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Installation Guide

Welcome to the big-AGI Installation Guide - Whether you're a developer eager to explore, a system integrator, or an enterprise looking for a white-label solution, this comprehensive guide ensures a smooth setup process for your own instance of big-AGI and related products.

Try big-AGI - You don't need to install anything if you want to play with big-AGI and have your API keys to various model services. You can access our free instance on big-AGI.com. The free instance runs the latest main-stable branch from this repository.

🧩 Build-your-own

If you want to change the code, have a deeper configuration, add your own models, or run your own instance, follow the steps below.

Local Development

Prerequisites:

  • Node.js and npm installed on your machine.

Steps:

  1. Clone the big-AGI repository: 
    git clone https://github.com/enricoros/big-AGI.git
cd big-AGI
  2. Install dependencies: 
    npm install
  3. Run the development server: 
    npm run dev
    Your big-AGI instance is now running at http://localhost:3000.

Local Production build

The production build is optimized for performance and follows the same steps 1 and 2 as for local development.

  1. Build the production version: 
    # .. repeat the steps above up to `npm install`, then:
npm run build
  2. Start the production server (npx may be optional): 
    npx next start --port 3000
    Your big-AGI production instance is on http://localhost:3000.

Advanced Customization

Want to pre-enable models, customize the interface, or deploy with username/password or alter code to your needs? Check out the Customizations Guide for detailed instructions.

☁️ Cloud Deployment Options

To deploy big-AGI on a public server, you have several options. Choose the one that best fits your needs.

Deploy on Vercel

Install big-AGI on Vercel with just a few clicks.

Create your GitHub fork, create a Vercel project over that fork, and deploy it. Or press the button below for convenience.

Deploy with Vercel

Deploy on Cloudflare

Deploy on Cloudflare's global network by installing big-AGI on Cloudflare Pages. Check out the Cloudflare Installation Guide for step-by-step instructions.

Docker Deployments

Containerize your big-AGI installation using Docker for portability and scalability. Our Docker Deployment Guide will walk you through the process, or follow the steps below for a quick start.

  1. (optional) Build the Docker image - if you do not want to use the pre-built Docker images: 
    docker build -t big-agi .
  2. Run the Docker container with either: 
    # 2A. if you built the image yourself:
docker run -d -p 3000:3000 big-agi

# 2B. or use the pre-built image:
docker run -d -p 3000:3000 ghcr.io/enricoros/big-agi

# 2C. or use docker-compose:
docker-compose up
    Access your big-AGI instance at http://localhost:3000.

If you deploy big-AGI behind a reverse proxy, you may want to check out the Reverse Proxy Configuration Guide.

Kubernetes Deployment

Deploy big-AGI on a Kubernetes cluster for enhanced scalability and management. Follow these steps for a Kubernetes deployment:

  1. Clone the big-AGI repository:

    git clone https://github.com/enricoros/big-AGI.git
cd big-AGI

  2. Configure the environment variables:

    cp docs/k8s/env-secret.yaml env-secret.yaml
vim env-secret.yaml  # Edit the file to set your environment variables

  3. Apply the Kubernetes configurations:

    kubectl create namespace ns-big-agi
kubectl apply -f docs/k8s/big-agi-deployment.yaml -f env-secret.yaml

  4. Verify the deployment:

    kubectl -n ns-big-agi get svc,pod,deployment

  5. Access the big-AGI application:

    kubectl -n ns-big-agi port-forward service/svc-big-agi 3000:3000

    Your big-AGI instance is now accessible at http://localhost:3000.

For more detailed instructions on Kubernetes deployment, including updating and troubleshooting, refer to our Kubernetes Deployment Guide.

Midori AI Subsystem for Docker Deployment

Follow the instructions found on Midori AI Subsystem Site for your host OS. After completing the setup process, install the Big-AGI docker backend to the Midori AI Subsystem.

Enterprise-Grade Installation

For businesses seeking a fully-managed, scalable solution, consider our managed installations. Enjoy all the features of big-AGI without the hassle of infrastructure management. [email protected] to learn more.

Support

Join our vibrant community of developers, researchers, and AI enthusiasts. Share your projects, get help, and collaborate with others.

For any questions or inquiries, please don't hesitate to reach out to our team.