foam_sync.sh (lifebalance) 2026-09-07T11:54:12Z

sync
2026-09-07 11:54:25 -06:00 · 2026-09-07 11:54:25 -06:00
12 changed files with 975 additions and 25 deletions
@@ -1,14 +1,18 @@
 # AI
-## Learning
+## Learning
 * [The Ultimate Guide to Local AI and AI Agents (The Future is Here) - YouTube](https://www.youtube.com/watch?v=mNcXue7X8H0)
  * Docker Compose based framework for running AI locally
  * https://github.com/coleam00/local-ai-packaged
-* https://www.reddit.com/r/LocalLLaMA/
+* https://www.reddit.com/r/LocalLLaMA/
-*
+*
-
+
-## LocalAI Packaged
+## Projects
 * [[self-hosting AI on lifebalance]]
 ## LocalAI Packaged
 ### Services
@@ -0,0 +1,36 @@
 {
 	"folders": [
 		{
 			"path": "../code/ai-stack"
 		}
  ],
  "settings": {
    "workbench.colorCustomizations": {
      "activityBar.activeBackground": "#81c3a0",
      "activityBar.background": "#81c3a0",
      "activityBar.foreground": "#15202b",
      "activityBar.inactiveForeground": "#15202b99",
      "activityBarBadge.background": "#8d68b7",
      "activityBarBadge.foreground": "#e7e7e7",
      "commandCenter.border": "#15202b99",
      "sash.hoverBorder": "#81c3a0",
      "statusBar.background": "#5eb386",
      "statusBar.foreground": "#15202b",
      "statusBarItem.hoverBackground": "#47976d",
      "statusBarItem.remoteBackground": "#efe9f5",
      "statusBarItem.remoteForeground": "#15202b",
      "titleBar.activeBackground": "#5eb386",
      "titleBar.activeForeground": "#15202b",
      "titleBar.inactiveBackground": "#5eb38699",
      "titleBar.inactiveForeground": "#15202b99",
      "activityBarTop.activeBackground": "#81c3a0",
      "activityBarTop.background": "#81c3a0",
      "activityBarTop.foreground": "#15202b",
      "activityBarTop.inactiveForeground": "#15202b99",
      "commandCenter.foreground": "#15202b",
      "statusBar.debuggingBackground": "#5eb386",
      "statusBar.debuggingForeground": "#15202b"
    },
    "peacock.color": "#5eb386"
  }
 }
@@ -22,5 +22,5 @@
 ### Tooth pendants
-* [🦷 Real Anatomy Tooth Seth #1・ 3D File for 3D printing・Cults](https://cults3d.com/en/3d-model/art/real-anatomy-tooth-seth-1)
+* [🦷 Real Anatomy Tooth Seth #1・ 3D File for 3D printing・Cults]https://cults3d.com/en/3d-model/art/real-anatomy-tooth-seth-1
  * https://cults3d.com/en/orders/128683287
@@ -0,0 +1,81 @@
 # chezmoi
 [chezmoi](https://www.chezmoi.io/) is a dotfile manager that keeps configuration files synchronized across machines using a git-backed source directory.
 ## Setup
 ### Configuration
 Config file: `~/.config/chezmoi/chezmoi.toml`
 ```toml
 [git]
    autoCommit = true
    autoPush = true
 [merge]
 command = "bash"
 args = [
    "-c",
    "cp {{ .Target | quote }} {{ printf \"%s.base\" .Target | quote }} && code --new-window --wait --merge {{ .Destination | quote }} {{ .Target | quote }} {{ printf \"%s.base\" .Target | quote }} {{ .Source | quote }}",
 ]
 ```
 - **autoCommit**: Automatically commits changes after `chezmoi apply`
 - **autoPush**: Automatically pushes to remote after commit
 - **merge**: Custom merge command using VS Code's merge editor
 ### Source Directory
 `~/.local/share/chezmoi/` - Git repository containing managed dotfiles
 ## Managed Dotfiles
 | File/Directory | Description |
 |----------------|-------------|
 | `.bash_aliases` | Shell aliases |
 | `.bashrc` | Bash configuration |
 | `.tmux.conf` | Tmux configuration |
 | `.config/opencode/` | OpenCode AI assistant config |
 | `.gemini/settings.json` | Gemini CLI settings |
 | `.ssh/authorized_keys` | SSH authorized keys (private) |
 ### OpenCode Config
 The `.config/opencode/` directory includes:
 - `opencode.jsonc` - Main OpenCode configuration
 - `oh-my-opencode-slim.json` - Slim preset configuration
 - `executable_opencode-tmux-launch.sh` - Script to launch OpenCode in tmux
 ## Common Commands
 ```bash
 # Edit a dotfile in the source directory
 chezmoi edit ~/.bashrc
 # Apply changes to the home directory
 chezmoi apply
 # See what would change
 chezmoi diff
 # Add a new file to chezmoi
 chezmoi add ~/.newconfig
 # Edit the config file
 chezmoi edit-config
 # Initialize chezmoi on a new machine
 chezmoi init https://github.com/username/dotfiles.git
 ```
 ## Workflow
 1. Edit dotfiles with `chezmoi edit` (opens source file)
 2. Apply changes with `chezmoi apply`
 3. Changes auto-commit and push to git remote
 ## Related
 - [[homelab]]
 - [[dev environments]]
@@ -6,6 +6,35 @@
  ],
  "settings": {
