KohakuTerrarium 1.0.0rc1.post1

A universal agent framework for building self-driven AI agents and multi-agent teams

Define what an agent is. Build any kind. Compose them into teams.

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What KohakuTerrarium is

KohakuTerrarium is a framework for building real agents, not just LLM wrappers.

Its core abstraction is the creature: a standalone agent with its own controller, tools, sub-agents, triggers, memory, and I/O. Creatures can run by themselves, or they can be composed into a terrarium, which is a pure multi-agent wiring layer.

The goal is simple: make agent systems modular enough to model serious products, while still staying configurable, composable, and hackable.

Where it fits

AI tooling usually lives at different layers:

	Product	Framework	Utility / Wrapper
LLM App	ChatGPT, Claude.ai	LangChain, LangGraph, Dify	DSPy
Agent	Claude Code, Codex, OpenCode	smolagents (thin), KohakuTerrarium	-
Multi-Agent	-	KohakuTerrarium	CrewAI, AutoGen

Most frameworks either operate below the agent layer, or they jump straight to multi-agent orchestration with a very thin idea of what an agent is.

KohakuTerrarium starts with the agent itself.

A creature is made of:

• Controller: the reasoning loop
• Input: how events enter the agent
• Output: how results leave the agent
• Tools: what actions it can take
• Triggers: what wakes it up
• Sub-agents: internal delegation for specialized tasks

Then a terrarium composes multiple creatures horizontally through channels, lifecycle management, and observability.

Why the split matters

A lot of systems blur internal agent logic and external multi-agent wiring into one abstraction. KohakuTerrarium keeps them separate on purpose.

Inside a creature One controller delegates to tools and sub-agents. This is the agent-level abstraction.

Between creatures Independent creatures communicate through channels. This is the multi-agent wiring layer.

That separation lets you:

• build a creature once and run it solo or in a team
• change tools, prompts, triggers, or outputs without redesigning the whole system
• reason about single-agent behavior separately from team topology
• keep the multi-agent layer simple instead of turning it into another hidden controller

Architecture at a glance

Terrarium view

  +---------+       +---------------------------+
  |  User   |<----->|        Root Agent         |
  +---------+       |  (terrarium tools, TUI)   |
                    +---------------------------+
                          |               ^
            sends tasks   |               |  observes results
                          v               |
                    +---------------------------+
                    |     Terrarium Layer       |
                    |   (pure wiring, no LLM)   |
                    ├-------┬----------┬--------┤
                    |  swe  | reviewer |  ....  |
                    +-------┴----------┴--------+

Creature view

    List, Create, Delete  +------------------+
                    +-----|   Tools System   |
      +---------+   |     +------------------+
      |  Input  |   |          ^        |
      +---------+   V          |        v
        |   +---------+   +------------------+   +------------+
        +-->| Trigger |-->|    Controller    |-->| Sub Agents |
User input  | System  |   |    (Main LLM)    |<--| with tools |
            +---------+   +------------------+   +------------+
                ^             |          |
                |             v          v
                |         +--------+  +------+
                +---------|Channels|  |Output|
                 Receive  +--------+  +------+
                             |  ^
                             v  |
                          +------------------+
                          | Other Creatures  |
                          +------------------+

Quick start

# Install from PyPI
pip install kohakuterrarium

# Or install from source (for development)
git clone https://github.com/Kohaku-Lab/KohakuTerrarium.git
cd KohakuTerrarium
pip install -e ".[dev]"

# Install the default creatures, terrariums, and plugins
kt install https://github.com/Kohaku-Lab/kt-defaults.git

# Set up LLM access (pick one)
kt login codex          # Codex OAuth (no API key needed)
kt model default gpt-5.4  # or configure any OpenAI-compatible API

# Run a single creature
kt run @kt-defaults/creatures/swe

# Run a multi-agent terrarium
kt terrarium run @kt-defaults/terrariums/swe_team

# Launch the web dashboard
kt serve

Supports OpenRouter, OpenAI, Anthropic, Google Gemini, and any OpenAI-compatible API.

