SmolFS

Durable workspace folders for AI agents.

Quickstart | Lifecycle | Python SDK | TypeScript SDK | Development | Releases

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SmolFS gives agents a workspace folder that can survive after the agent process stops. You mount it like a normal directory, write files into it, unmount it when the job is done, and mount it again later from another process.

SmolFS owns the developer experience around creating volumes, checking the machine, mounting, flushing, unmounting, and inspecting status. The storage backend is installed and managed for you.

Durable workspaces Agents can keep files across short-lived runtimes without each runtime managing storage setup directly. Read more ->	Local dev mode Use --dev for a local-only volume backed by SQLite metadata and local object files. Read more ->
Cloud volumes Use Redis plus S3-compatible object storage when the same workspace needs to outlive one machine. Read more ->	One CLI lifecycle Run doctor, init, mount, flush, status, and unmount from one command. Read more ->
Thin SDKs Python and TypeScript bindings call the same Rust core so agent tools can use SmolFS without shelling out. Read more ->	Explicit configuration Cloud metadata, buckets, and credentials stay explicit so durable agent data is easier to audit. Read more ->

Use Cases

• Keep agent work across turns. Mount the same workspace again after an agent process exits.
• Share a workspace across runtimes. Put metadata in Redis and file contents in S3-compatible storage.
• Test locally before using cloud storage. Start with --dev, then switch to explicit metadata and object storage settings.
• Wrap storage in agent tooling. Use the Python or TypeScript SDK from an agent runner instead of teaching every agent process about storage internals.

Quickstart

Install SmolFS:

curl -fsSL https://raw.githubusercontent.com/CelestoAI/smolfs/main/scripts/install.sh | sh

The installer downloads the latest CLI release asset for your platform and installs SmolFS' managed storage backend. If no release asset exists yet, use the source checkout flow in Development. Set SMOLFS_INSTALL_BACKEND=0 if you only want to install the CLI. Set SMOLFS_VERSION=dev to try the latest successful build from main; tagged v* releases remain the stable channel.

Check the machine and try a local volume:

smolfs doctor
smolfs init demo --dev
smolfs mount demo ./workspace
echo hello > ./workspace/hello.txt
smolfs flush demo
smolfs unmount demo
smolfs mount demo ./workspace
cat ./workspace/hello.txt

SmolFS needs local mount support on the machine that mounts volumes. Mount support lets SmolFS provide a folder your tools can read and write.

Install the Python SDK with the CLI

curl -fsSL https://raw.githubusercontent.com/CelestoAI/smolfs/main/scripts/install.sh | SMOLFS_INSTALL_PYTHON=1 sh

The installer runs uv add smolfs from a directory with pyproject.toml, or uv pip install smolfs inside an active virtualenv. Set SMOLFS_PYTHON_MODE=user to use uv pip install --user smolfs.

CLI Lifecycle

The normal SmolFS flow is: check the machine, create a volume, mount it, use the directory, flush important writes, unmount it, and mount it again when you need the same files later.

Check the Machine

Run doctor before creating or mounting volumes:

smolfs doctor

doctor checks whether SmolFS has its managed storage backend and whether the machine can mount local directories.

Useful options:

• smolfs doctor --install installs SmolFS' managed storage backend.
• smolfs doctor --json prints the same report as JSON for scripts.

SmolFS looks for its home directory in SMOLFS_HOME. If it is not set, SmolFS uses ~/.smolfs. The home directory stores SmolFS config, volume records, logs, managed binaries, and local dev-volume data.

Create a Local Volume

A volume is the named workspace that SmolFS can mount later.

smolfs init demo --dev

--dev creates a local-only volume. It uses SQLite for metadata and local files for object data under the SmolFS home directory. This is the simplest path for trying SmolFS on one machine.

Create a Cloud Volume

Cloud volumes need explicit metadata and object storage settings. Metadata stores the file tree. Object storage is where file contents live.

smolfs init agent-workspace \
  --metadata redis://localhost:6379/1 \
  --storage s3 \
  --bucket https://my-bucket.s3.us-east-2.amazonaws.com

You can pass object storage in either of these forms:

• --store s3://bucket/prefix, --store gs://bucket/prefix, or --store file:///path/to/objects.
• --storage TYPE --bucket BUCKET, which is useful for S3-compatible services that expect an endpoint-style bucket URL.

For Cloudflare R2 or another S3-compatible service, keep credentials in the environment used by SmolFS. Do not put access keys in command arguments or logs.

set -a
. ./.env
set +a

export SMOLFS_HOME=/tmp/smolfs-r2-home
VOL="r2demo-$(date +%Y%m%d%H%M%S)"

smolfs init "$VOL" \
  --metadata "$SMOLFS_R2_METADATA" \
  --storage s3 \
  --bucket "$SMOLFS_R2_BUCKET_URL"

Mount and Use the Volume

Mounting makes the volume appear as a normal local directory:

smolfs mount demo ./workspace
echo hello > ./workspace/hello.txt
cat ./workspace/hello.txt

SmolFS creates the mount directory if it does not exist. After the mount succeeds, programs can read and write files through that directory.

