feat: integrate Guide-Tab (Anleitung) for local Vibe Coding and compile frontend

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>

.claude/launch.json

@@ -0,0 +1,19 @@
+{
+  "version": "0.0.1",
+  "configurations": [
+    {
+      "name": "mc2",
+      "runtimeExecutable": "F:\\Coding Stuff\\mission-control-2\\backend\\.venv\\Scripts\\python.exe",
+      "runtimeArgs": [
+        "-m",
+        "uvicorn",
+        "app:app",
+        "--app-dir",
+        "F:\\Coding Stuff\\mission-control-2\\backend",
+        "--port",
+        "9000"
+      ],
+      "port": 9000
+    }
+  ]
+}

.gitignore

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+# Python
+backend/.venv/
+__pycache__/
+*.pyc
+
+# Node / Vite
+frontend/node_modules/
+# frontend/dist wird committet (kein Node-Build auf der Box) — siehe deploy/
+
+# Env / local
+*.env
+.DS_Store

README.md

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+# Mission Control 2.0
+
+Komponierbarer Local-AI-Stack für den Bosgame M5. Greenfield-Neuaufbau —
+siehe Architektur-Plan (`docs/` bzw. der genehmigte Plan).
+
+**Schichten:** Engine (llama-swap) · Routing-Gateway (LiteLLM, `model: auto`) ·
+Mission Control 2.0 (FastAPI + React/shadcn) · Hermes Agent + hermes-webui ·
+Shared Memory (SQLite via MCP). Jede Schicht hinter stabilem Vertrag austauschbar.
+
+## Status: Phasen 0–5 ✅ · MC2 **live auf der Box** (:9001) · Modelle/Hermes-Wiring + Cutover offen
+
+Fortschritt & Resume-Guide: siehe [`docs/STATUS.md`](docs/STATUS.md).
+
+- **Phase 0** — FastAPI-Skeleton + React/shadcn-Shell (Cmd+K, Dark, PWA).
+- **Phase 1** — Compute-Module (fit/caps/sources, portiert), **Discover** (live HF + Fit + Caps),
+  **Engine-Write** (register + `groups`/Ko-Residenz), **LiteLLM-Gateway** (Config + Service,
+  `model: auto` + Fallbacks), Frontend **Modelle & Routing** (Caps-Chips, Fit, Discover, Routing-View).
+
+- **Phase 2** — System-Status (CPU/RAM/GPU/Disk), Wartung (restart/self-update, sudo-frei),
+  **Connect** (saubere IDE-Snippets → Gateway `model:auto`, LAN-IP-Override).
+- **Phase 3** — Geteiltes **Gedächtnis** (SQLite/WAL, 5 Kategorien, Dedupe-Kurator) + **MCP-Server**
+  (`mcp/mcp_memory.py` shared, `mcp/mcp_mc.py` Stack-Management für Hermes), MemoryView.
+
+- **Phase 4** — Hermes-**Agent-Status** (`/api/agent/status`, AgentView mit Tiles + „Hermes öffnen"),
+  `deploy/hermes-webui.service`, **Box-Runbook** [`docs/HERMES_SETUP.md`](docs/HERMES_SETUP.md)
+  (hermes-webui, Brain=`auto`, Tools/MCP-Verdrahtung). Box-Ausführung steht noch aus.
+
+- **Phase 5** — **Backup** (Memory + Configs), **Services-Health** + Observability-Links,
+  **Theme-Toggle** (Hell/Dunkel). Box-Deploy/-Wiring + Cutover (Phase 6) brauchen die Box.
+
+API: `health · models · discover · fit · models/register · groups · routing · system/* · connect ·
+memory/* · agent/status` (Details in `docs/STATUS.md`). MCP: `mcp/` (siehe `mcp/requirements.txt`).
+Box-Runbooks: `docs/HERMES_SETUP.md` + `deploy/` (Units, deploy.sh, backup.sh).
+
+## Entwickeln
+
+**Backend:**
+```bash
+cd backend
+python -m venv .venv && .venv/Scripts/python -m pip install -r requirements.txt   # Windows
+.venv/Scripts/python -m uvicorn app:app --port 9000
+```
+
+**Frontend (Dev, proxyt /api → :9000):**
+```bash
+cd frontend
+npm install
+npm run dev          # http://localhost:5173
+```
+
+**Frontend (Build → wird vom Backend ausgeliefert):**
+```bash
+cd frontend && npm run build   # → frontend/dist
+```
+
+## Env-Vars (Auswahl)
+
+| Variable | Default | Zweck |
+|---|---|---|
+| `MC_LLAMA_SWAP_URL` | `http://127.0.0.1:8080` | Engine |
+| `MC_CONFIG_PATH` | `/etc/llama-swap/config.yaml` | llama-swap Config |
+| `MC_GATEWAY_URL` | `http://127.0.0.1:4000` | LiteLLM-Gateway |
+| `MC_PORT` | `9000` | MC-Backend-Port |

backend/app.py

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+"""
+Mission Control 2.0 — dünner FastAPI-Einstieg.
+
+Hängt die Router ein, liefert (in Prod) das gebaute React-Frontend aus und
+setzt eine no-cache-Middleware. Im Dev läuft das Frontend über den Vite-Dev-
+Server (proxyt /api hierher), daher CORS für localhost offen.
+"""
+
+from fastapi import FastAPI
+from fastapi.middleware.cors import CORSMiddleware
+from fastapi.responses import FileResponse
+from fastapi.staticfiles import StaticFiles
+from starlette.requests import Request
+
+from config import FRONTEND_DIST, VERSION
+from routers import agent, connect, gateway_proxy, health, maintenance, memory, models, routing, system
+
+app = FastAPI(title="Mission Control 2.0", version=VERSION)
+
+# Dev: Vite-Dev-Server (5173) ruft das Backend per /api auf.
+app.add_middleware(
+    CORSMiddleware,
+    allow_origins=["http://localhost:5173", "http://127.0.0.1:5173"],
+    allow_methods=["*"],
+    allow_headers=["*"],
+)
+
+
+@app.middleware("http")
+async def no_cache(request: Request, call_next):
+    resp = await call_next(request)
+    if request.url.path.startswith("/api"):
+        resp.headers["Cache-Control"] = "no-cache"
+    return resp
+
+
+app.include_router(health.router)
+app.include_router(models.router)
+app.include_router(routing.router)
+app.include_router(system.router)
+app.include_router(connect.router)
+app.include_router(memory.router)
+app.include_router(agent.router)
+app.include_router(gateway_proxy.router)  # OpenAI-kompatibler /v1-Gateway (model:auto)
+app.include_router(maintenance.router)
+
+
+# Prod: gebautes Frontend ausliefern (falls vorhanden). SPA-Fallback auf index.html.
+if FRONTEND_DIST.exists():
+    app.mount("/assets", StaticFiles(directory=FRONTEND_DIST / "assets"), name="assets")
+
+    @app.get("/{full_path:path}")
+    def spa(full_path: str):
+        # Falls die Datei direkt in FRONTEND_DIST liegt (z.B. manifest.webmanifest, favicon.ico), liefere sie aus
+        target = FRONTEND_DIST / full_path
+        if target.is_file():
+            return FileResponse(target)
+            
+        index = FRONTEND_DIST / "index.html"
+        if index.exists():
+            return FileResponse(index)
+        return {"detail": "frontend not built"}
+

backend/config.py

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+"""
+Zentrale Konfiguration für Mission Control 2.0.
+
+Eine Quelle der Wahrheit für Pfade, URLs und Defaults — alles über Env-Vars
+überschreibbar. Bewusst schlank: MC 2.0 ist ein Glue-Cockpit, das vorhandene
+Dienste (llama-swap, LiteLLM-Gateway, Hermes) steuert, statt sie nachzubauen.
+"""
+
+import os
+from pathlib import Path
+
+from ruamel.yaml import YAML
+
+# --- Engine (llama-swap) -----------------------------------------------------
+LLAMA_SWAP_URL = os.environ.get("MC_LLAMA_SWAP_URL", "http://127.0.0.1:8080").rstrip("/")
+CONFIG_PATH = Path(os.environ.get("MC_CONFIG_PATH", "/etc/llama-swap/config.yaml"))
+MODELS_DIR = Path(os.environ.get("MC_MODELS_DIR", "/srv/models"))
+# Cache der Modell-Entdeckung ("aktuell beste Modelle", live von HuggingFace).
+# Persistent neben den Modellen (übersteht Deploys). TTL = Frische-Fenster.
+DISCOVER_CACHE_PATH = Path(os.environ.get("MC_DISCOVER_CACHE", str(MODELS_DIR / "mc2-discover.json")))
+DISCOVER_TTL = int(os.environ.get("MC_DISCOVER_TTL", "43200"))  # 12 h
+# Geteiltes Gedächtnis (SQLite, WAL). Persistent neben den Modellen.
+MEMORY_DB = Path(os.environ.get("MC_MEMORY_DB", str(MODELS_DIR / "mc2-memory.db")))
+# Befehl-Vorlage für llama-swap: {model}=GGUF-Pfad, {ctx}=Kontext, ${PORT} bleibt stehen.
+_DEFAULT_CMD_TEMPLATE = (
+    "llama-server -m {model} --host 127.0.0.1 --port ${PORT} "
+    "-c {ctx} -ngl 999 -fa 1 --no-mmap"
+)
+CMD_TEMPLATE = os.environ.get("MC_CMD_TEMPLATE", _DEFAULT_CMD_TEMPLATE)
+if "{model}" not in CMD_TEMPLATE:
+    CMD_TEMPLATE = _DEFAULT_CMD_TEMPLATE
+DEFAULT_TTL = int(os.environ.get("MC_DEFAULT_TTL", "300"))
+# Env für HuggingFace-Downloads: XET deaktivieren (Hänger bei ~6 MB, siehe v1-Gotcha).
+HF_DOWNLOAD_ENV = {"HF_HUB_DISABLE_XET": "1"}
+
+# --- Routing-Gateway (LiteLLM, model: auto) ----------------------------------
+GATEWAY_URL = os.environ.get("MC_GATEWAY_URL", f"http://127.0.0.1:{os.environ.get('MC_PORT', '9000')}").rstrip("/")
+GATEWAY_CONFIG_PATH = Path(os.environ.get(
+    "MC_GATEWAY_CONFIG", str(Path(__file__).resolve().parent.parent / "gateway" / "config.yaml")))
+
+# --- Hermes Agent (eigener Dienst auf der Box) -------------------------------
+# Gateway (OpenAI-API des Agenten) + standalone Web-UI (nesquena/hermes-webui).
+HERMES_API_URL = os.environ.get("HERMES_API_URL", "http://127.0.0.1:8642").rstrip("/")
+HERMES_WEBUI_URL = os.environ.get("HERMES_WEBUI_URL", "http://127.0.0.1:8787").rstrip("/")
+HERMES_HOME = Path(os.path.expanduser(os.environ.get("HERMES_HOME", "~/.hermes")))
+
+# --- Server ------------------------------------------------------------------
+HOST = os.environ.get("MC_HOST", "0.0.0.0")
+PORT = int(os.environ.get("MC_PORT", "9000"))
+# Gebautes React-Frontend (frontend/dist). In Prod liefert FastAPI es statisch aus;
+# im Dev läuft der Vite-Dev-Server separat und proxyt /api hierher.
+FRONTEND_DIST = Path(os.environ.get("MC_FRONTEND_DIST", str(Path(__file__).resolve().parent.parent / "frontend" / "dist")))
+
+# Version (Phase 0 — Greenfield-Skeleton).
+VERSION = "2.0.0-w8"
+
+# Gemeinsame YAML-Instanz (preserve_quotes hält Kommentare/Quotes in config.yaml).
+yaml = YAML()
+yaml.preserve_quotes = True

backend/requirements.txt

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+fastapi>=0.115
+uvicorn[standard]>=0.30
+httpx>=0.27
+ruamel.yaml>=0.18
+psutil>=5.9
+huggingface_hub>=0.27
+mcp>=1.2.0

backend/routers/agent.py

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+"""Agent-Endpoint: Hermes-Status + WebUI-Link (MC verlinkt nur, betreibt nicht)."""
+
+from fastapi import APIRouter
+
+from services.agent import agent_status
+
+router = APIRouter(prefix="/api")
+
+
+@router.get("/agent/status")
+def status() -> dict:
+    return agent_status()

backend/routers/connect.py

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+"""Connect-Endpoint: erzeugt IDE-/Agent-Snippets (auf den Gateway + Memory-MCP)."""
+
+from fastapi import APIRouter
+
+from services.connect import DEFAULT_HOST, build_snippets
+
+router = APIRouter(prefix="/api")
+
+
+@router.get("/connect")
+def connect(host: str = DEFAULT_HOST, mcp_path: str | None = None) -> dict:
+    kwargs = {}
+    if mcp_path:
+        kwargs["mcp_script_path"] = mcp_path
+    return build_snippets(host=host, **kwargs)

backend/routers/gateway_proxy.py

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+"""
+Eingebauter Routing-Gateway (OpenAI-kompatibel) — EIN Endpunkt für Hermes + IDEs.
+
+`model: auto` → Komplexitäts-Routing fast↔heavy; jeder andere Name geht als
+llama-swap-Alias durch (das lädt das Modell bei Bedarf). Streaming wird
+durchgereicht. Ersetzt LiteLLM (das auf Python 3.14 nicht baut) — gleicher
+Vertrag, später austauschbar.
+"""
+
+import httpx
+from fastapi import APIRouter, Request
+from fastapi.responses import JSONResponse, StreamingResponse
+
+from config import LLAMA_SWAP_URL
+from services.router_logic import FAST, FAST_NO_THINK, choose_model
+
+router = APIRouter(prefix="/v1")
+
+
+@router.get("/models")
+async def models():
+    async with httpx.AsyncClient(timeout=10) as c:
+        r = await c.get(f"{LLAMA_SWAP_URL}/v1/models")
+        return JSONResponse(r.json(), status_code=r.status_code)
+
+
+async def _proxy(path: str, request: Request):
+    body = await request.json()
+    requested = str(body.get("model") or "auto")
+    if requested == "auto":
+        alias, reason = choose_model(body)
+        body["model"] = alias
+        routed = {"x-mc-routed-to": alias, "x-mc-route-reason": reason}
+    else:
+        alias = requested
+        routed = {"x-mc-routed-to": requested}
+    # fast-Spur: Thinking aus für flotte Antworten (sofern Client es nicht selbst setzt).
+    if FAST_NO_THINK and alias == FAST and "chat_template_kwargs" not in body:
+        body["chat_template_kwargs"] = {"enable_thinking": False}
+    url = f"{LLAMA_SWAP_URL}{path}"
+
+    if body.get("stream"):
+        async def gen():
+            async with httpx.AsyncClient(timeout=None) as c:
+                async with c.stream("POST", url, json=body) as r:
+                    async for chunk in r.aiter_raw():
+                        yield chunk
+        return StreamingResponse(gen(), media_type="text/event-stream", headers=routed)
+
+    async with httpx.AsyncClient(timeout=600) as c:
+        r = await c.post(url, json=body)
+        return JSONResponse(r.json(), status_code=r.status_code, headers=routed)
+
+
+@router.post("/chat/completions")
+async def chat_completions(request: Request):
+    return await _proxy("/v1/chat/completions", request)
+
+
+@router.post("/completions")
+async def completions(request: Request):
+    return await _proxy("/v1/completions", request)

backend/routers/health.py

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+"""Health-/Status-Endpoint — schlanker Lebenszeichen-Check für MC 2.0."""
+
+from fastapi import APIRouter
+
+from config import VERSION
+from services import gateway, llamaswap
+
+router = APIRouter(prefix="/api")
+
+
+@router.get("/health")
+def health() -> dict:
+    return {
+        "status": "ok",
+        "version": VERSION,
+        "engine_reachable": llamaswap.engine_reachable(),
+        "gateway_reachable": gateway.gateway_reachable(),
+    }

backend/routers/maintenance.py

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+"""Wartungs-Endpoints: Update-Badge, OS-/Engine-Update, Reboot, Restart, Logs."""
+
+from fastapi import APIRouter, HTTPException
+from pydantic import BaseModel
+
+from services import maintenance
+
+router = APIRouter(prefix="/api")
+
+
+@router.get("/maintenance/updates")
+def updates() -> dict:
+    return maintenance.updates()
+
+
+@router.post("/maintenance/os-update")
+def os_update() -> dict:
+    return {"job_id": maintenance.os_update_job()}
+
+
+@router.post("/maintenance/engine-update")
+def engine_update() -> dict:
+    job = maintenance.engine_update_job()
+    if not job:
+        raise HTTPException(400, "Kein Engine-Update-Befehl gesetzt (MC_ENGINE_UPDATE_CMD).")
+    return {"job_id": job}
+
+
+@router.post("/maintenance/reboot")
+def reboot() -> dict:
+    return maintenance.reboot()
+
+
+class RestartReq(BaseModel):
+    service: str
+
+
+@router.post("/maintenance/restart")
+def restart(body: RestartReq) -> dict:
+    return maintenance.restart_service(body.service)
+
+
+@router.get("/maintenance/logs")
+def logs(service: str, lines: int = 200) -> dict:
+    return maintenance.logs(service, lines)