    "foam.edit.linkReferenceDefinitions": "withExtensions",
-    "gitdoc.enabled": false
+    "gitdoc.enabled": false,
    "workbench.colorCustomizations": {
      "activityBar.activeBackground": "#ffb733",
      "activityBar.background": "#ffb733",
      "activityBar.foreground": "#15202b",
      "activityBar.inactiveForeground": "#15202b99",
      "activityBarBadge.background": "#008053",
      "activityBarBadge.foreground": "#e7e7e7",
      "commandCenter.border": "#15202b99",
      "sash.hoverBorder": "#ffb733",
      "statusBar.background": "#ffa500",
      "statusBar.foreground": "#15202b",
      "statusBarItem.hoverBackground": "#cc8400",
      "statusBarItem.remoteBackground": "#008053",
      "statusBarItem.remoteForeground": "#15202b",
      "titleBar.activeBackground": "#ffa500",
      "titleBar.activeForeground": "#15202b",
      "titleBar.inactiveBackground": "#ffa50099",
      "titleBar.inactiveForeground": "#15202b99",
      "activityBarTop.activeBackground": "#ffb733",
      "activityBarTop.background": "#ffb733",
      "activityBarTop.foreground": "#15202b",
      "activityBarTop.inactiveForeground": "#15202b99",
      "commandCenter.foreground": "#15202b",
      "statusBar.debuggingBackground": "#ffa500",
      "statusBar.debuggingForeground": "#15202b",
      "activityBar.activeBorder": "#15202b",
      "activityBarTop.activeBorder": "#15202b"
    },
    "peacock.color": "orange"
  }
 }
@@ -55,15 +55,23 @@
 ### Home auth
-## Hardware
+## Hardware
-
+
-* unnamed switch (TODO)
+* unnamed switch (TODO)
-  * [Mikrotik CSS318-16G-2S+IN](https://mikrotik.com/product/css318_16g_2s_in#fndtn-downloads)
+  * [Mikrotik CSS318-16G-2S+IN](https://mikrotik.com/product/css318_16g_2s_in#fndtn-downloads)
-  * SwOS management interface: http://192.168.86.54
+  * SwOS management interface: http://192.168.86.54
-  * [manual](https://help.mikrotik.com/docs/spaces/SWOS/pages/76415036/CRS3xx+and+CSS326-24G-2S+series+Manual#CRS3xxandCSS32624G2S+seriesManual-LAG)
+  * [manual](https://help.mikrotik.com/docs/spaces/SWOS/pages/76415036/CRS3xx+and+CSS326-24G-2S+series+Manual#CRS3xxandCSS32624G2S+seriesManual-LAG)
-* proxmox1
+* lifebalance
-  * Beelink Mini PC EQi12, Intel Core 1220P(Max 4.4GHz 10C/12T), 16GB DDR4 500GB PCle4.0 SSD Mini Computers,Dual LAN/Wifi6/BT5.2,Dual 4K Display,Built-in Power Supply Office PC
+  * Lenovo Legion T7 34IRZ8
-* proxmox2
+  * Intel Core i9-14900K
  * 62 GiB RAM
  * NVIDIA GeForce RTX 4090 (24 GiB VRAM)
  * Debian GNU/Linux forky/sid
  * [[self-hosting AI on lifebalance]]
  * [[rclone google drive]]
 * proxmox1
  * Beelink Mini PC EQi12, Intel Core 1220P(Max 4.4GHz 10C/12T), 16GB DDR4 500GB PCle4.0 SSD Mini Computers,Dual LAN/Wifi6/BT5.2,Dual 4K Display,Built-in Power Supply Office PC
 * proxmox2
  * Beelink Mini PC EQi12, Intel Core 1220P(Max 4.4GHz 10C/12T), 16GB DDR4 500GB PCle4.0 SSD Mini Computers,Dual LAN/Wifi6/BT5.2,Dual 4K Display,Built-in Power Supply Office PC
 * proxmox3
  * Beelink Mini PC EQi12, Intel Core 1220P(Max 4.4GHz 10C/12T), 16GB DDR4 500GB PCle4.0 SSD Mini Computers,Dual LAN/Wifi6/BT5.2,Dual 4K Display,Built-in Power Supply Office PC
@@ -1,5 +1,5 @@
-# making
+# making
-
+
 ## Collections
 * https://makerworld.com/en/@beepmill/collections
@@ -26,9 +26,11 @@
 ## Things to print
-* https://thangs.com/designer/ForgeCore
+* https://www.printables.com/model/613681-universal-key-cover/files
-  * Desk plants
+* https://thangs.com/designer/ForgeCore
  * Desk plants
 * Resin teeth #booloumud
 * https://www.printables.com/model/543553-gridfinity-storage-box-by-pred-now-parametric
 * [Modern Gridifinity Case](https://www.printables.com/model/894202-modern-gridfinity-case)
 * [Space Efficient Socket Holders - Gridfinity](https://www.printables.com/model/1101988-space-efficient-socket-holders-gridfinity/files)
  * Printing metric [[2025-06-15]]
@@ -71,11 +73,10 @@
 * Layer thickness
 [//begin]: # "Autogenerated link references for markdown compatibility"
 [2025-06-15]: 2025-06-15.md "2025-06-15"
 [2025-06-17]: 2025-06-17.md "2025-06-17"
 [2025-07-01]: 2025-07-01.md "2025-07-01"
 [2025-06-30]: 2025-06-30.md "2025-06-30"
 [2025-06-19]: 2025-06-19.md "2025-06-19"
 [2025-06-18]: 2025-06-18.md "2025-06-18"
-[//end]: # "Autogenerated link references"
+
@@ -0,0 +1,96 @@
 # rclone google drive
 Related: [[homelab]]
 ## Current setup
 This machine (`lifebalance`) is configured to access Google Drive through `rclone`.
