Sim Studio is a lightweight, user-friendly platform for building AI agent workflows.

Getting Started

1. Use our cloud-hosted version
2. Self-host using one of the methods below

Self-Hosting Options

Option 1: NPM Package (Simplest)

The easiest way to run Sim Studio locally is using our NPM package:

npx simstudio

After running these commands, open http://localhost:3000/ in your browser.

Options

• -p, --port <port>: Specify the port to run Sim Studio on (default: 3000)
• --no-pull: Skip pulling the latest Docker images

Requirements

• Docker must be installed and running on your machine

Option 2: Docker Compose

# Clone the repository
git clone https://github.com/simstudioai/sim.git

# Navigate to the project directory
cd sim

# Start Sim Studio
docker compose -f docker-compose.prod.yml up -d

Access the application at http://localhost:3000/

Using Local Models

To use local models with Sim Studio:

1. Pull models using our helper script:

./apps/sim/scripts/ollama_docker.sh pull <model_name>

2. Start Sim Studio with local model support:

# With NVIDIA GPU support
docker compose --profile local-gpu -f docker-compose.ollama.yml up -d

# Without GPU (CPU only)
docker compose --profile local-cpu -f docker-compose.ollama.yml up -d

# If hosting on a server, update the environment variables in the docker-compose.prod.yml file to include the server's public IP then start again (OLLAMA_URL to i.e. http://1.1.1.1:11434)
docker compose -f docker-compose.prod.yml up -d

Option 3: Dev Containers

1. Open VS Code with the Remote - Containers extension
2. Open the project and click "Reopen in Container" when prompted
3. Run bun run dev:full in the terminal or use the sim-start alias
   • This starts both the main application and the realtime socket server

Option 4: Manual Setup

Requirements:

• Bun runtime
• PostgreSQL 12+ with pgvector extension (required for AI embeddings)

Note: Sim Studio uses vector embeddings for AI features like knowledge bases and semantic search, which requires the pgvector PostgreSQL extension.

1. Clone and install dependencies:

git clone https://github.com/simstudioai/sim.git
cd sim
bun install

2. Set up PostgreSQL with pgvector:

You need PostgreSQL with the vector extension for embedding support. Choose one option:

Option A: Using Docker (Recommended)

# Start PostgreSQL with pgvector extension
docker run --name simstudio-db \
  -e POSTGRES_PASSWORD=your_password \
  -e POSTGRES_DB=simstudio \
  -p 5432:5432 -d \
  pgvector/pgvector:pg17

Option B: Manual Installation

• Install PostgreSQL 12+ and the pgvector extension
• See pgvector installation guide

3. Set up environment:

cd apps/sim
cp .env.example .env  # Configure with required variables (DATABASE_URL, BETTER_AUTH_SECRET, BETTER_AUTH_URL)

Update your .env file with the database URL:

DATABASE_URL="postgresql://postgres:your_password@localhost:5432/simstudio"

4. Set up the database:

bunx drizzle-kit migrate 

5. Start the development servers:

Recommended approach - run both servers together (from project root):

bun run dev:full

This starts both the main Next.js application and the realtime socket server required for full functionality.

Alternative - run servers separately:

Next.js app (from project root):

bun run dev

Realtime socket server (from apps/sim directory in a separate terminal):

cd apps/sim
bun run dev:sockets

Tech Stack

• Framework: Next.js (App Router)
• Runtime: Bun
• Database: PostgreSQL with Drizzle ORM
• Authentication: Better Auth
• UI: Shadcn, Tailwind CSS
• State Management: Zustand
• Flow Editor: ReactFlow
• Docs: Fumadocs
• Monorepo: Turborepo
• Realtime: Socket.io
• Background Jobs: Trigger.dev

Contributing

We welcome contributions! Please see our Contributing Guide for details.

License

This project is licensed under the Apache License 2.0 - see the LICENSE file for details.

Made with ❤️ by the Sim Studio Team