Choose your path

I want to run something now

• Start with Getting Started
• Browse CLI Reference
• See included examples

I want to build my own creature

• Read Creatures
• Read Configuration Reference
• See Custom Modules
• See Plugins

I want to build a terrarium

• Read Terrariums
• Read Channels
• Read Agents

I want to embed it in Python

• Read Programmatic Usage
• Read Python API
• See examples/code/

I want to work on the framework itself

• Start with docs/
• Read Testing
• Read Framework Internals
• Read package READMEs in src/kohakuterrarium/

Core mental model

Creature

A creature is a standalone agent with its own runtime, tools, sub-agents, prompts, and state.

You can run it directly:

kt run path/to/creature

Terrarium

A terrarium is a composition layer that wires creatures together through channels and manages their lifecycle.

It does not add a second reasoning loop.

Root agent

A terrarium can define a root agent that sits outside the team and operates it through terrarium management tools.

Channels

Channels are how creatures communicate:

• Queue: one consumer receives each message
• Broadcast: all subscribers receive each message

Modules

Everything extensible in KohakuTerrarium fits into one of five main module types:

Module	What it does	Example custom use
Input	Receives external events	Discord listener, webhook, voice input
Output	Delivers agent output	Discord sender, TTS, file writer
Tool	Executes actions	API calls, database access, RAG retrieval
Trigger	Generates automatic events	Timer, scheduler, channel watcher
Sub-agent	Delegated task execution	Planning, code review, research

Session and environment

• Environment: shared terrarium state such as shared channels
• Session: private creature state such as scratchpad and sub-agent state

That keeps team communication shared while creature internals stay isolated.

Practical capabilities

KohakuTerrarium already includes a broad runtime surface:

• built-in file, shell, web, JSON, channel, trigger, and introspection tools
• built-in sub-agents for exploration, planning, implementation, review, summarization, and research
• background tool execution and non-blocking agent flow
• session persistence with resumable operational state, not just chat history
• package installation for creatures and terrariums
• Python embedding through Agent, TerrariumRuntime, and KohakuManager
• HTTP and WebSocket serving
• web dashboard and native desktop app
• custom module and plugin systems

Programmatic usage

Use agents and terrariums as libraries — your code is the orchestrator:

import asyncio
from kohakuterrarium.core.agent import Agent
from kohakuterrarium.core.channel import ChannelMessage
from kohakuterrarium.terrarium.config import load_terrarium_config
from kohakuterrarium.terrarium.runtime import TerrariumRuntime

async def main():
    # ── Single agent ──────────────────────────────────────────────
    agent = Agent.from_path("@kt-defaults/creatures/swe")
    agent.set_output_handler(lambda text: print(text, end=""), replace_default=True)
    await agent.start()
    await agent.inject_input("Explain what this codebase does.")
    await agent.stop()

    # ── Multi-agent terrarium ─────────────────────────────────────
    runtime = TerrariumRuntime(load_terrarium_config("@kt-defaults/terrariums/swe_team"))
    await runtime.start()
    tasks = runtime.environment.shared_channels.get("tasks")
    await tasks.send(ChannelMessage(sender="user", content="Fix the auth bug."))
    await runtime.run()
    await runtime.stop()

asyncio.run(main())

Composition algebra

Compose agents with Python operators — >> (sequence), & (parallel), | (fallback), * (retry), async for (loop):

import asyncio
from kohakuterrarium.compose import agent, factory
from kohakuterrarium.core.config import load_agent_config

def make_agent(name, prompt):
    config = load_agent_config("@kt-defaults/creatures/general")
    config.name, config.system_prompt, config.tools, config.subagents = name, prompt, [], []
    return config

async def main():
    # Persistent agents (accumulate conversation context)
    async with await agent(make_agent("writer", "You are a writer.")) as writer, \
               await agent(make_agent("reviewer", "You are a strict reviewer. Say APPROVED if good.")) as reviewer:

        # Pipeline: writer >> bridge >> reviewer
        pipeline = writer >> (lambda text: f"Review this:\n{text}") >> reviewer

        # Loop until approved (native Python control flow)
        async for feedback in pipeline.iterate("Write a haiku about coding"):
            print(f"Reviewer: {feedback[:100]}")
            if "APPROVED" in feedback:
                break

    # Parallel ensemble with fallback
    fast = factory(make_agent("fast", "Answer concisely."))
    deep = factory(make_agent("deep", "Answer thoroughly."))
    safe = (fast & deep) >> (lambda results: max(results, key=len))  # pick best
    safe_with_retry = (safe * 2) | fast  # retry twice, then fallback
    print(await safe_with_retry("What is recursion?"))

asyncio.run(main())

For more, see Programmatic Usage, Python API, and examples/code/.

