feat(setModel): remember selection; bump llama.cpp to b10450; refresh docs

.github/workflows/syncNext.yml

@@ -0,0 +1,16 @@
+name: Sync next
+
+# Carries every change that lands on the base branch onto the paired `next`
+# iteration branch, so `next` never drifts behind what has already shipped.
+# `next` is created on the first run if the repo does not have one yet.
+on:
+  push:
+    branches: ['master']
+  workflow_dispatch:
+
+jobs:
+  sync:
+    uses: Start9Labs/start-technologies/.github/workflows/syncNext.yml@master
+    permissions:
+      contents: write
+      pull-requests: write

AGENTS.md

@@ -6,12 +6,11 @@ Develop it inside a StartOS packaging workspace created by `start-cli s9pk init-
 which provides the packaging guide and agent context one level up. If you're reading this in a
 bare clone with no workspace, the full guide is at <https://docs.start9.com/packaging>.
 
-Work this package's `TODO.md` from top to bottom. Keep `README.md` (architecture, for developers and LLMs) and `instructions.md` (end-user docs) in sync with your changes.
+Work this package's `TODO.md` from top to bottom. Keep `README.md` (technical reference for an AI support or administering agent) and `instructions.md` (end-user docs) in sync with your changes.
 
 ## This repo
 
-- **Package id is `llama-cpp`.** Ships four image variants — `generic` (CPU), `nvidia` (CUDA), `rocm` (AMD), and `vulkan` — selected at build time via `VARIANT=…`; the `Makefile` overrides `ARCHES`/`TARGETS` before the `s9pk.mk` include and fans out to per-variant targets. `rocm` is x86-only. Exposes one `ui` interface (`api`, port 8080): the OpenAI-compatible API plus built-in chat UI, gated by OS reverse-proxy basic auth (username `admin`, password set via the **Set UI Password** critical action). No dependencies.
-
-## Inspecting a running install
-
-To run a command inside the service's container (read its generated config, grep app logs), use `start-cli package attach llama-cpp -n llama-cpp-sub -- <cmd>`. Select the subcontainer by **name** with `-n` (the name passed to `SubContainer.of` in `main.ts` — here `llama-cpp-sub`) or by image with `-i`. Note: `-s/--subcontainer` matches the internal **Guid**, not the name, so passing a name to `-s` fails with "no matching subcontainers".
+- **One repo, four builds.** `VARIANT` (see the `Makefile` targets) selects the image, architectures, and `hardwareRequirements` for `generic`, `nvidia`, `rocm`, and `vulkan`. Bump `upstreamBuild` once in `startos/manifest/index.ts` and every variant follows.
+- **The AMD matcher is a positive allowlist of discrete product names, not an iGPU exclusion.** StartOS's regex engine has no lookahead, and ROCm is unreliable on integrated Radeon — so a broad `amdgpu` match would route Ryzen APUs onto a build that does not work for them.
+- **The one-hour grace period on the health check is the model download.** Don't shorten it to something that looks more like a health check.
+- **Preset sizing reads VRAM where it can and system memory otherwise** (`startos/hardware.ts`), and the result is cached per process. `minMemoryGB` in `actions/presets.ts` is weights plus roughly 25% for the KV cache — keep that convention when adding a preset.

UPDATING.md

@@ -4,11 +4,11 @@ This package wraps [`ggml-org/llama.cpp`](https://github.com/ggml-org/llama.cpp)
 
 llama.cpp releases use monotonic build numbers of the form `bNNNN` (no semver), one per merged commit. Each release publishes four server image variants on `ghcr.io`:
 
-| Variant   | Image tag                                 | Arches       |
-| --------- | ----------------------------------------- | ------------ |
-| `generic` | `ghcr.io/ggml-org/llama.cpp:server-bNNNN` | amd64, arm64 |
-| `nvidia`  | `ghcr.io/ggml-org/llama.cpp:server-cuda-bNNNN` | amd64, arm64 |
-| `rocm`    | `ghcr.io/ggml-org/llama.cpp:server-rocm-bNNNN` | amd64        |
+| Variant   | Image tag                                        | Arches       |
+| --------- | ------------------------------------------------ | ------------ |
+| `generic` | `ghcr.io/ggml-org/llama.cpp:server-bNNNN`        | amd64, arm64 |
+| `nvidia`  | `ghcr.io/ggml-org/llama.cpp:server-cuda-bNNNN`   | amd64, arm64 |
+| `rocm`    | `ghcr.io/ggml-org/llama.cpp:server-rocm-bNNNN`   | amd64        |
 | `vulkan`  | `ghcr.io/ggml-org/llama.cpp:server-vulkan-bNNNN` | amd64, arm64 |
 
