diff --git a/app/api/admin.py b/app/api/admin.py
index b52d112..b8c0fc1 100644
--- a/app/api/admin.py
+++ b/app/api/admin.py
@@ -175,6 +175,14 @@ async def wipe_all_user_data(request: Request):
return counts
+@router.get("/admin/model-menu", dependencies=[Depends(require_admin)])
+async def model_menu():
+ """Benutzbare Cloud-Modelle (OpenRouter): Tool-Fähigkeit, ⬆/⬇-Preise pro
+ Mio. Token und geschätzte $/Antwort. Lokale Modelle folgen in Phase 2."""
+ from app.model_menu import build_model_menu
+ return await build_model_menu(get_store())
+
+
@router.post("/admin/users/{user_id}/token", response_model=UserCreated, dependencies=[Depends(require_admin)])
async def reset_token(user_id: str):
"""Stellt einen neuen Bearer-Token aus; der alte wird sofort ungueltig.
diff --git a/app/core/costs.py b/app/core/costs.py
index 0d0ade0..6145112 100644
--- a/app/core/costs.py
+++ b/app/core/costs.py
@@ -16,11 +16,13 @@ _meter: contextvars.ContextVar = contextvars.ContextVar("cost_meter", default=No
class CostMeter:
- __slots__ = ("total", "by_cat")
+ __slots__ = ("total", "by_cat", "prompt_tokens", "completion_tokens")
def __init__(self):
self.total: float = 0.0
self.by_cat: dict[str, float] = {}
+ self.prompt_tokens: int = 0 # Summe über alle (Cloud-)Sub-Calls des Turns
+ self.completion_tokens: int = 0
def add(self, usd, category: str) -> None:
try:
@@ -32,6 +34,13 @@ class CostMeter:
self.total += usd
self.by_cat[category] = self.by_cat.get(category, 0.0) + usd
+ def add_tokens(self, prompt, completion) -> None:
+ try:
+ self.prompt_tokens += int(prompt or 0)
+ self.completion_tokens += int(completion or 0)
+ except (TypeError, ValueError):
+ pass
+
def start_meter() -> CostMeter:
"""Setzt einen frischen Zähler für den aktuellen (Request-)Kontext."""
@@ -52,18 +61,25 @@ def add_cost(usd, category: str) -> None:
def record_openrouter_cost(usage, category: str) -> None:
- """Liest `cost` aus einem OpenRouter-`usage`-Objekt und bucht es (USD)."""
+ """Liest `cost` + Token aus einem OpenRouter-`usage`-Objekt und bucht sie."""
if isinstance(usage, dict):
add_cost(usage.get("cost"), category)
+ meter = _meter.get()
+ if meter is not None:
+ meter.add_tokens(usage.get("prompt_tokens"), usage.get("completion_tokens"))
def persist_costs(user, store) -> None:
- """Schreibt die im aktuellen Meter gesammelten Kosten pro Kategorie in den Store."""
+ """Schreibt die Kosten pro Kategorie in den Store und aktualisiert das
+ globale Turn-Token-Profil (für die „$/Antwort"-Schätzung im Modell-Menü)."""
meter = _meter.get()
if meter is None or user is None:
return
for category, amount in meter.by_cat.items():
store.add_cost_usage(user.id, category, amount)
+ # Nur Turns mit echter Cloud-Token-Messung ins Profil aufnehmen.
+ if meter.completion_tokens > 0:
+ store.update_turn_profile(meter.prompt_tokens, meter.completion_tokens)
def _cfg(cfg):
diff --git a/app/model_menu.py b/app/model_menu.py
new file mode 100644
index 0000000..ac592c2
--- /dev/null
+++ b/app/model_menu.py
@@ -0,0 +1,96 @@
+"""Modell-Auswahlmenü (Phase 1: Cloud/OpenRouter).
+
+Liefert die benutzbaren Chat-Modelle aus dem OpenRouter-Katalog mit Tool-Fähigkeit,
+⬆/⬇-Preisen pro Mio. Token und einer geschätzten „$/Antwort" (aus dem live
+gemessenen Turn-Token-Profil). Katalog wird gecacht. Lokale Modelle: Phase 2.
+
+Siehe Ideen/MODELL_MENUE_KONZEPT.md.
+"""
+import time
+
+import httpx
+
+from app.runtime_config import runtime_settings
+
+_CATALOG_URL = "https://openrouter.ai/api/v1/models"
+_TTL = 3600.0 # Katalog ändert sich selten
+_cache: dict = {"t": 0.0, "data": None}
+
+# Im eval/tool_calling als web-suchtauglich bestätigt (✅). Klein halten/pflegen.
