Auto-Sync: 2026-04-09 17:15
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4 changed files with 353 additions and 8 deletions
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# Arakava News — Live State
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> Auto-generiert: 2026-04-09 16:45
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> Auto-generiert: 2026-04-09 17:15
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## Service Status
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| Service | CT | Status |
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@ -8,11 +8,11 @@
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| WordPress Docker | 101 | running |
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## Letzte Feed-Aktivität (Top 5)
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Antispiegel: 2026-04-09 14:30:42
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PAZ: 2026-04-09 14:30:21
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Junge Freiheit: 2026-04-09 14:00:45
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Dr. Bines Substack: 2026-04-09 14:00:00
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Tichys Einblick: 2026-04-09 13:30:24
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Apollo News: 2026-04-09 15:00:33
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Photon.info (KI-Analyse): 2026-04-09 14:46:35
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Rubikon.news: 2026-04-09 14:45:29
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Norbert Häring: 2026-04-09 14:45:29
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Antispiegel: 2026-04-09 14:30:42
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## Fehler (letzte 24h)
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- Fehler gesamt: 0
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345
homelab-ai-bot/model_library_routes.py
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345
homelab-ai-bot/model_library_routes.py
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"""Model Library Integration — Telegram-Buttons, Befehle, Watcher-Webhook.
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Wird von telegram_bot.py eingebunden:
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import model_library_routes
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model_library_routes.register(app, bot_token, chat_id)
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"""
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import json
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import logging
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import threading
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import time
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import requests
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from telegram import InlineKeyboardButton, InlineKeyboardMarkup, Update
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from telegram.ext import ContextTypes
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log = logging.getLogger(__name__)
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MODEL_LIBRARY_URL = "http://100.116.108.62:8090"
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_CHAT_ID: int | None = None
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_APP = None
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_TG_TOKEN: str | None = None
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_PENDING_FILE = "/var/cache/model-library-pending.json"
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# --- Persistence for pending notifications ---
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def _load_pending() -> list[dict]:
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try:
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with open(_PENDING_FILE) as f:
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return json.load(f)
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except (FileNotFoundError, json.JSONDecodeError):
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return []
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def _save_pending(items: list[dict]):
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with open(_PENDING_FILE, "w") as f:
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json.dump(items, f, ensure_ascii=False, indent=2)
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def _remove_pending(repo_id: str, filename: str):
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items = [
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m for m in _load_pending()
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if not (m.get("repo_id") == repo_id and m.get("filename") == filename)
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]
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_save_pending(items)
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# --- Telegram handlers ---
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async def cmd_modelle(update: Update, ctx: ContextTypes.DEFAULT_TYPE):
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"""Zeigt heruntergeladene Modelle aus dem Katalog."""
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try:
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r = requests.get(f"{MODEL_LIBRARY_URL}/api/catalog", timeout=10)
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r.raise_for_status()
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catalog = r.json()
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except Exception as e:
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await update.message.reply_text(f"Fehler beim Abruf: {e}")
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return
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models = catalog.get("models", [])
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if not models:
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await update.message.reply_text("📂 Bibliothek ist leer.")
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return
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try:
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sr = requests.get(f"{MODEL_LIBRARY_URL}/api/storage", timeout=5)
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storage = sr.json()
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header = (
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f"💾 {storage['used_gb']:.0f} / {storage['total_gb']:.0f} GB "
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f"({storage['percent_used']:.0f}%) belegt\n\n"
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)
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except Exception:
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header = ""
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cat_groups: dict[str, list] = {}
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for m in models:
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cat_groups.setdefault(m.get("category", "llm"), []).append(m)
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cat_icons = {
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"llm": "🧠", "code": "💻", "vision": "👁", "embedding": "📐",
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"audio": "🎵", "image-gen": "🎨",
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}
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lines = [f"📚 *KI-Modell-Bibliothek* ({len(models)} Modelle)\n{header}"]
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for cat, items in sorted(cat_groups.items()):
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icon = cat_icons.get(cat, "📦")
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lines.append(f"{icon} *{cat.upper()}*")
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for m in sorted(items, key=lambda x: x["filename"]):
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q = m.get("quant", "?")
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sz = m.get("size_gb", 0)
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lines.append(f" • `{m['filename']}` ({q}, {sz:.1f} GB)")
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lines.append("")
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await update.message.reply_text("\n".join(lines), parse_mode="Markdown")
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async def cmd_watchlist(update: Update, ctx: ContextTypes.DEFAULT_TYPE):
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"""Zeigt die aktuelle Model-Watchlist."""
