A handful of companies control the vast majority of global AI traffic — and with it, your data, your costs, and your uptime. Every query you send to a centralized provider is business intelligence you don’t own, running on infrastructure you don’t control, priced on terms you can’t negotiate.
If AI is becoming critical infrastructure, it shouldn’t be rented. Self-hosting local AI should be a sovereign human right, not a career choice.
Dream Server is the exit. A fully local AI stack — LLM inference, chat, voice, agents, workflows, RAG, image generation, and privacy tools — deployed on your hardware with a single command. No cloud. No subscriptions. No one watching.
New here? Read the Friendly Guide or listen to the audio version — a complete walkthrough of what Dream Server is, how it works, and how to make it your own. No technical background needed.
Platform Support — March 2026
Platform Status Linux (NVIDIA + AMD) Supported — install and run today Windows (NVIDIA + AMD) Supported — install and run today macOS (Apple Silicon) Supported — install and run today Tested Linux distros: Ubuntu 24.04/22.04, Debian 12, Fedora 41+, Arch Linux, CachyOS, openSUSE Tumbleweed. Other distros using apt, dnf, pacman, or zypper should also work — open an issue if yours doesn't.
Windows: Requires Docker Desktop with WSL2 backend. NVIDIA GPUs use Docker GPU passthrough; AMD Strix Halo runs llama-server natively with Vulkan.
macOS: Requires Apple Silicon (M1+) and Docker Desktop. llama-server runs natively with Metal GPU acceleration; all other services run in Docker.
See the Support Matrix for details.
Technology was made to empower people — not to concentrate power. Dream Server exists because we believe access to AI should come with full control over your data, your privacy, and your costs.
The practical problem is real too: setting up local AI usually means stitching together a dozen projects, debugging CUDA drivers, writing Docker configs, and hoping everything talks to each other. Dream Server replaces all of that.
- Run one command — the installer detects your GPU, picks the right model for your hardware, generates secure credentials, and launches everything
- Chat in under 2 minutes — bootstrap mode starts a small model instantly while your full model downloads in the background
- 13 integrated services — chat, agents, voice, workflows, search, RAG, image generation, and more, all pre-wired and working together
- Fully moddable — drop in a folder, run
dream enable, done. Every service is an extension
curl -fsSL https://raw.githubusercontent.com/Light-Heart-Labs/DreamServer/main/dream-server/get-dream-server.sh | bashOpen http://localhost:3000 and start chatting.
No GPU? Dream Server also runs in cloud mode — same full stack, powered by OpenAI/Anthropic/Together APIs instead of local inference:
./install.sh --cloud
Port conflicts? Every port is configurable via environment variables. See
.env.examplefor the full list, or override at install time:WEBUI_PORT=9090 ./install.sh
The DREAMGATE installer handles everything — GPU detection, model selection, service orchestration.
Manual install (Linux)
git clone https://github.com/Light-Heart-Labs/DreamServer.git
cd DreamServer/dream-server
./install.shWindows (PowerShell)
Requires Docker Desktop with WSL2 backend enabled. Install Docker Desktop first and make sure it is running before you start.
git clone https://github.com/Light-Heart-Labs/DreamServer.git
cd DreamServer
.\install.ps1The installer detects your GPU, picks the right model, generates credentials, starts all services, and creates a Desktop shortcut to the Dashboard. Manage with .\dream-server\installers\windows\dream.ps1 status.
macOS (Apple Silicon)
Requires Apple Silicon (M1+) and Docker Desktop. Install Docker Desktop first and make sure it is running before you start.
git clone https://github.com/Light-Heart-Labs/DreamServer.git
cd DreamServer/dream-server
./install.shThe installer detects your chip, picks the right model for your unified memory, launches llama-server natively with Metal acceleration, and starts all other services in Docker. Manage with ./dream-macos.sh status.
See the macOS Quickstart for details.
