v5 Phase 3: News-Quellen aufgeraeumt + Upgrade-Vorschlaege

- news.py: Git-Release-Feeds raus (b9745-Rauschen), Qualitaetsquellen rein
  (HuggingFace, r/LocalLLaMA, Simon Willison, Latent Space, Ahead of AI, The Batch).
- cookbook.py: /upgrades (matcht installierte alte Modelle gegen UPGRADES-Map) +
  /install-model (einzelnes Modell tauschen, GGUF dynamisch, optimaler ctx).
- news.js: 'Fuer dich: Upgrades'-Sektion oben (Modell X ersetzt dein Y, weil ... [Installieren]).

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

routers/cookbook.py

@@ -15,7 +15,7 @@ from hw_math import evaluate_fit, max_ctx_for
 from config import MODELS_DIR, CMD_TEMPLATE, DEFAULT_TTL
 from llamaswap import read_config, write_config
 from jobengine import start_job, JOBS
-from recipes import RECIPES
+from recipes import RECIPES, UPGRADES
 
 router = APIRouter(prefix="/api/cookbook", dependencies=[Depends(auth)])
 
@@ -34,6 +34,13 @@ class InstallRecipeReq(BaseModel):
     recipe_id: str
     hf_token: str | None = None
 
+class InstallModelReq(BaseModel):
+    repo: str
+    role: str
+    params_b: float
+    quant: str = "Q4_K_M"
+    hf_token: str | None = None
+
 def extract_params_b(repo_id: str) -> float:
     """Extrahiert die Parametergröße (in Milliarden) aus dem Repo-Namen."""
     # z.B. Qwen2.5-Coder-32B -> 32
@@ -177,3 +184,54 @@ def _pick_gguf(repo: str, quant: str = "Q4_K_M") -> str | None:
     nosplit = [g for g in ggufs if "-of-" not in g]
     return (pref or nosplit or ggufs)[0]
 
+
+@router.get("/upgrades")
+def upgrades():
+    """Schlägt für installierte 'alte' Modelle ein aktuelleres vor (UPGRADES-Map)."""
+    ram_gb = psutil.virtual_memory().total / (1024 ** 3)
+    installed = (read_config().get("models") or {})
+    out, seen = [], set()
+    for up in UPGRADES:
+        new_base = up["repo"].split("/")[-1].lower()
+        if any(new_base in str(s.get("cmd", "")).lower() for s in installed.values()):
+            continue  # neueres Modell schon installiert
+        old = None
+        for alias, spec in installed.items():
+            hay = (alias + " " + str(spec.get("cmd", ""))).lower()
+            if any(k in hay for k in up["match"]):
+                old = alias
+                break
+        if not old or up["repo"] in seen:
+            continue
+        seen.add(up["repo"])
+        out.append({
+            "name": up["name"], "repo": up["repo"], "params_b": up["params_b"], "quant": up["quant"],
+            "why": up["why"], "old": old, "role": old,
+            "fit": evaluate_fit(up["params_b"], up["quant"], 8192, ram_gb),
+            "optimal_ctx": max_ctx_for(up["params_b"], up["quant"], ram_gb),
+        })
+    return {"upgrades": out}
+
+
+@router.post("/install-model")
+def install_model(req: InstallModelReq):
+    """Ein einzelnes Modell installieren (Download + Einpflegen unter 'role', optimaler ctx)."""
+    file = _pick_gguf(req.repo, req.quant)
+    if not file:
+        raise HTTPException(404, "Keine GGUF-Datei im Repo gefunden.")
+    ram_gb = psutil.virtual_memory().total / (1024 ** 3)
+    env = {"HF_XET_HIGH_PERFORMANCE": "1"}
+    if req.hf_token:
+        env["HF_TOKEN"] = req.hf_token
+    target = MODELS_DIR / req.repo.split("/")[-1]
+    target.mkdir(parents=True, exist_ok=True)
+    jid = start_job(["hf", "download", req.repo, file, "--local-dir", str(target)],
+                    f"download {req.repo.split('/')[-1]}", env=env)
+    JOBS[jid]["result_path"] = str(target / file)
+    cfg = read_config()
+    ctx = min(max_ctx_for(req.params_b, req.quant, ram_gb), 32768)
+    cmd = CMD_TEMPLATE.replace("{model}", str(target / file)).replace("{ctx}", str(ctx))
+    cfg["models"][req.role] = {"cmd": LiteralScalarString(cmd + "\n"), "ttl": DEFAULT_TTL}
+    write_config(cfg)
+    return {"job_id": jid}
+