backend/routers/memory.py

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+"""Memory-Endpoints (geteiltes Gedächtnis). LAN-only, kein Token in 2.0-Phase 3."""
+
+from fastapi import APIRouter, HTTPException
+from pydantic import BaseModel
+
+from services import memory
+
+router = APIRouter(prefix="/api")
+
+
+class MemIn(BaseModel):
+    content: str
+    category: str = "stable"
+    source: str = "manual"
+
+
+class MemUp(BaseModel):
+    content: str | None = None
+    category: str | None = None
+
+
+class DedupeIn(BaseModel):
+    apply: bool = False
+    threshold: float = 0.85
+
+
+@router.get("/memory/export")
+def export() -> dict:
+    return memory.export_text()
+
+
+@router.post("/memory/dedupe")
+def dedupe(body: DedupeIn) -> dict:
+    return memory.dedupe(apply=body.apply, threshold=body.threshold)
+
+
+@router.get("/memory")
+def list_mem(q: str = "", category: str = "") -> list[dict]:
+    return memory.list_memories(q=q, category=category)
+
+
+@router.post("/memory", status_code=201)
+def add(body: MemIn) -> dict:
+    if body.category not in memory.CATEGORIES:
+        raise HTTPException(400, f"Kategorie '{body.category}' unbekannt.")
+    return memory.add_memory(body.content, body.category, body.source)
+
+
+@router.put("/memory/{mid}")
+def update(mid: str, body: MemUp) -> dict:
+    res = memory.update_memory(mid, content=body.content, category=body.category)
+    if not res:
+        raise HTTPException(404, "Eintrag nicht gefunden")
+    return res
+
+
+@router.delete("/memory/{mid}")
+def delete(mid: str) -> dict:
+    if not memory.delete_memory(mid):
+        raise HTTPException(404, "Eintrag nicht gefunden")
+    return {"ok": True}

backend/routers/models.py

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+"""Modelle-Endpoints: Liste (mit Caps), Discover, Fit, Register, Groups."""
+
+import psutil
+from fastapi import APIRouter, HTTPException
+from pydantic import BaseModel
+
+from config import HF_DOWNLOAD_ENV, MODELS_DIR
+from services import discover, hf, jobengine, llamaswap
+from services.fit import evaluate_fit, extract_params_b, max_ctx_for
+
+router = APIRouter(prefix="/api")
+
+
+def _ram_gb() -> float:
+    return psutil.virtual_memory().total / (1024 ** 3)
+
+
+@router.get("/models")
+def models() -> dict:
+    items = llamaswap.list_models()
+    return {"models": items, "count": len(items), "running": llamaswap.get_running_models()}
+
+
+@router.get("/discover")
+def discover_models(force: bool = False) -> dict:
+    ram = _ram_gb()
+    data = discover.refresh_discover(ram) if force else discover.safe_discover(ram)
+    if not data:
+        raise HTTPException(502, "Modell-Quellen gerade nicht erreichbar — später erneut.")
+    return {**data, "sys_ram_gb": round(ram, 1)}
+
+
+@router.get("/fit")
+def fit(params_b: float, quant: str = "Q4_K_M", ctx: int = 8192, name: str = "") -> dict:
+    ram = _ram_gb()
+    return {
+        "fit": evaluate_fit(params_b, quant, ctx, ram, name=name),
+        "optimal_ctx": max_ctx_for(params_b, quant, ram),
+        "sys_ram_gb": round(ram, 1),
+    }
+
+
+class RegisterReq(BaseModel):
+    model_path: str
+    role: str | None = None
+    ctx: int = 8192
+    ttl: int | None = None
+    mmproj_path: str | None = None
+    jinja: bool = False
+
+
+@router.post("/models/register")
+def register(req: RegisterReq) -> dict:
+    try:
+        model_id = llamaswap.register_model(
+            req.model_path, role=req.role, ctx=req.ctx, ttl=req.ttl,
+            mmproj_path=req.mmproj_path, jinja=req.jinja,
+        )
+    except PermissionError as exc:
+        raise HTTPException(500, str(exc))
+    return {"ok": True, "model_id": model_id}
+
+
+class InstallReq(BaseModel):
+    repo: str
+    role: str | None = None
+    quant: str = "Q4_K_M"
+    ctx: int | None = None
+    jinja: bool = False
+    hf_token: str | None = None
+
+
+@router.get("/hf/search")
+def hf_search(q: str) -> dict:
+    return {"results": hf.search(q)}
+
+
+@router.get("/hf/quants")
+def hf_quants(repo: str) -> dict:
+    repo = hf.normalize_repo(repo)
+    return {"repo": repo, "quants": hf.list_quants(repo)}
+
+
+@router.post("/models/install")
+def install(req: InstallReq) -> dict:
+    """Lädt ein Modell von HuggingFace (Hintergrund-Job) UND trägt es sofort in
+    llama-swap ein (cmd + Rolle-Alias). llama-swap (-watch-config) lädt es, sobald
+    die Datei da ist. Split-GGUFs werden komplett geladen, registriert wird der
+    erste Teil (-00001-of-…). Akzeptiert volle HF-URL ODER org/repo."""
+    repo = hf.normalize_repo(req.repo)
+    info = hf.resolve_gguf(repo, req.quant)
+    if not info["first"]:
+        raise HTTPException(404, f"Keine GGUF-Datei für Quant '{req.quant}' in {repo} gefunden.")
+
+    subdir = repo.split("/")[-1]
+    target = MODELS_DIR / subdir
+    target.mkdir(parents=True, exist_ok=True)
+    model_path = str(target / info["first"])
+    mmproj_path = str(target / info["mmproj"]) if info["mmproj"] else None
+
+    ctx = req.ctx
+    if ctx is None:
+        ram = _ram_gb()
+        ctx = max_ctx_for(extract_params_b(repo), req.quant, ram)
+
+    # Sofort registrieren (Datei kommt gleich) — robust gegen -watch-config.
+    try:
+        model_id = llamaswap.register_model(
+            model_path, role=req.role, ctx=ctx, mmproj_path=mmproj_path, jinja=req.jinja)
+    except PermissionError as exc:
+        raise HTTPException(500, str(exc))
+
+    # Download-Job: alle GGUF-Teile (+ mmproj) per --include holen.
+    args = [hf.hf_bin(), "download", repo]
+    for f in info["files"]:
+        args.append(f)
+    if info["mmproj"]:
+        args.append(info["mmproj"])
+    args += ["--local-dir", str(target)]
+    env = dict(HF_DOWNLOAD_ENV)
+    if req.hf_token:
+        env["HF_TOKEN"] = req.hf_token
+    job_id = jobengine.start_job(args, f"download {req.repo}", env=env)
+    jobengine.attach_download_progress(job_id, str(target), info["total_bytes"])
+    return {"ok": True, "job_id": job_id, "model_id": model_id, "model_path": model_path,
+            "total_bytes": info["total_bytes"], "files": len(info["files"])}
+
+
+@router.get("/jobs")
+def jobs() -> dict:
+    return {"jobs": jobengine.public_jobs()}
+
+
+@router.post("/jobs/{job_id}/cancel")
+def cancel(job_id: str) -> dict:
+    return {"ok": jobengine.cancel_job(job_id)}
+
+
+class RoleReq(BaseModel):
+    role: str | None = None
+
+
+@router.post("/models/{model_id}/role")
+def set_model_role(model_id: str, body: RoleReq) -> dict:
+    if not llamaswap.set_role(model_id, body.role):
+        raise HTTPException(404, "Modell nicht gefunden")
+    return {"ok": True}
+
+
+class CtxReq(BaseModel):
+    ctx: int
+
+
+@router.post("/models/{model_id}/ctx")
+def set_model_ctx(model_id: str, body: CtxReq) -> dict:
+    if not llamaswap.set_ctx(model_id, body.ctx):
+        raise HTTPException(404, "Modell nicht gefunden")
+    return {"ok": True}
+
+
+@router.delete("/models/{model_id}")
+def delete(model_id: str) -> dict:
+    if not llamaswap.delete_model(model_id):
+        raise HTTPException(404, "Modell nicht gefunden")
+    return {"ok": True}
+
+
+@router.get("/groups")
+def groups() -> dict:
+    return {"groups": llamaswap.list_groups()}
+
+
+class GroupReq(BaseModel):
+    group: str
+    members: list[str]
+    swap: bool = False
+    persist: bool = False
+
+
+@router.put("/groups")
+def set_group(req: GroupReq) -> dict:
+    try:
+        llamaswap.set_group(req.group, req.members, swap=req.swap, persist=req.persist)
+    except PermissionError as exc:
+        raise HTTPException(500, str(exc))
+    return {"ok": True}

backend/routers/routing.py

@@ -0,0 +1,12 @@
+"""Routing-Endpoint: zeigt den eingebauten Gateway (model:auto fast↔heavy)."""
+
+from fastapi import APIRouter
+
+from services import gateway
+
+router = APIRouter(prefix="/api")
+
+
+@router.get("/routing")
+def routing() -> dict:
+    return {**gateway.routing_summary(), "gateway_reachable": gateway.gateway_reachable()}

backend/routers/system.py

@@ -0,0 +1,90 @@
+"""System-Endpoints: Live-Status + Wartung (Restart/Self-Update — auf der Box).
+
+Wartung läuft als systemd-USER-Dienst → KEIN sudo/Passwort (Nordstern).
+Lokal (Windows) schlagen die Shell-Befehle harmlos fehl und werden als Fehler
+zurückgegeben statt zu crashen.
+"""
+
+import os
+import subprocess
+
+from fastapi import APIRouter, HTTPException
+from pydantic import BaseModel
+
+from config import GATEWAY_URL, HERMES_API_URL, HERMES_WEBUI_URL, LLAMA_SWAP_URL
+from services import backup as backup_svc
+from services.agent import agent_status
+from services.gateway import gateway_reachable
+from services.llamaswap import engine_reachable
+from services.system import system_status
+
+router = APIRouter(prefix="/api")
+
+# Nur diese User-Dienste dürfen neugestartet werden.
+ALLOWED_SERVICES = {"mission-control-2", "hermes-gateway", "hermes-webui"}
+# Quelle für Self-Update (auf der Box ~/mission-control-v2).
+SOURCE_DIR = os.path.expanduser(os.environ.get("MC2_SOURCE_DIR", "~/mission-control-v2"))
+
+
+@router.get("/system/status")
+def status() -> dict:
+    return system_status()
+
+
+@router.get("/system/services")
+def services() -> dict:
+    """Aggregierte Erreichbarkeit aller Stack-Dienste (für die Health-Anzeige)."""
+    a = agent_status()
+    gw_url = f"{GATEWAY_URL}/v1"
+    return {
+        "services": [
+            {"name": "Engine (llama-swap)", "url": LLAMA_SWAP_URL, "ok": engine_reachable()},
+            {"name": "Gateway (integriert)", "url": gw_url, "ok": gateway_reachable()},
+            {"name": "Hermes-Gateway", "url": HERMES_API_URL, "ok": a["gateway_reachable"]},
+            {"name": "Hermes-WebUI", "url": HERMES_WEBUI_URL, "ok": a["webui_reachable"]},
+        ],
+        "links": {
+            "engine_ui": f"{LLAMA_SWAP_URL}/ui",
+            "gateway": gw_url,
+            "hermes_webui": HERMES_WEBUI_URL,
+        },
+    }
+
+
+@router.post("/system/backup")
+def backup() -> dict:
+    return backup_svc.backup_now()
+
+
+@router.get("/system/backups")
+def backups() -> dict:
+    return {"backups": backup_svc.list_backups()}
+
+
+def _run(cmd: list[str], cwd: str | None = None) -> dict:
+    try:
+        p = subprocess.run(cmd, cwd=cwd, capture_output=True, text=True, timeout=180)
+        return {"ok": p.returncode == 0, "code": p.returncode,
+                "out": (p.stdout or "")[-2000:], "err": (p.stderr or "")[-2000:]}
+    except Exception as exc:  # noqa: BLE001
+        return {"ok": False, "code": -1, "out": "", "err": str(exc)}
+
+
+class RestartReq(BaseModel):
+    service: str
+
+
+@router.post("/system/restart")
+def restart(req: RestartReq) -> dict:
+    if req.service not in ALLOWED_SERVICES:
+        raise HTTPException(400, f"Dienst '{req.service}' nicht erlaubt.")
+    return _run(["systemctl", "--user", "restart", req.service])
+
+
+@router.post("/system/self-update")
+def self_update() -> dict:
+    """git pull (Source) → venv-Deps → Dienst-Restart. Auf der Box; lokal Fehler."""
+    pull = _run(["git", "fetch", "--all"], cwd=SOURCE_DIR)
+    reset = _run(["git", "reset", "--hard", "origin/main"], cwd=SOURCE_DIR)
+    restart_res = _run(["systemctl", "--user", "restart", "mission-control-2"])
+    return {"pull": pull, "reset": reset, "restart": restart_res}

backend/services/agent.py

@@ -0,0 +1,48 @@
+"""
+Hermes-Agent-Status (Control-Plane-Read). MC betreibt Hermes NICHT — es zeigt nur
+Status + verlinkt das standalone hermes-webui. Voller Zugriff + Tools/MCP werden in
+Hermes' eigener Config verdrahtet (siehe docs/HERMES_SETUP.md).
+"""
+
+import httpx
+
+from config import HERMES_API_URL, HERMES_HOME, HERMES_WEBUI_URL, yaml
+
+
+def _reach(url: str, path: str = "") -> bool:
+    try:
+        with httpx.Client(timeout=3.0) as c:
+            return c.get(f"{url}{path}").status_code < 500
+    except Exception:
+        return False
+
+
+def agent_status() -> dict:
+    """Erreichbarkeit von Gateway (:8642) + WebUI (:8787) + lokale Hinweise."""
+    home = HERMES_HOME
+    brain_model = "auto"
+    config_path = home / "config.yaml"
+    if config_path.exists():
+        try:
+            from ruamel.yaml import YAML
+            r_yaml = YAML()
+            with config_path.open("r", encoding="utf-8") as f:
+                cfg = r_yaml.load(f) or {}
+                if isinstance(cfg, dict):
+                    brain_model = cfg.get("model", {}).get("model", "auto")
+        except Exception:
+            pass
+
+
+    return {
+        "gateway_url": HERMES_API_URL,
+        "webui_url": HERMES_WEBUI_URL,
+        "gateway_reachable": _reach(HERMES_API_URL, "/v1/models"),
+        "webui_reachable": _reach(HERMES_WEBUI_URL),
+        "home_exists": home.exists(),
+        "brain_model": brain_model,
+        # Best-effort: welche Verdrahtung lokal sichtbar ist (auf der Box aussagekräftig).
+        "has_config": (home / "config.yaml").exists() or (home / "config.json").exists(),
+        "has_skills": (home / "skills").exists(),
+        "has_memories": (home / "memories").exists(),
+    }

backend/services/backup.py

@@ -0,0 +1,51 @@
+"""
+Backup der „Verfassung" (Shared-Memory-SQLite) + aller Configs.
+Snapshot in einen Zeitstempel-Ordner; die letzten N bleiben erhalten.
+"""
+
+import shutil
+import time
+from pathlib import Path
+
+from config import CONFIG_PATH, GATEWAY_CONFIG_PATH, MEMORY_DB, MODELS_DIR
+
+BACKUP_DIR = Path(MODELS_DIR) / "mc2-backups"
+RETAIN = 7
+
+
+def _safe_copy(src: Path, dst_dir: Path) -> str | None:
+    try:
+        if src and src.exists():
+            shutil.copy2(src, dst_dir / src.name)
+            return src.name
+    except Exception:
+        pass
+    return None
+
+
+def backup_now() -> dict:
+    """Erstellt einen Snapshot (Memory-DB inkl. WAL/SHM + Configs). Alte Snapshots
+    über RETAIN hinaus werden entfernt."""
+    ts = time.strftime("%Y%m%d-%H%M%S")
+    dst = BACKUP_DIR / ts
+    dst.mkdir(parents=True, exist_ok=True)
+    saved = []
+    for src in (MEMORY_DB, Path(str(MEMORY_DB) + "-wal"), Path(str(MEMORY_DB) + "-shm"),
+                CONFIG_PATH, GATEWAY_CONFIG_PATH):
+        if (name := _safe_copy(src, dst)):
+            saved.append(name)
+    # Aufräumen: nur die letzten RETAIN Snapshots behalten.
+    snaps = sorted([p for p in BACKUP_DIR.iterdir() if p.is_dir()], reverse=True)
+    for old in snaps[RETAIN:]:
+        shutil.rmtree(old, ignore_errors=True)
+    return {"ok": bool(saved), "snapshot": ts, "files": saved, "dir": str(dst)}
+
+
+def list_backups() -> list[dict]:
+    if not BACKUP_DIR.exists():
+        return []
+    out = []
+    for p in sorted([d for d in BACKUP_DIR.iterdir() if d.is_dir()], reverse=True):
+        files = [f.name for f in p.iterdir() if f.is_file()]
+        out.append({"snapshot": p.name, "files": files})
+    return out

