Swarms Installation Guide¶

You can install swarms with pip in a Python>=3.10 environment.

Prerequisites¶

Before you begin, ensure you have the following installed:

Python 3.10 or higher: Download Python
pip (specific version recommended): pip >= 21.0
git (for cloning the repository): Download Git

Installation Options¶

pip (Recommended)UV InstallationPoetry InstallationDevelopment InstallationUsing DockerUsing KubernetesCI/CD Pipelines

Simple Installation¶

Simplest manner of installing swarms leverages using PIP. For faster installs and build times, we recommend using UV

pip install swarms

UV is a fast Python package installer and resolver written in Rust. It's significantly faster than pip and provides better dependency resolution.

Basic InstallationDevelopment Installation

# Install UV first
curl -LsSf https://astral.sh/uv/install.sh | sh

# Install swarms using UV
uv pip install swarms

# Clone the repository
git clone https://github.com/kyegomez/swarms.git
cd swarms

# Install in editable mode
uv pip install -e .

For desktop installation with extras:

uv pip install -e .[desktop]

Poetry is a modern dependency management and packaging tool for Python. It provides a more robust way to manage project dependencies and virtual environments.

Basic InstallationDevelopment InstallationUsing Poetry with existing projects

# Install Poetry first
curl -sSL https://install.python-poetry.org | python3 -

# Install swarms using Poetry
poetry add swarms

# Clone the repository
git clone https://github.com/kyegomez/swarms.git
cd swarms

# Install in editable mode
poetry install

For desktop installation with extras:

poetry install --extras "desktop"

If you have an existing project with a pyproject.toml file:

# Add swarms to your project dependencies
poetry add swarms

# Or add with specific extras
poetry add "swarms[desktop]"

Using virtualenvUsing AnacondaUsing Poetry

Clone the repository and navigate to the root directory:

git clone https://github.com/kyegomez/swarms.git
cd swarms

Setup Python environment and activate it:

python3 -m venv venv
source venv/bin/activate
pip install --upgrade pip

Install Swarms:

Headless install:
```
pip install -e .
```
Desktop install:
```
pip install -e .[desktop]
```

Create and activate an Anaconda environment:

conda create -n swarms python=3.10
conda activate swarms

Clone the repository and navigate to the root directory:

git clone https://github.com/kyegomez/swarms.git
cd swarms

Install Swarms:

Headless install:
```
pip install -e .
```
Desktop install:
```
pip install -e .[desktop]
```

Clone the repository and navigate to the root directory:

git clone https://github.com/kyegomez/swarms.git
cd swarms

Setup Python environment and activate it:
```
poetry env use python3.10
poetry shell
```

Install Swarms:

Headless install:
```
poetry install
```
Desktop install:
```
poetry install --extras "desktop"
```

Docker is an excellent option for creating isolated and reproducible environments, suitable for both development and production. Contact us if there are any issues with the docker setup

Pull the Docker image:
```
docker pull swarmscorp/swarms:tagname
```

Run the Docker container:

docker run -it --rm swarmscorp/swarms:tagname

Build and run a custom Docker image:

# Use Python 3.11 instead of 3.13
FROM python:3.11-slim

# Set environment variables
ENV PYTHONDONTWRITEBYTECODE=1 \
    PYTHONUNBUFFERED=1 \
    WORKSPACE_DIR="agent_workspace" \
    OPENAI_API_KEY="your_swarm_api_key_here"

# Set the working directory
WORKDIR /usr/src/swarms

# Install system dependencies
RUN apt-get update && apt-get install -y \
    build-essential \
    gcc \
    g++ \
    gfortran \
    && rm -rf /var/lib/apt/lists/*

# Install swarms package
RUN pip3 install -U swarm-models
RUN pip3 install -U swarms

# Copy the application
COPY . .

Kubernetes provides an automated way to deploy, scale, and manage containerized applications.

Create a Deployment YAML file:

apiVersion: apps/v1
kind: Deployment
metadata:
  name: swarms-deployment
spec:
  replicas: 3
  selector:
    matchLabels:
      app: swarms
  template:
    metadata:
      labels:
        app: swarms
    spec:
      containers:
      - name: swarms
        image: kyegomez/swarms
        ports:
        - containerPort: 8080

Apply the Deployment:
```
kubectl apply -f deployment.yaml
```

Expose the Deployment:

kubectl expose deployment swarms-deployment --type=LoadBalancer --name=swarms-service

Integrating Swarms into your CI/CD pipeline ensures automated testing and deployment.

Using GitHub Actions¶

# .github/workflows/ci.yml
name: CI

on:
  push:
    branches: [ main ]
  pull_request:
    branches: [ main ]

jobs:
  build:

    runs-on: ubuntu-latest

    steps:
    - uses: actions/checkout@v2
    - name: Set up Python
      uses: actions/setup-python@v2
      with:
        python-version: 3.10
    - name: Install dependencies
      run: |
        python -m venv venv
        source venv/bin/activate
        pip install --upgrade pip
        pip install -e .
    - name: Run tests
      run: |
        source venv/bin/activate
        pytest

Using Jenkins¶

pipeline {
    agent any

    stages {
        stage('Clone repository') {
            steps {
                git 'https://github.com/kyegomez/swarms.git'
            }
        }
        stage('Setup Python') {
            steps {
                sh 'python3 -m venv venv'
                sh 'source venv/bin/activate && pip install --upgrade pip'
            }
        }
        stage('Install dependencies') {
            steps {
                sh 'source venv/bin/activate && pip install -e .'
            }
        }
        stage('Run tests') {
            steps {
                sh 'source venv/bin/activate && pytest'
            }
        }
    }
}

Rust¶

Cargo install

Get started with the Rust implementation of Swarms. Get started with the docs here

cargo add swarms-rs