- Open WebUI — full-featured chat interface with conversation history, web search, document upload, and 30+ languages
- llama-server — high-performance LLM inference with continuous batching, auto-selected for your GPU
- LiteLLM — API gateway supporting local/cloud/hybrid modes
- Whisper — speech-to-text
- Kokoro — text-to-speech
- OpenClaw — autonomous AI agent framework
- n8n — workflow automation with 400+ integrations (Slack, email, databases, APIs)
- Qdrant — vector database for retrieval-augmented generation (RAG)
- SearXNG — self-hosted web search (no tracking)
- Perplexica — deep research engine
- ComfyUI — node-based image generation
- Privacy Shield — PII scrubbing proxy for API calls
- Dashboard — real-time GPU metrics, service health, model management
The installer detects your GPU and picks the optimal model automatically. No manual configuration.
| VRAM | Model | Example GPUs |
|---|---|---|
| 8–11 GB | Qwen3 8B (Q4_K_M) | RTX 4060 Ti, RTX 3060 12GB |
| 12–20 GB | Qwen3 8B (Q4_K_M) | RTX 3090, RTX 4080 |
| 20–40 GB | Qwen3 14B (Q4_K_M) | RTX 4090, A6000 |
| 40+ GB | Qwen3 30B-A3B (MoE, Q4_K_M) | A100, multi-GPU |
| 90+ GB | Qwen3 Coder Next (80B MoE, Q4_K_M) | Multi-GPU A100/H100 |
| Unified RAM | Model | Hardware |
|---|---|---|
| 64–89 GB | Qwen3 30B-A3B (30B MoE) | Ryzen AI MAX+ 395 (64GB) |
| 90+ GB | Qwen3 Coder Next (80B MoE) | Ryzen AI MAX+ 395 (96GB) |
| Unified RAM | Model | Example Hardware |
|---|---|---|
| 8–24 GB | Qwen3 4B (Q4_K_M) | M1/M2 base, M4 Mac Mini (16GB) |
| 32 GB | Qwen3 8B (Q4_K_M) | M4 Pro Mac Mini, M3 Max MacBook Pro |
| 48 GB | Qwen3 30B-A3B (MoE, Q4_K_M) | M4 Pro (48GB), M2 Max (48GB) |
| 64+ GB | Qwen3 30B-A3B (MoE, Q4_K_M) | M2 Ultra Mac Studio, M4 Max (64GB+) |
Override tier selection: ./install.sh --tier 3
No waiting for large downloads. Dream Server uses bootstrap mode by default:
- Downloads a tiny 1.5B model in under a minute
- You start chatting immediately
- The full model downloads in the background
- Hot-swap to the full model when it's ready — zero downtime
The installer pulls all services in parallel. Downloads are resume-capable — interrupted downloads pick up where they left off.
Skip bootstrap: ./install.sh --no-bootstrap
The installer picks a model for your hardware, but you can switch anytime:
dream model current # What's running now?
dream model list # Show all available tiers
dream model swap T3 # Switch to a different tierIf the new model isn't downloaded yet, pre-fetch it first:
./scripts/pre-download.sh --tier 3 # Download before switching
dream model swap T3 # Then swap (restarts llama-server)Already have a GGUF you want to use? Drop it in data/models/, update GGUF_FILE and LLM_MODEL in .env, and restart:
docker compose restart llama-serverRollback is automatic — if a new model fails to load, Dream Server reverts to your previous model.
Dream Server is designed to be modded. Every service is an extension — a folder with a manifest.yaml and a compose.yaml. The dashboard, CLI, health checks, and compose stack all discover extensions automatically.
extensions/services/
my-service/
manifest.yaml # Metadata: name, port, health endpoint, GPU backends
compose.yaml # Docker Compose fragment (auto-merged into the stack)
dream enable my-service # Enable it
dream disable my-service # Disable it
dream list # See everythingThe installer itself is modular — 6 libraries and 13 phases, each in its own file. Want to add a hardware tier, swap a default model, or skip a phase? Edit one file.
Full extension guide | Installer architecture
The dream CLI manages your entire stack:
dream status # Health checks + GPU status
dream list # All services and their state
dream logs llm # Tail logs (aliases: llm, stt, tts)
dream restart [service] # Restart one or all services
dream start / stop # Start or stop the stack
dream mode cloud # Switch to cloud APIs via LiteLLM
dream mode local # Switch back to local inference
dream mode hybrid # Local primary, cloud fallback
dream model swap T3 # Switch to a different hardware tier
dream enable n8n # Enable an extension
dream disable whisper # Disable one
dream config show # View .env (secrets masked)
dream preset save gaming # Snapshot current config
dream preset load gaming # Restore it| Dream Server | Ollama + Open WebUI | LocalAI | |
|---|---|---|---|
| Built for | Sovereign local AI ownership | Running a model locally | Running a model locally |
| One-command full-stack install | LLM + agents + workflows + RAG + voice + images | LLM + chat only | LLM only |
| Hardware auto-detect + model selection | NVIDIA + AMD Strix Halo | No | No |
| AMD APU unified memory support | ROCm + llama-server | Partial (Vulkan) | No |
| Autonomous AI agents | OpenClaw | No | No |
| Workflow automation | n8n (400+ integrations) | No | No |
| Voice (STT + TTS) | Whisper + Kokoro | No | No |
| Image generation | ComfyUI | No | No |
| RAG pipeline | Qdrant + embeddings | No | No |
| Extension system | Manifest-based, hot-pluggable | No | No |
| Multi-GPU | Yes (NVIDIA) | Partial | Partial |
| Quickstart | Step-by-step install guide with troubleshooting |
| Hardware Guide | What to buy, tier recommendations |
| FAQ | Common questions and configuration |
| Extensions | How to add custom services |
| Installer Architecture | Modular installer deep dive |
| Changelog | Version history and release notes |
| Contributing | How to contribute |
Dream Server exists because people chose to build instead of wait. Every contributor here is part of something bigger than code — a growing resistance against the idea that AI should be rented, gated, and controlled by the few. These are the founders of the sovereign AI movement, proving that one person, one machine, and one dream is enough.