backend/services/caps.py

@@ -0,0 +1,131 @@
+"""
+Modell-Capabilities — EINE Quelle der Wahrheit für Modell-Eigenschaften
+(MoE / Tools / Vision / Coder / Reasoning / Embedding / Kontext).
+Portiert aus Mission Control v1 (model_caps.py).
+
+Quellen, geschichtet: GGUF-Header (offline, authoritativ) → cmd-Flags
+(--jinja/--mmproj) → HF-Block (tags + chat_template) → Familien-Fallback.
+Tool-Fähigkeit dreistufig: yes (bestätigt) | likely (Familie) | no.
+"""
+
+import re
+import struct
+
+from services.fit import extract_active_params_b, extract_params_b
+
+_GGUF_FIXED = {0: 1, 1: 1, 2: 2, 3: 2, 4: 4, 5: 4, 6: 4, 7: 1, 10: 8, 11: 8, 12: 8}
+
+
+def _read_gguf_meta(path: str) -> dict:
+    """Liest nur den GGUF-Metadaten-Header (architecture/context_length/expert_count/
+    parameter_count). Bricht vor dem Tokenizer-Array ab → schnell, lädt NICHT das Modell."""
+    out: dict = {}
+    try:
+        with open(path, "rb") as f:
+            if f.read(4) != b"GGUF":
+                return {}
+            struct.unpack("<I", f.read(4))[0]
+            f.read(8)
+            kv = struct.unpack("<Q", f.read(8))[0]
+
+            def ru32() -> int: return struct.unpack("<I", f.read(4))[0]
+            def ru64() -> int: return struct.unpack("<Q", f.read(8))[0]
+            def rstr() -> str: return f.read(ru64()).decode("utf-8", "replace")
+
+            def rval(t: int):
+                if t == 8:  return rstr()
+                if t == 0:  return struct.unpack("<B", f.read(1))[0]
+                if t == 1:  return struct.unpack("<b", f.read(1))[0]
+                if t == 2:  return struct.unpack("<H", f.read(2))[0]
+                if t == 3:  return struct.unpack("<h", f.read(2))[0]
+                if t == 4:  return struct.unpack("<I", f.read(4))[0]
+                if t == 5:  return struct.unpack("<i", f.read(4))[0]
+                if t == 6:  return struct.unpack("<f", f.read(4))[0]
+                if t == 7:  return f.read(1) != b"\x00"
+                if t == 10: return struct.unpack("<Q", f.read(8))[0]
+                if t == 11: return struct.unpack("<q", f.read(8))[0]
+                if t == 12: return struct.unpack("<d", f.read(8))[0]
+                if t == 9:
+                    et = ru32(); cnt = ru64()
+                    if et == 8:
+                        for _ in range(cnt):
+                            f.seek(ru64(), 1)
+                    elif et == 9:
+                        for _ in range(cnt):
+                            rval(9)
+                    else:
+                        f.seek(cnt * _GGUF_FIXED.get(et, 0), 1)
+                    return None
+                raise ValueError(f"unbekannter GGUF-Typ {t}")
+
+            want = {"architecture", "context_length", "expert_count", "parameter_count"}
+            for _ in range(kv):
+                key = rstr()
+                t = ru32()
+                if key == "tokenizer.ggml.tokens":
+                    break
+                v = rval(t)
+                short = key.split(".")[-1]
+                if short in want and short not in out:
+                    out[short] = v
+    except Exception:
+        return out
+    return out
+
+
+_TOOL_FAMILIES = (
+    "qwen2.5", "qwen3", "qwen2", "hermes", "mistral", "mixtral", "devstral",
+    "command-r", "command_r", "llama-3.1", "llama3.1", "llama-3.3", "llama-4", "llama4",
+    "functionary", "watt", "firefunction", "granite", "glm-4", "glm-5", "ministral",
+)
+_REASON_KW = (
+    "-r1", "deepseek-r1", "qwq", "magistral", "-think", "thinking", "-o1",
+    "gpt-oss", "reasoning", "exaone-deep", "phi-4-reasoning", "phi-4-mini-reasoning",
+)
+_CODE_KW = ("coder", "-code", "code-", "codestral", "starcoder", "deepseek-coder")
+_VISION_KW = ("-vl", "vision", "llava", "pixtral", "multimodal", "-mm-", "qwen3vl", "qwen2-vl")
+_EMBED_KW = ("bge", "e5-", "gte-", "nomic-embed", "embed")
+_MOE_ARCH = ("moe", "mixtral", "deepseek2", "deepseek3", "llama4", "qwen3moe", "grok")
+
+
+def capabilities(name: str = "", cmd: str = "", gguf_path: str = "", hf: dict | None = None) -> dict:
+    """Capability-Tag-Set für ein Modell. Alle Quellen optional — nutzt, was da ist."""
+    low = (name or "").lower()
+    cmdl = (cmd or "").lower()
+    hf = hf or {}
+
+    meta = _read_gguf_meta(gguf_path) if gguf_path else {}
+    arch = str(meta.get("architecture") or hf.get("architecture") or "").lower()
+    tags = [str(t).lower() for t in (hf.get("tags") or [])]
+    chat_tpl = str(hf.get("chat_template") or "")
+
+    expert_count = int(meta.get("expert_count") or 0)
+    moe = (
+        expert_count > 1
+        or any(a in arch for a in _MOE_ARCH)
+        or bool(re.search(r"\d+x\d+\.?\d*b", low))
+        or bool(re.search(r"a\d+\.?\d*b", low))
+    )
+    active_b = extract_active_params_b(name)
+
+    pcount = int(meta.get("parameter_count") or 0)
+    params_b = round(pcount / 1e9, 1) if pcount else extract_params_b(name)
+    ctx = meta.get("context_length")
+    if not ctx:
+        m = re.search(r"-(?:c|-ctx-size)\s+(\d+)", cmdl)
+        ctx = int(m.group(1)) if m else None
+
+    tool_confirmed = "--jinja" in cmdl or "tool_call" in chat_tpl or "<tools>" in chat_tpl
+    tool_family = any(fam in low for fam in _TOOL_FAMILIES) or "function-calling" in tags
+    tools = "yes" if tool_confirmed else ("likely" if tool_family else "no")
+
+    vision = "--mmproj" in cmdl or "vl" in arch or "clip" in arch or any(k in low for k in _VISION_KW)
+    coder = any(k in low for k in _CODE_KW)
+    reasoning = any(k in low for k in _REASON_KW) or "reasoning" in tags
+    embedding = "bert" in arch or any(k in low for k in _EMBED_KW)
+
+    return {
+        "moe": moe, "active_b": active_b, "tools": tools, "vision": vision,
+        "coder": coder, "reasoning": reasoning, "embedding": embedding,
+        "ctx": ctx, "params_b": params_b or None, "arch": arch or None,
+    }

backend/services/connect.py

@@ -0,0 +1,105 @@
+"""
+Connect: erzeugt saubere, getestete Konfig-Snippets für IDEs/Agenten auf dem
+LOKALEN PC (separate Maschine im LAN). Alle zeigen auf den **Gateway** der Box
+(`model: auto`, LiteLLM :4000) + den **Shared-Memory-MCP** (MC :9000).
+
+Wichtig: Host ist die LAN-IP der Box (NICHT eine Proxy-Domain) — das war in v1
+die häufigste Fehlerquelle. Der Aufrufer übergibt den Host explizit.
+"""
+
+import json
+
+from config import PORT
+
+DEFAULT_HOST = "192.168.178.151"
+
+# Modelle, die der Gateway anbietet (model:auto = Standard).
+GATEWAY_MODELS = ["auto", "fast", "heavy", "coder", "vision"]
+
+
+def _gw(host: str) -> str:
+    # Eingebauter Gateway: MC2 serviert /v1 selbst (gleicher Port wie das Cockpit).
+    return f"http://{host}:{PORT}/v1"
+
+
+def build_snippets(host: str = DEFAULT_HOST,
+                   mcp_script_path: str = r"C:\\Users\\TobisPC\\mission-control-v2\\mcp\\mcp_memory.py",
+                   mcp_python: str = "python") -> dict:
+    gw = _gw(host)
+    mc_url = f"http://{host}:{PORT}"
+
+    cline = json.dumps({
+        "apiProvider": "openai",
+        "openAiBaseUrl": gw,
+        "openAiApiKey": "local",
+        "openAiModelId": "auto",
+    }, indent=2)
+
+    opencode = json.dumps({
+        "providers": {
+            "litellm": {
+                "npm": "@ai-sdk/openai-compatible",
+                "name": "Bosgame Gateway",
+                "options": {"baseURL": gw, "apiKey": "local"},
+                "models": {m: {"name": m} for m in GATEWAY_MODELS},
+            }
+        }
+    }, indent=2)
+
+    zed = json.dumps({
+        "language_models": {
+            "openai_compatible": {
+                "bosgame": {
+                    "api_url": gw,
+                    "available_models": [
+                        {"name": m, "display_name": m, "max_tokens": 131072,
+                         "capabilities": {"tools": True}} for m in GATEWAY_MODELS
+                    ],
+                }
+            }
+        }
+    }, indent=2)
+
+    cont = json.dumps({
+        "models": [
+            {"title": f"Bosgame / {m}", "provider": "openai", "model": m,
+             "apiBase": gw, "apiKey": "local"} for m in ("auto", "coder", "heavy")
+        ]
+    }, indent=2)
+
+    # Claude Code spricht Anthropic-Format; der eingebaute Gateway ist OpenAI-kompatibel.
+    claude_code = (
+        f"# Der eingebaute Gateway ist OpenAI-kompatibel ({gw}, model: auto).\n"
+        f"# Claude Code nutzt das Anthropic-Format — dafür braucht es einen Anthropic-Shim\n"
+        f"# (z.B. LiteLLM /v1/messages) als Aufsatz. Für lokale Modelle direkt: Cline / OpenCode /\n"
+        f"# Continue / Zed nutzen (oben), die sprechen OpenAI-kompatibel mit diesem Gateway."
+    )
+
+    memory_mcp = json.dumps({
+        "mcpServers": {
+            "mission-control-memory": {
+                "command": mcp_python,
+                "args": [mcp_script_path],
+                "env": {"MC_URL": mc_url},
+            }
+        }
+    }, indent=2)
+
+    return {
+        "host": host,
+        "gateway_url": gw,
+        "tools": {
+            "cline": {"label": "Cline (VS Code)", "lang": "json", "snippet": cline,
+                      "note": "OpenAI-Provider → Gateway. Modell 'auto' (schnell, eskaliert bei Bedarf)."},
+            "opencode": {"label": "OpenCode", "lang": "jsonc", "snippet": opencode,
+                         "note": "Datei opencode.jsonc, Key 'providers'."},
+            "zed": {"label": "Zed", "lang": "json", "snippet": zed,
+                    "note": "settings.json → language_models.openai_compatible."},
+            "continue": {"label": "Continue", "lang": "json", "snippet": cont,
+                         "note": "~/.continue/config.json."},
+            "claude_code": {"label": "Claude Code", "lang": "bash", "snippet": claude_code,
+                            "note": "Anthropic-Format über LiteLLM /v1/messages."},
+            "memory_mcp": {"label": "Shared Memory (MCP)", "lang": "json", "snippet": memory_mcp,
+                           "note": "Für jedes MCP-fähige Tool. mcp_memory.py muss lokal liegen."},
+        },
+    }

backend/services/discover.py

@@ -0,0 +1,133 @@
+"""
+Automatische Modell-Entdeckung ("aktuell beste Modelle"): fragt vertrauenswürdige
+HF-Orgs live ab, kategorisiert per Stichwort, rankt nach Hardware-Fit + Beliebtheit
+und cached. Portiert aus Mission Control v1 (cookbook.py-Discover).
+
+Wichtig (Greenfield-Fix gegen v1): EIN gemeinsamer Ranking-Helfer `rank_runnable`
+ist die Quelle der Wahrheit — sowohl die „beste Empfehlung" je Kategorie als auch
+spätere Auto-Setups nutzen ihn, damit sie nie auseinanderlaufen.
+"""
+
+import json
+import os
+import time
+
+import httpx
+
+from config import DISCOVER_CACHE_PATH, DISCOVER_TTL
+from services.caps import capabilities
+from services.fit import evaluate_fit, extract_params_b, max_ctx_for
+from services.sources import CATEGORIES, SKIP_TOKENS, TRUSTED_AUTHORS
+
+_FIT_ORDER = {"perfect": 0, "marginal": 1, "too_tight": 2}
+
+
+def _categorize(repo_id: str) -> str:
+    low = repo_id.lower()
+    for cat in CATEGORIES:
+        if any(k in low for k in cat["kw"]):
+            return cat["role"]
+    return "scout"
+
+
+def _fetch_author_models(author: str) -> list:
+    url = (f"https://huggingface.co/api/models?author={author}"
+           f"&filter=gguf&sort=downloads&direction=-1&limit=40")
+    try:
+        with httpx.Client(timeout=12.0) as c:
+            data = c.get(url).json()
+        return data if isinstance(data, list) else []
+    except Exception:
+        return []
+
+
+def rank_runnable(models: list[dict]) -> list[dict]:
+    """EINE Quelle der Wahrheit fürs Ranking lauffähiger Modelle:
+    bestes Fit-Level zuerst (perfect < marginal), bei Gleichstand meistgeladen.
+    Zu große Modelle (too_tight) fliegen raus."""
+    return sorted(
+        [m for m in models if m["fit"]["level"] != "too_tight"],
+        key=lambda m: (_FIT_ORDER[m["fit"]["level"]], -int(m.get("downloads") or 0)),
+    )
+
+
+def refresh_discover(ram_gb: float) -> dict:
+    """Quellen live abfragen, kategorisieren, ranken, cachen. Wirft nur, wenn KEINE
+    Quelle erreichbar war."""
+    raw, seen, ok = [], set(), 0
+    for author in TRUSTED_AUTHORS:
+        models = _fetch_author_models(author)
+        if models:
+            ok += 1
+        for m in models:
+            rid = m.get("id")
+            if not rid or rid in seen:
+                continue
+            seen.add(rid)
+            raw.append(m)
+    if ok == 0:
+        raise RuntimeError("Keine Quelle erreichbar.")
+
+    by_cat: dict[str, list] = {c["role"]: [] for c in CATEGORIES}
+    for m in raw:
+        rid = m["id"]
+        low = rid.lower()
+        if any(tok in low for tok in SKIP_TOKENS):
+            continue
+        role = _categorize(rid)
+        params_b = extract_params_b(rid)
+        quant = "Q4_K_M"  # Referenz-Quant für die Fit-Einschätzung
+        fit = evaluate_fit(params_b, quant, 8192, ram_gb, name=rid)
+        tags = [str(t) for t in (m.get("tags") or [])]
+        by_cat[role].append({
+            "name": rid.split("/")[-1], "author": rid.split("/")[0], "repo": rid,
+            "role": role, "params_b": params_b, "quant": quant, "tags": tags,
+            "downloads": int(m.get("downloads") or 0), "likes": int(m.get("likes") or 0),
+            "lastModified": m.get("lastModified"),
+            "fit": fit, "optimal_ctx": max_ctx_for(params_b, quant, ram_gb),
+            "caps": capabilities(name=rid, hf={"tags": tags}),
+        })
+
+    cats = []
+    for c in CATEGORIES:
+        items = by_cat[c["role"]]
+        ranked = rank_runnable(items)
+        # Top 4 je Kategorie (für die Anzeige) — gerankt, dann nach Downloads aufgefüllt.
+        items.sort(key=lambda x: (x["fit"]["level"] != "too_tight", x["downloads"]), reverse=True)
+        top = items[:4]
+        if top:
+            cats.append({
+                "role": c["role"], "title": c["title"], "icon": c["icon"],
+                "models": top,
+                "recommended": ranked[0]["repo"] if ranked else None,
+            })
+
+    data = {"updated": time.time(), "categories": cats}
+    try:
+        DISCOVER_CACHE_PATH.parent.mkdir(parents=True, exist_ok=True)
+        tmp = DISCOVER_CACHE_PATH.with_name(DISCOVER_CACHE_PATH.name + ".tmp")
+        tmp.write_text(json.dumps(data, ensure_ascii=False, indent=2), encoding="utf-8")
+        os.replace(tmp, DISCOVER_CACHE_PATH)
+    except Exception:
+        pass  # Cache ist nur Beschleunigung
+    return data
+
+
+def load_discover() -> dict | None:
+    try:
+        if DISCOVER_CACHE_PATH.exists():
+            return json.loads(DISCOVER_CACHE_PATH.read_text(encoding="utf-8"))
+    except Exception:
+        pass
+    return None
+
+
+def safe_discover(ram_gb: float) -> dict | None:
+    """Aus Cache (wenn frisch) oder live; wirft nie — None wenn nichts da."""
+    cached = load_discover()
+    if cached and (time.time() - cached.get("updated", 0) < DISCOVER_TTL):
+        return cached
+    try:
+        return refresh_discover(ram_gb)
+    except Exception:
+        return cached

