Lalabase
Tickets, Doku, Zeiterfassung und Kundengespräche an einem Ort, durchsuchbar per KI. Für Softwarefirmen mit Kundenprojekten. Open Source: auf deinem eigenen Server oder in unserer Cloud in Deutschland.
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An open-source platform for running a small team of AI agents inside your business. Your server or ours, your keys, your rules.
BusinessTypeScript · PythonGitHub @Heiberg-IndustriesOnlineOwner unconfirmed
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Experimental self-hosted agent engine. AGPL-3.0-only.
Translation pending
Taken from the repository README
Loading the full README.
Read the full README ↗Lares is a self-hosted fleet of named AI agents that runs the operating overhead of a small business: the inbox, the calendar, deadlines and renewals, meeting follow-ups, the daily brief. It runs on one server you control, talks to models through a gateway on that server, and keeps what it learns as plain Markdown in Git.
Alpha. Lares is experimental and under active development. There is no tagged release yet, only release candidates. Expect breaking changes, rough edges and manual steps. Try it on a disposable server before you connect real accounts.
An installation runs one or more agents. Each agent is a definition, not a build: a name, a role, a voice, the doors it answers on and exactly what it may touch. The engine ships two neutral role templates:
Across all of them:
/srv/lares/agents/<name>/, settings and secrets, read at runtime by the engine's images.
Adding an agent never needs a new image.The reasoning behind each of these is in docs/decisions/.
The tested path is:
Images are built in CI and pulled by digest; nothing is built on your server. Other Linux distributions and macOS are best-effort: expected to work, not tried.
There is one tested path: a fresh Ubuntu server and one installer that asks four questions
(domain, e-mail, name and model key), tests the key with a real call, and offers to start fresh
or restore from a backup. See
the tested install path for what that means.
The installer is services/box/ops/install.sh.
The step-by-step guide is docs/install.md. To have a coding agent such as Claude Code or Codex do the install for you, point it at docs/install-with-an-agent.md.
No one has yet installed Lares from the docs alone without help, and we are working on that next. If you try it, notes on where you got stuck are the most useful thing you can send.
Lares is a tested path, not supported software. There is no support agreement or promised response time. Ask questions in the community Slack and file bugs as GitHub issues; answers are best effort. Report security problems privately as described in SECURITY.md, never in Slack or an issue.
Use Node.js 24 and pnpm 9.15.0. From the repository root, run pnpm install --frozen-lockfile,
then pnpm typecheck and pnpm test. The test suites start disposable PostgreSQL containers,
so Docker must be running. See PR CI coverage and exclusions before reading
too much into a green result. Image builds and runtime probes run only in CI.
Agent definition backups to Git are optional and off by default; see definition backups.
Lares is developed with substantial code contributions generated by Anthropic Claude and OpenAI Codex, under the maintainer's direction. The maintainer is responsible for deciding what is reviewed, merged and released. GitHub's contributor list reflects commit attribution and does not fully describe the tools used to write the code.
Original Lares code is licensed under the GNU Affero General Public License, version 3 only (LICENSE), except where a file states otherwise. Third-party components retain their own licences and notices; see THIRD_PARTY_NOTICES.md.
See CONTRIBUTING.md for contribution requirements, CODE_OF_CONDUCT.md for how we treat each other, and SECURITY.md for reporting vulnerabilities.