Runtime surfaces

CLI and TUI

KohakuTerrarium supports multiple interactive modes:

• cli: rich inline terminal experience
• tui: full-screen Textual application
• plain: simple stdout and stdin mode for piping and CI

See CLI Reference for command details.

Web dashboard

The project includes a Vue-based dashboard and FastAPI server.

python -m kohakuterrarium.api.main
# For frontend development:
npm run dev --prefix src/kohakuterrarium-frontend

See HTTP API and Frontend Architecture.

Desktop app

kt app launches the same web UI inside a native desktop window.

Sessions and persistence

Sessions are automatically saved to ~/.kohakuterrarium/sessions/ unless disabled.

Resume anytime:

kt resume
kt resume --last
kt resume swe_team

Session files use the .kohakutr format and store operational state such as:

• conversation history
• tool call metadata
• event logs
• scratchpad state
• sub-agent state
• channel messages
• jobs
• resumable triggers
• config and topology metadata

See Sessions.

Packages, defaults, and examples

Install creature and terrarium packages from Git or local paths:

kt install https://github.com/someone/cool-creatures.git
kt install ./my-creatures -e
kt list

Run installed configs with package references:

kt run @cool-creatures/creatures/my-agent
kt terrarium run @cool-creatures/terrariums/my-team

Included resources:

• kt-defaults/ contains installable default creatures and terrariums
• examples/agent-apps/ contains config-driven examples
• examples/code/ contains Python usage examples
• examples/terrariums/ contains multi-agent examples
• examples/plugins/ contains plugin examples

See examples/README.md and kt-defaults/README.md.

Codebase map

src/kohakuterrarium/
  core/           # Agent runtime, controller, executor, events, environment
  bootstrap/      # Agent initialization factories for LLM, tools, I/O, triggers
  cli/            # CLI command handlers
  terrarium/      # Multi-agent runtime, config loading, topology wiring, hot-plug
  builtins/       # Built-in tools, sub-agents, I/O modules, TUI, user commands
  builtin_skills/ # Markdown skill manifests for on-demand tool and sub-agent docs
  session/        # Session persistence, memory search, embeddings
  serving/        # Transport-agnostic service manager and event streaming
  api/            # FastAPI HTTP and WebSocket server
  modules/        # Base protocols for tools, inputs, outputs, triggers, sub-agents
  llm/            # LLM providers, profiles, API key management
  parsing/        # Tool-call parsing and stream handling
  prompt/         # Prompt assembly, aggregation, plugins, skill loading
  testing/        # Test infrastructure

src/kohakuterrarium-frontend/  # Vue web frontend
kt-defaults/                   # Installable defaults package
examples/                      # Example agents, terrariums, code samples, plugins
docs/                          # Guides, concepts, API reference, contributor docs

Several source packages also include local README.md files that explain internal responsibilities and dependency flow. Those are worth reading if you are contributing to the framework.

Documentation map

Full documentation lives in docs/.

Guides

• Getting Started
• Configuration Reference
• Creatures
• Terrariums
• Sessions
• Programmatic Usage
• Custom Modules
• Plugins
• Examples

Concepts

• Overview
• Agents
• Terrariums
• Channels
• Execution Model
• Prompt System
• Serving Layer
• Environment and Session
• Tool Formats

API reference

• Python API
• HTTP API
• CLI Reference

Contributing

• Contributing docs
• Testing
• Framework Internals
• Frontend Architecture

License

KohakuTerrarium License 1.0: based on Apache-2.0 with naming and attribution requirements.

• Derivative works must include Kohaku or Terrarium in their name
• Derivative works must provide visible attribution with a link to this project

Copyright 2024-2026 Shih-Ying Yeh (KohakuBlueLeaf) and contributors