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+# Local AI Stack
+
+A fully offline, self-hosted AI environment for Ubuntu 24.04. Runs on any NVIDIA GPU (or CPU-only).
+
+**Services:** Ollama · Open WebUI · RAG · MCP · ChromaDB · SearXNG · Kiwix · Gitea · InvokeAI · Portainer
+
+---
+
+## Quick Start
+
+```bash
+git clone <this-repo>
+cd local-ai
+./laptop_full_setup.sh
+```
+
+That's it. The script installs Docker, NVIDIA drivers (if needed), generates all config, starts the stack, and optionally pulls models.
+
+---
+
+## Service URLs
+
+After setup, all services are available on your LAN:
+
+| Service    | URL                        | Purpose                        |
+|------------|----------------------------|--------------------------------|
+| Open WebUI | `http://<ip>:3000`         | Chat interface (Ollama + RAG)  |
+| InvokeAI   | `http://<ip>:9090`         | Image generation               |
+| SearXNG    | `http://<ip>:8888`         | Private web search             |
+| Kiwix      | `http://<ip>:8181`         | Offline Wikipedia / docs       |
+| Gitea      | `http://<ip>:3001`         | Self-hosted Git                |
+| RAG Health | `http://<ip>:8001/health`  | RAG server status              |
+| MCP SSE    | `http://<ip>:8002/sse`     | MCP endpoint for Claude Code   |
+| Portainer  | `https://<ip>:9443`        | Docker management UI           |
+
+---
+
+## Day-to-Day Commands
+
+All generated into `~/docker/ai-stack/` by the setup script:
+
+```bash
+bash ~/docker/ai-stack/start.sh       # pull latest images + docker compose up -d
+bash ~/docker/ai-stack/stop.sh        # docker compose down
+bash ~/docker/ai-stack/status.sh      # GPU / container / RAG health
+bash ~/docker/ai-stack/pull-models.sh # pull Ollama models (run once after first install)
+```
+
+The stack also registers as a **systemd service** that starts on boot:
+
+```bash
+sudo systemctl start local-ai
+sudo systemctl stop local-ai
+sudo systemctl status local-ai
+```
+
+---
+
+## Script Reference
+
+| Script | Lines | What it does |
+|---|---|---|
+| `laptop_full_setup.sh` | 620 | **Main setup.** Installs Docker + NVIDIA toolkit, creates `~/docker/ai-stack/`, writes `docker-compose.yml`, starts stack, registers systemd service. |
+| `local-ai-setup.sh` | 837 | Alternative setup script. Same as above but also **auto-detects VRAM** and selects models accordingly (14B for ≥14GB VRAM, 7B for CPU). Use this instead of `laptop_full_setup.sh` if you want VRAM-aware model selection. |
+| `ubuntu-post-install.sh` | 8,889 | Full Ubuntu 24.04 post-install (dev tools, fonts, apps, tweaks). Run once on a fresh OS install. Independent of the AI stack. |
+| `configure-storage.sh` | 239 | Storage/mount configuration helper. Run separately if you have a secondary drive for AI data. |
+| `kiwix_download.sh` | 198 | Downloads ZIM files (Wikipedia, Stack Overflow, etc.) for offline use. Run separately — files are large. |
+
+### Which setup script should I use?
+
+- `laptop_full_setup.sh` — fixed model selection (`qwen2.5:14b` / `qwen2.5-coder:7b`), simpler
+- `local-ai-setup.sh` — detects your VRAM at runtime and picks appropriate models, also embeds `server.py` and `mcp_server.py` directly (doesn't need repo files copied separately)
+
+Both scripts are **idempotent** — safe to re-run for updates. Config files are kept on re-run unless you pass `--force`.
+
+---
+
+## Generated File Layout
+
+```
+~/docker/ai-stack/
+├── docker-compose.yml      # generated by setup script
+├── .env                    # API tokens — edit this, never overwritten
+├── server.py               # RAG server (copied from repo)
+├── mcp_server.py           # MCP server (copied from repo)
+├── requirements.txt        # RAG Python deps
+├── mcp_requirements.txt    # MCP Python deps
+├── start.sh                # start the stack
+├── stop.sh                 # stop the stack
+├── status.sh               # GPU + container + RAG health
+├── pull-models.sh          # pull Ollama models
+├── Caddyfile.example       # reverse proxy config template
+├── papers/                 # drop PDFs here for RAG indexing
+├── repos/                  # git repos indexed by RAG
+├── workspace/              # MCP working directory
+├── index/                  # ChromaDB vector store (persistent)
+├── kiwix/                  # ZIM files for Kiwix
+├── gitea/                  # Gitea data
+├── invokeai-outputs/       # InvokeAI generated images
+└── logs/
+```
+
+---
+
+## First Run Checklist
+
+1. **Run setup:**
+   ```bash
+   ./laptop_full_setup.sh
+   ```
+2. **Pull models** (prompted at end of setup, or run manually):
+   ```bash
+   bash ~/docker/ai-stack/pull-models.sh
+   ```
+   Downloads ~15-30GB. Takes 10-40 min depending on connection.
+
+3. **Add API tokens** (optional — for Gitea/GitHub MCP tools):
+   ```bash
+   nano ~/docker/ai-stack/.env
+   ```
+
+4. **Connect Claude Code to MCP:**
+   ```bash
+   claude mcp add local http://<your-ip>:8002/sse
+   ```
+
+5. **Download ZIMs** for offline docs (optional, large):
+   ```bash
+   ./kiwix_download.sh
+   ```
+
+---
+
+## Updating
+
+Re-run the setup script — it detects an existing install and skips prereqs:
+
+```bash
+./laptop_full_setup.sh
+# or
+./laptop_full_setup.sh --force   # also overwrites config files
+```
+
+---
+
+## GPU / Model Tiers (`local-ai-setup.sh`)
+
+| VRAM    | Chat model      | Code model            | Context |
+|---------|-----------------|-----------------------|---------|
+| ≥ 14 GB | qwen2.5:14b     | qwen2.5-coder:14b     | 32k     |
+| 8–14 GB | qwen2.5:14b     | qwen2.5-coder:7b      | 16k     |
+| 4–8 GB  | qwen2.5:7b      | qwen2.5-coder:7b      | 8k      |
+| CPU     | qwen2.5:7b      | qwen2.5-coder:7b      | 4k      |
+
+Embed model is always `nomic-embed-text` (required for RAG).