 All four variants are cut from the same upstream commit and bump together.

instructions.md

@@ -44,7 +44,7 @@ curl -s -u admin:<your-ui-password> <your-interface-url>/v1/chat/completions \
 
 ### Actions
 
-- **Set Model** — switch to a different preset or custom GGUF. The service restarts with the new weights; uncached models download on this restart.
+- **Set Model** — switch to a different preset or custom GGUF. The form opens with your current selection already filled in, so you can change one setting without re-entering the rest. The service restarts with the new weights; uncached models download on this restart.
 - **Set UI Password** — generate a new web UI password (username stays `admin`). Use it for first-time setup or to rotate the password later.
 - **Delete Model Cache** — remove a specific filename from the cache (e.g. `Qwen2.5-7B-Instruct-Q4_K_M.gguf`) to reclaim disk space. A deleted model will be re-downloaded if you select it again.
 

startos/actions/setModel.ts

@@ -113,11 +113,29 @@ export const setModel = sdk.Action.withInput(
 
   inputSpec,
 
-  async ({ effects }) => ({}),
+  async ({ effects }) => {
+    const saved = await storeJson.read((s) => s?.modelSelection).const(effects)
+    if (!saved || !(saved.selection in allVariants)) return {}
+    return {
+      config: { selection: saved.selection, value: saved.custom ?? {} },
+    }
+  },
 
   async ({ effects, input }) => {
     const config = input.config
     let serveArgs: string[]
+    let modelSelection: {
+      selection: string
+      custom:
+        | {
+            hfRepo: string
+            hfFile?: string
+            ctx: number
+            ngl: number
+            extraArgs?: string
+          }
+        | undefined
+    }
     if (config.selection === 'custom') {
       const v = config.value
       serveArgs = ['-hf', v.hfRepo]
@@ -129,6 +147,16 @@ export const setModel = sdk.Action.withInput(
       if (v.extraArgs && v.extraArgs.trim().length > 0) {
         serveArgs.push(...v.extraArgs.split(/\s+/).filter(Boolean))
       }
+      modelSelection = {
+        selection: 'custom',
+        custom: {
+          hfRepo: v.hfRepo,
+          hfFile: v.hfFile?.trim() || undefined,
+          ctx: v.ctx,
+          ngl: v.ngl,
+          extraArgs: v.extraArgs?.trim() || undefined,
+        },
+      }
     } else {
       const preset = models.find((m) => m.id === config.selection)
       if (!preset) {
@@ -138,7 +166,8 @@ export const setModel = sdk.Action.withInput(
       if (preset.hfFile) serveArgs.push('-hff', preset.hfFile)
       serveArgs.push('-c', String(preset.defaultCtx))
       if (isGpuVariant) serveArgs.push('-ngl', '999')
+      modelSelection = { selection: config.selection, custom: undefined }
     }
-    await storeJson.merge(effects, { serveArgs })
+    await storeJson.merge(effects, { serveArgs, modelSelection })
   },
 )

startos/fileModels/store.json.ts

@@ -4,6 +4,21 @@ import { sdk } from '../sdk'
 const shape = z.object({
   serveArgs: z.array(z.string()).optional().catch(undefined),
   uiPassword: z.string().optional().catch(undefined),
+  modelSelection: z
+    .object({
+      selection: z.string(),
+      custom: z
+        .object({
+          hfRepo: z.string(),
+          hfFile: z.string().optional(),
+          ctx: z.number(),
+          ngl: z.number(),
+          extraArgs: z.string().optional(),
+        })
+        .optional(),
+    })
+    .optional()
+    .catch(undefined),
 })
 