backend/services/fit.py

@@ -0,0 +1,92 @@
+"""
+Hardware-Fit-Mathe (VRAM/RAM, tps-Schätzung) für APUs mit Unified Memory
+(Bosgame M5 / Strix Halo). Portiert aus Mission Control v1 (hw_math.py).
+"""
+
+import re
+
+# Bytes pro Parameter je GGUF-Quant (Annahme).
+QUANT_BYTES_PER_PARAM = {
+    "Q2_K": 0.35, "Q3_K_S": 0.38, "Q3_K_M": 0.42, "Q3_K_L": 0.45,
+    "Q4_0": 0.50, "Q4_1": 0.55, "Q4_K_S": 0.50, "Q4_K_M": 0.55,
+    "Q5_0": 0.62, "Q5_1": 0.68, "Q5_K_S": 0.62, "Q5_K_M": 0.65,
+    "Q6_K": 0.75, "Q8_0": 1.00, "F16": 2.00, "BF16": 2.00,
+}
+
+
+def estimate_memory_gb(params_b: float, quant: str, ctx: int) -> float:
+    """Geschätzter Speicherbedarf in GB (Gewichte + Kontext-KV)."""
+    bpp = QUANT_BYTES_PER_PARAM.get(quant.upper(), 0.65)
+    weights = params_b * bpp
+    context_vram = (ctx / 8192) * (max(params_b, 7) / 7) * 0.8
+    return weights + context_vram
+
+
+def extract_active_params_b(name: str) -> float | None:
+    """Aktive Parameter bei MoE ('30B-A3B' → 3.0). None bei Dense."""
+    m = re.search(r"(?<![a-zA-Z])a(\d+(?:\.\d+)?)b\b", name.lower())
+    return float(m.group(1)) if m else None
+
+
+def estimate_speed(req_gb: float, sys_ram_gb: float, moe_active_ratio: float = 1.0) -> float:
+    """Geschätzte t/s anhand der ~273 GB/s Bandbreite der APU.
+    moe_active_ratio = aktive/gesamt Params; < 1 bei MoE."""
+    bw = 273 if sys_ram_gb > 8 else 70
+    if req_gb <= 0:
+        return 0.0
+    raw_tps = (bw / req_gb) * 0.55
+    if moe_active_ratio < 0.8:
+        raw_tps *= (1.0 / moe_active_ratio) ** 0.5
+    return raw_tps
+
+
+def evaluate_fit(params_b: float, quant: str, ctx: int, sys_ram_gb: float, name: str = "") -> dict:
+    """Fit für ein Shared-Memory-System (APU). name → MoE-Erkennung (optional)."""
+    req_gb = estimate_memory_gb(params_b, quant, ctx)
+    active_b = extract_active_params_b(name) if name else None
+    moe_ratio = (active_b / params_b) if (active_b and params_b > 0) else 1.0
+    tps = estimate_speed(req_gb, sys_ram_gb, moe_ratio)
+    usable_ram = max(sys_ram_gb - 4.0, 0)
+    if req_gb > usable_ram:
+        fit_level, text = "too_tight", "Zu groß (OOM)"
+    elif req_gb > usable_ram * 0.8:
+        fit_level, text = "marginal", "Könnte knapp werden"
+    else:
+        fit_level, text = "perfect", "Passt perfekt"
+    return {"level": fit_level, "text": text, "req_gb": round(req_gb, 1), "tps": round(tps, 0)}
+
+
+def extract_params_b(name: str) -> float:
+    """Parametergröße (Mrd.) aus Repo-/Dateiname. 8x7B (MoE) → 56."""
+    moe = re.search(r"(\d+)x(\d+(?:\.\d+)?)[bB]", name)
+    if moe:
+        return float(moe.group(1)) * float(moe.group(2))
+    m = re.search(r"(\d+(?:\.\d+)?)[bB](?![a-zA-Z])", name)
+    return float(m.group(1)) if m else 7.0
+
+
+_NICE_CTX = [2048, 4096, 8192, 16384, 32768, 49152, 65536, 98304, 131072]
+
+
+def max_ctx_for(params_b: float, quant: str, sys_ram_gb: float) -> int:
+    """Größter 'schöner' Kontext, der komfortabel passt (80 % des nutzbaren RAM)."""
+    bpp = QUANT_BYTES_PER_PARAM.get(quant.upper(), 0.65)
+    weights = params_b * bpp
+    usable = max(sys_ram_gb - 4.0, 0) * 0.8
+    ctx_budget = usable - weights
+    if ctx_budget <= 0:
+        return 2048
+    per_8k = (max(params_b, 7) / 7) * 0.8
+    raw_ctx = (ctx_budget / per_8k) * 8192
+    best = _NICE_CTX[0]
+    for c in _NICE_CTX:
+        if c <= raw_ctx:
+            best = c
+    return best
+
+
+def recommend_ctx(params_b: float, quant: str, sys_ram_gb: float) -> dict:
+    ctx = max_ctx_for(params_b, quant, sys_ram_gb)
+    k = ctx // 1024
+    return {"ctx": ctx, "k": k,
+            "note": f"Bis ~{k}k Kontext passt komfortabel auf deine Hardware ({round(sys_ram_gb)} GB)."}

backend/services/gateway.py

@@ -0,0 +1,30 @@
+"""
+Routing-Gateway-Status (eingebauter Modus). MC2 IST der Gateway: serviert
+`/v1/*` mit `model: auto`-Komplexitäts-Routing vor llama-swap. Kein externer
+LiteLLM-Dienst nötig (baut auf Python 3.14 nicht); bleibt später austauschbar.
+"""
+
+from config import PORT
+from services.llamaswap import engine_reachable
+from services.router_logic import FAST, HEAVY, HEAVY_CHARS
+
+
+def routing_summary() -> dict:
+    return {
+        "mode": "builtin",
+        "endpoint": f":{PORT}/v1  (OpenAI-kompatibel)",
+        "routes": [
+            {"name": "auto", "target": f"{FAST} ↔ {HEAVY} (nach Komplexität)"},
+            {"name": FAST, "target": "llama-swap-Alias 'fast'"},
+            {"name": HEAVY, "target": "llama-swap-Alias 'heavy'"},
+            {"name": "<alias>", "target": "llama-swap-Passthrough (lädt bei Bedarf)"},
+        ],
+        "heavy_threshold_chars": HEAVY_CHARS,
+        "fallbacks": [],
+        "context_window_fallbacks": [],
+    }
+
+
+def gateway_reachable() -> bool:
+    # Der eingebaute Gateway lebt in MC und proxyt llama-swap → erreichbar, wenn Engine läuft.
+    return engine_reachable()

backend/services/hf.py

@@ -0,0 +1,101 @@
+"""HuggingFace-Helfer: GGUF-Dateien eines Repos auflösen (inkl. Split-Teile) + Größen,
+freie Suche, Repo-URL→ID, verfügbare Quants."""
+
+import os
+import re
+import sys
+
+import httpx
+
+
+def normalize_repo(s: str) -> str:
+    """Akzeptiert volle HF-URL oder `org/repo` → liefert immer `org/repo`."""
+    s = (s or "").strip()
+    m = re.search(r"huggingface\.co/([^/\s]+/[^/\s?#]+)", s)
+    if m:
+        return m.group(1)
+    return s.strip("/")
+
+
+def list_quants(repo: str) -> list[str]:
+    """Verfügbare Quant-Stufen eines Repos (aus den GGUF-Dateinamen, ohne mmproj)."""
+    quants: set[str] = set()
+    for e in _tree(repo):
+        p = str(e.get("path", ""))
+        if p.lower().endswith(".gguf") and "mmproj" not in p.lower():
+            m = re.search(r"(I?Q\d[\w]*|F16|BF16|FP16|F32)", p, re.IGNORECASE)
+            if m:
+                quants.add(m.group(1).upper())
+    # gängige Reihenfolge zuerst
+    order = {"Q4_K_M": 0, "Q4_K_S": 1, "Q5_K_M": 2, "Q6_K": 3, "Q8_0": 4, "Q3_K_M": 5, "Q2_K": 6}
+    return sorted(quants, key=lambda q: (order.get(q, 99), q))
+
+
+def search(q: str, limit: int = 20) -> list[dict]:
+    """Freie HF-Suche nach GGUF-Repos."""
+    url = (f"https://huggingface.co/api/models?search={q}"
+           f"&filter=gguf&sort=downloads&direction=-1&limit={limit}")
+    try:
+        with httpx.Client(timeout=12.0) as c:
+            data = c.get(url).json()
+    except Exception:
+        return []
+    out = []
+    for m in (data if isinstance(data, list) else []):
+        rid = m.get("id")
+        if rid:
+            out.append({"repo": rid, "downloads": int(m.get("downloads") or 0),
+                        "likes": int(m.get("likes") or 0)})
+    return out
+
+
+def hf_bin() -> str:
+    """Pfad zur `hf`-CLI (bevorzugt neben dem laufenden Python im venv)."""
+    cand = os.path.join(os.path.dirname(sys.executable), "hf")
+    return cand if os.path.exists(cand) else "hf"
+
+
+def _tree(repo: str) -> list[dict]:
+    url = f"https://huggingface.co/api/models/{repo}/tree/main?recursive=true"
+    with httpx.Client(timeout=20.0) as c:
+        data = c.get(url).json()
+    return data if isinstance(data, list) else []
+
+
+def _size(entry: dict) -> int:
+    return int(entry.get("size") or (entry.get("lfs") or {}).get("size") or 0)
+
+
+def resolve_gguf(repo: str, quant: str = "Q4_K_M") -> dict:
+    """Beste GGUF-Auswahl eines Repos für einen Quant. Behandelt Split-GGUFs
+    (-00001-of-000NN) als Gruppe. Liefert die Datei-/Pattern-Infos für den Download.
+
+    Rückgabe: {files:[paths], first:path, total_bytes:int, mmproj:path|None, split:bool}
+    """
+    tree = _tree(repo)
+    ggufs = [e for e in tree if str(e.get("path", "")).lower().endswith(".gguf")]
+    q = quant.lower()
+    # mmproj separat (Vision-Projektor)
+    mmproj = next((e["path"] for e in ggufs if "mmproj" in e["path"].lower()), None)
+    model = [e for e in ggufs if "mmproj" not in e["path"].lower()]
+    # bevorzugt den gewünschten Quant
+    pref = [e for e in model if q in e["path"].lower()]
+    chosen = pref or model
+    if not chosen:
+        return {"files": [], "first": None, "total_bytes": 0, "mmproj": mmproj, "split": False}
+    # Split? Wenn die gewählten Dateien -of- enthalten → alle Teile dieser Gruppe.
+    split = any("-of-" in e["path"].lower() for e in chosen)
+    if split:
+        parts = sorted([e for e in chosen if "-of-" in e["path"].lower()], key=lambda e: e["path"])
+        files = [e["path"] for e in parts]
+        first = files[0]
+        total = sum(_size(e) for e in parts)
+    else:
+        # ein einzelnes File: nimm das kleinste passende (typisch genau eins)
+        chosen.sort(key=lambda e: _size(e))
+        first = chosen[0]["path"]
+        files = [first]
+        total = _size(chosen[0])
+    if mmproj:
+        total += next((_size(e) for e in ggufs if e["path"] == mmproj), 0)
+    return {"files": files, "first": first, "total_bytes": total, "mmproj": mmproj, "split": split}

backend/services/jobengine.py

@@ -0,0 +1,163 @@
+"""
+Mini-Job-System: Hintergrund-Prozesse mit Live-Log + Download-Fortschritt.
+Portiert aus Mission Control v1 (jobengine.py). In-Memory, ein Daemon-Thread je Job.
+"""
+
+import glob
+import os
+import shlex
+import subprocess
+import threading
+import time
+import uuid
+
+JOBS: dict[str, dict] = {}
+_PROCS: dict[str, subprocess.Popen] = {}
+_LOG_CAP = 400
+
+
+def _append_log(job: dict, line: str) -> None:
+    job["log"].append(line)
+    if len(job["log"]) > _LOG_CAP:
+        del job["log"][0]
+
+
+def _pump_output(job: dict, stream) -> None:
+    """Liest byteweise; `\\r` (tqdm/hf-Fortschritt) überschreibt die letzte Zeile."""
+    buf = b""
+    overwrite = False
+    pending_cr = False
+
+    def commit():
+        line = buf.decode("utf-8", "replace")
+        if overwrite and job["log"]:
+            job["log"][-1] = line
+        else:
+            _append_log(job, line)
+
+    while True:
+        ch = stream.read(1)
+        if not ch:
+            break
+        if pending_cr:
+            pending_cr = False
+            if ch == b"\n":
+                commit(); overwrite = False; buf = b""
+                continue
+            commit(); overwrite = True; buf = b""
+        if ch == b"\r":
+            pending_cr = True
+        elif ch == b"\n":
+            commit(); overwrite = False; buf = b""
+        else:
+            buf += ch
+    if pending_cr:
+        commit(); overwrite = True; buf = b""
+    if buf:
+        commit()
+
+
+def _run_job(job_id: str, args: list[str], env: dict | None = None):
+    job = JOBS[job_id]
+    job["state"] = "running"
+    try:
+        proc = subprocess.Popen(
+            args, stdout=subprocess.PIPE, stderr=subprocess.STDOUT, bufsize=0,
+            env={**os.environ, **(env or {})},
+        )
+        _PROCS[job_id] = proc
+        _pump_output(job, proc.stdout)
+        proc.wait()
+        job["returncode"] = proc.returncode
+        job["state"] = "canceled" if job.get("canceled") else ("done" if proc.returncode == 0 else "failed")
+    except Exception as exc:  # noqa: BLE001
+        _append_log(job, f"[mc] Fehler: {exc}")
+        job["state"] = "failed"
+        job["returncode"] = -1
+    finally:
+        _PROCS.pop(job_id, None)
+        job["finished_at"] = time.time()
+        cb = job.pop("_on_done", None)
+        if cb and job["state"] == "done":
+            try:
+                cb()
+            except Exception as exc:  # noqa: BLE001
+                _append_log(job, f"[mc] Nachbearbeitung-Fehler: {exc}")
+
+
+def attach_download_progress(job_id: str, local_dir: str, total_bytes: int) -> None:
+    """Fortschritt in % aus wachsenden *.incomplete-Dateien (hf schreibt sie)."""
+    if not total_bytes or total_bytes <= 0:
+        return
+    job = JOBS.get(job_id)
+    if job is not None:
+        job["progress"] = 0
+        job["total_bytes"] = total_bytes
+
+    def _watch():
+        pat = os.path.join(local_dir, ".cache", "huggingface", "download", "**", "*.incomplete")
+        prev_t = prev_b = None
+        rate = 0.0
+        while True:
+            j = JOBS.get(job_id)
+            if not j or j["state"] in ("done", "failed", "canceled"):
+                break
+            try:
+                inc = glob.glob(pat, recursive=True)
+                cur = sum(os.path.getsize(f) for f in inc) if inc else 0
+                if cur:
+                    j["progress"] = min(99, int(cur * 100 / total_bytes))
+                    j["done_bytes"] = cur
+                    now = time.time()
+                    if prev_t is not None and now > prev_t and cur >= prev_b:
+                        inst = (cur - prev_b) / (now - prev_t)
+                        rate = inst if rate == 0 else 0.3 * inst + 0.7 * rate
+                        if rate > 0:
+                            j["rate_bps"] = rate
+                            j["eta_s"] = int((total_bytes - cur) / rate)
+                    prev_t, prev_b = now, cur
+            except Exception:  # noqa: BLE001
+                pass
+            time.sleep(1.0)
+        j = JOBS.get(job_id)
+        if j and j["state"] == "done":
+            j["progress"] = 100
+            j.pop("eta_s", None)
+
+    threading.Thread(target=_watch, daemon=True).start()
+
+
+def start_job(args: list[str], label: str, env: dict | None = None, on_done=None) -> str:
+    job_id = uuid.uuid4().hex[:12]
+    JOBS[job_id] = {
+        "id": job_id, "label": label, "state": "queued",
+        "log": ["$ " + " ".join(shlex.quote(a) for a in args)],
+        "returncode": None, "started_at": time.time(), "finished_at": None,
+    }
+    if on_done:
+        JOBS[job_id]["_on_done"] = on_done
+    threading.Thread(target=_run_job, args=(job_id, args, env), daemon=True).start()
+    return job_id
+
+
+def cancel_job(job_id: str) -> bool:
+    job = JOBS.get(job_id)
+    if not job or job["state"] in ("done", "failed", "canceled"):
+        return False
+    job["canceled"] = True
+    _append_log(job, "[mc] Abbruch angefordert…")
+    proc = _PROCS.get(job_id)
+    if proc is not None:
+        try:
+            proc.terminate()
+        except Exception:  # noqa: BLE001
+            pass
+    else:
+        job["state"] = "canceled"
+        job["finished_at"] = time.time()
+    return True
+
+
+def public_jobs() -> list[dict]:
+    """Jobs ohne interne Felder (_on_done) für die API."""
+    return [{k: v for k, v in j.items() if not k.startswith("_")} for j in JOBS.values()]

