Skip to main content
The Alquimia stack runs entirely via Docker Compose. No local builds, no dependency management — just pull and run.

​
Prerequisites

  • Docker Desktop (v24+) or Docker Engine + Docker Compose v2
  • Git
  • 8 GB RAM minimum (16 GB recommended if using local models with Ollama)

​
Quick start

git clone https://github.com/alquimia-ai/alquimia-local.git
cd alquimia-local
cp .env.example .env
docker compose up -d
Studio is now running at http://localhost:3001.
On first startup, give the stack 30–60 seconds to finish bootstrapping before logging in.
If your .env uses the Lite auth strategy for Studio or InsightHub, the default credentials are:
FieldValue
Usernameadmin
Passwordadmin
Change the default Lite credentials before exposing the stack to any network. Lite auth is intended for local development only.

​
Cloud and custom models

Studio is where you register cloud LLMs (Anthropic, OpenAI, Groq, etc.): open Settings → Models Registry, add each model, and paste the API key — credentials are stored as secrets. Use Base URL when you point at OpenAI-compatible gateways, proxies, or self-hosted endpoints; you are not limited to a fixed list baked into .env. (The optional Ollama workflow below still uses Compose for local pull-and-register — see Local models with Ollama.)

​
Local models with Ollama

The stack includes optional Ollama support for running inference locally (CPU-based): 
# Add to .env before starting
OLLAMA_MODELS=qwen2.5:0.5b nomic-embed-text

# Start with the local models profile
docker compose --profile with-local-models up -d
Naming convention for OLLAMA_MODELS:
  • Models with embed in the name → registered as Embeddings Models in Studio
  • All others → registered as chat models
Ollama runs on CPU inside Docker. Models larger than 3B parameters require significant RAM. Recommended: use 0.5B–3B models for local development.

​
Adding Ollama models without restarting

# Pull a new model into the running Ollama container
docker compose exec ollama ollama pull llama3.2:3b

# Re-run studio-init to register it in Studio
docker compose --profile with-local-models run --rm studio-init

​
Useful commands

# View logs for all services
docker compose logs -f

# View logs for a specific service
docker compose logs -f studio

# Stop all services (data is preserved)
docker compose down

# Stop and delete all data (volumes)
docker compose down -v

# Restart a single service
docker compose restart studio

​
Next steps

First login

Log in to Studio and take the onboarding tour.