python -m demos.datasets.falling_ball.generate python -m demos.datasets.server_metrics.generate # Install the demo contracts into Aurora's contracts dir: cp demos/contracts/*.json ~/.aurora/decision_contracts/ # macOS / Linux copy demos\contracts\*.json $env:USERPROFILE\.aurora\decision_contracts\ # Windows # Configure your webhooks once (copy the template + paste your URLs): cp demos/.env.demos.example demos/.env.demos # macOS / Linux copy demos\.env.demos.example demos\.env.demos # Windows # Run the relay (it reads .env.demos for Discord/Slack URLs): python -m demos.relay.app ``` Full step-by-step recording walkthrough with OBS setup, contract installation, and a per-demo runbook lives at **[`demos/README.md`](demos/README.md)**. --- ## See Aurora in action A real run on an environmental air-quality dataset — captured straight from a Studio session. <div align="center"> <img src="docs/screenshots/07-summary-run.png" alt="Aurora run summary banner — domain selec
Lo que la gente pregunta sobre aurora
¿Qué es FantasyLab-ai/aurora?
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FantasyLab-ai/aurora es tools para el ecosistema de Claude AI. Local Quantitative Glass Box AI Intelligence Tiene 5 estrellas en GitHub y se actualizó por última vez today.
¿Cómo se instala aurora?
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Puedes instalar aurora clonando el repositorio (https://github.com/FantasyLab-ai/aurora) o siguiendo las instrucciones del README en GitHub. ClaudeWave también te ofrece bloques de instalación rápida en esta misma página.
¿Es seguro usar FantasyLab-ai/aurora?
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FantasyLab-ai/aurora aún no ha sido auditado por nuestro agente de seguridad. Revisa el repositorio original en GitHub antes de usarlo en producción.
¿Quién mantiene FantasyLab-ai/aurora?
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FantasyLab-ai/aurora es mantenido por FantasyLab-ai. La última actividad registrada en GitHub es de today, con 0 issues abiertos.
¿Hay alternativas a aurora?
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Sí. En ClaudeWave puedes explorar tools similares en /categories/tools, ordenados por popularidad o actividad reciente.
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