swarmbox 0.3.0

Python orchestration for coding agents in local, container, and cloud sandboxes.

SwarmBox

SwarmBox runs coding agents in isolated, git-aware workspaces from Python. It gives Claude Code, Codex, OpenCode, Pi, and registry-backed terminal agents a repeatable place to work, a branch strategy, a prompt, streamed logs, session handling, and a cleanup path.

Use it when a task should happen outside your current checkout, inside Docker or Podman, or inside a cloud sandbox while still producing normal git commits you can inspect, merge, or discard.

Install

python -m pip install swarmbox

Optional cloud sandbox integrations:

python -m pip install "swarmbox[vercel]"
python -m pip install "swarmbox[daytona]"

For local development:

python -m pip install -e ".[dev]"

Quick Start

Create a project config:

swarmbox init --interactive

Run a task from the CLI:

swarmbox run \
  --agent codex-cli \
  --sandbox docker \
  --prompt-file .swarmbox/prompt.md \
  --name fix-login

Run the same shape from Python:

from swarmbox import Timeouts, codex, docker, run

result = run(
    agent=codex("gpt-5.4-codex"),
    sandbox=docker(),
    prompt_file=".swarmbox/prompt.md",
    name="fix-login",
    idle_timeout_seconds=600,
    timeouts=Timeouts(sandbox_start_ms=60_000, copy_to_worktree_ms=60_000),
)

print(result.branch)
print([commit.sha for commit in result.commits])

What SwarmBox Manages

Area	What you get
Agents	First-class adapters plus generic command wrappers for SwarmVault-style CLI agents.
Sandboxes	Host execution, Docker, Podman, Vercel Sandbox, and Daytona entry points.
Git isolation	Current-branch, temporary merge branch, explicit branch, and owned worktree workflows.
Prompts	Inline prompts, prompt files, {{ARG}} substitution, built-in branch args, and shell expansion with !`command` .
Runtime control	Stream events, idle timeout, cancellation token, startup/copy/sync timeouts, and session transfer helpers.
Recovery	Dirty worktree preservation, sync recovery artifacts, log files, and human-readable error messages.

Supported Agents

First-class adapters:

ID	Binary	Notes
claude-cli	claude	Stream JSON, session capture, interactive mode.
codex-cli	codex	JSON print-mode execution through stdin.
opencode-cli	opencode	Print and interactive command support.
pi	pi	JSON-streaming print-mode support.

Registry-backed generic adapters include Gemini CLI, GitHub Copilot CLI, Cursor Agent, Qwen Code, Goose, Aider, Amp, Augment, Continue, OpenHands, Replit Agent, Roo Code, Warp, Windsurf, Zencoder, and other SwarmVault or SwarmClaw-compatible command-line agents.

Useful commands:

swarmbox agents list
swarmbox agents detect
swarmbox agents doctor

For a custom CLI, use command_agent:

from swarmbox import command_agent, no_sandbox, run

agent = command_agent(
    name="my-agent",
    command_template=["my-agent", "run", "--model", "{model}", "{prompt}"],
    model="default",
)

run(agent=agent, sandbox=no_sandbox(), prompt="Refactor the parser.")

Sandbox Providers

Provider	Function	Best for
Host	no_sandbox()	Fast local workflows and trusted agents.
Docker	docker()	Local isolation with bind mounts.
Podman	podman()	Rootless/container-native Linux workflows.
Vercel	vercel()	Cloud sandbox execution with the optional Vercel SDK.
Daytona	daytona()	Cloud development sandbox execution with the optional Daytona SDK.

from swarmbox import MountConfig, docker

sandbox = docker(
    image_name="swarmbox:my-project",
    mounts=[MountConfig("~/shared-cache", "~/cache", readonly=False)],
    env={"NODE_ENV": "development"},
)

Image helpers:

swarmbox docker build-image
swarmbox docker remove-image
swarmbox podman build-image
swarmbox podman remove-image

Branch And Worktree Modes

from swarmbox import branch, create_worktree, head, merge_to_head

Strategy	Behavior
head()	Run directly on the current branch.
merge_to_head()	Run on a temporary branch, then merge successful commits back.
branch("swarmbox/task-123")	Run on an explicit branch.
create_worktree(...)	Keep a reusable worktree alive until worktree.close().

Owned worktrees are useful when several operations should happen in the same isolated checkout:

from swarmbox import branch, codex, create_worktree, no_sandbox

worktree = create_worktree(branch_strategy=branch("swarmbox/task-123"))
try:
    worktree.run(
        agent=codex("gpt-5.4-codex"),
        sandbox=no_sandbox(),
        prompt="Implement the task and commit it.",
    )
finally:
    worktree.close()

Init Templates

swarmbox init creates .swarmbox/ with prompt files, a container file, .env.example, main.py, and swarmbox.json.

swarmbox templates list
swarmbox init \
  --agent codex-cli \
  --sandbox podman \
  --template parallel-planner-with-review \
  --backlog github-issues \
  --no-build

Templates:

Template	Purpose
blank	Minimal prompt scaffold.
simple-loop	Implement one backlog item and close it.
sequential-reviewer	Implementation prompt plus review prompt and coding standards.
parallel-planner	Planning, implementation, and merge prompts.
parallel-planner-with-review	Parallel planning plus review prompts.

Backlog integrations currently scaffold commands for GitHub Issues and Beads. The generated files are normal text files, so you can replace the commands with Jira, Linear, custom scripts, or local task files.

Configuration And Secrets

Runtime secrets belong in .swarmbox/.env; generated projects ignore that file by default. Keep API keys, PyPI tokens, provider tokens, and agent credentials out of git.

Typical keys:

OPENAI_API_KEY=
ANTHROPIC_API_KEY=
GH_TOKEN=
DAYTONA_API_KEY=
VERCEL_TOKEN=

SwarmBox also reads process environment values for keys declared in .swarmbox/.env, so CI systems can inject secrets without writing them to disk.

Streaming, Sessions, And Timeouts

from swarmbox import CancellationToken, Timeouts, claude_code, docker, run

events = []
token = CancellationToken()

result = run(
    agent=claude_code("claude-sonnet-4-6"),
    sandbox=docker(),
    prompt_file=".swarmbox/implement-prompt.md",
    idle_timeout_seconds=600,
    timeouts=Timeouts(
        sandbox_start_ms=60_000,
        copy_to_worktree_ms=60_000,
        sync_in_ms=120_000,
        sync_out_ms=120_000,
    ),
    logging={"type": "file", "on_agent_stream_event": events.append},
    signal=token,
)

Claude-compatible session files can be transferred between host and sandbox paths with host_session_store, sandbox_session_store, and transfer_session.

Troubleshooting

Symptom	Check
docker or podman not found	Install the runtime or use no_sandbox().
Container starts but agent command is missing	Rebuild the generated image after editing .swarmbox/Dockerfile or .swarmbox/Containerfile.
Git refuses to operate in a mounted repo	Confirm the sandbox can write its home directory and git safe-directory config.
Agent hangs silently	Set idle_timeout_seconds and check the log file under .swarmbox/logs.
Sync from an isolated provider fails	Use the recovery instructions printed in the error message and inspect .swarmbox/patches.

Development

python -m pip install -e ".[dev]"
PYTHONPATH=src python -m pytest
python -m ruff check .
python -m compileall -q src
python -m build
python -m twine check dist/*

Live smoke tests for Docker, Podman, Vercel, Daytona, and real coding-agent CLIs should be run before release when the required tools and credentials are available.