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try:
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r = requests.get(f"{MODEL_LIBRARY_URL}/api/watchlist", timeout=10)
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r.raise_for_status()
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data = r.json()
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except Exception as e:
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await update.message.reply_text(f"Fehler beim Abruf: {e}")
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return
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authors = data.get("authors", [])
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if not authors:
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await update.message.reply_text("Watchlist ist leer.")
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return
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lines = ["👀 *Model-Watchlist*\n"]
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for a in authors:
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name = a.get("name", "?")
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comment = a.get("comment", "")
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lines.append(f" • *{name}* — {comment}")
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await update.message.reply_text("\n".join(lines), parse_mode="Markdown")
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def _resolve_callback(data: str) -> tuple[str, str] | None:
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"""Löst Callback-Data auf — direkt (repo|file) oder über Index (idx_N)."""
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prefix = data[:9]
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payload = data[9:]
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if payload.startswith("idx_"):
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try:
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idx = int(payload[4:])
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pending = _load_pending()
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if 0 <= idx < len(pending):
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m = pending[idx]
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return m.get("repo_id"), m.get("filename")
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except (ValueError, IndexError):
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pass
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return None
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if "|" in payload:
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return tuple(payload.split("|", 1))
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return None
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async def handle_model_callback(data: str, query) -> bool:
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"""Verarbeitet model_dl_* und model_ig_* Callbacks. Gibt True zurück wenn verarbeitet."""
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if data.startswith("model_dl_"):
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resolved = _resolve_callback(data)
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if not resolved:
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await query.edit_message_text(query.message.text + "\n\n⚠️ Modell nicht mehr verfügbar")
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return True
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repo_id, filename = resolved
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await query.edit_message_text(
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query.message.text + f"\n\n⏳ Download gestartet: `{filename}`",
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parse_mode="Markdown",
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)
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try:
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r = requests.post(
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f"{MODEL_LIBRARY_URL}/api/download",
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json={"repo_id": repo_id, "filename": filename},
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timeout=15,
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)
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result = r.json()
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if result.get("status") == "started":
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await query.edit_message_text(
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query.message.text.split("\n\n⏳")[0]
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+ f"\n\n✅ Download läuft: `{filename}`",
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parse_mode="Markdown",
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)
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else:
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err = result.get("error", "Unbekannter Fehler")
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await query.edit_message_text(
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query.message.text.split("\n\n⏳")[0]
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+ f"\n\n⚠️ {err}",
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parse_mode="Markdown",
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)
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except Exception as e:
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log.exception("Model download trigger failed")
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await query.edit_message_text(
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query.message.text.split("\n\n⏳")[0]
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+ f"\n\n❌ Fehler: {e}",
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parse_mode="Markdown",
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)
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_remove_pending(repo_id, filename)
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return True
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if data.startswith("model_ig_"):
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resolved = _resolve_callback(data)
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if not resolved:
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await query.edit_message_text(query.message.text + "\n\n⚠️ Modell nicht mehr verfügbar")
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return True
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repo_id, filename = resolved
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try:
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requests.post(
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f"{MODEL_LIBRARY_URL}/api/ignore",
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json={"repo_id": repo_id, "filename": filename},
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timeout=10,
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)
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except Exception:
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pass
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await query.edit_message_text(
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query.message.text + "\n\n🚫 Ignoriert"
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)
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_remove_pending(repo_id, filename)
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return True
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return False
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# --- Webhook: Watcher meldet neue Modelle ---
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def _notify_new_models_sync(models: list[dict]):
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"""Sendet Telegram-Nachrichten mit Inline-Buttons fuer jedes neue Modell.
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Nutzt die Telegram HTTP API direkt (nicht python-telegram-bot),
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da wir in einem Worker-Thread ohne asyncio-Loop laufen.
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"""
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if not _TG_TOKEN or not _CHAT_ID:
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log.warning("Bot-Token oder Chat-ID nicht konfiguriert")
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return
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MAX_PER_BATCH = 10
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if len(models) > MAX_PER_BATCH:
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log.warning("Benachrichtigungen begrenzt: %d -> %d", len(models), MAX_PER_BATCH)
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models = models[:MAX_PER_BATCH]
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pending = _load_pending()
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sent = 0
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for m in models:
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repo_id = m.get("repo_id", "?")