backend/services/llamaswap.py

@@ -0,0 +1,248 @@
+"""
+Engine-Service: liest/schreibt die llama-swap config.yaml und spricht die
+llama-swap-API. Portiert & erweitert aus Mission Control v1.
+
+NEU in 2.0: `groups` für Ko-Residenz (schnell + schwer gleichzeitig geladen,
+`swap:false`) → Multi-Model-Delegation ohne Nachlade-Latenz.
+"""
+
+import os
+import re
+
+import httpx
+from ruamel.yaml.scalarstring import LiteralScalarString
+
+from config import CMD_TEMPLATE, CONFIG_PATH, DEFAULT_TTL, LLAMA_SWAP_URL
+
+# Kanonische Rollen (vereinheitlicht ggü. v1: kein manager/reviewer mehr).
+ROLE_IDS = {"vision", "coder", "reasoning", "agent", "scout"}
+
+_CTX_RE = re.compile(r"-(?:c|-ctx-size)\s+(\d+)")
+_PATH_RE = re.compile(r"-(?:m|-model)\s+([^\s]+)")
+_QUANT_RE = re.compile(r"(Q\d_[A-Z0-9_]+|IQ\d_[A-Z0-9_]+|fp16|bf16)\.gguf", re.IGNORECASE)
+
+
+# --- Lesen -------------------------------------------------------------------
+def read_config() -> dict:
+    if not CONFIG_PATH.exists():
+        return {"models": {}}
+    from ruamel.yaml import YAML
+    r_yaml = YAML()
+    r_yaml.preserve_quotes = True
+    with CONFIG_PATH.open("r", encoding="utf-8") as f:
+        data = r_yaml.load(f) or {}
+    if not data.get("models"):
+        data["models"] = {}
+    return data
+
+
+def _parse_model(name: str, spec: dict) -> dict:
+    spec = spec or {}
+    cmd = str(spec.get("cmd", "")).strip()
+    ctx = int(m.group(1)) if (m := _CTX_RE.search(cmd)) else None
+
+    path = filename = quant = ""
+    size_bytes = None
+    if (m := _PATH_RE.search(cmd)):
+        path = m.group(1).replace("'", "").replace('"', "")
+        filename = os.path.basename(path)
+        if os.path.exists(path):
+            size_bytes = os.path.getsize(path)
+        if (q := _QUANT_RE.search(path)):
+            quant = q.group(1).upper()
+
+    aliases = spec.get("aliases") or []
+    if isinstance(aliases, str):
+        aliases = [aliases]
+    aliases = [str(a) for a in aliases]
+    role = aliases[0].lower() if aliases else (name.lower() if name.lower() in ROLE_IDS else None)
+
+    from services.caps import capabilities
+    return {
+        "name": name,
+        "role": role,
+        "aliases": aliases,
+        "api_ids": [name] + aliases,
+        "ctx": ctx,
+        "ttl": spec.get("ttl"),
+        "cmd": cmd,
+        "gguf_path": path,
+        "filename": filename,
+        "quant": quant,
+        "size_bytes": size_bytes,
+        "incomplete": not path,
+        "capabilities": capabilities(
+            name=filename or name, cmd=cmd,
+            gguf_path=(path if (path and os.path.exists(path)) else ""),
+        ),
+    }
+
+
+def list_models() -> list[dict]:
+    cfg = read_config()
+    return [_parse_model(name, spec) for name, spec in (cfg.get("models") or {}).items()]
+
+
+def engine_reachable() -> bool:
+    try:
+        with httpx.Client(timeout=3.0) as c:
+            return c.get(f"{LLAMA_SWAP_URL}/v1/models").status_code == 200
+    except Exception:
+        return False
+
+
+# --- Schreiben ---------------------------------------------------------------
+def model_id_from_path(model_path: str) -> str:
+    """Sprechende Modell-ID (= API-Name) aus dem GGUF-Pfad: Repo-Ordnername ohne
+    '-GGUF'. Fallback: Dateiname ohne Quant-Suffix.
+    Split-GGUFs liegen oft in einem Quant-Unterordner (…/Q4_K_M/file-00001-of-…) →
+    dann eine Ebene höher (Repo-Ordner) nehmen, sonst hieße das Modell 'Q4_K_M'."""
+    d = os.path.basename(os.path.dirname(model_path))
+    if re.fullmatch(r"(I?Q\d[\w]*|UD-Q\d[\w]*|F16|BF16|FP16|F32)", d, flags=re.I):
+        d = os.path.basename(os.path.dirname(os.path.dirname(model_path)))
+    name = re.sub(r"[-_]?GGUF$", "", d, flags=re.I).strip("-_")
+    if not name:
+        fn = re.sub(r"\.gguf$", "", os.path.basename(model_path), flags=re.I)
+        fn = re.sub(r"-\d+-of-\d+$", "", fn)
+        name = re.sub(r"[-_](Q\d[\w]*|IQ\d[\w]*|F16|BF16|FP16|F32)$", "", fn, flags=re.I)
+    return name or "modell"
+
+
+def set_role_alias(cfg: dict, model_id: str, role: str | None) -> None:
+    """Rolle als eindeutigen llama-swap-`aliases`-Eintrag setzen (vorher bei allen
+    anderen Modellen entfernen). role=None/leer entfernt den Alias."""
+    models = cfg.get("models") or {}
+    role = (role or "").strip().lower()
+    if role:
+        for mid, spec in models.items():
+            if mid == model_id or not isinstance(spec, dict):
+                continue
+            al = [a for a in (spec.get("aliases") or []) if str(a).lower() != role]
+            if al:
+                spec["aliases"] = al
+            else:
+                spec.pop("aliases", None)
+    spec = models.get(model_id)
+    if isinstance(spec, dict):
+        if role and role != model_id.lower():
+            spec["aliases"] = [role]
+        else:
+            spec.pop("aliases", None)
+
+
+def _augment_vision(cmd: str, model_path: str, mmproj_path: str | None) -> str:
+    """Vision-Modelle brauchen --mmproj <projektor> und --jinja."""
+    if mmproj_path:
+        if "--mmproj" not in cmd:
+            cmd += f" --mmproj {mmproj_path}"
+        if "--jinja" not in cmd:
+            cmd += " --jinja"
+    return cmd
+
+
+def write_config(cfg: dict) -> None:
+    """Atomar schreiben (tmp + os.replace), damit llama-swap mit -watch-config nie
+    eine halbe Datei sieht. Fehlende Schreibrechte → klare Meldung."""
+    try:
+        CONFIG_PATH.parent.mkdir(parents=True, exist_ok=True)
+        tmp = CONFIG_PATH.with_name(CONFIG_PATH.name + ".tmp")
+        from ruamel.yaml import YAML
+        r_yaml = YAML()
+        r_yaml.preserve_quotes = True
+        with tmp.open("w", encoding="utf-8") as f:
+            r_yaml.dump(cfg, f)
+        os.replace(tmp, CONFIG_PATH)
+    except PermissionError as exc:
+        raise PermissionError(
+            f"Mission Control darf '{CONFIG_PATH}' nicht schreiben. "
+            f"Einmalig: sudo chown -R hitonabi:hitonabi {CONFIG_PATH.parent}"
+        ) from exc
+
+
+
+def register_model(model_path: str, role: str | None = None, ctx: int = 8192,
+                   ttl: int | None = None, mmproj_path: str | None = None,
+                   jinja: bool = False) -> str:
+    """Ein GGUF als llama-swap-Modell eintragen (cmd + Rolle-Alias). Gibt die
+    Modell-ID zurück. jinja=True erzwingt --jinja (Tool-Calling, z.B. fürs Agent-Hirn)."""
+    cfg = read_config()
+    model_id = model_id_from_path(model_path)
+    cmd = CMD_TEMPLATE.replace("{model}", model_path).replace("{ctx}", str(ctx))
+    cmd = _augment_vision(cmd, model_path, mmproj_path)
+    if jinja and "--jinja" not in cmd:
+        cmd += " --jinja"
+    cfg.setdefault("models", {})[model_id] = {
+        "cmd": LiteralScalarString(cmd + "\n"),
+        "ttl": ttl if ttl is not None else DEFAULT_TTL,
+    }
+    set_role_alias(cfg, model_id, role)
+    write_config(cfg)
+    return model_id
+
+
+# --- Groups (Ko-Residenz) ----------------------------------------------------
+def set_group(group: str, members: list[str], swap: bool = False, persist: bool = False) -> None:
+    """llama-swap-`groups`-Eintrag setzen. swap=False → alle Mitglieder dürfen
+    GLEICHZEITIG laufen (Ko-Residenz, keine Nachlade-Latenz). persist=True →
+    Mitglieder werden nie automatisch entladen."""
+    cfg = read_config()
+    groups = cfg.setdefault("groups", {})
+    groups[group] = {"swap": swap, "persist": persist, "members": list(members)}
+    write_config(cfg)
+
+
+def list_groups() -> dict:
+    return read_config().get("groups") or {}
+
+
+def set_role(model_id: str, role: str | None) -> bool:
+    """Rolle (llama-swap-Alias) eines bestehenden Modells setzen/ändern. So tauscht man
+    z.B. das `fast`-Hirn: Rolle `fast` auf ein anderes Modell legen (Alias wandert)."""
+    cfg = read_config()
+    if model_id not in (cfg.get("models") or {}):
+        return False
+    set_role_alias(cfg, model_id, role)
+    write_config(cfg)
+    return True
+
+
+def set_ctx(model_id: str, ctx: int) -> bool:
+    """Kontextlänge (-c) eines bestehenden Modells ändern."""
+    cfg = read_config()
+    spec = (cfg.get("models") or {}).get(model_id)
+    if not spec:
+        return False
+    cmd = str(spec.get("cmd", ""))
+    if _CTX_RE.search(cmd):
+        cmd = re.sub(r"-(?:c|-ctx-size)\s+\d+", f"-c {ctx}", cmd)
+    else:
+        cmd = cmd.rstrip() + f" -c {ctx}"
+    spec["cmd"] = LiteralScalarString(cmd if cmd.endswith("\n") else cmd + "\n")
+    write_config(cfg)
+    return True
+
+
+def delete_model(model_id: str) -> bool:
+    """Entfernt einen Modell-Eintrag aus der config.yaml (und aus allen Gruppen)."""
+    cfg = read_config()
+    models = cfg.get("models") or {}
+    if model_id not in models:
+        return False
+    del models[model_id]
+    for g in (cfg.get("groups") or {}).values():
+        if isinstance(g, dict) and model_id in (g.get("members") or []):
+            g["members"] = [m for m in g["members"] if m != model_id]
+    write_config(cfg)
+    return True
+
+
+def get_running_models() -> list[str]:
+    """Fragt den /running Endpunkt von llama-swap ab. Gibt geladene Modelle zurück."""
+    try:
+        with httpx.Client(timeout=2.0) as c:
+            r = c.get(f"{LLAMA_SWAP_URL}/running")
+            if r.status_code == 200:
+                return r.json().get("running") or []
+    except Exception:
+        pass
+    return []

backend/services/maintenance.py

@@ -0,0 +1,127 @@
+"""
+Wartung: Updates (OS/Engine/Modelle), Dienst-Neustart (system- vs user-aware),
+Reboot, Logs. Portiert/modernisiert aus Mission Control v1 (routers/maintenance.py).
+
+Passwortfrei über NOPASSWD-Whitelist (sudo -n). OS-Update/Reboot brauchen einmalig
+erweiterte sudoers (siehe docs/BEDIENUNG.md). Lange Ops laufen als jobengine-Job.
+"""
+
+import os
+import subprocess
+import time
+from datetime import datetime
+
+import httpx
+import psutil
+
+from services import discover, jobengine, llamaswap
+
+# System-Dienste (root, via sudo -n NOPASSWD) vs. User-Dienste (systemctl --user).
+SYSTEM_SERVICES = {"llama-swap"}
+USER_SERVICES = {"mission-control-2", "hermes-gateway", "hermes-dashboard", "hermes-webui"}
+
+ENGINE_UPDATE_CMD = os.environ.get("MC_ENGINE_UPDATE_CMD", "")
+ENGINE_PATH = os.environ.get("MC_ENGINE_PATH", "/opt/llamacpp")
+_engine_cache = {"ts": 0.0, "avail": False}
+
+
+def _ram_gb() -> float:
+    return psutil.virtual_memory().total / (1024 ** 3)
+
+
+def _os_upgradable() -> int:
+    try:
+        out = subprocess.run(
+            ["bash", "-c", "apt list --upgradable 2>/dev/null | grep -c upgradable || true"],
+            capture_output=True, text=True, timeout=10)
+        return int((out.stdout or "0").strip() or 0)
+    except Exception:
+        return 0
+
+
+def _engine_update_available() -> bool:
+    now = time.time()
+    if now - _engine_cache["ts"] < 3600:
+        return _engine_cache["avail"]
+    avail = False
+    try:
+        rel = httpx.get("https://api.github.com/repos/lemonade-sdk/llamacpp-rocm/releases/latest",
+                        timeout=6, headers={"User-Agent": "MissionControl2"}).json()
+        pub = datetime.fromisoformat(rel["published_at"].replace("Z", "+00:00")).timestamp()
+        inst = os.path.getmtime(ENGINE_PATH)
+        avail = pub > inst + 86400
+    except Exception:
+        avail = False
+    _engine_cache.update(ts=now, avail=avail)
+    return avail
+
+
+def model_upgrades() -> list[dict]:
+    """Dynamisch: je discover-Kategorie das empfohlene Modell, das NOCH NICHT installiert ist
+    → Upgrade-Vorschlag für diese Rolle. Self-updating (kein Hardcode wie v1)."""
+    disc = discover.safe_discover(_ram_gb())
+    if not disc:
+        return []
+    cmds = " ".join(str(s.get("cmd", "")).lower()
+                    for s in (llamaswap.read_config().get("models") or {}).values())
+    out = []
+    for c in disc.get("categories", []):
+        rec = c.get("recommended")
+        if not rec:
+            continue
+        base = rec.split("/")[-1].lower()
+        stem = base[:-5] if base.endswith("-gguf") else base
+        if base in cmds or (stem and stem in cmds):
+            continue
+        out.append({"role": c["role"], "title": c["title"], "repo": rec})
+    return out
+
+
+def updates() -> dict:
+    ups = model_upgrades()
+    return {"os": _os_upgradable(), "engine": 1 if _engine_update_available() else 0,
+            "models": len(ups), "model_list": ups}
+
+
+def _run(cmd: list[str]) -> dict:
+    try:
+        p = subprocess.run(cmd, capture_output=True, text=True, timeout=120)
+        return {"ok": p.returncode == 0, "out": (p.stdout or "")[-4000:], "err": (p.stderr or "")[-2000:]}
+    except Exception as exc:  # noqa: BLE001
+        return {"ok": False, "out": "", "err": str(exc)}
+
+
+def restart_service(name: str) -> dict:
+    if name in SYSTEM_SERVICES:
+        return _run(["sudo", "-n", "systemctl", "restart", name])
+    if name in USER_SERVICES:
+        return _run(["systemctl", "--user", "restart", name])
+    return {"ok": False, "err": f"Dienst '{name}' nicht erlaubt."}
+
+
+def logs(service: str, lines: int = 200) -> dict:
+    lines = max(1, min(lines, 1000))
+    if service in SYSTEM_SERVICES:
+        cmd = ["sudo", "-n", "journalctl", "-u", service, "-n", str(lines), "--no-pager"]
+    elif service in USER_SERVICES:
+        cmd = ["journalctl", "--user", "-u", service, "-n", str(lines), "--no-pager"]
+    else:
+        return {"ok": False, "text": "", "err": "Dienst nicht erlaubt."}
+    r = _run(cmd)
+    return {"ok": r["ok"], "text": r["out"] or r["err"]}
+
+
+def os_update_job() -> str:
+    cmd = "sudo -n apt-get update && sudo -n DEBIAN_FRONTEND=noninteractive apt-get upgrade -y"
+    return jobengine.start_job(["bash", "-c", cmd], "OS-Update (apt)")
+
+
+def engine_update_job() -> str | None:
+    if not ENGINE_UPDATE_CMD:
+        return None
+    cmd = f"{ENGINE_UPDATE_CMD} && sudo -n systemctl restart llama-swap"
+    return jobengine.start_job(["bash", "-c", cmd], "Engine-Update (llama.cpp)")
+
+
+def reboot() -> dict:
+    return _run(["sudo", "-n", "reboot"])

backend/services/memory.py

@@ -0,0 +1,149 @@
+"""
+Geteiltes Gedächtnis (die „Verfassung") — SQLite aus stdlib, WAL-Mode.
+Portiert aus Mission Control v1 (routers/memory.py), DB-Logik als Service isoliert.
+
+5 Kategorien: user · instruction · stable · versioned · ephemeral (7-Tage-TTL).
+Dedupe = deterministischer Kurator (exakt/enthalten/ähnlich), KEIN LLM.
+"""
+
+import re
+import sqlite3
+import uuid
+from datetime import datetime, timezone
+from difflib import SequenceMatcher
+
+from config import MEMORY_DB
+
+CATEGORIES = ("user", "instruction", "stable", "versioned", "ephemeral")
+
+_conn: sqlite3.Connection | None = None
+
+
+def db() -> sqlite3.Connection:
+    global _conn
+    if _conn is None:
+        MEMORY_DB.parent.mkdir(parents=True, exist_ok=True)
+        _conn = sqlite3.connect(str(MEMORY_DB), check_same_thread=False)
+        _conn.row_factory = sqlite3.Row
+        _conn.execute("PRAGMA journal_mode=WAL")
+        _conn.execute("""
+            CREATE TABLE IF NOT EXISTS memories (
+                id         TEXT PRIMARY KEY,
+                content    TEXT NOT NULL,
+                category   TEXT NOT NULL DEFAULT 'stable',
+                source     TEXT NOT NULL DEFAULT 'manual',
+                created_at TEXT NOT NULL,
+                updated_at TEXT NOT NULL
+            )
+        """)
+        _conn.execute(
+            "DELETE FROM memories WHERE category='ephemeral'"
+            " AND datetime(created_at) < datetime('now','-7 days')"
+        )
+        _conn.commit()
+    return _conn
+
+
+def _now() -> str:
+    return datetime.now(timezone.utc).isoformat()
+
+
+def list_memories(q: str = "", category: str = "") -> list[dict]:
+    sql, params, conds = "SELECT * FROM memories", [], []
+    if q:
+        conds.append("content LIKE ?"); params.append(f"%{q}%")
+    if category:
+        conds.append("category = ?"); params.append(category)
+    if conds:
+        sql += " WHERE " + " AND ".join(conds)
+    sql += " ORDER BY created_at DESC"
+    return [dict(r) for r in db().execute(sql, params).fetchall()]
+
+
+def add_memory(content: str, category: str = "stable", source: str = "manual") -> dict:
+    now, mid = _now(), str(uuid.uuid4())
+    db().execute(
+        "INSERT INTO memories (id,content,category,source,created_at,updated_at) VALUES (?,?,?,?,?,?)",
+        (mid, content.strip(), category, source, now, now),
+    )
+    db().commit()
+    return {"id": mid, "content": content.strip(), "category": category,
+            "source": source, "created_at": now, "updated_at": now}
+
+
+def update_memory(mid: str, content: str | None = None, category: str | None = None) -> dict | None:
+    row = db().execute("SELECT * FROM memories WHERE id=?", (mid,)).fetchone()
+    if not row:
+        return None
+    now = _now()
+    new_content = content.strip() if content is not None else row["content"]
+    new_cat = category if category is not None else row["category"]
+    db().execute("UPDATE memories SET content=?,category=?,updated_at=? WHERE id=?",
+                 (new_content, new_cat, now, mid))
+    db().commit()
+    return {"id": mid, "content": new_content, "category": new_cat,
+            "source": row["source"], "created_at": row["created_at"], "updated_at": now}
+
+
+def delete_memory(mid: str) -> bool:
+    if not db().execute("SELECT id FROM memories WHERE id=?", (mid,)).fetchone():
+        return False
+    db().execute("DELETE FROM memories WHERE id=?", (mid,))
+    db().commit()
+    return True
+
+
+def export_text() -> dict:
+    rows = db().execute("SELECT * FROM memories ORDER BY category, updated_at DESC").fetchall()
+    lines = ["# Mission Control — Gedächtnis\n"]
+    current = ""
+    for r in rows:
+        if r["category"] != current:
+            lines.append(f"\n## {r['category']}\n")
+            current = r["category"]
+        lines.append(f"- {r['content']}  _(Quelle: {r['source']}, {r['updated_at'][:10]})_")
+    return {"text": "\n".join(lines), "count": len(rows)}
+
+
+def _norm(s: str) -> str:
+    s = re.sub(r"[^\w\s]", " ", s.lower(), flags=re.UNICODE)
+    return re.sub(r"\s+", " ", s).strip()
+
+
+def dedupe(apply: bool = False, threshold: float = 0.85) -> dict:
+    """Deterministischer Kurator: findet Dubletten (exakt/enthalten/ähnlich) je Kategorie,
+    behält den vollständigsten (längsten) Eintrag. Konservativ, kein LLM."""
+    rows = [dict(r) for r in db().execute(
+        "SELECT * FROM memories ORDER BY length(content) DESC, created_at ASC").fetchall()]
+    used: set[str] = set()
+    groups: list[dict] = []
+    for i, a in enumerate(rows):
+        if a["id"] in used:
+            continue
+        na = _norm(a["content"])
+        if not na:
+            continue
+        dups = []
+        for b in rows[i + 1:]:
+            if b["id"] in used or b["category"] != a["category"]:
+                continue
+            nb = _norm(b["content"])
+            if not nb:
+                continue
+            if nb in na or na in nb or SequenceMatcher(None, na, nb).ratio() >= threshold:
+                dups.append(b); used.add(b["id"])
+        if dups:
+            used.add(a["id"])
+            groups.append({
+                "keep": {"id": a["id"], "content": a["content"], "category": a["category"]},
+                "remove": [{"id": d["id"], "content": d["content"]} for d in dups],
+            })
+    dup_count = sum(len(g["remove"]) for g in groups)
+    removed = 0
+    if apply:
+        for g in groups:
+            for d in g["remove"]:
+                db().execute("DELETE FROM memories WHERE id=?", (d["id"],)); removed += 1
+        if removed:
+            db().commit()
+    return {"groups": groups, "duplicate_count": dup_count, "removed": removed, "applied": apply}

