A toolkit for building AI agents that use devices
Project description
Surfkit
A toolkit for building and sharing AI agents that operate on devices
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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
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