Thanks to kyuz0 for amd-strix-halo-toolboxes — pre-built ROCm containers for Strix Halo that saved us a lot of pain from having to build our own. And to lhl for strix-halo-testing — the foundational Strix Halo AI research and rocWMMA performance work that the broader community builds on.
- llama.cpp (ggerganov) — LLM inference engine
- Qwen (Alibaba Cloud) — Default language models
- Open WebUI — Chat interface
- ComfyUI — Image generation engine
- FLUX.1 (Black Forest Labs) — Image generation model
- AMD ROCm — GPU compute platform
- AMD Strix Halo Toolboxes (kyuz0) — Pre-built ROCm containers for AMD inference
- Strix Halo Testing (lhl) — Foundational Strix Halo AI research and rocWMMA optimizations
- n8n — Workflow automation
- Qdrant — Vector database
- SearXNG — Privacy-respecting search
- Perplexica — AI-powered search
- LiteLLM — LLM API gateway
- Kokoro FastAPI (remsky) — Text-to-speech
- Speaches — Speech-to-text
- Strix Halo Home Lab — Community knowledge base
-
Yasin Bursali (yasinBursali) — Fixed CI workflow discovery, added dashboard-api router test coverage with security-focused tests (auth enforcement, path traversal protection), documented all 14 undocumented extension services, fixed macOS disk space preflight to check the correct volume for external drive installs, moved embeddings platform override to prevent orphaned service errors when RAG is disabled, fixed macOS portability issues restoring broken Apple Silicon Neural Engine detection (GNU date/grep to POSIX), fixed docker compose failure diagnostic unreachable under pipefail, added stderr warning on manifest parse failure in compose resolver, fixed socket FD leak in dashboard-api, added open-webui health gate to prevent 502 errors during model warmup, hardened ComfyUI with loopback binding and no-new-privileges on both NVIDIA and AMD, fixed Apple Silicon memory limit variable mismatch, added
set -euo pipefailto the installer catching silent failures, secured OpenCode with loopback binding and auto-generated passwords, added missing external_port_env to token-spy and dashboard manifests fixing hardcoded port resolution, fixed Apple Silicon dashboard to show correct RAM and GPU info using HOST_RAM_GB unified memory override, added VRAM gate fallback for Apple Silicon so features no longer incorrectly show insufficient_vram on unified memory machines, set OLLAMA_PORT=8080 in the macOS compose overlay with GPU_BACKEND=apple alignment, added dynamic port conflict detection from extension manifests on macOS, added cross-platform_sed_ihelper for BSD/GNU sed compatibility, removed API key from token-spy HTML response replacing it with a sessionStorage-based login overlay, added WSL2 host RAM detection via powershell.exe for correct tier selection, fixed dashboard health checks to treat HTTP 4xx as unhealthy, replaced GNU-onlydate +%s%Nwith portable_now_ms()timestamps across 8 files, fixed COMPOSE_FLAGS word-splitting bugs by converting to arrays, added a macOS readiness sidecar for native llama-server before open-webui starts, added mode-aware compose overlays for litellm/openclaw/perplexica depends_on (local/hybrid only), and fixed subprocess leak on client disconnect in setup.py -
latentcollapse (Matt C) — Security audit and hardening: OpenClaw localhost binding fix, multi-GPU VRAM detection, AMD dashboard hardening, and the Agent Policy Engine (APE) extension
-
Igor Lins e Silva (igorls) — Stability audit fixing 9 infrastructure bugs: dynamic compose discovery in backup/restore/update scripts, Token Spy persistent storage and connection pool hardening, dotglob rollback fix, systemd auto-resume service correction, removed auth gate from preflight ports endpoint for setup wizard compatibility, added ESLint flat config for the dashboard, cleaned up unused imports and linting across the Python codebase, and resolved CI failures across dashboard and smoke tests
-
Nino Skopac (NinoSkopac) — Token Spy dashboard improvements: shared metric normalization with parity tests, budget and active session tracking, configurable secure CORS replacing wildcard origins, and DB backend compatibility shim for sidecar migration
-
Glexy (fullstackdev0110) — Fixed dream-cli chat port initialization bug, hardened validate.sh environment variable handling with safer quoting and .env parsing, removed all