backend/services/router_logic.py

@@ -0,0 +1,33 @@
+"""
+Komplexitäts-Routing für `model: auto` (eingebauter Gateway).
+Schnell im Alltag (fast), schwer bei Bedarf (heavy) — regelbasiert, sub-ms, ohne Cloud.
+"""
+
+import os
+import re
+
+FAST = os.environ.get("MC_ROUTE_FAST", "fast")
+HEAVY = os.environ.get("MC_ROUTE_HEAVY", "heavy")
+HEAVY_CHARS = int(os.environ.get("MC_GATEWAY_HEAVY_CHARS", "8000"))
+# Thinking auf der fast-Spur ausschalten → flotte Alltags-Antworten (Qwen3.6 ist ein
+# Reasoning-Modell). heavy behält Thinking für harte Aufgaben. Abschaltbar via Env.
+FAST_NO_THINK = os.environ.get("MC_FAST_NO_THINK", "1") not in ("0", "false", "")
+
+_HEAVY_KW = re.compile(
+    r"\b(beweis|prove|theorem|refactor|architect|komplex|complex|schwierig|"
+    r"think\s*hard|reason\s*carefully|tief\s*nachdenk|optimi[sz]e|algorithm|"
+    r"root\s*cause|debug|analy[sz]e\s+deeply|step[-\s]?by[-\s]?step)\b",
+    re.IGNORECASE,
+)
+
+
+def choose_model(body: dict) -> tuple[str, str]:
+    """Wählt fast|heavy für eine Chat-Anfrage. Gibt (alias, begründung) zurück."""
+    msgs = body.get("messages") or []
+    text = "\n".join(str(m.get("content") or "") for m in msgs)
+    n = len(text)
+    if n > HEAVY_CHARS:
+        return HEAVY, f"langer Kontext ({n} > {HEAVY_CHARS} Zeichen)"
+    if _HEAVY_KW.search(text):
+        return HEAVY, "Komplexitäts-Schlüsselwort erkannt"
+    return FAST, "Standard"

backend/services/sources.py

@@ -0,0 +1,27 @@
+"""
+Vertrauenswürdige Quellen + Kategorien für die automatische Modell-Entdeckung.
+Portiert aus Mission Control v1 (sources.py). Rollen sind die EINE Quelle der
+Wahrheit (vereinheitlicht): vision · coder · reasoning · agent · scout.
+"""
+
+# HF-Orgs, die zuverlässig aktuelle, hochwertige GGUF-Quants veröffentlichen.
+TRUSTED_AUTHORS = ["unsloth", "bartowski", "ggml-org", "lmstudio-community"]
+
+# Kategorien (Reihenfolge = Anzeige + Zuordnungs-Priorität). Ein Modell wird der
+# ERSTEN Kategorie zugeordnet, deren Stichwort im Repo-Namen vorkommt; sonst „scout".
+# Die `role` ist zugleich der Alias-Vorschlag und gehört zu ROLE_IDS.
+CATEGORIES = [
+    {"role": "vision", "title": "Bilder verstehen", "icon": "eye",
+     "kw": ["-vl-", "-vl", "vision", "llava", "multimodal", "-mm-", "pixtral"]},
+    {"role": "coder", "title": "Coden & Programmieren", "icon": "code",
+     "kw": ["coder", "-code-", "code-", "codestral", "starcoder"]},
+    {"role": "reasoning", "title": "Nachdenken & Logik", "icon": "pulse",
+     "kw": ["-r1", "deepseek-r1", "reasoning", "qwq", "magistral", "-think", "thinking", "-o1"]},
+    {"role": "agent", "title": "Agenten & Tool-Use", "icon": "layers",
+     "kw": ["hermes", "-tool", "command-r", "watt", "-fc-", "function"]},
+    {"role": "scout", "title": "Allrounder & Chat", "icon": "compass",
+     "kw": []},  # Fallback: instruct/chat-Modelle
+]
+
+# Repo-Namensteile, die bei der Entdeckung übersprungen werden (Roh-/Spezialformate).
+SKIP_TOKENS = ["-base", "-bnb-", "-gptq", "-awq", "-fp8", "draft", "tokenizer"]

backend/services/system.py

@@ -0,0 +1,81 @@
+"""
+System/OS-Metriken für die Box (Bosgame / Strix Halo).
+
+CPU/RAM/Disk via psutil (plattformübergreifend). GPU-Auslastung/VRAM/Temperatur
+via sysfs (amdgpu) — nur Linux; auf anderen Plattformen None (amd-smi fehlt auf
+der Box, daher sysfs). Verschachtelte Struktur wie v1 (cpu.percent, ram.used Bytes).
+"""
+
+import glob
+import os
+
+import psutil
+
+from config import MODELS_DIR
+
+
+def _read_int(path: str) -> int | None:
+    try:
+        with open(path) as f:
+            return int(f.read().strip())
+    except Exception:
+        return None
+
+
+def _gpu_sysfs() -> dict | None:
+    """AMD-GPU-Auslastung + Speicher via sysfs (Linux). Findet die Basis-Card
+    dynamisch (Strix Halo ist oft card1, nicht card0) und überspringt die
+    Connector-Verzeichnisse (card1-DP-1 …). Strix Halo nutzt Unified Memory →
+    GTT ist der eigentliche große Pool; VRAM ist nur der kleine Carve-out."""
+    for dev in sorted(glob.glob("/sys/class/drm/card*/device")):
+        card = dev.split("/")[-2]            # z.B. "card1" oder "card1-DP-1"
+        if "-" in card:                      # Connector-Dir → kein GPU-Device
+            continue
+        busy = _read_int(f"{dev}/gpu_busy_percent")
+        if busy is None:
+            continue
+        return {
+            "busy_percent": busy,
+            "vram_used": _read_int(f"{dev}/mem_info_vram_used"),
+            "vram_total": _read_int(f"{dev}/mem_info_vram_total"),
+            "gtt_used": _read_int(f"{dev}/mem_info_gtt_used"),
+            "gtt_total": _read_int(f"{dev}/mem_info_gtt_total"),
+        }
+    return None
+
+
+def _temps() -> dict | None:
+    """CPU/GPU-Temperatur via hwmon (Linux). None bei Fehlen."""
+    out: dict = {}
+    for hw in glob.glob("/sys/class/hwmon/hwmon*"):
+        name = ""
+        try:
+            with open(f"{hw}/name") as f:
+                name = f.read().strip()
+        except Exception:
+            continue
+        t = _read_int(f"{hw}/temp1_input")
+        if t is None:
+            continue
+        c = round(t / 1000.0, 1)
+        if name in ("k10temp", "zenpower", "coretemp"):
+            out["cpu"] = c
+        elif name in ("amdgpu", "edge"):
+            out["gpu"] = c
+    return out or None
+
+
+def system_status() -> dict:
+    vm = psutil.virtual_memory()
+    try:
+        du = psutil.disk_usage(str(MODELS_DIR) if MODELS_DIR.exists() else os.getcwd())
+        disk = {"total": du.total, "used": du.used, "percent": du.percent}
+    except Exception:
+        disk = None
+    return {
+        "cpu": {"percent": psutil.cpu_percent(interval=0.1), "cores": psutil.cpu_count()},
+        "ram": {"total": vm.total, "used": vm.used, "percent": vm.percent},
+        "gpu": _gpu_sysfs(),
+        "temp": _temps(),
+        "disk": disk,
+    }

deploy/backup.sh

@@ -0,0 +1,19 @@
+#!/usr/bin/env bash
+# Backup der Shared-Memory-SQLite + Configs (cron-bar auf der Box).
+# Behält die letzten 7 Snapshots. Identisch zur /api/system/backup-Logik.
+set -euo pipefail
+
+MODELS_DIR="${MC_MODELS_DIR:-/srv/models}"
+MEM_DB="${MC_MEMORY_DB:-$MODELS_DIR/mc2-memory.db}"
+LSWAP="${MC_CONFIG_PATH:-/etc/llama-swap/config.yaml}"
+GW="${MC_GATEWAY_CONFIG:-/opt/mission-control-2/gateway/config.yaml}"
+DEST="$MODELS_DIR/mc2-backups/$(date +%Y%m%d-%H%M%S)"
+
+mkdir -p "$DEST"
+for f in "$MEM_DB" "$MEM_DB-wal" "$MEM_DB-shm" "$LSWAP" "$GW"; do
+  [ -f "$f" ] && cp -p "$f" "$DEST/" || true
+done
+
+# nur die letzten 7 behalten
+ls -1dt "$MODELS_DIR"/mc2-backups/*/ 2>/dev/null | tail -n +8 | xargs -r rm -rf
+echo "OK — Backup unter $DEST"

deploy/build.sh

@@ -0,0 +1,8 @@
+#!/usr/bin/env bash
+# Frontend bauen (vor jedem Deploy auf dem Entwickler-PC). Output → frontend/dist,
+# das committet wird (kein Node-Build auf der Box).
+set -euo pipefail
+cd "$(dirname "$0")/../frontend"
+npm ci
+npm run build
+echo "OK — frontend/dist gebaut."

deploy/deploy.sh

@@ -0,0 +1,33 @@
+#!/usr/bin/env bash
+# Deploy AUF DER BOX als systemd-USER-Dienst — KEIN sudo, KEIN /opt, KEIN Passwort.
+# Erstinstallation + Updates in einem. Läuft als User hitonabi.
+#
+# Erstinstallation (einmalig):
+#   git clone https://git.tobisniceshomelab.ddnsfree.com/Hitonabi/mission-control-v2 ~/mission-control-v2
+#   bash ~/mission-control-v2/deploy/deploy.sh
+set -euo pipefail
+
+SRC="${MC2_SRC:-$HOME/mission-control-v2}"
+
+cd "$SRC"
+git fetch -q origin && git reset -q --hard origin/main
+
+# venv + Abhängigkeiten
+if [ ! -d "$SRC/backend/.venv" ]; then
+  python3 -m venv "$SRC/backend/.venv"
+fi
+"$SRC/backend/.venv/bin/python" -m pip install -q --upgrade pip
+"$SRC/backend/.venv/bin/python" -m pip install -q -r "$SRC/backend/requirements.txt"
+
+# systemd-USER-Unit installieren/aktualisieren
+mkdir -p "$HOME/.config/systemd/user"
+cp "$SRC/deploy/mission-control-2.service" "$HOME/.config/systemd/user/mission-control-2.service"
+systemctl --user daemon-reload
+systemctl --user enable mission-control-2 >/dev/null 2>&1 || true
+loginctl enable-linger "$USER" >/dev/null 2>&1 || true
+systemctl --user restart mission-control-2
+
+sleep 2
+echo "--- Health ---"
+curl -sf http://127.0.0.1:9001/api/health && echo
+echo "OK — Mission Control 2.0 läuft auf :9001 (User-Dienst, sudo-frei)."

deploy/hermes-webui.service

@@ -0,0 +1,27 @@
+# systemd-USER-Unit für das standalone Hermes-WebUI (nesquena/hermes-webui).
+# Eigene Oberfläche des Agenten (Chat/Sessions/Workspace/Cron/Skills/Memory).
+# An 0.0.0.0:8787 gebunden, damit der Windows-PC im LAN direkt zugreifen kann
+# → Passwort-Schutz aktivieren (HERMES_WEBUI_PASSWORD)!
+# Ablage: ~/.config/systemd/user/hermes-webui.service ; dann:
+#   systemctl --user enable --now hermes-webui
+#   loginctl enable-linger hitonabi   # läuft auch ohne aktive Session
+
+[Unit]
+Description=Hermes WebUI (standalone)
+After=network-online.target
+Wants=network-online.target
+
+[Service]
+Type=simple
+WorkingDirectory=%h/hermes-webui
+# Start über das mitgelieferte Control-Skript (siehe docs/HERMES_SETUP.md).
+ExecStart=%h/hermes-webui/ctl.sh start --foreground
+Environment=HERMES_WEBUI_HOST=0.0.0.0
+Environment=HERMES_WEBUI_PORT=8787
+Environment=HERMES_HOME=%h/.hermes
+# Environment=HERMES_WEBUI_PASSWORD=...   # in ~/.config/environment.d/ setzen, NICHT hier committen
+Restart=on-failure
+RestartSec=3
+
+[Install]
+WantedBy=default.target

deploy/mission-control-2.service

@@ -0,0 +1,29 @@
+# systemd-USER-Unit für Mission Control 2.0 (PARALLEL zu v1, Port 9001).
+# Läuft sudo-frei aus dem Home-Verzeichnis (Nordstern: kein Passwort/sudo).
+# Ablage: ~/.config/systemd/user/mission-control-2.service ; dann:
+#   systemctl --user daemon-reload
+#   systemctl --user enable --now mission-control-2
+#   loginctl enable-linger hitonabi   # läuft auch ohne aktive Session
+
+[Unit]
+Description=Mission Control 2.0 (Cockpit)
+After=network-online.target
+Wants=network-online.target
+
+[Service]
+Type=simple
+WorkingDirectory=%h/mission-control-v2/backend
+ExecStart=%h/mission-control-v2/backend/.venv/bin/python -m uvicorn app:app --host 0.0.0.0 --port 9001
+Environment=MC_PORT=9001
+Environment=MC_LLAMA_SWAP_URL=http://127.0.0.1:8080
+Environment=MC_CONFIG_PATH=/etc/llama-swap/config.yaml
+Environment=MC_MODELS_DIR=/srv/models
+# Geteiltes Gedächtnis = die bestehende v1-DB (Kontinuität bis/über Cutover).
+Environment=MC_MEMORY_DB=/srv/models/mission-control-memory.db
+Environment=MC_ENGINE_UPDATE_CMD=/usr/local/bin/update-llamacpp
+Restart=on-failure
+
+RestartSec=3
+
+[Install]
+WantedBy=default.target

docs/BEDIENUNG.md

@@ -0,0 +1,54 @@
+# Mission Control 2.0 — Bedienung (kurz & klartext)
+
+**Öffnen:** `http://192.168.178.151:9001` (vom Windows-PC im LAN). Dark/Light-Umschalter oben rechts,
+**Cmd/Strg+K** springt zu jedem Bereich.
+
+> Im Alltag fasst du MC kaum an: `model: auto` + Auto-Swap laden Modelle selbst. Du öffnest es, um ein
+> Modell zu installieren/tauschen, die Auslastung zu prüfen, Gedächtnis zu pflegen oder ein Tool zu verbinden.
+
+## Die 6 Bereiche
+- **Modelle & Routing** — installierte Modelle (mit Fähigkeiten) + neue finden/laden.
+- **Routing** — zeigt `model: auto` (schnell ↔ schwer) + Schwelle.
+- **System** — Live CPU/RAM/GPU/GTT/Temp, Dienste-Status, **Backup**, Updates/Restart (Wartung).
+- **Gedächtnis** — geteilte Fakten/Regeln, die ALLE Tools (Hermes, IDEs) via MCP lesen/schreiben.
+- **Verbinden** — fertige Konfig-Snippets für deine IDEs (zeigen auf den Gateway).
+- **Hermes** — Agent-Status + „Hermes öffnen".
+
+## Modell installieren
+**Tab „Modelle & Routing" → „Modelle finden":**
+- **Kuratiert:** auf einer Empfehlungs-Karte „Installieren" klicken (⭐ = beste Wahl je Kategorie).
+- **Eigenes (HuggingFace):** oben **HF-URL oder `org/repo`** einfügen → „Quants laden" → Quant wählen →
+  „Installieren". Oder die **Suchleiste** nutzen → Treffer anklicken → Quant → Installieren.
+- Der Download läuft als Job mit **Fortschrittsbalken** oben; llama-swap pflegt das Modell automatisch ein.
+
+## LLM tauschen (z.B. anderes „fast"-Hirn)
+„Modelle & Routing" → **„Installiert"**: in der Zeile des Modells im **Rollen-Dropdown**
+`fast` (bzw. `heavy`/`coder`/`vision`/`scout`) wählen → der Alias wandert auf dieses Modell.
+- `model: auto` nutzt ab sofort dieses Modell als schnelles/schweres Hirn — für Hermes **und** Vibe Coding.
+- **Kontext** ändern: auf die Kontext-Zahl (✎) klicken. **Entfernen:** 🗑 (GGUF-Datei bleibt erhalten).
+- „Auto-Swap" = llama-swap lädt automatisch, was gerade angefragt wird; du musst nichts laden/entladen.
+
+## IDE verbinden (Vibe Coding am eigenen PC)
+„Verbinden" → Tool wählen (Cline/OpenCode/Zed/Continue) → Snippet kopieren. Zeigt auf
+`http://192.168.178.151:9001/v1`, Modell **`auto`**. Memory-MCP-Snippet separat einfügen → geteiltes Gedächtnis.
+
+## Gedächtnis pflegen
+„Gedächtnis": Fakt/Regel hinzufügen (Kategorie wählen), suchen/filtern, **🧹 Aufräumen** entfernt Dubletten.
+Das ist die geteilte „Verfassung" für alle Tools.
+
+## Wartung & Backup
+„System" → **Wartung & Updates**: Badge (offene OS-Pakete / Engine / Modell-Upgrades), Buttons
+**OS aktualisieren · Engine aktualisieren · Engine neu starten · Reboot**, Modell-Upgrade-Vorschläge
+(1-Klick), **Backup jetzt** (Gedächtnis-DB + Configs), Dienste-Health.
+
+`Engine neu starten`, Logs & Modell-Upgrades laufen sofort (NOPASSWD vorhanden). **OS-Update + Reboot**
+brauchen einmalig erweiterte sudoers — `sudo visudo`, ergänze:
+```
+hitonabi ALL=(root) NOPASSWD: /usr/bin/apt-get, /usr/sbin/reboot
+```
+(Engine-Update: `MC_ENGINE_UPDATE_CMD` in der mc2-Unit setzen — Befehl, der /opt/llamacpp aktualisiert.)
+Danach ist die komplette Wartung klicki-bunti, ohne Passwort.
+
+## Wenn etwas hakt
+- Modell antwortet nicht → „System" → Dienste-Health (Engine online?) + Engine-Logs-Link (llama-swap `/ui`).
+- Hermes langsam/komisch → im Hermes-WebUI **neuen Chat** starten (frische Session); Details: `docs/CUTOVER.md`.