 * Remote name: `gdrive`
 * Config file: `~/.config/rclone/rclone.conf`
 * Mount point: `~/gdrive`
 * Auth flow used: local browser OAuth on the machine during `rclone config create`
 ## Installation
 Installed from Debian packages:
 ```bash
 sudo apt-get update
 sudo apt-get install -y rclone
 ```
 ## Remote configuration
 The Google Drive remote was created with full-drive scope and verified successfully.
 Useful commands:
 ```bash
 rclone listremotes
 rclone lsd gdrive:
 rclone ls gdrive:docs
 ```
 ## Persistent mount
 The Drive mount is managed by a user systemd service.
 * Service file: `~/.config/systemd/user/rclone-gdrive.service`
 * Mount command:
 ```bash
 /usr/bin/rclone mount gdrive: /home/ben/gdrive --config=/home/ben/.config/rclone/rclone.conf --vfs-cache-mode=writes
 ```
 Service contents:
 ```ini
 [Unit]
 Description=Rclone mount for Google Drive
 Wants=network-online.target
 After=network-online.target
 [Service]
 Type=simple
 ExecStart=/usr/bin/rclone mount gdrive: /home/ben/gdrive --config=/home/ben/.config/rclone/rclone.conf --vfs-cache-mode=writes
 ExecStop=/usr/bin/fusermount3 -uz /home/ben/gdrive
 Restart=on-failure
 RestartSec=10
 [Install]
 WantedBy=default.target
 ```
 ## Service management
 ```bash
 systemctl --user daemon-reload
 systemctl --user enable --now rclone-gdrive.service
 systemctl --user status rclone-gdrive.service
 systemctl --user restart rclone-gdrive.service
 systemctl --user stop rclone-gdrive.service
 systemctl --user start rclone-gdrive.service
 ```
 Note: this mount starts automatically when the user session starts. If it should start before login after reboot, enable lingering for the user.
 ## Verification
 These checks succeeded:
 ```bash
 mountpoint ~/gdrive
 ls ~/gdrive
 ```
 ## Troubleshooting
 If the mount stops working:
 ```bash
 systemctl --user status rclone-gdrive.service
 journalctl --user -u rclone-gdrive.service -n 100 --no-pager
 fusermount3 -uz ~/gdrive
 systemctl --user restart rclone-gdrive.service
 ```
@@ -0,0 +1,616 @@
 # self-hosting AI on lifebalance
 Related: [[AI]], [[homelab]]
 ## Current host baseline
 * Hostname: `lifebalance`
 * Hardware: Lenovo Legion T7 34IRZ8, Intel Core i9-14900K, 62 GiB RAM, NVIDIA GeForce RTX 4090 (24 GiB VRAM), 1.9 TB NVMe (`/home` on a 1.6 TB logical volume)
 * OS: Debian GNU/Linux forky/sid, kernel `6.18.15+deb14-amd64`
 * NVIDIA stack: driver `550.163.01`, CUDA `12.4`
 * Container stack: Docker `29.3.1`, containerd `2.2.2`, NVIDIA Container Toolkit `1.19.0`
 ## Current AI status
 * No AI model server is currently running on `lifebalance`.
 * `docker.service` and `containerd.service` are running.
 * No `ollama` binary was found.
 * No `conda` install was found.
 * Global `python3` is `3.13.12`.
 * A dedicated `~/sglang` virtualenv exists, but it currently only has `pip` and `uv` installed.