Useful options:

• --check-storage asks SmolFS to test object storage access before the mount completes.
• --foreground runs the mount process in the foreground instead of starting it in the background.

Flush, Inspect, and Unmount

Run flush when you want a best-effort check that recent writes have reached the mounted filesystem:

smolfs flush demo

Run status to see known volumes:

smolfs status
smolfs status demo
smolfs status --json

Unmount when the job is done:

smolfs unmount demo

unmount asks SmolFS to flush before detaching the mountpoint. Use smolfs umount demo if you prefer the shorter alias. Add --force when the mountpoint is busy and you want SmolFS to force the unmount.

After unmounting, you can mount the same volume again and read the files:

smolfs mount demo ./workspace
cat ./workspace/hello.txt

Commands

Command	What it does
smolfs doctor	Checks SmolFS storage, local mount support, and configuration.
smolfs init NAME --dev	Creates a local development volume.
smolfs init NAME --metadata URL --storage TYPE --bucket BUCKET	Creates a cloud volume with explicit metadata and object storage.
smolfs mount NAME PATH	Mounts a volume at a local directory.
smolfs flush NAME	Probes the mounted volume and syncs a small file through it.
smolfs status [NAME]	Shows known volumes and current mountpoints.
smolfs unmount NAME	Unmounts a mounted volume and asks SmolFS to flush.
smolfs umount NAME	Alias for smolfs unmount NAME.

Every command has its own help page:

smolfs help
smolfs init --help

Python SDK

The Python package is SDK-only. Install it with uv:

uv add smolfs

For local development from this checkout:

uv run --isolated --with-editable ./bindings/python python -c "from smolfs import doctor; print(doctor())"

Use the SDK from any Python agent runner:

from pathlib import Path

from smolfs import SmolFS, doctor

report = doctor()
if not report["storage_backend"]["found"] or not report["mount_support"]["found"]:
    raise RuntimeError(f"SmolFS is not ready: {report}")

fs = SmolFS.from_env()
volume = fs.ensure_volume("demo", dev=True)
mount = fs.mount(volume.name, "./workspace")

workspace = Path(mount.mountpoint)
(workspace / "hello.txt").write_text("hello from SmolFS\n")

try:
    fs.flush(volume.name)
finally:
    fs.unmount(volume.name)

Cloud volumes use the same API with explicit metadata and object storage:

fs.ensure_volume(
    "agent-workspace",
    metadata="redis://localhost:6379/1",
    storage="s3",
    bucket="https://my-bucket.s3.us-east-2.amazonaws.com",
)

For S3-compatible services such as MinIO or Cloudflare R2, pass the service bucket URL and provide ACCESS_KEY and SECRET_KEY in the environment used by SmolFS.

TypeScript SDK

The TypeScript package is a native Node.js binding over the same Rust core. The npm package ships prebuilt native bindings for Linux and macOS on x86_64 and arm64.

Install it with npm:

npm install @celestoai/smolfs

For local development from this checkout, use Node.js 18 or newer:

cd bindings/node
npm ci
npm run build:debug
npm test

Use the SDK from a Node.js agent runner:

import { SmolFS, doctor } from "@celestoai/smolfs";
import { writeFile } from "node:fs/promises";
import { join } from "node:path";

const report = doctor();
if (!report.storageBackend.found || !report.mountSupport.found) {
  throw new Error(`SmolFS is not ready: ${JSON.stringify(report)}`);
}

const fs = SmolFS.fromEnv();
const volume = fs.ensureVolume({ name: "demo", dev: true });
const mount = fs.mount({ name: volume.name, path: "./workspace" });

try {
  await writeFile(join(mount.mountpoint, "hello.txt"), "hello from SmolFS\n");
  fs.flush(volume.name);
} finally {
  fs.unmount(volume.name);
}

Cloud volumes use the same options object:

fs.ensureVolume({
  name: "agent-workspace",
  metadata: "redis://localhost:6379/1",
  storage: "s3",
  bucket: "https://my-bucket.s3.us-east-2.amazonaws.com"
});

Security and Reliability

SmolFS stores agent workspace data outside the sandbox lifecycle. Treat it like durable infrastructure.

• Do not log credentials, S3 access keys, Redis URLs with secrets, or mount tokens.
• Prefer explicit object-store configuration over hidden global state.
• Make mount and unmount behavior idempotent where possible.
• Fail loudly on missing storage backend, missing metadata URLs, missing object-store config, or missing local mount support.
• Avoid changes that weaken persistence guarantees without calling them out.

License

Apache 2.0.

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