gardener — Database-Based OS for LLMs

🇩🇪 Deutsche Version

Status: Prototype | Author: Lukas Geiger + Claude | 2026-03-12

What is Gardener?

An operating system built for LLMs. Everything lives in a searchable database. Four functions are all you need.

Quickstart

from gardener import Gardener
af = Gardener()

# Search
af.find("taxes")

# Read
af.get("receipt-scanner")

# Write
af.put("note", content="Important!", type="memory", tags="todo")

# Execute
af.run("file-info", input={"path": "/path/to/file"})

CLI

python gardener.py find <query>
python gardener.py get <name>
python gardener.py put <name> <text>
python gardener.py run <name>
python gardener.py absorb <file>
python gardener.py materialize <name>
python gardener.py sync
python gardener.py observe
python gardener.py status

Architecture

Gardener/
  gardener.py          # Core: Gardener class + CLI
  seed.py              # Initial system knowledge
  KONZEPT.md           # Design documentation (German)
  README.md            # This file
  workspace/           # Materialized code for execution
  blobs/               # Storage for large files (>50MB)

Local (not in cloud):
  AppData/Local/Gardener/
    gardener.db        # System: Knowledge, tools, blueprints
    user.db            # User: Memory, tasks, personal data
    blobs/             # Large files

User directory (cloud ok):
  ~/gardener/
    .absorber/         # Files here → automatically absorbed into DB
    .output/           # Materialized files appear here
    documents/         # Observed files (LLM reads along)

Data Model

One table for (almost) everything:

Type	Description	Target DB
knowledge	Knowledge, docs, rules	gardener.db
tool	Executable code	gardener.db
memory	Memories, notes	user.db
task	Tasks	user.db
document	Absorbed files	user.db
observed	Observed files	user.db
config	Configuration	user.db
export	Marked for materialization	user.db

Memory (No Separate Memory System!)

Instead of 5 tables: everything in everything with types and meta fields. The FTS5 search IS the associative memory.

af.memo("Quick note")                    # Working memory (decays fast)
af.lesson("Title", "Insight")            # Best practice (barely decays)
af.session_end("Summary")               # Session report
af.recall("taxes")                       # Remember (searches + boosts weight)
af.consolidate()                         # Sleep: Decay + Forget

gardener memo <text>            # Note
gardener lesson <title> [text]  # Lesson
gardener recall <query>         # Remember
gardener consolidate            # Consolidate
gardener session-end <text>     # End session

Details: KONZEPT.md#memory

Tasks (No Separate System!)

Tasks are entries of type task in the everything table. No separate task system needed. find("taxes") finds knowledge AND tasks simultaneously.

af.task("taxes-2025", content="File return", priority="high", due="2026-05-31")
af.tasks()                     # All tasks
af.tasks(status="open")        # Open only
af.task_done("taxes-2025")     # Mark done

gardener task <name> [text]     # Create
gardener tasks [status]         # List
gardener done <name>            # Mark done

Details: KONZEPT.md#tasks

Three Relationships with Files

1. Observe: File stays in folder, LLM reads along (looking out the window)
2. Absorb: File gets pulled into the DB (now lives in the house)
3. Direct edit: LLM edits file in folder (working in front of the house)

Transporter

af.absorb("/path/to/file.pdf")     # File → DB (dematerialize)
af.materialize("file.pdf")          # DB → File (rematerialize)

Seeding

python seed.py    # Populates gardener.db with base knowledge and example tools

Comparison: Gardener vs Rinnsal

Gardener and Rinnsal are both lightweight LLM operating systems from the ellmos ecosystem. Here are the differences:

Feature	Detail	Gardener	Rinnsal
Core API	Style	4 functions (find/get/put/run)	~20 CLI commands, module-based
Data Model	Tables	1 (everything + type field)	4+ (facts, notes, lessons, sessions)
	FTS5 Search	Yes (core feature, IS the memory)	No (structured queries)
Memory	Working	memo() with decay	notes (session-scoped)
	Long-term	lesson() + weighting	facts (confidence score)
	Consolidation	consolidate() (decay+forget)	No
	Recall/Boost	recall() boosts weight	No
	Context Export	No	api.context() (LLM-ready)
Tasks	Priorities	Yes (meta field)	critical/high/medium/low
	Agent Assignment	No	Yes
	Deadlines	Yes (due field)	No
Files	Absorb (file→DB)	Yes	No
	Materialize (DB→file)	Yes	No
	Observe (watch)	Yes	No
	Blob Storage (>50MB)	Yes	No
Automation	Chains	No	Marble-run model
	Ollama	No	Yes (REST client)
Connectors	Telegram/Discord/HA	No (planned)	Yes
Architecture	Dependencies	Zero	Zero
	Event Bus	No	Yes
	Multi-Agent	No	Yes (event bus + USMC)

In short: Gardener = radical minimalism (1 table, search = everything). Rinnsal = more structure, but connectors and chains out of the box.

Extensibility

Gardener is designed as a core that can be extended with ellmos modules:

Module	Function	Status
connectors	Telegram, Discord, Webhook, etc.	Planned
USMC	Cross-Agent Shared Memory	Integrable
clutch	Smart Model Routing	Integrable
swarm-ai	Parallel LLM Patterns	Integrable

The vision: The LLM serves itself from a library of modules. Gardener provides search, memory, and the execution environment — everything else is added as a plugin when needed.

Design Document

Detailed design documentation: KONZEPT.md (German)

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Haftung / Liability

Dieses Projekt ist eine unentgeltliche Open-Source-Schenkung im Sinne der §§ 516 ff. BGB. Die Haftung des Urhebers ist gemäß § 521 BGB auf Vorsatz und grobe Fahrlässigkeit beschränkt. Ergänzend gelten die Haftungsausschlüsse aus GPL-3.0 / MIT / Apache-2.0 §§ 15–16 (je nach gewählter Lizenz).

Nutzung auf eigenes Risiko. Keine Wartungszusage, keine Verfügbarkeitsgarantie, keine Gewähr für Fehlerfreiheit oder Eignung für einen bestimmten Zweck.

This project is an unpaid open-source donation. Liability is limited to intent and gross negligence (§ 521 German Civil Code). Use at your own risk. No warranty, no maintenance guarantee, no fitness-for-purpose assumed.