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filename = m.get("filename", "?")
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size_gb = m.get("size_gb", 0)
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quant = m.get("quant", "?")
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already = any(
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p.get("repo_id") == repo_id and p.get("filename") == filename
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for p in pending
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)
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if already:
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continue
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cb_dl = f"model_dl_{repo_id}|{filename}"
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cb_ig = f"model_ig_{repo_id}|{filename}"
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used_index = False
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if len(cb_dl.encode()) > 64 or len(cb_ig.encode()) > 64:
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pending.append(m)
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idx = len(pending) - 1
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_save_pending(pending)
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used_index = True
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cb_dl = f"model_dl_idx_{idx}"
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cb_ig = f"model_ig_idx_{idx}"
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safe_repo = repo_id.replace("_", "\\_")
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text = (
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f"🆕 *Neues KI-Modell verfügbar*\n\n"
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f"📦 `{filename}`\n"
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f"🏷 Repo: {safe_repo}\n"
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f"📏 {size_gb:.1f} GB | Quant: {quant}"
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)
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keyboard = {
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"inline_keyboard": [[
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{"text": "✅ Herunterladen", "callback_data": cb_dl},
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{"text": "🚫 Ignorieren", "callback_data": cb_ig},
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]]
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}
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try:
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resp = requests.post(
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f"https://api.telegram.org/bot{_TG_TOKEN}/sendMessage",
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json={
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"chat_id": _CHAT_ID,
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"text": text,
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"parse_mode": "Markdown",
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"reply_markup": keyboard,
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},
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timeout=15,
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)
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if resp.ok:
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log.info("Modell-Benachrichtigung gesendet: %s", filename)
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sent += 1
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else:
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log.error("Telegram API Fehler: %s %s", resp.status_code, resp.text[:200])
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except Exception:
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log.exception("Fehler beim Senden der Modell-Benachrichtigung: %s", filename)
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if not used_index:
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pending.append(m)
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_save_pending(pending)
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time.sleep(1.5)
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def start_webhook_listener():
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"""Startet einen kleinen Flask-Server (Port 8767) fuer Watcher-Webhooks."""
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from flask import Flask, request as freq, jsonify
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webhook_app = Flask("model-library-webhook")
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webhook_app.logger.setLevel(logging.WARNING)
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werkzeug_log = logging.getLogger("werkzeug")
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werkzeug_log.setLevel(logging.WARNING)
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@webhook_app.route("/api/notify_new_models", methods=["POST"])
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def notify():
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data = freq.get_json(silent=True)
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if not data:
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return jsonify({"error": "no data"}), 400
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models = data.get("models", [])
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if models:
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threading.Thread(
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target=_notify_new_models_sync, args=(models,), daemon=True
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).start()
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return jsonify({"status": "ok", "queued": len(models)})
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@webhook_app.route("/health", methods=["GET"])
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def health():
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return jsonify({"status": "ok"})
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t = threading.Thread(
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target=lambda: webhook_app.run(host="0.0.0.0", port=8767, use_reloader=False),
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daemon=True,
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)
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t.start()
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log.info("Model-Library Webhook-Listener auf Port 8767 gestartet")
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# --- Registration ---
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def register(app, chat_id: int | None, token: str | None = None):
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"""Wird von telegram_bot.py aufgerufen."""
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global _CHAT_ID, _APP, _TG_TOKEN
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_CHAT_ID = chat_id
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_APP = app
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_TG_TOKEN = token
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from telegram.ext import CommandHandler
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app.add_handler(CommandHandler("modelle", cmd_modelle))
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app.add_handler(CommandHandler("watchlist", cmd_watchlist))
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start_webhook_listener()
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log.info("Model-Library Routes registriert (/modelle, /watchlist, Webhook :8767)")
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@ -1,5 +1,5 @@
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# Infrastruktur — Live State
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> Auto-generiert: 2026-04-09 16:45
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> Auto-generiert: 2026-04-09 17:15
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## pve-hetzner Disk
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| Mount | Belegt |
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@ -1,5 +1,5 @@
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# Smart Home Muldenstein — Live State
|
||||
> Auto-generiert: 2026-04-09 16:45
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> Auto-generiert: 2026-04-09 17:15
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## Backup-Status
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- Letztes Backup: 656MB, 2026-04-09 04:01
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Loading…
Add table
Reference in a new issue