LibreAI / KI-Agenten / atmosphere
// agents · Atmosphere/atmosphere

atmosphere

atmosphere ist ein Open-Source-Projekt aus der Kategorie KI-Agenten von Atmosphere (Atmosphere/atmosphere auf GitHub). Es hat 3.818 Sterne auf GitHub und 764 Forks, wird unter der Lizenz Apache-2.0 veröffentlicht und wurde zuletzt am 6. Oktober 2026 auf GitHub aktualisiert.

A portable AI agent runtime for the JVM — write one @Agent, run it on any Java AI stack.

★ 3,8 Tsd. Sterne⑂ 764 ForksApache-2.0aktualisiert Okt 2026
▦ Visual — das README dieses Projekts enthält keinen einbettbaren Screenshot,
darum hier ein Platzhalter. Die Anleitung unten ist trotzdem vollständig.
// projektdaten

Projektdaten

GitHub-Sterne
3.818
Forks
764
Lizenz
Apache-2.0
Zuletzt auf GitHub aktualisiert
6. Oktober 2026
Kategorie
KI-Agenten
Eintragstyp
Vollständige Installationsanleitung
Offizielle Website
Official site
// so funktioniert es

So funktioniert es

  1. Clarify your goal

    Decide the first concrete outcome you want from it, so you can pick the right example, template or mode instead of exploring everything at once.

  2. Get the project

    Clone the repository (or install the published package) and skim its README quick start for the requirements for your platform.

  3. Install and configure

    Run the documented install step and set any required configuration — such as provider keys, data sources or local services — before the first run.

  4. Run your first task

    Execute the smallest documented example end to end, confirm the output is what you expected, then adapt it to your real data or workflow.

// funktionen

Warum es so beliebt ist

One agent, many runtimes

Write an @Agent once and swap the runtime adapter — built-in, Spring AI, LangChain4j and more — without rewriting the agent.

Deep agents, batteries included

Long-term memory, a maintained plan (write_todos), a bounded virtual filesystem and sub-agent delegation on @Coordinator.

Every modern protocol

MCP, A2A and AG-UI support, streamed over WebSocket, SSE, gRPC or WebTransport/HTTP3.

Enterprise controls

Human approvals, policy engines (OPA Rego, AWS Cedar), audit sinks to Kafka/Postgres and an admin control plane.

Durable by design

Durable sessions (SQLite/Redis), checkpoints and a sandbox module for long-running agents.

CLI scaffolding

atmosphere new creates apps from templates, atmosphere run launches samples, and atmosphere import turns a SKILL.md into a project.

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// selbst ausführen

Führe es selbst aus

  1. Clone the repository

    Get the source so you can inspect, configure and run it locally.

    git clone https://github.com/Atmosphere/atmosphere.git
    cd atmosphere
  2. Install the CLI

    Install Atmosphere via Homebrew or the install script.

    brew install Atmosphere/tap/atmosphere
    # Or: curl -fsSL https://raw.githubusercontent.com/Atmosphere/atmosphere/main/cli/install.sh | sh
  3. Create and run an agent

    Scaffold a chat agent, set your model key, and run it — swap --runtime to target Spring AI or LangChain4j.

    atmosphere new my-agent --template ai-chat
    cd my-agent
    LLM_API_KEY=your-key ./mvnw spring-boot:run
// anwendungsfälle

Was du damit bauen kannst

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// häufige fragen

Häufige Fragen

Who maintains atmosphere?

It is maintained by Atmosphere on GitHub (Atmosphere/atmosphere), where the source, issues and releases live.

Is it free to use?

Yes — it is free and open source under Apache-2.0, which permits use, modification and commercial redistribution, with licence/notice retention.

Does it need a paid API key?

Yes — agents call an LLM through the runtime you choose, so you supply that provider's API key (the samples read LLM_API_KEY).

How does it compare to building directly on Spring AI or LangChain4j alone?

Compared with building directly on Spring AI or LangChain4j alone, atmosphere's distinguishing focus is: a portable AI agent runtime for the JVM — write one @Agent, run it on any Java AI stack. Pick it when that focus matches your need; the alternative may suit you better if its broader or different scope is the priority.

How do I get started?

Clone https://github.com/Atmosphere/atmosphere (or install its published package), follow the README quick start to install and configure it, then run the smallest documented example — the Run section on this page mirrors those steps.

// weiter entdecken

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// alternativen

Alternativen im Bereich KI-Agenten

Die anderen Projekte der Kategorie KI-Agenten mit den meisten Sternen im LibreAI-Katalog — die realistische Auswahl, falls atmosphere nicht das Richtige ist.

// mehr in agents

Mehr in KI-Agenten

Verwandte Projekte der Kategorie KI-Agenten im Katalog, die atmosphere bei den Sternen am nächsten stehen — zum Weiterstöbern auf beiden Seiten.

Hol dir atmosphere

Kostenlos und offen — hol dir den Quellcode, gib dem Repository einen Stern und leg los.