 ## Evidence of previous setup
 ### SGLang
 * Virtualenv: `~/sglang`
 * Startup script: `~/sglang/bin/start-sglang.sh`
 * Intended launch command:
 ```shell
 python -m sglang.launch_server \
  --model Qwen/Qwen3-8B-AWQ \
  --port 30000 \
  --host 127.0.0.1 \
  --mem-fraction-static 0.88 \
  --context-length 32768 \
  --dtype auto \
  --trust-remote-code
 ```
 * Notes:
  * configured for localhost-only serving on port `30000`
  * sized to use most of the 4090 VRAM
  * comment suggests it was intended for "oh-my-opencode utility agents"
  * the script comments still reference `~/scripts/start-sglang.sh`, but the file currently lives in `~/sglang/bin/start-sglang.sh`
  * the venv is currently incomplete, so this script would not run without reinstalling `sglang`
 ### Unsloth (Docker)
 * Shell history shows installation of the NVIDIA container toolkit followed by `docker run ... --gpus all unsloth/unsloth`.
 * Current Docker artifacts:
  * image present: `unsloth/unsloth:latest` (~40.8 GB)
  * stopped container: `brave_dewdney`
  * published ports: `8888`, `8000`, `2222`
  * bind mount: `/home/ben/work:/workspace/work`
 * Notes:
  * `/home/ben/work` is currently empty
  * only `/workspace/work` was bind-mounted, so data under `/workspace/.cache/huggingface` would have lived inside the container layer instead of a persistent host path
  * shell history/container environment included a hard-coded Jupyter password; do not reuse that pattern without rotating the credential and moving it into a safer secret/env file flow
 ### LocalAI Packaged / Ollama notes
 * [[AI]] already contains notes for a `local-ai-packaged` stack with:
  * Open WebUI
  * n8n
  * Langfuse
  * Ollama
  * Qdrant
  * `python start_services.py --profile gpu-nvidia`
 * I did not find:
  * a local checkout of that repo on `lifebalance`
  * a `start_services.py` file on this PC
  * an installed `ollama` binary
  * matching running containers or service units
 * This likely refers to another machine, a deleted checkout, or a plan that was documented before the actual install happened.
 ### Related but separate artifacts
 * `homefoam/local-ai-beepmill.code-workspace` points at a missing `../local-ai-beepmill` folder.
 * `code/homelab_tofu/vm_beepboop.tf` defines a `beepboop` VM on `proxmox1` with GPU passthrough, 12 GiB RAM, and a 150 GiB disk.
 * `beepboop` may have been intended as a separate AI host, but there is not enough evidence on `lifebalance` to say it was actually used for this stack.
 ## Gaps to resolve
 These are the main unanswered execution details, not fundamental direction questions:
 * pick the exact `sglang` container image/tag strategy for reproducible deployment
 * decide whether model files should be stored explicitly under `${AI_DATA_ROOT}/models` or primarily re-hydrated through Hugging Face cache paths
 * define the exact Compose profile/default-start behavior for `open-webui`
 * decide the local secret storage pattern outside git (`.env`, separate secret file, password manager, or similar)
 * define the minimum backup policy for `open-webui` state, exported manifests, and any future adapters/checkpoints
 * document the exact fresh-host prerequisite list before the first real deployment
 ## Working plan v1
 ### Planning assumptions
 These are the current decisions for planning purposes:
 * first success = a local-only inference API on `lifebalance`
 * phase 1 should be Docker-first
 * phase 1 should target `Qwen3 8B AWQ` first
 * `Open WebUI` should come after the `SGLang` API is working
 * `lifebalance` is now the canonical LLM host; `beepboop` is no longer the intended host for this project
 * use a custom large-data storage root from day 1 instead of tool defaults
 * plan for host recreation from the beginning
 * keep reproducible stack-definition files in a separate dedicated repo/worktree, not inside this KB repo
 * phase 1 should include:
  * OpenAI-style API access
  * model switching
  * a web UI
  * quantized models
 * training/fine-tuning should come later, not in the initial stack
 ### Recommended architecture
 Use a phased hybrid approach:
 * **Phase 1 baseline:** `SGLang + Open WebUI`
 * **Phase 2 convenience track:** add `Ollama` only if easier model switching and broader casual experimentation become more important
 * **Phase 3 training track:** keep `Unsloth` separate as an occasional training/fine-tuning workflow, not part of the always-on serving stack
 ### Why this is the current recommendation
 * The primary goal is a strong local inference API, not just a chat UI.
 * `SGLang` fits that goal better than starting with an Ollama-first stack.
 * There is already evidence of prior `SGLang` experimentation on this machine, so this path builds on existing intent.
 * `Open WebUI` can still provide the human-facing UI without forcing Ollama to be the primary backend.
 * This keeps the first phase local-only while optimizing earlier for agent/tool use.
 ### Why not start with Ollama as the primary backend
 * It is more convenient for casual local experimentation than for an API-first serving plan.
