Skip to main content

A toolkit for building AI agents that use devices

Project description


Surfkit

A toolkit for building and sharing AI agents that operate on devices
Explore the docs »

View Demo · Report Bug · Request Feature


Features

  • Build multimodal agents that can operate on devices
  • Share agents with the community
  • Run agents and devices locally or in the cloud
  • Manage agent tasks at scale
  • Track and observe agent actions

Demo

https://github.com/agentsea/surfkit/assets/5533189/98b7714d-9692-4369-8fbf-88aff61e741c

Installation

pip install surfkit

Quickstart

Prerequisites

  • Docker
  • Python >= 3.10
  • MacOS or Linux
  • Qemu

Create an Agent

Find available agents on the Hub

surfkit find

Create a new agent

surfkit create agent -t mariyadavydova/SurfSlicer -n agent01

List running agents

surfkit list agents

Create a Device

Create an Ubuntu desktop for our agent to use.

surfkit create device --provider qemu -n desktop01

List running devices

surfkit list devices

Solve a task

Use the agent to solve a task on the device

surfkit solve "Search for the most common variety of french duck" \
  --agent agent01 \
  --device desktop01

Documentation

View our documentation for more in depth information.

Usage

Building Agents

Initialize a new project

surfkit new

Build a docker container for the agent

surfkit build

Running Agents

Create an agent locally

surfkit create agent --name foo -t pbarker/SurfPizza

Create an agent on kubernetes

surfkit create agent --runtime kube -t pbarker/SurfPizza

List running agents

surfkit list agents

Get details about a specific agent

surfkit get agent foo

Fetch logs for a specific agent

surfkit logs foo

Delete an agent

surfkit delete agent foo

Managing Devices

Create a device

surfkit create device --type desktop --provicer gce --name bar

List devices

surfkit list devices

View device in UI

surfkit view bar

Delete a device

surfkit delete device bar

Tracking Tasks

Create a tracker

surfkit create tracker

List trackers

surfkit list trackers

Delete a tracker

surfkit delete tracker foo

Solving Tasks

Solve a task with an existing setup

surfkit solve "search for common french ducks" --agent foo --device bar

Solve a task creating the agent ad hoc

surfkit solve "search for alpaca sweaters" \
--device bar --agent-file ./agent.yaml

List tasks

surfkit list tasks

Publishing Agents

Login to the hub

surfkit login

Publish the agent

surfkit publish

List published agent types

surfkit find

Integrations

Skillpacks is integrated with:

  • MLLM A prompt management, routing, and schema validation library for multimodal LLMs
  • Taskara A task management library for AI agents
  • Skillpacks A library to fine tune AI agents on tasks.
  • Threadmem A thread management library for AI agents

Community

Come join us on Discord.

Developing

Add the following function to your ~/.zshrc (or similar)

function sk() {
  local project_dir="/path/to/surfkit/repo"
  local venv_dir="$project_dir/.venv"
  local ssh_auth_sock="$SSH_AUTH_SOCK"
  local ssh_agent_pid="$SSH_AGENT_PID"

  export SSH_AUTH_SOCK="$ssh_auth_sock"
  export SSH_AGENT_PID="$ssh_agent_pid"

  # Add the Poetry environment's bin directory to the PATH
  export PATH="$venv_dir/bin:$PATH"

  # Execute the surfkit.cli.main module using python -m
  surfkit "$@"
}

Replacing /path/to/surfkit/repo with the absolute path to your local repo.

Then calling sk will execute the working code in your repo from any location.

Project details


Release history Release notifications | RSS feed

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

surfkit-0.1.233.tar.gz (69.7 kB view details)

Uploaded Source

Built Distribution

surfkit-0.1.233-py3-none-any.whl (85.6 kB view details)

Uploaded Python 3

File details

Details for the file surfkit-0.1.233.tar.gz.

File metadata

  • Download URL: surfkit-0.1.233.tar.gz
  • Upload date:
  • Size: 69.7 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/1.8.3 CPython/3.12.4 Darwin/23.4.0

File hashes

Hashes for surfkit-0.1.233.tar.gz
Algorithm Hash digest
SHA256 9c4f1a3a28169487531409e00c5e0f96cb2b4413ef29b0f3737af40e245620bc
MD5 e343a83b41b7f1a981954796f9987ab3
BLAKE2b-256 cc495f2429e0b74ba610732457e949e97ef3c87812316d72e871765ecf744173

See more details on using hashes here.

File details

Details for the file surfkit-0.1.233-py3-none-any.whl.

File metadata

  • Download URL: surfkit-0.1.233-py3-none-any.whl
  • Upload date:
  • Size: 85.6 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/1.8.3 CPython/3.12.4 Darwin/23.4.0

File hashes

Hashes for surfkit-0.1.233-py3-none-any.whl
Algorithm Hash digest
SHA256 0620bca6662591514e883e079b781f1b5cc0ae8aa8a24c222becad10f1686373
MD5 2199a80cc9e442afa41389262b0ec956
BLAKE2b-256 40d195c97d21aec5556e48b67010718d772d8481e3351bdcd460b3fe3de572cc

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page