+EVAL_VERIFIED = {
+ "mistralai/mistral-small-3.2-24b-instruct",
+}
+
+# Annahmen, bis echte Turn-Messdaten vorliegen.
+_DEFAULT_PROMPT_TOKENS = 700
+_DEFAULT_COMPLETION_TOKENS = 130
+
+
+def invalidate_cache() -> None:
+ _cache["data"] = None
+
+
+def _f(x) -> float:
+ try:
+ return float(x)
+ except (TypeError, ValueError):
+ return 0.0
+
+
+async def _fetch_catalog(api_key: str) -> list:
+ now = time.monotonic()
+ if _cache["data"] is not None and now - _cache["t"] < _TTL:
+ return _cache["data"]
+ headers = {"Authorization": f"Bearer {api_key}"} if api_key else {}
+ async with httpx.AsyncClient(timeout=30.0) as client:
+ resp = await client.get(_CATALOG_URL, headers=headers)
+ resp.raise_for_status()
+ data = resp.json().get("data", [])
+ _cache["data"] = data
+ _cache["t"] = now
+ return data
+
+
+async def build_model_menu(store=None, cfg=None) -> dict:
+ cfg = cfg or runtime_settings
+ try:
+ catalog = await _fetch_catalog(cfg.openrouter_api_key)
+ except Exception as exc: # noqa: BLE001 — graceful, UI zeigt Fehler
+ return {"available": False, "error": str(exc), "models": [], "profile": {}}
+
+ prof = store.get_turn_profile() if store is not None else {}
+ avg_p = prof.get("avg_prompt") or _DEFAULT_PROMPT_TOKENS
+ avg_c = prof.get("avg_completion") or _DEFAULT_COMPLETION_TOKENS
+
+ models = []
+ for m in catalog:
+ modality = (m.get("architecture") or {}).get("modality") or ""
+ if not modality.endswith("->text"): # nur Chat-/Completion-Modelle
+ continue
+ pricing = m.get("pricing") or {}
+ p_in = _f(pricing.get("prompt")) # $/Token
+ p_out = _f(pricing.get("completion"))
+ mid = m.get("id")
+ models.append({
+ "id": mid,
+ "name": m.get("name") or mid,
+ "context_length": m.get("context_length"),
+ "price_in_per_mtok": round(p_in * 1_000_000, 4),
+ "price_out_per_mtok": round(p_out * 1_000_000, 4),
+ "tool_supported": "tools" in (m.get("supported_parameters") or []),
+ "eval_verified": mid in EVAL_VERIFIED,
+ "est_cost_per_answer": round(avg_p * p_in + avg_c * p_out, 6),
+ })
+ # Sortierung: eval-bestätigt zuerst, dann tool-fähig, dann alphabetisch.
+ models.sort(key=lambda x: (not x["eval_verified"], not x["tool_supported"], x["name"].lower()))
+
+ return {
+ "available": True,
+ "models": models,
+ "profile": {
+ "avg_prompt": round(avg_p),
+ "avg_completion": round(avg_c),
+ "measured": bool(prof.get("samples")),
+ },
+ "current": cfg.openrouter_llm_model,
+ }
diff --git a/app/store.py b/app/store.py
index 6a1dcd6..3b0f456 100644
--- a/app/store.py
+++ b/app/store.py
@@ -136,6 +136,14 @@ class Store(ABC):
def cost_for_day(self, user_id: str, day: str | None = None) -> float:
"""Summe der Kosten (USD) des Nutzers am Tag (Default: heute, UTC)."""
+ @abstractmethod
+ def update_turn_profile(self, prompt_tokens: int, completion_tokens: int) -> None:
+ """Aktualisiert das gleitende Mittel der Token je Turn (für „$/Antwort")."""
+
+ @abstractmethod
+ def get_turn_profile(self) -> dict:
+ """Liefert {avg_prompt, avg_completion, samples} oder {} (noch ungemessen)."""