docs/CUTOVER.md

@@ -0,0 +1,45 @@
+# Cutover — Stand & Anleitung
+
+## Was auf der Box LÄUFT (verifiziert)
+- **MC2** auf `:9001` (sudo-freier User-Dienst, `~/mission-control-v2`). Update: `deploy/deploy.sh`.
+- **Modelle/Rollen:** `fast` = Qwen3.6-35B-A3B, `heavy` = Qwen3.5-122B-A10B, `coder` = Qwen3-Coder-30B,
+  `vision` = Qwen3-VL-8B, `scout` = Qwen3-8B, `hermes` = Hermes-4-14B (immer warm, ttl 99999). Alle
+  tool-fähig (`--jinja` wo nötig). Legacy `manager`/`reviewer` entfernt.
+- **Gateway (eingebaut, `:9001/v1`, OpenAI-kompatibel):** `model: auto` → kurz/Standard = `fast`,
+  lang/komplex = `heavy`. End-to-End verifiziert.
+- **Hermes:** **eigenes festes Hirn = Hermes-4-14B** (`model.model: hermes`) + **Delegation an `heavy`**.
+  `model:auto` ist NUR für Vibe Coding/IDEs, nicht Hermes. MCP verdrahtet: `mission-control-memory` +
+  `mission-control-stack`. Verifiziert: „bist du da?" → 3s, sauber, kein Thrash.
+- **Gedächtnis vereinheitlicht:** MC2 nutzt die bestehende DB (`mission-control-memory.db`) — geteilte
+  „Verfassung" für Cockpit, Hermes, IDEs.
+- **Cockpit-Features:** HF-Link/Suche-Install (W2), Rollen/ctx/löschen-UX (W3), Wartung (W8: OS/Engine-
+  Update, Restart, Reboot, Logs, dyn. Modell-Upgrades), Bedien-Anleitung (BEDIENUNG.md + Hilfe-Link).
+
+## Thrash-Fix (war der „Hermes ist dumm"-Grund)
+Ursache war NICHT das Modell/die Session, sondern **kaputte/Cloud-Tools im Toolset** (browser ohne Chrome
+→ Loop, vision auf Text, natives memory falsch aufgerufen). Global abgeschaltet über
+`agent.disabled_toolsets` in `~/.hermes/config.yaml` (Achtung: `hermes tools disable` greift nur cli,
+NICHT den api_server). Natives memory zusätzlich aus (`memory.memory_enabled:false`); geteiltes
+Gedächtnis bleibt via MCP. Behaltene Tools: web/terminal/file/code_execution/skills/todo/session_search/
+clarify/delegation/cronjob + 2 MCP.
+
+## Cutover-Schritte
+1. v2 läuft bereits auf `:9001` parallel — alles dort testen: `http://192.168.178.151:9001`.
+2. Vibe-Coding-Tools auf den Gateway zeigen (Verbinden-Tab → `:9001/v1`, `model: auto`).
+3. **v1 stilllegen** — bereits erledigt: `hermes-dashboard` (:9119) disabled (killte 4 v1-MCP-Zombies).
+   **Noch offen (braucht dein sudo, NOPASSWD deckt nur `restart`):**
+   ```
+   sudo systemctl disable --now mission-control      # v1-Cockpit :9000 aus
+   ```
+   `llama-swap` (System) + `hermes-gateway` (User) bleiben — die nutzt v2 weiter.
+4. Optional v2 auf den „Haupt"-Port legen — `MC_PORT` in der mc2-Unit.
+5. Backup vorher: Cockpit → System → „Backup jetzt".
+
+## Offene Tuning-/Setup-Punkte (kein Blocker)
+1. **nesquena hermes-webui** (:8787) installieren (Plan Block C) → „Hermes öffnen" zeigt darauf statt :9119.
+2. **Ko-Residenz** `hermes`+`fast` (swap:false, Plan Block E) — GTT beobachten, bei OOM-Nähe zurück.
+3. **SSH→Windows** (voller PC-Zugriff): OpenSSH-Server am Windows-PC + Key `id_ed25519_hermes_agent`.
+4. **sudoers erweitern** (`apt-get`, `reboot`) → OS-Update/Reboot klicki-bunti (Zeilen in BEDIENUNG.md).
+5. **Delegation an heavy** ist konfiguriert; triggert modell-diskretionär bei echt harten Teilaufgaben.
+
+> v1 bleibt bis zum `disable` lauffähig — Cutover ist reversibel (`sudo systemctl enable --now mission-control`).

docs/HERMES_SETUP.md

@@ -0,0 +1,82 @@
+# Hermes-Schicht — Box-Runbook
+
+> Diese Schritte laufen **auf der Bosgame** (`192.168.178.151`, User `hitonabi`).
+> MC betreibt Hermes nicht — es zeigt nur Status + verlinkt das WebUI. Hier wird die
+> eigentliche **volle Verdrahtung** gemacht (das war in v1 der „Hermes ist dumm"-Grund).
+
+## Reihenfolge der Dienste
+`llama-swap (:8080)` → **builtin Gateway (`:9001/v1`, Teil von MC2)** → `hermes-gateway (:8642)` →
+`hermes-webui (:8787, nesquena)`
+
+## 1. Gateway = builtin (kein LiteLLM)
+LiteLLM scheitert auf Python 3.14 (uvloop/orjson). MC2 bringt einen **eingebauten** OpenAI-kompatiblen
+Gateway auf `:9001/v1` mit: `model: auto` (kurz→`fast`, komplex→`heavy`) + explizite Aliase
+(`fast`/`heavy`/`coder`/`vision`/`hermes`). Verifizieren:
+```bash
+curl -s http://127.0.0.1:9001/v1/models
+```
+
+## 2. Engine: Rollen (llama-swap)
+Aliase sauber: `fast` (Qwen3.6-35B-A3B), `heavy` (Qwen3.5-122B-A10B), `coder`, `vision`, `scout`,
+`hermes` (Hermes-4-14B, `ttl 99999` = immer warm). Verwaltung im Cockpit (Modelle & Routing).
+**Ko-Residenz** (optional): Gruppe `swap:false` für `hermes`+`fast` → beide warm; `heavy`/`vision`
+on-demand. GTT beobachten (~124 GB Limit).
+
+## 3. hermes-webui installieren (nesquena, standalone)
+```bash
+cd ~ && git clone https://github.com/nesquena/hermes-webui && cd hermes-webui
+python3 bootstrap.py          # erkennt hermes-agent, baut venv, installiert Deps
+mkdir -p ~/.config/environment.d
+echo 'HERMES_WEBUI_PASSWORD=<dein-passwort>' > ~/.config/environment.d/hermes-webui.conf
+# Unit deploy/hermes-webui.service → ~/.config/systemd/user/ (HOST=0.0.0.0, PORT=8787)
+systemctl --user enable --now hermes-webui
+loginctl enable-linger hitonabi
+```
+Zugriff vom Windows-PC: `http://192.168.178.151:8787` (mit Passwort). MC2-Unit
+`HERMES_WEBUI_URL=http://192.168.178.151:8787` setzen → „Hermes öffnen" zeigt darauf.
+**Danach das alte offizielle Dashboard stilllegen** (eine WebUI):
+`systemctl --user disable --now hermes-dashboard` (:9119).
+
+## 4. Hermes-Hirn = dediziertes Hermes-4-14B + Delegation (NICHT model:auto)
+In `~/.hermes/config.yaml`:
+```yaml
+model:
+  default: Hermes-4-14B
+  provider: custom
+  base_url: http://127.0.0.1:9001/v1
+  api_key: local
+  model: hermes              # Hermes' eigenes Hirn (Alias→Hermes-4-14B), NICHT 'auto'
+delegation:
+  model: heavy               # harte Teilaufgaben → Qwen3.5-122B
+  provider: custom
+  base_url: http://127.0.0.1:9001/v1
+  api_key: local
+  orchestrator_enabled: true
+  subagent_auto_approve: true
+```
+`model:auto` bleibt ausschließlich Gateway-Funktion für Vibe Coding/IDEs.
+
+## 5. Tools/MCP verdrahten — UND kaputte Tools abschalten (Thrash-Fix!)
+- **Kaputte/Cloud-Tools global abschalten** (sonst Endlos-Loops, siehe Memory `hermes-thrash-rootcause-fix`):
+  ```yaml
+  agent:
+    disabled_toolsets: [browser, vision, computer_use, image_gen, tts, video, video_gen, memory]
+  memory:
+    memory_enabled: false
+    user_profile_enabled: false
+  ```
+  ⚠️ `hermes tools disable <x>` wirkt nur für die cli-Plattform, **nicht den api_server** — nutze
+  `agent.disabled_toolsets` (gilt für ALLE Plattformen).
+- **Behalten:** terminal/shell, file, code_execution, skills, todo, session_search, clarify,
+  delegation, cronjob, web. `approvals: auto` (rein lokal).
+- **MCP-Server** (`mcp_servers` in config) — laufen über die v2-venv (hat das `mcp`-Modul nach pip install):
+  - geteiltes Gedächtnis: `~/mission-control-v2/backend/.venv/bin/python ~/mission-control-v2/mcp/mcp_memory.py` (Env `MC_URL=http://127.0.0.1:9001`)
+  - Stack-Management: `~/mission-control-v2/backend/.venv/bin/python ~/mission-control-v2/mcp/mcp_mc.py` (Env `MC_URL=http://127.0.0.1:9001`)
+- **SSH→Windows-PC** (voller Zugriff): OpenSSH-Server auf Windows aktiv + Key
+  `~/.ssh/id_ed25519_hermes_agent` autorisiert; Hermes nutzt sein terminal-Tool für `ssh TobisPC@<win-ip>`.
+
+## 6. Verifikation
+- `curl :8642/v1/chat/completions` „bist du da?" → kurze Antwort in wenigen Sekunden, **kein** Tool-Loop
+  im `journalctl --user -u hermes-gateway`; llama-swap `/running` zeigt `Hermes-4-14B`.
+- WebUI öffnet vom Windows-PC, Chat antwortet.
+- Hermes kann via `mcp_mc` Modelle listen/Routing ändern; erreicht (nach §5-SSH) den Windows-PC.

docs/STATUS.md

@@ -0,0 +1,57 @@
+# Mission Control 2.0 — Status & Resume-Guide
+
+> So machst du jederzeit nahtlos weiter. Der vollständige Architektur-Plan liegt in
+> `C:\Users\TobisPC\.claude\plans\piped-cuddling-sloth.md` (genehmigt).
+
+## Wo das Projekt lebt
+- **Code:** `F:\Coding Stuff\mission-control-2` (Windows-Dev-PC) + Gitea-Remote
+  `https://git.tobisniceshomelab.ddnsfree.com/Hitonabi/mission-control-v2` (Branch `main`).
+- **v1** (`F:\Coding Stuff\mission-control`) wird abgelöst (Cutover läuft, s.u.).
+- **Box** (Bosgame, `192.168.178.151`): **MC2 LIVE auf :9001** als sudo-freier systemd-USER-Dienst
+  (`~/mission-control-v2`, Update via `deploy/deploy.sh`).
+
+## Gateway = builtin (NICHT LiteLLM)
+LiteLLM verlangt Python <3.14; die Box hat nur 3.14 (uvloop+orjson scheitern). Der **eingebaute
+Gateway** (`:9001/v1`, OpenAI-kompatibel) liefert `model:auto` (kurz→`fast`, komplex→`heavy`) +
+Streaming und ist E2E verifiziert. Vertrag (OpenAI-API) bleibt austauschbar.
+
+## Phasen-Fortschritt
+- [x] **Phase 0 — Gerüst:** FastAPI + React/shadcn-Shell (Cmd+K, Dark, PWA). Live auf Box.
+- [x] **Phase 1 — Engine + Routing:** Compute (fit/caps/sources), Discover (live HF), Engine-Write
+      (register + groups), **builtin Gateway** `model:auto`, Modelle&Routing-UI. Box-verifiziert.
+- [x] **Phase 2 — System/OS + Connect:** Metriken, Dienste, Self-Update, Connect-Snippets → Gateway.
+- [x] **Phase 3 — Memory + MCP:** Memory-UI, `mcp_memory.py` + `mcp_mc.py` (Stack-Management).
+- [x] **Phase 4 — Hermes-Schicht:** Agent-Status + AgentView; **Box: Hermes verdrahtet** (eigenes Hirn,
+      MCP memory+stack). hermes-webui (nesquena) = Block C offen.
+- [x] **Phase 5 — Betrieb/Politur:** Backup, Services-Health, Observability-Links, Theme-Toggle.
+- [x] **W1–W8** (Audit-Arbeitspaket): Thrash-Fix, HF-Install, Rollen-UX, BEDIENUNG.md, Wartung. ✅
+- [~] **Phase 6 — Cutover:** läuft (s.u.). v1-Dashboard+Zombies weg; v1 :9000 Stop offen (User-sudo).
+
+## Hermes-Hirn (Entscheidung 2026-06-25)
+Hermes hat ein **eigenes festes Hirn = Hermes-4-14B** (`model.model: hermes`, ttl 99999 = immer warm)
++ **interne Delegation an `heavy`** (Qwen3.5-122B) für harte Teilaufgaben. **`model:auto` ist NUR
+Gateway/Vibe-Coding**, nicht Hermes. Verifiziert: „bist du da?" → **3s, sauber, kein Thrash**.
+
+## Box-Stand (Session 2026-06-25)
+- **8 Modelle**, Rollen sauber: `fast` (Qwen3.6-35B-A3B), `heavy` (Qwen3.5-122B-A10B), `coder`
+  (Qwen3-Coder-30B), `vision` (Qwen3-VL-8B), `scout` (Qwen3-8B), `hermes` (Hermes-4-14B). Legacy
+  `manager`/`reviewer`-Aliase entfernt (Modelle bleiben per Realname ladbar).
+- **Thrash behoben** (war NICHT die Session): kaputte Tools global via `agent.disabled_toolsets`
+  abgeschaltet (browser/vision/computer_use/image_gen/tts/video*/memory). Details: Memory
+  `hermes-thrash-rootcause-fix`. **`hermes tools disable` greift NICHT am api_server** — nur die config.
+- **Cutover teilweise:** `hermes-dashboard` (:9119) disabled (killte 4 v1-MCP-Zombies);
+  **v1 `mission-control.service` (:9000) läuft noch** → `sudo systemctl disable --now mission-control`.
+- MCP nutzt `/opt/mission-control/.venv/bin/python` (hat `mcp`-Modul) für v2-Skripte → /opt-Dir bleibt.
+
+## Nächste Schritte (siehe Plan „Nächste Schritte" + docs/CUTOVER.md)
+- **Block C:** nesquena hermes-webui (:8787) installieren → „Hermes öffnen" zeigt darauf.
+- **Block E:** Ko-Residenz `hermes`+`fast` (swap:false) testen, GTT beobachten.
+- **User-sudo:** v1 :9000 stoppen; sudoers für apt-get/reboot erweitern (OS-Update/Reboot).
+- Offen/user-seitig: SSH→Windows (OpenSSH am PC), v1-Passwort-Hygiene (Git-Historie).
+
+## Lokal entwickeln/verifizieren
+```bash
+cd backend && .venv/Scripts/python -m uvicorn app:app --port 9000   # Backend
+cd frontend && npm run dev                                          # http://localhost:5173
+cd frontend && npm run build                                        # Prod-Build (committet)
+```