 * It may still be useful later, but it is no longer the best fit for the primary phase-1 objective.
 * We can add it later without redesigning the whole stack.
 ### Why not start with SGLang as the only component
 * A web UI still matters in phase 1.
 * `Open WebUI` remains useful as the human-facing interface even if `SGLang` is the main backend.
 ### Why not start with Unsloth
 * The first outcome should be reliable inference, not training.
 * Training adds larger storage, cache, dataset, and secret-management concerns.
 * Keeping training separate reduces operational complexity.
 ## Phased roadmap
 ### Phase 1 — stable local workstation stack
 Goal: a local-only, Docker-managed baseline for everyday use.
 Planned components:
 * `sglang` for local model serving
 * `open-webui` as the follow-on chat/testing interface after the API baseline is working
 * persistent host directories for:
  * models
  * app data
  * logs
  * exported configuration
 Success criteria:
 * at least one primary quantized model is served reliably
 * the UI works locally on `lifebalance`
 * the API is usable by local scripts/tools and is documented as the canonical local endpoint
 * all services bind locally first, or are otherwise restricted to local use
 * storage locations are explicit and documented before large downloads begin
 ### Phase 2 — convenience and model-flexibility lane
 Goal: add easier model switching and a broader casual-use path only if phase-1 usage shows it is worth the extra moving parts.
 Planned changes:
 * evaluate whether adding `Ollama` improves day-to-day experimentation enough to justify dual backends
 * keep `SGLang` as the canonical agent/API backend unless there is a good reason to change that
 * decide whether:
  * `Open WebUI` should talk to SGLang only
  * `Open WebUI` should talk to Ollama only
  * both backends should coexist for different purposes
 Success criteria:
 * any second backend has a clear purpose
 * model/API behavior is predictable and documented
 * added convenience does not make the core serving path harder to operate
 ### Phase 3 — training and fine-tuning lane
 Goal: support occasional LoRA/fine-tuning experiments without destabilizing the serving stack.
 Planned components:
 * a separate `Unsloth` workflow
 * dedicated storage/caching locations for datasets, checkpoints, and Hugging Face assets
 * clear separation between:
  * always-on inference services
  * temporary experiment/training workloads
 Success criteria:
 * training artifacts persist outside disposable containers
 * secrets are not passed via shell history
 * training jobs do not accidentally overwrite or disrupt inference setup
 ## Planned implementation decisions
 When work begins, prefer:
 * one project directory for Compose files, env files, and documentation
 * one persistent storage root for models/caches/data
 * localhost-first networking before any LAN exposure
 * explicit secrets handling instead of shell-history passwords
 * one canonical source of truth in this note for ports, paths, and services
 ### Recommended storage layout
 Use a configurable storage root variable instead of hard-coding paths throughout the stack.
 Recommended current value on `lifebalance`:
 ```shell
 AI_DATA_ROOT=/home/ben/llm-data
 ```
 Recommended layout under that root:
 ```text
 ${AI_DATA_ROOT}/
  models/            # durable model files when not using opaque tool defaults
  huggingface/       # HF cache and downloads
  sglang/            # SGLang-specific state/config
  open-webui/        # Open WebUI persistent app data
  logs/              # service logs kept outside containers
  exports/           # saved manifests, model lists, config exports
  scratch/           # temporary working area
 ```
 Rationale:
 * `lifebalance` has a large `/home` logical volume, so `/home/ben/llm-data` is a practical first location.
 * The path should still be treated as configurable so another host can recreate the same setup with a different mount point.
 * The important invariant is the directory structure and variable name, not the literal absolute path.
 ### Reproducibility-first approach
 Treat the AI stack as something that should be rebuildable on a fresh host with minimal guesswork.
 Preferred pattern:
 * one small project directory for the stack definition
 * one configurable data root for persistent state
 * one env file for host-specific values
 * one setup note as the source of truth for how the stack is intended to work
 ### Project repo and workflow pivot
 The implementation repo now exists at:
 * `/home/ben/code/ai-stack`
 Current repo state:
 * git repo initialized
 * default branch set to `main`
 * OpenSpec initialized in the repo
 * tool integrations generated for `codex` and `opencode`
 * first OpenSpec change created: `bootstrap-local-ai-stack`
 Repository intent:
 * `openspec/` becomes the spec/change-management home for implementation work
 * this Foam note remains the KB-facing planning and operator-context note
 * implementation artifacts should now be tracked in the repo, with this note linking back to them as needed
 Current OpenSpec structure in the repo:
 ```text
 /home/ben/code/ai-stack/
  README.md
  openspec/
    changes/
      bootstrap-local-ai-stack/
        proposal.md
        design.md
        tasks.md
        specs/
          local-ai-stack/
            spec.md
    specs/
  .codex/
  .opencode/
 ```
 Operational implication:
 * future concrete stack work should start as OpenSpec changes in `ai-stack`
 * Foam should reference the repo and summarize decisions, rather than becoming the only place where implementation structure lives
 * the current baseline implementation change is `openspec/changes/bootstrap-local-ai-stack/`
 ## Stack definition v1
 This is the concrete definition for the separate stack repo/worktree that now exists outside this KB at `/home/ben/code/ai-stack`.