evalusage from installer/preflight env parsing, added a safe-env loader (lib/safe-env.sh) to prevent shell injection, unified all .env loading across 9 scripts to useload_env_file()eliminating duplicated parsers, added dream-cli status-json/config-validate/mode-summary commands, added extension manifest validation with versioned compatibility gating (dream_min/dream_max) for the v2 extension ecosystem, added comprehensive compatibility matrix documentation, and added test suites with CI integration for manifest validation, health checks, env validation, and CPU-only path -
bugman-007 — Parallelized health checks in dream status for 5–10× speedup using async gather with proper timeout handling, benchmark and test scripts, integrated backup/restore commands into dream-cli, added preset import/export with path traversal protection and archive validation, added preset diff command for comparing configurations with secret masking, quarantined broken edge quickstart instructions replacing them with supported cloud mode path, added SHA256 integrity manifests and verification for backups, added restore safety prompts requiring backup ID confirmation, added backup/restore round-trip integration test, added preset compatibility validation before load, added service registry tests to CI, and added Python type checking with mypy
-
norfrt6-lab — Replaced 12+ silent exception-swallowing patterns with specific exception types and proper logging, added cross-platform system metrics (macOS/Windows) for uptime, CPU, and RAM, plus Apple Silicon GPU detection via sysctl/vm_stat
-
boffin-dmytro — Added SHA256 integrity verification for GGUF model downloads with pre- and post-download checks, corrupt file detection with automatic re-download, fixed model filename casing mismatches, added network timeout hardening across 33+ HTTP operations preventing indefinite hangs, added port conflict and Ollama detection for the Linux installer matching macOS parity, fixed trap handler bugs in installer phases replacing explicit tmpfile cleanup for safe early-exit, added retry logic with error classification and exponential backoff for Docker image pulls, added a GPU detection progress indicator eliminating user anxiety during hardware scans, added Windows zip integrity validation with retry logic, added Docker image pull retry with timeout and post-pull validation via
docker inspect, added Intel Arc GPU detection and CPU-only default fallback replacing incorrect NVIDIA assumption, added compose stack validation during phase 02 catching syntax errors early, added background process tracking for FLUX model downloads with JSON-based task registry, and improved health check robustness with per-request timeout and adaptive exponential backoff -
takutakutakkun0420-hue — Added log rotation to all base services preventing unbounded disk growth, and added open-webui startup dependency on llama-server health ensuring the UI never shows a broken state
-
reo0603 — Fixed Makefile paths after dashboard-api move and heredoc quoting bug in session-manager.sh SSH command, narrowed broad exception catches to specific types across dashboard-api, and parallelized health checks for 17× faster execution
-
nt1412 — Wired dashboard-api agent metrics to Token Spy with background metrics collection, added TOKEN_SPY_URL/TOKEN_SPY_API_KEY env vars, and fixed missing key_management.py in privacy-shield Dockerfile
-
evereq — Relocated docs/images to resources/docs/images for cleaner monorepo root
-
championVisionAI — Added Alpine Linux (apk) and Void Linux (xbps) package manager support to the installer abstraction layer
-
Tony363 — Hardened service-registry.sh against shell injection in service IDs, narrowed silent exception catches in db.py to specific types, improved PII scrubber with Luhn check for credit card detection and deterministic token round-trip, fixed token-spy settings persistence with atomic writes replacing broken fcntl locking, fixed SSH command injection in session-manager.sh using stdin piping with shlex.quote, narrowed broad exception catches across dashboard-api to specific types with appropriate log levels, and added CLAUDE.md with project instructions and design philosophy If we missed anyone, open an issue. We want to get this right.
Apache 2.0 — Use it, modify it, ship it. See LICENSE.
Built by Light Heart Labs and The Collective