One-Command Deployment: Launch Your AI Platform

The Swiss AI Hub platform deploys with a single Docker Compose command. This streamlined process gets your complete AI infrastructure running in minutes, not hours.

Quick Install

Run a single command to download, extract, and set up the platform:

curl -fsSL https://raw.githubusercontent.com/bbvch-ai/aihub-core/main/install.sh | bash

The installer auto-detects GPU hardware, downloads the correct release bundle, and generates all secrets. Afterwards, edit .env and run docker compose up -d.

Flag	Default	Description
--version VERSION	latest	Pin to a specific release
--gpu	auto-detect	Force GPU bundle
--cpu	auto-detect	Force CPU-only bundle
--dir PATH	./swiss-ai-hub	Installation directory
--help		Show usage

Examples:

# Install with GPU bundle to a custom directory
curl -fsSL https://raw.githubusercontent.com/bbvch-ai/aihub-core/main/install.sh | bash -s -- --gpu --dir /opt/swiss-ai-hub

# Pin a specific version
curl -fsSL https://raw.githubusercontent.com/bbvch-ai/aihub-core/main/install.sh | bash -s -- --version v0.269.2

Upgrading: Run the installer again with the same --dir. It detects the existing installation, backs up your .env, replaces bundle files, restores .env, and reports any new environment variables added in the release.

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Deployment Overview

Two Deployment Options

The Swiss AI Hub supports two deployment modes. Follow the same steps for both, using the appropriate commands for your deployment type:

• Production Deployment: Deploy to a server with a real domain name (e.g., swiss-ai-hub.yourcompany.com)

  • Uses the CPU or GPU release bundle from GitHub Releases
  • Uses Let's Encrypt for automatic SSL certificates
  • Requires DNS configuration pointing to your server

• Local Deployment: Run on your local machine for development/testing

  • Uses infra/docker-compose.local.yml from the repository
  • Uses self-signed SSL certificates (mkcert)
  • Uses 127.0.0.1.nip.io domain (automatically resolves to localhost)

Each step below shows commands for both deployment types. Simply follow the commands that match your chosen deployment mode.

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Step 1: Get Deployment Files

For Production:

Download the latest release bundle from GitHub Releases. Each release provides two self-contained bundles:

• swissaihub-<version>.tar.gz — CPU-only deployment
• swissaihub-<version>-gpu.tar.gz — GPU-enabled deployment (includes vLLM, GPU-accelerated inference)

# Set the version you want to deploy
VERSION="v0.266.0"  # Replace with the desired version

# Download and extract the release bundle (CPU example)
mkdir swiss-ai-hub && cd swiss-ai-hub
curl -L "https://github.com/bbvch-ai/aihub-core/releases/download/${VERSION}/swissaihub-${VERSION}.tar.gz" \
  | tar -xz

# For GPU-enabled deployment, use this instead:
# curl -L "https://github.com/bbvch-ai/aihub-core/releases/download/${VERSION}/swissaihub-${VERSION}-gpu.tar.gz" \
#   | tar -xz

The release bundle contains everything needed to deploy: docker-compose.yml, all service configuration files, an .env.template, and the setup-env.sh script.

For Local Deployment:

# Clone the repository
git clone https://github.com/bbvch-ai/aihub-core.git
cd swiss-ai-hub

# Generate SSL certificates with mkcert
mkcert -install  # Install local CA (only needed once)
make local-cert

What is nip.io?

The *.127.0.0.1.nip.io domain automatically resolves to your localhost (127.0.0.1), providing wildcard DNS resolution without needing to modify your hosts file. This allows subdomain-based routing in local development.

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Step 2: Configure Environment Variables

Generate Environment Configuration

For Production (release bundle):

The release bundle includes a setup-env.sh script that generates a .env file from the included .env.template. It automatically creates unique secrets for all database passwords, tokens, and signing keys:

# Generate .env with auto-generated secrets
./setup-env.sh

What does setup-env.sh do?

The script reads .env.template and replaces all REPLACE_WITH_* placeholders with cryptographically secure random values. Each placeholder gets its own unique secret. The script requires only openssl and bash — no Python or other dependencies needed.

# Options:
./setup-env.sh                              # Default: .env.template → .env
./setup-env.sh -t custom.template -o out.env  # Custom paths
./setup-env.sh --force                      # Overwrite existing .env

For Local Deployment:

cp .env.dev .env

Configure Remaining Values

After generating your .env file, review it and fill in the values that require manual configuration:

Critical Values to Replace:

1. Domain — Set DOMAIN to your production domain (e.g., swiss-ai-hub.yourcompany.com) or 127.0.0.1.nip.io for local testing

2. Authentication Values (from Prerequisites):

   • REPLACE_WITH_YOUR_CLIENT_ID → Your Azure App Registration Client ID
   • REPLACE_WITH_YOUR_CLIENT_SECRET → Your Azure App Registration Client Secret
   • REPLACE_WITH_YOUR_TENANT_ID → Your Azure Tenant ID

3. AI Model Access (Swiss LLM Cloud — required for non-GPU deployments):

   • REPLACE_WITH_SWISS_LLM_CLOUD_URL → Your Swiss LLM Cloud text generation endpoint
   • REPLACE_WITH_SWISS_LLM_CLOUD_KEY → Your Swiss LLM Cloud API key
   • Configure the remaining endpoint pairs for embedding, reranking, whisper, and OCR

4. Expert Escalation (optional — for expert-in-the-loop features):

   • REPLACE_WITH_TEAMS_CHANNEL_ID → Your Teams channel ID (format: 19:xxx@thread.tacv2)
   • REPLACE_WITH_TEAMS_TENANT_ID → Your Azure AD tenant ID
   • REPLACE_WITH_TEAMS_BOT_ID → Your Azure Bot Service application ID

Simplified Configuration

Internal service endpoints (like database URLs, message queues, etc.) are hardcoded in the Docker Compose files. You only need to configure credentials and external service connections. All database passwords, tokens, and signing keys are auto-generated by setup-env.sh.

Environment Validation

Before deployment, verify your configuration:

# Check for placeholder values that still need replacement
grep -n "REPLACE_WITH" .env

This should return no results if all placeholders are replaced.

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Step 3: Deploy the Platform

Launch All Services

Deploy the complete platform with one command:

For Production (release bundle):

docker compose up -d

This command will:

• Download all necessary Docker images
• Create required networks and volumes
• Start all platform services in the correct order
• Configure service discovery and communication

Monitor Deployment Progress

Watch the deployment progress:

# See all services starting
docker compose logs -f

# Check service health status
docker compose ps

Expected Services: The platform includes these core services:

• Web Interface (swiss-ai-hub-web)
• API (swiss-ai-hub-api)
• Authentication (auth services)
• Databases (FerretDB, PostgreSQL, Valkey)
• Vector Database (Milvus)
• LLM Proxy (LiteLLM)
• Document Processing (MinerU)
• Observability (Langfuse)
• Message Queue (NATS)
• Storage (SeaweedFS)

Wait for Service Initialization

Initial startup takes 3-5 minutes while services initialize. All services should show "healthy" status:

# Wait for healthy status
docker compose ps --format "table {{.Name}}\t{{.Status}}"

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Step 4: Verify Successful Deployment

Access the Platform

1. Make sure your User that you test with has the roles "AIHubAdmin" and "AIHubSysAdmin" assigned in the Azure Enterprise Application

2. Web Interface:

   • Production: https://your-domain.com

3. Expected Login Flow:

   • Redirects to Azure authentication
   • After login, returns to Swiss AI Hub interface
   • Should see the main dashboard