frontend/dist/assets/JobsBar-CetMgfaw.js

@@ -1 +0,0 @@
-import{u,ah as m,k as x,j as s,y as n,ai as b,b as p,n as f,q as h}from"./index-oOOd5nTt.js";function y(){const d=u(),{data:t=[]}=m(),{showAlert:l,dialogElement:o}=x();async function i(e){try{await f(`/api/jobs/${e}/cancel`,{method:"POST"}),d.invalidateQueries({queryKey:h.jobs})}catch(c){l("Fehler",c.message)}}const a=t.filter(e=>e.state==="running"||e.state==="queued"),r=t.filter(e=>e.state!=="running"&&e.state!=="queued").slice(-3);return a.length===0&&r.length===0?null:s.jsxs("div",{className:"space-y-3 mc-card p-4",children:[s.jsx("div",{className:"text-[11px] font-semibold text-muted-foreground uppercase tracking-wider",children:"Aktive Downloads"}),a.map(e=>s.jsxs("div",{className:"space-y-1.5 p-3 rounded-xl bg-background/20 border border-border/40",children:[s.jsxs("div",{className:"flex justify-between items-center text-xs",children:[s.jsx("span",{className:"font-semibold truncate max-w-[250px]",children:e.label}),s.jsxs("div",{className:"flex items-center gap-3",children:[s.jsxs("span",{className:"text-muted-foreground font-mono",children:[e.progress??0,"% • ",n(e.done_bytes),"/",n(e.total_bytes),e.eta_s?` • ETA ${b(e.eta_s)}`:""]}),s.jsx("button",{onClick:()=>i(e.id),className:"text-[10px] text-red-400 hover:text-red-300 font-semibold border border-red-500/25 bg-red-500/5 px-2 py-0.5 rounded transition-all cursor-pointer",children:"Abbrechen"})]})]}),s.jsx("div",{className:"h-1.5 overflow-hidden rounded-full bg-muted",children:s.jsx("div",{className:"h-full rounded-full bg-primary transition-all duration-500",style:{width:`${e.progress??0}%`}})})]},e.id)),r.map(e=>s.jsxs("div",{className:"flex justify-between items-center text-xs text-muted-foreground px-1",children:[s.jsx("span",{className:"truncate",children:e.label}),s.jsx("span",{className:p("font-semibold text-[10px] px-1.5 py-0.5 rounded uppercase font-mono",e.state==="done"?"bg-emerald-500/10 text-emerald-400":"bg-amber-500/10 text-amber-400"),children:e.state})]},e.id)),o]})}export{y as J};

frontend/dist/assets/KonsoleView-Copf1e0n.js

@@ -1 +0,0 @@
-import{I as b,u as f,K as h,r as d,j as e,b as c,J as g,T as p,R as j,Q as N,n as v,U as w,q as x}from"./index-oOOd5nTt.js";function y(){const{data:s}=b(),m=f(),r=s!=null&&s.box_console_url?h(s.box_console_url):void 0,a=s==null?void 0:s.box_console_reachable,[l,o]=d.useState(!1),[i,n]=d.useState("");async function u(){o(!0),n("");try{const t=await v("/api/maintenance/restart",{method:"POST",body:JSON.stringify({service:"box-console"})});n(t.ok?"Neu gestartet — einen Moment, dann lädt das Terminal.":`Fehlgeschlagen: ${t.err||"Unbekannter Fehler"}`),w(m,x.agentStatus,x.services)}catch(t){n(`Fehlgeschlagen: ${(t==null?void 0:t.message)||t}`)}finally{o(!1)}}return e.jsxs("div",{className:"flex h-full flex-col gap-4",children:[e.jsxs("div",{className:"flex flex-wrap items-end justify-between gap-3",children:[e.jsxs("div",{children:[e.jsx("h1",{className:"bg-gradient-to-r from-foreground via-foreground to-primary bg-clip-text font-space text-2xl font-bold tracking-tight text-transparent",children:"Konsole"}),e.jsx("p",{className:"flex items-center gap-2 text-sm text-muted-foreground",children:"Direkte Shell auf der Box — wie ein SSH-Fenster, mitten im Browser."})]}),e.jsxs("div",{className:"flex items-center gap-3",children:[e.jsxs("span",{className:"flex items-center gap-1.5 text-[11px] font-medium text-muted-foreground",children:[e.jsx("span",{className:c("h-2 w-2 rounded-full",a?"bg-emerald-500 animate-pulse":"bg-amber-500")}),a?"online":"offline"]}),r&&e.jsxs("a",{href:r,target:"_blank",rel:"noopener",className:"flex h-8 items-center gap-1.5 rounded-lg border border-border/60 bg-background/20 px-3 text-xs font-semibold text-muted-foreground transition-all hover:border-primary/50 hover:text-foreground",children:[e.jsx(g,{className:"h-3.5 w-3.5"})," In neuem Tab"]})]})]}),r?e.jsxs("div",{className:"relative min-h-[58vh] flex-1 overflow-hidden rounded-2xl border border-border/60 bg-black/50 shadow-lg shadow-black/25",children:[a===!1&&e.jsxs("div",{className:"absolute inset-0 z-10 flex flex-col items-center justify-center gap-3 bg-black/70 text-center",children:[e.jsx(p,{className:"h-8 w-8 text-amber-400"}),e.jsx("div",{className:"text-sm font-semibold text-amber-300",children:"Konsole nicht erreichbar"}),e.jsxs("p",{className:"max-w-sm text-[11px] leading-normal text-muted-foreground",children:["Der Terminal-Dienst (",e.jsx("code",{className:"font-mono text-primary",children:"box-console"}),") läuft gerade nicht."]}),e.jsxs("button",{onClick:u,disabled:l,className:"flex h-9 items-center gap-1.5 rounded-lg border border-amber-500/40 bg-amber-500/10 px-4 text-[11px] font-bold uppercase tracking-wide text-amber-300 transition-all hover:bg-amber-500/20 cursor-pointer disabled:opacity-50",children:[e.jsx(j,{className:c("h-3.5 w-3.5",l&&"animate-spin")})," Dienst neu starten"]}),i&&e.jsx("p",{className:"max-w-sm text-[11px] text-muted-foreground",children:i})]}),e.jsx("iframe",{src:r,title:"Box-Konsole",className:"h-full w-full border-0",style:{minHeight:"58vh"}})]}):e.jsxs("div",{className:"flex min-h-[58vh] flex-1 items-center justify-center rounded-2xl border border-border/60 bg-background/20 text-xs text-muted-foreground",children:[e.jsx(N,{className:"mr-2 h-4 w-4"})," Lade Konsole…"]})]})}export{y as KonsoleView};

frontend/dist/assets/SectionLabel-DqgIvFso.js

@@ -1,6 +0,0 @@
-import{c as s,j as e}from"./index-oOOd5nTt.js";/**
- * @license lucide-react v0.460.0 - ISC
- *
- * This source code is licensed under the ISC license.
- * See the LICENSE file in the root directory of this source tree.
- */const r=s("Hammer",[["path",{d:"m15 12-8.373 8.373a1 1 0 1 1-3-3L12 9",key:"eefl8a"}],["path",{d:"m18 15 4-4",key:"16gjal"}],["path",{d:"m21.5 11.5-1.914-1.914A2 2 0 0 1 19 8.172V7l-2.26-2.26a6 6 0 0 0-4.202-1.756L9 2.96l.92.82A6.18 6.18 0 0 1 12 8.4V10l2 2h1.172a2 2 0 0 1 1.414.586L18.5 14.5",key:"b7pghm"}]]);function c({icon:a,children:t}){return e.jsxs("p",{className:"flex items-center gap-1.5 text-[11px] font-semibold uppercase tracking-wider text-muted-foreground/60",children:[e.jsx(a,{className:"h-3.5 w-3.5"})," ",t]})}export{r as H,c as S};

frontend/dist/assets/SkillsView-DuQGfeBJ.js

@@ -1,6 +0,0 @@
-var M=r=>{throw TypeError(r)};var O=(r,e,t)=>e.has(r)||M("Cannot "+t);var a=(r,e,t)=>(O(r,e,"read from private field"),t?t.call(r):e.get(r)),y=(r,e,t)=>e.has(r)?M("Cannot add the same private member more than once"):e instanceof WeakSet?e.add(r):e.set(r,t),v=(r,e,t,n)=>(O(r,e,"write to private field"),n?n.call(r,t):e.set(r,t),t),j=(r,e,t)=>(O(r,e,"access private method"),t);import{a9 as B,aa as F,ab as E,ac as I,ad as P,u as A,r as f,ae as J,af as Q,c as T,ag as U,j as s,G as D,T as H,b as K,L,M as G,q as V,n as R}from"./index-oOOd5nTt.js";import{J as _}from"./JobsBar-CetMgfaw.js";var c,g,o,h,m,w,C,q,z=(q=class extends B{constructor(e,t){super();y(this,m);y(this,c);y(this,g);y(this,o);y(this,h);v(this,c,e),this.setOptions(t),this.bindMethods(),j(this,m,w).call(this)}bindMethods(){this.mutate=this.mutate.bind(this),this.reset=this.reset.bind(this)}setOptions(e){var n;const t=this.options;this.options=a(this,c).defaultMutationOptions(e),F(this.options,t)||a(this,c).getMutationCache().notify({type:"observerOptionsUpdated",mutation:a(this,o),observer:this}),t!=null&&t.mutationKey&&this.options.mutationKey&&E(t.mutationKey)!==E(this.options.mutationKey)?this.reset():((n=a(this,o))==null?void 0:n.state.status)==="pending"&&a(this,o).setOptions(this.options)}onUnsubscribe(){var e;this.hasListeners()||(e=a(this,o))==null||e.removeObserver(this)}onMutationUpdate(e){j(this,m,w).call(this),j(this,m,C).call(this,e)}getCurrentResult(){return a(this,g)}reset(){var e;(e=a(this,o))==null||e.removeObserver(this),v(this,o,void 0),j(this,m,w).call(this),j(this,m,C).call(this)}mutate(e,t){var n;return v(this,h,t),(n=a(this,o))==null||n.removeObserver(this),v(this,o,a(this,c).getMutationCache().build(a(this,c),this.options)),a(this,o).addObserver(this),a(this,o).execute(e)}},c=new WeakMap,g=new WeakMap,o=new WeakMap,h=new WeakMap,m=new WeakSet,w=function(){var t;const e=((t=a(this,o))==null?void 0:t.state)??I();v(this,g,{...e,isPending:e.status==="pending",isSuccess:e.status==="success",isError:e.status==="error",isIdle:e.status==="idle",mutate:this.mutate,reset:this.reset})},C=function(e){P.batch(()=>{var t,n,l,x,d,p,k,i;if(a(this,h)&&this.hasListeners()){const u=a(this,g).variables,N=a(this,g).context,S={client:a(this,c),meta:this.options.meta,mutationKey:this.options.mutationKey};if((e==null?void 0:e.type)==="success"){try{(n=(t=a(this,h)).onSuccess)==null||n.call(t,e.data,u,N,S)}catch(b){Promise.reject(b)}try{(x=(l=a(this,h)).onSettled)==null||x.call(l,e.data,null,u,N,S)}catch(b){Promise.reject(b)}}else if((e==null?void 0:e.type)==="error"){try{(p=(d=a(this,h)).onError)==null||p.call(d,e.error,u,N,S)}catch(b){Promise.reject(b)}try{(i=(k=a(this,h)).onSettled)==null||i.call(k,void 0,e.error,u,N,S)}catch(b){Promise.reject(b)}}}this.listeners.forEach(u=>{u(a(this,g))})})},q);function W(r,e){const t=A(),[n]=f.useState(()=>new z(t,r));f.useEffect(()=>{n.setOptions(r)},[n,r]);const l=f.useSyncExternalStore(f.useCallback(d=>n.subscribe(P.batchCalls(d)),[n]),()=>n.getCurrentResult(),()=>n.getCurrentResult()),x=f.useCallback((d,p)=>{n.mutate(d,p).catch(J)},[n]);if(l.error&&Q(n.options.throwOnError,[l.error]))throw l.error;return{...l,mutate:x,mutateAsync:l.mutate}}/**
- * @license lucide-react v0.460.0 - ISC
- *
- * This source code is licensed under the ISC license.
- * See the LICENSE file in the root directory of this source tree.
- */const X=T("Play",[["polygon",{points:"6 3 20 12 6 21 6 3",key:"1oa8hb"}]]);function ee(){const r=A(),{data:e,isLoading:t,isError:n}=U({queryKey:["skills-list"],queryFn:()=>R("/api/skills"),refetchInterval:5e3}),[l,x]=f.useState(null),[d,p]=f.useState(null),k=W({mutationFn:i=>R("/api/skills/run",{method:"POST",body:JSON.stringify({skill_name:i})}),onMutate:i=>{x(i),p(null)},onSuccess:(i,u)=>{x(null),p({name:u,ok:i.ok,msg:i.msg||i.err||"Unbekannter Fehler"}),r.invalidateQueries({queryKey:V.jobs}),r.invalidateQueries({queryKey:["skills-list"]})},onError:(i,u)=>{x(null),p({name:u,ok:!1,msg:String(i)})}});return s.jsxs("div",{className:"space-y-6",children:[s.jsx("div",{className:"flex flex-col sm:flex-row justify-between sm:items-center gap-4",children:s.jsxs("div",{children:[s.jsx("h1",{className:"text-2xl font-space font-bold tracking-tight bg-gradient-to-r from-foreground via-foreground to-primary bg-clip-text text-transparent",children:"Skills & Jobs"}),s.jsx("p",{className:"text-sm text-muted-foreground",children:"Löst autonome Agent-Skills manuell auf der Box aus. Die Ausführung erfolgt im Hintergrund durch Hermes."})]})}),s.jsx(_,{}),d&&s.jsxs("div",{className:K("p-4 rounded-lg border flex gap-3 items-start",d.ok?"bg-emerald-500/10 border-emerald-500/20 text-emerald-600 dark:text-emerald-400":"bg-red-500/10 border-red-500/20 text-red-600 dark:text-red-400"),children:[d.ok?s.jsx(D,{className:"h-5 w-5 mt-0.5 shrink-0"}):s.jsx(H,{className:"h-5 w-5 mt-0.5 shrink-0"}),s.jsxs("div",{children:[s.jsx("div",{className:"font-semibold text-sm",children:d.name}),s.jsx("div",{className:"text-sm opacity-90",children:d.msg})]})]}),t&&s.jsx("div",{className:"flex h-32 items-center justify-center",children:s.jsx(L,{className:"h-6 w-6 animate-spin text-muted-foreground"})}),n&&s.jsx("div",{className:"text-red-500 p-4 mc-card text-sm",children:"Fehler beim Laden der Skills. Ist das Backend erreichbar?"}),(e==null?void 0:e.skills)&&s.jsxs("div",{className:"grid grid-cols-1 md:grid-cols-2 xl:grid-cols-3 gap-4",children:[e.skills.map(i=>s.jsxs("div",{className:"mc-card p-5 flex flex-col hover:border-primary/40 transition-colors group",children:[s.jsxs("div",{className:"flex items-start justify-between gap-3 mb-2",children:[s.jsxs("div",{className:"flex items-center gap-2 font-semibold text-base font-space",children:[s.jsx(G,{className:"h-5 w-5 text-primary/80"}),i.name]}),s.jsxs("button",{onClick:()=>k.mutate(i.name),disabled:l===i.name||i.running||k.isPending,className:K("shrink-0 h-8 px-3 rounded-md text-xs font-semibold uppercase tracking-wider flex items-center gap-1.5 transition-all cursor-pointer",l===i.name||i.running?"bg-sky-500/10 border border-sky-500/40 text-sky-400 cursor-not-allowed":"bg-primary/10 text-primary hover:bg-primary hover:text-primary-foreground group-hover:shadow-md group-hover:shadow-primary/20"),children:[l===i.name||i.running?s.jsx(L,{className:"h-3.5 w-3.5 animate-spin"}):s.jsx(X,{className:"h-3.5 w-3.5"}),l===i.name||i.running?"Läuft …":"Starten"]})]}),s.jsx("div",{className:"text-sm text-muted-foreground flex-1",children:i.description})]},i.name)),e.skills.length===0&&s.jsxs("div",{className:"col-span-full p-8 text-center text-muted-foreground mc-card border-dashed border-2",children:["Keine Skills im Ordner ",s.jsx("code",{className:"text-xs text-foreground bg-muted px-1.5 py-0.5 rounded",children:"deploy/skills"})," gefunden."]})]})]})}export{ee as SkillsView};

frontend/dist/assets/chevron-down-Dpr3yWU0.js

@@ -1,6 +0,0 @@
-import{c as o}from"./index-oOOd5nTt.js";/**
- * @license lucide-react v0.460.0 - ISC
- *
- * This source code is licensed under the ISC license.
- * See the LICENSE file in the root directory of this source tree.
- */const n=o("ChevronDown",[["path",{d:"m6 9 6 6 6-6",key:"qrunsl"}]]);export{n as C};

frontend/dist/assets/code-xml-CJt1Bh8a.js

@@ -1,6 +0,0 @@
-import{c as e}from"./index-oOOd5nTt.js";/**
- * @license lucide-react v0.460.0 - ISC
- *
- * This source code is licensed under the ISC license.
- * See the LICENSE file in the root directory of this source tree.
- */const o=e("CodeXml",[["path",{d:"m18 16 4-4-4-4",key:"1inbqp"}],["path",{d:"m6 8-4 4 4 4",key:"15zrgr"}],["path",{d:"m14.5 4-5 16",key:"e7oirm"}]]);export{o as C};

frontend/dist/assets/folder-open-DNozsmQ6.js

@@ -1,6 +0,0 @@
-import{c as a}from"./index-oOOd5nTt.js";/**
- * @license lucide-react v0.460.0 - ISC
- *
- * This source code is licensed under the ISC license.
- * See the LICENSE file in the root directory of this source tree.
- */const o=a("FolderOpen",[["path",{d:"m6 14 1.5-2.9A2 2 0 0 1 9.24 10H20a2 2 0 0 1 1.94 2.5l-1.54 6a2 2 0 0 1-1.95 1.5H4a2 2 0 0 1-2-2V5a2 2 0 0 1 2-2h3.9a2 2 0 0 1 1.69.9l.81 1.2a2 2 0 0 0 1.67.9H18a2 2 0 0 1 2 2v2",key:"usdka0"}]]);export{o as F};