Initial: Mesh-Skills, Configs, Scripts

2026-09-02 23:49:07 +02:00
commit 26c7980750
783 changed files with 145393 additions and 0 deletions
@@ -0,0 +1,162 @@
+#!/usr/bin/env python3
+"""
+daily_model_check.py
+
+Ebene 1 des Skills: läuft 1x täglich (Cron), baut die grobe
+Modell-Prioritätsliste pro Agent und schreibt sie nach
+state/model_priority.json.
+
+Nutzt aktuell Mock-Daten (mock_data.py). Für den Wechsel auf die
+echte OpenRouter-API muss nur fetch_model_list() in mock_data.py
+ersetzt werden - dieses Script bleibt unverändert.
+
+Aufruf:
+    python3 daily_model_check.py
+"""
+
+import json
+import sys
+from pathlib import Path
+
+import yaml
+
+sys.path.insert(0, str(Path(__file__).parent))
+from mock_data import fetch_model_list, fetch_timestamp  # noqa: E402
+
+CONFIG_PATH = Path(__file__).parent.parent / "config" / "agents.yaml"
+STATE_DIR = Path(__file__).parent.parent / "state"
+OUTPUT_PATH = STATE_DIR / "model_priority.json"
+
+
+def load_config():
+    with open(CONFIG_PATH, "r", encoding="utf-8") as f:
+        return yaml.safe_load(f)
+
+
+def index_models_by_id(models):
+    return {m["id"]: m for m in models}
+
+
+def build_agent_priority(agent_name, agent_cfg, models_by_id, min_context, max_escalation_factor):
+    """Baut die Eskalationsleiter für einen Agent, gefiltert nach
+    Mindest-Kontext und verfügbaren/bekannten Modellen.
+    """
+    ladder = []
+    warnings = []
+
+    for step_idx, step in enumerate(agent_cfg["escalation_ladder"]):
+        model_id = step["model"]
+        cost_factor = step["cost_factor"]
+
+        # Free-Tier-Router-Strings wie "openrouter/free" stehen nicht in
+        # der Modell-Liste selbst - die werden unverändert übernommen.
+        if model_id not in models_by_id:
+            if model_id.startswith("openrouter/"):
+                ladder.append({"model": model_id, "cost_factor": cost_factor, "note": "auto-router, nicht einzeln geprüft"})
+                continue
+            warnings.append(f"{agent_name}: Modell '{model_id}' nicht in aktueller Modell-Liste gefunden - übersprungen")
+            continue
+
+        model = models_by_id[model_id]
+
+        if not model.get("available", True):
+            warnings.append(f"{agent_name}: Modell '{model_id}' aktuell nicht verfügbar - übersprungen")
+            continue
+
+        if model["context_length"] < min_context:
+            warnings.append(
+                f"{agent_name}: Modell '{model_id}' hat nur {model['context_length']} Kontext, "
+                f"unter Minimum von {min_context} - übersprungen"
+            )
+            continue
+
+        # Verhältnismäßigkeits-Check: Stufen jenseits von Stufe 0 dürfen
+        # den max_auto_escalation_factor nicht überschreiten, sonst braucht's
+        # manual_override.
+        if step_idx > 0 and cost_factor > max_escalation_factor and not agent_cfg.get("manual_override_allowed", False):
+            warnings.append(
+                f"{agent_name}: Eskalationsstufe '{model_id}' hat Faktor {cost_factor}x, "
+                f"über dem erlaubten Automatik-Limit von {max_escalation_factor}x - "
+                f"nur per manual_override nutzbar, aus Automatik-Leiter entfernt"
+            )
+            continue
+
+        ladder.append({
+            "model": model_id,
+            "cost_factor": cost_factor,
+            "context_length": model["context_length"],
+            "price_per_1k_tokens_eur": model["price_per_1k_tokens_eur"],
+            "family": model["family"],
+        })
+
+    return ladder, warnings
+
+
+def check_diversity(priority_by_agent, min_distinct_families):
+    families_in_use = set()
+    for agent_name, ladder in priority_by_agent.items():
+        for step in ladder:
+            if "family" in step:
+                families_in_use.add(step["family"])
+
+    diverse_enough = len(families_in_use) >= min_distinct_families
+    return diverse_enough, sorted(families_in_use)
+
+
+def main():
+    config = load_config()
+    global_cfg = config["global"]
+    min_context = global_cfg["min_context_tokens"]
+    max_escalation_factor = global_cfg["max_auto_escalation_factor"]
+    min_distinct_families = global_cfg["min_distinct_model_families"]
+
+    models = fetch_model_list()
+    models_by_id = index_models_by_id(models)
+
+    priority_by_agent = {}
+    all_warnings = []
+
+    for agent_name, agent_cfg in config["agents"].items():
+        ladder, warnings = build_agent_priority(
+            agent_name, agent_cfg, models_by_id, min_context, max_escalation_factor
+        )
+        priority_by_agent[agent_name] = ladder
+        all_warnings.extend(warnings)
+
+        if not ladder:
+            all_warnings.append(
+                f"WARNUNG: Agent '{agent_name}' hat NACH Filterung keine nutzbaren Modelle mehr - "
+                f"lokaler Fallback sollte hier greifen"
+            )
+
+    diverse_enough, families_in_use = check_diversity(priority_by_agent, min_distinct_families)
+    if not diverse_enough:
+        all_warnings.append(
+            f"WARNUNG: Nur {len(families_in_use)} Modell-Familien im Einsatz "
+            f"({', '.join(families_in_use)}), Minimum wäre {min_distinct_families}"
+        )
+
+    output = {
+        "generated_at": fetch_timestamp(),
+        "min_context_tokens": min_context,
+        "max_auto_escalation_factor": max_escalation_factor,
+        "diversity_ok": diverse_enough,
+        "model_families_in_use": families_in_use,
+        "agents": priority_by_agent,
+        "local_fallback": config["local_fallback"],
+        "warnings": all_warnings,
+    }
+
+    STATE_DIR.mkdir(exist_ok=True)
+    with open(OUTPUT_PATH, "w", encoding="utf-8") as f:
+        json.dump(output, f, indent=2, ensure_ascii=False)
+
+    print(f"Prioritätsliste geschrieben nach {OUTPUT_PATH}")
+    if all_warnings:
+        print(f"\n{len(all_warnings)} Warnung(en):")
+        for w in all_warnings:
+            print(f"  - {w}")
+
+
+if __name__ == "__main__":
+    main()