 ### Scope of v1
 Include in v1:
 * one Docker Compose stack definition repo called `ai-stack`
 * one always-on inference service: `sglang`
 * one follow-on UI service: `open-webui`
 * one shared host data root: `${AI_DATA_ROOT}`
 * localhost-only published ports by default
 * enough docs and templates to recreate the stack on another host
 Do **not** include in v1:
 * `ollama`
 * `unsloth`
 * training jobs
 * public LAN exposure by default
 * extra observability/services unless a real need appears
 ### Service topology
 ```text
 local tools / scripts
        |
        v
  127.0.0.1:30000
     sglang API
        |
        +---- model weights / HF cache / logs under ${AI_DATA_ROOT}
  127.0.0.1:3001
    Open WebUI
        |
        v
     talks to sglang over local Docker networking or local host endpoint
 ```
 Operational intent:
 * `sglang` is the canonical local inference backend
 * `open-webui` is a convenience client on top of that backend, not the center of the stack
 * if `open-webui` breaks, the API stack should still be usable directly
 ### Repo/worktree layout
 ```text
 ai-stack/
  compose.yaml
  .env.example
  .gitignore
  README.md
  docs/
    architecture.md
    recovery-checklist.md
    model-inventory.md
  sglang/
    launch.env.example
    notes.md
  open-webui/
    notes.md
  scripts/
    preflight-checklist.md
 ```
 File intent:
 * `compose.yaml` = the canonical service definition
 * `.env.example` = documented host-specific variables with placeholder values only
 * `.gitignore` = protect `.env`, logs, caches, exports, and downloaded assets from accidental commits
 * `README.md` = operator-first quickstart for bring-up, shutdown, update, and rebuild
 * `docs/architecture.md` = why the stack is shaped this way
 * `docs/recovery-checklist.md` = fresh-host rebuild order
 * `docs/model-inventory.md` = canonical list of intended models/adapters and where they are expected to come from
 * `sglang/launch.env.example` = model/server launch parameters that may vary by host or model choice
 * `sglang/notes.md` = operational notes for the inference service
 * `open-webui/notes.md` = operational notes for the UI layer
 * `scripts/preflight-checklist.md` = manual prerequisites/validation list before first start
 ### Compose contract
 Initial Compose services:
 * `sglang`
  * required in v1
  * NVIDIA-enabled container
  * publishes `127.0.0.1:30000:30000`
  * mounts model/cache/state/log paths from `${AI_DATA_ROOT}`
  * uses `Qwen/Qwen3-8B-AWQ` as the first default model
  * should be startable independently of any UI
 * `open-webui`
  * optional during initial API bring-up, but part of the v1 repo definition
  * publishes `127.0.0.1:3001:8080`
  * persists app state under `${AI_DATA_ROOT}/open-webui`
  * points at the existing `sglang` OpenAI-compatible endpoint
 Recommended Compose profiles:
 * default / baseline: `sglang`
 * optional UI profile: `open-webui`
 Meaning:
 * the inference API can come up first by itself
 * the UI can be layered on later without redefining the stack
 ### Host path contract
 `AI_DATA_ROOT` remains the root for all durable local state.
 ```text
 ${AI_DATA_ROOT}/
  models/            # model files if intentionally stored outside tool-managed caches
  huggingface/       # HF_HOME / HF hub cache
  sglang/            # sglang-specific state, configs, temp runtime data
  open-webui/        # persistent UI state
  logs/              # host-visible logs
  exports/           # inventories, backup manifests, saved config exports
  scratch/           # temporary manual work area
 ```
 Path rules:
 * containers should only write durable state inside `${AI_DATA_ROOT}`
 * container-internal default paths should be overridden where practical
 * logs worth keeping should land on the host, not only inside container stdout history
 ### Env contract
 The real `.env` should stay outside git. `.env.example` should document the contract.