 export const storeJson = FileHelper.json(

startos/i18n/dictionaries/default.ts

@@ -14,25 +14,19 @@ const dict = {
 
   // actions/setModel.ts
   'Set Model': 7,
-  'Pick a curated GGUF preset sized for your hardware, or supply a custom HuggingFace model. The model will be downloaded on first startup if not already cached.':
-    8,
-  'Changing the model will restart the service and may require downloading a new model.':
-    9,
+  'Pick a curated GGUF preset sized for your hardware, or supply a custom HuggingFace model. The model will be downloaded on first startup if not already cached.': 8,
+  'Changing the model will restart the service and may require downloading a new model.': 9,
   Configuration: 10,
   'HuggingFace repo': 11,
-  'A HuggingFace GGUF repo, optionally with a quant tag (e.g. `unsloth/Qwen2.5-7B-Instruct-GGUF:Q4_K_M`).':
-    12,
+  'A HuggingFace GGUF repo, optionally with a quant tag (e.g. `unsloth/Qwen2.5-7B-Instruct-GGUF:Q4_K_M`).': 12,
   'HuggingFace file (optional)': 13,
-  'Specific GGUF filename inside the repo. Leave empty to let llama-server pick.':
-    14,
+  'Specific GGUF filename inside the repo. Leave empty to let llama-server pick.': 14,
   'Context size': 15,
   'Maximum context length in tokens. 0 uses the model default.': 16,
   'GPU layers': 17,
-  'Number of model layers to offload to GPU. Use a large value (e.g. 999) to offload everything; ignored on the generic CPU variant.':
-    18,
+  'Number of model layers to offload to GPU. Use a large value (e.g. 999) to offload everything; ignored on the generic CPU variant.': 18,
   'Extra arguments': 19,
-  'Additional `llama-server` flags, space-separated. Advanced — split on whitespace, so quoted values will not survive.':
-    20,
+  'Additional `llama-server` flags, space-separated. Advanced — split on whitespace, so quoted values will not survive.': 20,
   Custom: 21,
 
   // model preset labels
@@ -50,17 +44,13 @@ const dict = {
   'Delete Model Cache': 31,
   'Remove a downloaded GGUF model from the cache to free up disk space': 32,
   'Cached file': 33,
-  'Filename inside `/data/models` to delete (e.g. `Qwen2.5-7B-Instruct-Q4_K_M.gguf`).':
-    34,
-  'This will permanently delete the cached file. The model will be re-downloaded if selected again.':
-    35,
+  'Filename inside `/data/models` to delete (e.g. `Qwen2.5-7B-Instruct-Q4_K_M.gguf`).': 34,
+  'This will permanently delete the cached file. The model will be re-downloaded if selected again.': 35,
 
   // actions/setUiPassword.ts
   'Set UI Password': 36,
-  'Generate a new password for logging in to the llama.cpp web UI. The username is always "admin".':
-    37,
-  'This replaces any existing password. Update saved logins after running it.':
-    38,
+  'Generate a new password for logging in to the llama.cpp web UI. The username is always "admin".': 37,
+  'This replaces any existing password. Update saved logins after running it.': 38,
 
   // init/initializeService.ts
   'Generate a password to log in to the llama.cpp web UI': 39,

startos/manifest/i18n.ts

@@ -16,5 +16,5 @@ export const long = {
   pl_PL:
     'llama.cpp to wydajne środowisko uruchomieniowe C/C++ dla dużych modeli językowych w formacie GGUF. Ten pakiet otacza oficjalny plik binarny `llama-server`, udostępniając API HTTP zgodne z OpenAI i wbudowany interfejs czatu webowego. Wybierz wyselekcjonowany preset dopasowany do Twojego sprzętu lub podaj własny GGUF z HuggingFace — serwer pobierze wagi przy pierwszym uruchomieniu i będzie je obsługiwał lokalnie, bez żadnych połączeń z usługami zewnętrznymi.',
   fr_FR:
-    "llama.cpp est un runtime C/C++ haute performance pour les grands modèles de langage au format GGUF. Ce paquet enveloppe le binaire officiel `llama-server`, exposant une API HTTP compatible OpenAI et une interface de chat web intégrée. Choisissez un préréglage de modèle dimensionné pour votre matériel, ou fournissez un GGUF HuggingFace personnalisé — le serveur télécharge les poids au premier démarrage et les sert localement, sans appels à des tiers.",
+    'llama.cpp est un runtime C/C++ haute performance pour les grands modèles de langage au format GGUF. Ce paquet enveloppe le binaire officiel `llama-server`, exposant une API HTTP compatible OpenAI et une interface de chat web intégrée. Choisissez un préréglage de modèle dimensionné pour votre matériel, ou fournissez un GGUF HuggingFace personnalisé — le serveur télécharge les poids au premier démarrage et les sert localement, sans appels à des tiers.',
 }

startos/manifest/index.ts

@@ -6,7 +6,7 @@ const variant = process.env.VARIANT || 'generic'
 type Mutable<T> = { -readonly [K in keyof T]: Mutable<T[K]> }
 const mutable = <T>(value: T): Mutable<T> => value as Mutable<T>
 
-const upstreamBuild = 'b10438'
+const upstreamBuild = 'b10450'
 
 const imageConfigs = {
   generic: {