+
@abstractmethod
def delete_user(self, user_id: str) -> bool:
"""Loescht einen Nutzer und alle seine Daten (Sessions, Nachrichten, Erinnerungen,
@@ -272,6 +280,10 @@ class SQLiteStore(Store):
amount_usd REAL NOT NULL DEFAULT 0,
PRIMARY KEY (user_id, day, category)
);
+ CREATE TABLE IF NOT EXISTS turn_profile (
+ k TEXT PRIMARY KEY,
+ v REAL NOT NULL
+ );
CREATE TABLE IF NOT EXISTS emergency_events (
id INTEGER PRIMARY KEY AUTOINCREMENT,
user_id TEXT NOT NULL,
@@ -569,6 +581,28 @@ class SQLiteStore(Store):
).fetchone()
return float(row["s"]) if row else 0.0
+ def update_turn_profile(self, prompt_tokens: int, completion_tokens: int,
+ alpha: float = 0.1) -> None:
+ with self._connect() as conn:
+ cur = {r["k"]: r["v"] for r in conn.execute("SELECT k, v FROM turn_profile")}
+ n = cur.get("samples", 0)
+ if n <= 0:
+ ap, ac = float(prompt_tokens), float(completion_tokens)
+ else:
+ ap = (1 - alpha) * cur.get("avg_prompt", 0.0) + alpha * prompt_tokens
+ ac = (1 - alpha) * cur.get("avg_completion", 0.0) + alpha * completion_tokens
+ for k, val in (("avg_prompt", ap), ("avg_completion", ac), ("samples", n + 1)):
+ conn.execute(
+ "INSERT INTO turn_profile(k, v) VALUES(?, ?)"
+ " ON CONFLICT(k) DO UPDATE SET v = excluded.v",
+ (k, val),
+ )
+
+ def get_turn_profile(self) -> dict:
+ with self._connect() as conn:
+ rows = conn.execute("SELECT k, v FROM turn_profile").fetchall()
+ return {r["k"]: r["v"] for r in rows}
+
def delete_user(self, user_id: str) -> bool:
if user_id == ANONYMOUS_USER_ID:
raise ValueError("Der anonyme Nutzer kann nicht geloescht werden.")
diff --git a/app/web/app.js b/app/web/app.js
index 036133f..9886d2f 100644
--- a/app/web/app.js
+++ b/app/web/app.js
@@ -1785,6 +1785,17 @@ async function loadStatus() {
${modelCard}
+
+
+
+
Modell-Browser (Cloud)
+
+
+
✅ im Eval bestätigt · 🔧 Tools laut Anbieter · Preise pro Mio. Token (⬆ Eingabe / ⬇ Ausgabe) · ~$/Antwort geschätzt.
+
+
+
Provider (Standard-Route)
@@ -1817,6 +1828,7 @@ async function loadStatus() {
`;
wireModelPicker();
+ wireModelBrowser();
} catch (e) {
console.error("loadStatus error:", e);
container.innerHTML = 'Fehler beim Laden.
';
@@ -1839,6 +1851,70 @@ function wireModelPicker() {
});
}
+// Modell-Browser (Cloud): Katalog laden, filtern, ein Modell als openrouter_llm_model setzen.
+let _modelMenu = [];
+let _modelCurrent = "";
+function wireModelBrowser() {
+ const btn = $("#model-menu-load");
+ if (btn) btn.addEventListener("click", loadModelMenu);
+}
+
+async function loadModelMenu() {
+ const box = $("#model-menu-results");
+ const search = $("#model-menu-search");
+ if (!box) return;
+ box.innerHTML = 'lade …
';
+ const data = await adminFetch("/api/admin/model-menu");
+ if (!data) { box.innerHTML = 'Fehler beim Laden.
'; return; }
+ if (!data.available) {
+ box.innerHTML = `Katalog nicht verfügbar: ${escHtml(data.error || "unbekannt")}
`;
+ return;
+ }
+ _modelMenu = data.models || [];
+ _modelCurrent = data.current || "";
+ const p = data.profile || {};
+ box.dataset.note = `~$/Antwort bei Ø ${p.avg_prompt ?? "?"} Eingabe- + ${p.avg_completion ?? "?"} Ausgabe-Token (${p.measured ? "gemessen" : "Default"}).`;
+ if (search) {
+ search.classList.remove("hidden");
+ search.value = "";
+ search.oninput = () => renderModelMenu(search.value.trim().toLowerCase());
+ }
+ renderModelMenu("");
+}
+
+function renderModelMenu(q) {
+ const box = $("#model-menu-results");
+ if (!box) return;
+ const list = q
+ ? _modelMenu.filter((m) => (m.id + " " + m.name).toLowerCase().includes(q))
+ : _modelMenu;
+ const fmt = (n) => "$" + (Number(n) || 0);
+ const rows = list.slice(0, 400).map((m) => {
+ const badge = m.eval_verified ? "✅" : (m.tool_supported ? "🔧" : "·");
+ const cur = m.id === _modelCurrent;
+ return `
+
+ ${badge}
+ ${escHtml(m.name)}
+ ⬆${fmt(m.price_in_per_mtok)}
+ ⬇${fmt(m.price_out_per_mtok)}
+ ~$${(Number(m.est_cost_per_answer) || 0).toFixed(5)}
+
+
`;
+ }).join("");
+ box.innerHTML = `
+ ${escHtml(box.dataset.note || "")} ${list.length} Modelle.
+ ${rows || '
keine Treffer
'}