 Expected variables for v1:
 ```dotenv
 AI_DATA_ROOT=/home/ben/llm-data
 SGLANG_HOST_PORT=30000
 OPEN_WEBUI_HOST_PORT=3001
 SGLANG_MODEL=Qwen/Qwen3-8B-AWQ
 SGLANG_CONTEXT_LENGTH=32768
 SGLANG_MEM_FRACTION_STATIC=0.88
 SGLANG_DTYPE=auto
 HF_HOME=/home/ben/llm-data/huggingface
 OPEN_WEBUI_DATA_DIR=/home/ben/llm-data/open-webui
 ```
 Notes:
 * secrets should be added only if/when a service actually needs them
 * avoid putting host-specific absolute paths directly into `compose.yaml` when a variable will do
 * if another host replaces `lifebalance`, the main required change should be env values, not Compose structure
 ### Canonical endpoints and names
 Use these as the first-pass defaults unless execution reveals a conflict:
 * stack repo/worktree name: `ai-stack`
 * primary service name: `sglang`
 * UI service name: `open-webui`
 * canonical local inference endpoint: `http://127.0.0.1:30000/v1`
 * canonical local UI URL: `http://127.0.0.1:3001`
 * primary model identifier: `Qwen/Qwen3-8B-AWQ`
 ### Operating rules for v1
 * prefer explicit image tags over floating `latest` where possible
 * prefer localhost binding over broad exposure
 * keep `sglang` usable without `open-webui`
 * treat model downloads as reproducible inputs, not irreplaceable state
 * treat UI state, manifests, and future adapters/checkpoints as state worth intentional preservation
 * do not add routing until there is a real second-model need
 ### Future extension points
 Planned later, but not part of the initial stack definition:
 * `ollama` as a separate convenience lane if model switching becomes more valuable than keeping one backend
 * a routing/gateway layer only after there are multiple active model backends to justify it
 * `unsloth` as a separate workflow/repo path for training or fine-tuning
 ### What should be reproducible vs backed up
 Rebuildable from config:
 * container definitions
 * image tags
 * port mappings
 * bind mounts
 * service-level configuration
 * startup commands
 * model identifiers to download
 Back up or preserve intentionally:
 * secrets outside git
 * exported model inventory/manifests
 * any local UI/app data worth keeping
 * any future training outputs, datasets, adapters, or checkpoints
 Usually re-download instead of backing up:
 * public base model weights
 * Hugging Face cache contents
 * container images
 Optional exception:
 * if download time becomes painful, a local backup of model files may still be worth doing, but that should be a conscious backup policy rather than an accident of where files ended up
 ### What belongs in git vs not in git
 Commit:
 * Compose files
 * config templates
 * `.env.example`
 * setup scripts that do not contain secrets
 * documentation, recovery notes, and model manifests
 Never commit:
 * `.env` with real values
 * API tokens, auth secrets, passwords
 * downloaded model weights
 * Hugging Face cache directories
 * logs
 * databases/app state unless deliberately exporting sanitized fixtures
 ## Implementation checklist (draft)
 This is a future execution checklist only. It does **not** mean these steps have been performed yet.
 ### 1. Create the reproducible stack-definition repo/worktree
 - [ ] create a dedicated repo/worktree for the AI stack definition
 - [ ] add `compose.yaml`
 - [ ] add `.env.example`
 - [ ] add a `README.md` with recovery/rebuild instructions
 - [ ] add config templates for `sglang` and later `open-webui`
 - [ ] add `.gitignore` rules for secrets, logs, caches, and downloaded assets
 ### 2. Define host-specific variables and conventions
 - [ ] define `AI_DATA_ROOT`
 - [ ] define canonical service names, ports, and container names
 - [ ] define the canonical local API endpoint for `sglang`
 - [ ] define where logs should live on the host
 - [ ] define the host-specific values that belong in `.env` rather than in committed files
 ### 3. Create the persistent storage layout
 - [ ] create `${AI_DATA_ROOT}`
 - [ ] create `${AI_DATA_ROOT}/models`
 - [ ] create `${AI_DATA_ROOT}/huggingface`
 - [ ] create `${AI_DATA_ROOT}/sglang`
 - [ ] create `${AI_DATA_ROOT}/open-webui`
 - [ ] create `${AI_DATA_ROOT}/logs`
 - [ ] create `${AI_DATA_ROOT}/exports`
 - [ ] create `${AI_DATA_ROOT}/scratch`
 - [ ] document ownership/permissions expectations for these paths
 ### 4. Prepare secrets and env handling
 - [ ] decide how local secrets will be stored outside git
 - [ ] create `.env` from `.env.example`
 - [ ] ensure no passwords or tokens are passed through shell history
 - [ ] document which values are required for a fresh-host rebuild
 ### 5. Stand up the SGLang API baseline
 - [ ] define the `sglang` image/tag strategy
 - [ ] define bind mounts for model/cache/log locations
 - [ ] define the startup command for `Qwen3 8B AWQ`
 - [ ] keep networking local-only by default
 - [ ] document how the service is started, stopped, restarted, and updated
