One installer gets you from bare metal to a fully running local AI stack — LLM inference, chat UI, voice agents, workflow automation, RAG, and privacy tools. No manual config. No dependency hell. No six months of piecing it together. Run one command, answer a few questions, everything works.
curl -fsSL https://raw.githubusercontent.com/Light-Heart-Labs/Lighthouse-AI/main/dream-server/get-dream-server.sh | bash
The installer detects your hardware, picks the optimal model, and asks how deep you want to go.
Everything running, at a glance. GPU metrics, service health, one-click access to Chat, Voice, Workflows, Agents, and Documents.
graph TB
subgraph User[" You "]
Browser(["Browser"])
Mic(["Microphone"])
API(["API Client"])
end
subgraph DreamServer["Dream Server (Docker Compose)"]
subgraph Core["Core"]
VLLM["vLLM · :8000<br/>LLM Inference"]
WebUI["Open WebUI · :3000<br/>Chat Interface"]
Dashboard["Dashboard · :3001<br/>GPU Metrics"]
end
subgraph Voice["Voice"]
Whisper["Whisper · :9000<br/>Speech → Text"]
Kokoro["Kokoro · :8880<br/>Text → Speech"]
LiveKit["LiveKit · :7880<br/>WebRTC"]
VoiceAgent["Voice Agent"]
end
subgraph RAGp["RAG"]
Qdrant["Qdrant · :6333<br/>Vector DB"]
Embeddings["Embeddings · :8090"]
end
subgraph Workflows["Workflows"]
N8N["n8n · :5678<br/>400+ Integrations"]
end
subgraph Agents["Agents"]
OpenClaw["OpenClaw · :7860<br/>Multi-Agent"]
ToolProxy["Tool Proxy<br/>vLLM Bridge"]
end
subgraph Privacy["Privacy"]
Shield["Privacy Shield · :8085<br/>PII Redaction"]
end
end
Browser --> WebUI
Browser --> Dashboard
Browser --> N8N
Mic --> LiveKit
API --> VLLM
WebUI --> VLLM
VoiceAgent --> Whisper
VoiceAgent --> Kokoro
VoiceAgent --> VLLM
LiveKit --> VoiceAgent
OpenClaw --> ToolProxy
ToolProxy --> VLLM
Shield -.->|PII scrubbed| VLLM
style Core fill:#e8f0fe,stroke:#1a73e8,color:#1a1a1a
style Voice fill:#fce8e6,stroke:#d93025,color:#1a1a1a
style RAGp fill:#e6f4ea,stroke:#1e8e3e,color:#1a1a1a
style Workflows fill:#fef7e0,stroke:#f9ab00,color:#1a1a1a
style Agents fill:#f3e8fd,stroke:#9334e6,color:#1a1a1a
style Privacy fill:#e8eaed,stroke:#5f6368,color:#1a1a1a
The installer auto-detects your GPU and activates the right profiles. Core services start immediately; voice, RAG, workflows, and agents activate based on your hardware and preferences.
Hobbyists — Want local ChatGPT without subscriptions? Install Dream Server, open localhost:3000, start chatting. Voice mode, document Q&A, and workflow automation are one toggle away.
Developers — Building AI agents? Dream Server gives you a local OpenAI-compatible API (vLLM), multi-agent coordination (OpenClaw), and a workflow engine (n8n) — all on your GPU. No API keys, no rate limits, no cost per token.
Teams — Need private AI infrastructure? Everything runs on your hardware. The Privacy Shield scrubs PII before anything leaves your network. Deploy once, use from any device on your LAN.
| Component | What It Does |
|---|---|
| vLLM | GPU-accelerated LLM inference with continuous batching — auto-selects 7B to 72B models for your hardware |
| Open WebUI | Full-featured chat interface with conversation history, model switching, web search |
| Dashboard | Real-time GPU metrics (VRAM, temp, utilization), service health, model management |
| Whisper | Speech-to-text — local, fast, private |
| Kokoro | Text-to-speech — natural-sounding voices, no cloud |
| LiveKit | Real-time WebRTC voice conversations — talk to your AI like a phone call |
| n8n | Visual workflow automation with 400+ integrations (GitHub, Slack, email, webhooks) |
| Qdrant | Vector database for document Q&A (RAG) |
| OpenClaw | Multi-agent AI framework — agents coordinating autonomously on your GPU |
| Privacy Shield | PII redaction proxy — scrubs personal data before any external API call |
| Tier | VRAM | Model | Example GPUs |
|---|---|---|---|
| Entry | <12GB | Qwen2.5-7B | RTX 3080, RTX 4070 |
| Prosumer | 12–20GB | Qwen2.5-14B-AWQ | RTX 3090, RTX 4080 |
| Pro | 20–40GB | Qwen2.5-32B-AWQ | RTX 4090, A6000 |
| Enterprise | 40GB+ | Qwen2.5-72B-AWQ | A100, H100, multi-GPU |
Bootstrap mode: Chat in 2 minutes. A tiny model starts instantly while the full model downloads in the background. Hot-swap with zero downtime when ready.
| Dream Server | Ollama + Open WebUI | LocalAI | |
|---|---|---|---|
| Full-stack install (LLM + voice + workflows + RAG + privacy) | One command | Manual assembly | Manual assembly |
| Hardware auto-detection + model selection | Yes | No | No |
| Voice agents (STT + TTS + WebRTC) | Built in | No | Partial |
| Inference engine | vLLM (continuous batching) | llama.cpp | llama.cpp |
| Workflow automation | n8n (400+ integrations) | No | No |
| PII redaction | Built in | No | No |
| Multi-agent framework | OpenClaw | No | No |
Ollama is great for running models locally. Dream Server is a complete AI platform — inference, voice, workflows, RAG, agents, privacy, and monitoring in one installer.
Standalone tools for running persistent AI agents in production. Each works independently — grab what you need.
| Tool | Purpose |
|---|---|
| Guardian | Self-healing process watchdog — monitors services, auto-restores from backup, runs as root so agents can't kill it |
| Memory Shepherd | Periodic memory reset to prevent identity drift in long-running agents |
| Token Spy | API cost monitoring with real-time dashboard and auto-kill for runaway sessions |
| vLLM Tool Proxy | Makes local vLLM tool calling work with OpenClaw — SSE re-wrapping, extraction, loop protection |
| LLM Cold Storage | Archives idle HuggingFace models to free disk, keeps them resolvable via symlink |
These tools were born from the OpenClaw Collective — 3 AI agents running autonomously on local GPUs, producing 3,464 commits in 8 days. Dream Server packages the infrastructure they built into something anyone can use.
| Quickstart | Step-by-step install guide with troubleshooting |
| FAQ | Common questions, hardware advice, configuration |
| Hardware Guide | GPU recommendations with real prices |
| Cookbook | Recipes: voice agents, RAG pipelines, code assistant, privacy proxy |
| Architecture | Deep dive into the system design |
| Contributing | How to contribute to Lighthouse AI |
Windows: install.ps1 handles WSL2 + Docker + NVIDIA drivers automatically.
Apache 2.0 — see LICENSE. Use it, modify it, ship it.
Built by Lightheart Labs and the OpenClaw Collective.