Build integrated IS/BS/CF financial workbooks in Excel.
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openamer/openamer8Updated Oct 21, 2026
FreePublished on GitHub
self-hosted
Use for local LLM fallback, failover, and Ollama health.
The English summary is being prepared. Showing the original description.
See how to installFiles included (1)
- SKILL.md2.4 KB
SKILL.md (original)
Review the instructions the agent will receive before you install.
Self-Hosted Independence — Local LLM Fallback + Auto-Failover
Erkennt lokale LLM-Provider (Ollama, llama.cpp), generiert Fallback-Config, überwacht Health von primary + fallback, und schaltet bei 3× Fehlschlag automatisch auf local um.
Verfügbare CLI-Befehle
# Alle Provider prüfen
python scripts/self-hosted.py --check
# Status + Config anzeigen
python scripts/self-hosted.py --status
# Manuell umschalten
python scripts/self-hosted.py --switch-to local
python scripts/self-hosted.py --switch-to primary
python scripts/self-hosted.py --switch-to auto
# Benchmark (Latenz remote vs local)
python scripts/self-hosted.py --bench
# JSON-Report
python scripts/self-hosted.py --report
# Setup: Ollama installieren + Modelle laden
python scripts/self-hosted.py --setup
Wichtige Pfade
| Pfad | Beschreibung |
|---|---|
~/.self-hosted/config.json | Konfiguration (primary, fallback, failover) |
~/.self-hosted/state.json | Laufender State (active_provider, failures, history) |
~/scripts/self-hosted.py | Hauptscript |
~/scripts/self-hosted-cron.py | Cron-Wrapper (alle 5 Min) |
Auto-Failover
- Prüft primary (OpenRouter/Remote) alle 60s
- Wenn 3× hintereinander fehlschlägt → automatisch auf local (Ollama)
- Wenn primary wieder da ist → automatische Recovery (nach 3 erfolgreichen Checks)
- History der letzten 100 Health-Checks in state.json
Fallback-Plan
- Ollama mit qwen3.5:latest (oder phi4-mini:latest)
- CPU-Modus mit qwen3:1.7b (tiny model) falls kein GPU-Modell verfügbar
- llama.cpp auf localhost:8080 (OpenAI-kompatibel) wird ebenfalls erkannt
Auto-Detection
Das Script erkennt beim Start automatisch das beste verfügbare Ollama-Modell:
- Bevorzugt deepseek-coder-Modelle, dann qwen3.5, phi4-mini
- Wählt automatisch einen kleinen CPU-Modus (qwen3:1.7b / phi4-mini)
- Die Config wird nur einmal generiert und kann manuell editiert werden
Setup (Erstinstallation)
python scripts/self-hosted.py --setup
Das lädt automatisch (abhängig von Verfügbarkeit):
- deepseek-coder (falls vorhanden)
- qwen3.5:latest (Standard)
- phi4-mini:latest (Fallback)
- qwen3:1.7b (CPU-Modus)
Exit-Codes
0= alles OK (primary aktiv)1= Fallback aktiv (local läuft, primary down)2= kein LLM verfügbar
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