 - [ ] document how the model is fetched or made available reproducibly
 ### 6. Validate the API baseline
 - [ ] confirm the service starts cleanly
 - [ ] confirm the model loads successfully on the 4090
 - [ ] confirm the local OpenAI-compatible endpoint works
 - [ ] confirm logs are written to the expected host path
 - [ ] document basic smoke tests for future rebuild validation
 ### 7. Add Open WebUI after the API baseline is stable
 - [ ] add `open-webui` to the stack-definition repo/worktree
 - [ ] bind its persistent data to `${AI_DATA_ROOT}/open-webui`
 - [ ] connect it to the existing `sglang` API
 - [ ] document the intended UI URL and local-only access model
 - [ ] document what configuration is UI state vs committed config
 ### 8. Capture disaster-recovery details
 - [ ] document host prerequisites required before stack deployment
 - [ ] document the exact rebuild order on a fresh machine
 - [ ] document what must be restored from backup vs re-downloaded
 - [ ] export a model/config inventory into `${AI_DATA_ROOT}/exports`
 - [ ] add a short recovery checklist for "lifebalance died, rebuild elsewhere"
 ### 9. Leave room for later phases
 - [ ] define how a future `ollama` lane would coexist without replacing `sglang` as the primary API
 - [ ] define how a future `unsloth` workflow would keep training artifacts separate from inference services
 - [ ] document what additional storage/backup policy would be needed for adapters, datasets, and checkpoints
 [AI]: AI.md "AI"
 [homelab]: homelab.md "homelab"
@@ -1,7 +1,7 @@
 {
  "folders": [
    {
-      "path": "../shopify_theme"
+      "path": "../code/shopify_theme"
    }
  ],
  "settings": {
@@ -17,12 +17,21 @@
      "statusBar.background": "#96bf48",
      "statusBar.foreground": "#15202b",
      "statusBarItem.hoverBackground": "#7a9d37",
-      "statusBarItem.remoteBackground": "#96bf48",
+      "statusBarItem.remoteBackground": "#3a80a5",
      "statusBarItem.remoteForeground": "#15202b",
      "titleBar.activeBackground": "#96bf48",
      "titleBar.activeForeground": "#15202b",
      "titleBar.inactiveBackground": "#96bf4899",
-      "titleBar.inactiveForeground": "#15202b99"
+      "titleBar.inactiveForeground": "#15202b99",
      "activityBarTop.activeBackground": "#accc6e",
      "activityBarTop.background": "#accc6e",
      "activityBarTop.foreground": "#15202b",
      "activityBarTop.inactiveForeground": "#15202b99",
      "commandCenter.foreground": "#15202b",
      "statusBar.debuggingBackground": "#96bf48",
      "statusBar.debuggingForeground": "#15202b",
      "activityBar.activeBorder": "#15202b",
      "activityBarTop.activeBorder": "#15202b"
    },
    "peacock.color": "#96bf48"
  }
@@ -0,0 +1,70 @@
 # tmux
 Terminal multiplexer configuration managed via [[chezmoi]].
 ## Configuration
 `~/.tmux.conf` - sourced from chezmoi at `~/.local/share/chezmoi/dot_tmux.conf`
 ```conf
 # TPM - Tmux Plugin Manager
 set -g @plugin 'tmux-plugins/tpm'
 set -g @plugin 'tmux-plugins/tmux-sensible'
 # Session persistence
 set -g @plugin 'tmux-plugins/tmux-resurrect'
 set -g @plugin 'tmux-plugins/tmux-continuum'
 # Resurrect options
 set -g @resurrect-capture-pane-contents 'on'
 # Continuum options
 set -g @continuum-restore 'on'
 set -g @continuum-save-interval '15'
 # Initialize TPM (must be at the bottom)
 run '~/.tmux/plugins/tpm/tpm'
 # Base settings
 set-option -g mouse
 set-window-option -g window-size latest
 set-window-option -g aggressive-resize on
 ```
 ## Plugins
 ### TPM (Tmux Plugin Manager)
 Plugin manager for tmux. Install new plugins by adding them to `.tmux.conf` then pressing `prefix + I`.
 ### tmux-sensible
 Basic settings that most tmux users want. Included by default.
 ### tmux-resurrect
 Saves and restores tmux environment after restart.
 - `prefix + Ctrl-s` - Save current environment
 - `prefix + Ctrl-r` - Restore last save
 Saves: sessions, windows, panes, layouts, working directories, running programs
 ### tmux-continuum
 Automatic saving and restoring. Requires tmux-resurrect.
 - Auto-saves every 15 minutes (configurable via `@continuum-save-interval`)
 - Auto-restores on tmux start when `@continuum-restore 'on'`
 Saves stored in `~/.tmux/resurrect/` (~5KB per save)
 ## Base Settings
 | Setting | Description |
 |---------|-------------|
 | `mouse` | Enable mouse support (click, scroll, resize) |
 | `window-size latest` | Use newest window size when creating new windows |
 | `aggressive-resize` | Aggressively resize windows to fit smallest client |
 ## Installation
 After updating `.tmux.conf`:
 1. Reload config: `tmux source-file ~/.tmux.conf`
 2. Install plugins: press `prefix + I` inside tmux
Author	SHA1	Message	Date
Ben	574fbfeba9	foam_sync.sh (lifebalance) 2026-09-07T11:54:12Z	2026-09-07 11:54:25 -06:00
Ben	d304fd0e6e	sync	2026-09-07 11:54:25 -06:00