Prerequisites

Required

Linux machine (Ubuntu/Debian) or macOS on the same network as your laptop
Docker + Docker Compose v2 — install guide
Git
GitHub personal access token — needed to pull private fimula-base packages during build. Generate at https://github.com/settings/tokens (needs repo:read scope). Containers will not build without this.

LLM Provider Keys (optional)

The platform works in mock mode without any LLM keys — dashboard data is hardcoded, AI queries return demo responses. Add keys when you're ready for live AI features.

Key	Where to get	Cost	Default for
`OPENAI_API_KEY`	https://platform.openai.com/api-keys	~$0.15/1M tokens	Orchestrator, Knowledge, Context, Document Extraction
`ANTHROPIC_API_KEY`	https://console.anthropic.com/settings/keys	~$3/1M tokens	Analytics, Behavioral Scoring, Anomaly Detection, Forecast

Additional providers

Key	Where to get	Notes
`OPENROUTER_API_KEY`	https://openrouter.ai/keys	Unified gateway — access 100+ models with one key
`GLM_API_KEY`	https://open.bigmodel.cn	Zhipu AI. Also works as Anthropic-compatible via custom `api_base`
`DEEPSEEK_API_KEY`	https://platform.deepseek.com	Cheap reasoning models
`MISTRAL_API_KEY`	https://console.mistral.ai	European provider
`GROQ_API_KEY`	https://console.groq.com	Fast inference (LPU hardware)

What works without LLM keys

Full frontend UI (dashboards, admin, knowledge library)
Login and authentication
Dashboard widgets with mock data
All CRUD operations (semantic model, widgets, goals)
Document upload and storage (MinIO)

What requires LLM keys

AI query answers (text-to-SQL, RAG)
Document extraction (structured field synthesis)
Behavioral scoring explanations
Anomaly detection analysis
Revenue forecasting

Hardware

12 Docker containers run simultaneously. Recommended minimum:

RAM: 8 GB (16 GB preferred)
Disk: 20 GB free (Docker images + data volumes)
CPU: 4 cores

Info

Adding LLM keys later is seamless — edit .env.testip.local and restart containers. No rebuild needed.