#!/usr/bin/env python3
"""Schwerer Zaehl-Vergleich (Generalisierungs-Set: Sonderzeichen, Ueberlaenge, Code, andere Prompts).

Dieselben 28 Aufgaben und Prompts wie beim Generalisierungstest unseres Modells, gestellt an QuiteQue-Modelle.
"""
import json
import sys
import threading
import time
from concurrent.futures import ThreadPoolExecutor

sys.path.insert(0, "/mnt/models/graf_zahl")
from compare_counting_quiteque import ALLOWED, ask, last_int  # noqa: E402

PLATTE = "/home/david/Schreibtisch/Platte"
GEN = f"{PLATTE}/models/graf_zahl/generalization_results.json"
OUT = f"{PLATTE}/models/graf_zahl/compare_counting_hard_results.json"
SUFFIX = " Antworte nur mit der Zahl."

MODELS = [
    ("50", "T79 Qwen3 4B Instruct (CPU)", 1),
    ("gemma-12b-chat", "Gemma 4 12B (lokal)", 2),
    ("120", "PropellerA Qwen3.8 27B (lokal)", 1),
    ("or-liquid/lfm-2.5-2.6b:free", "Liquid LFM 2.5 2.6B (free)", 2),
    ("or-google/gemma-4-31b-it:free", "Gemma 4 31B (free)", 2),
    ("or-nvidia/nemotron-3-nano-omni-30b-a3b-reasoning:free", "Nemotron 3 Nano 30B Reasoning (free)", 2),
    ("or-nex-agi/nex-n2.5-pro:free", "Nex-N2.5 Pro (free)", 2),
    ("or-nvidia/nemotron-3.5-lightning:free", "Nemotron 3.5 Lightning (free)", 2),
]


def main():
    assert all(ALLOWED(m[0]) for m in MODELS)
    ours = json.load(open(GEN, encoding="utf-8"))
    items = [(r["kategorie"], r["text"], len(r["text"]), r["prompt"] + SUFFIX, r["endzahl"]) for r in ours]
    cats = list(dict.fromkeys(i[0] for i in items))
    print(f"{len(items)} Aufgaben, {len(MODELS)} Modelle", flush=True)
    results, lock = {}, threading.Lock()

    for mid, name, threads in MODELS:
        rows = []
        def one(it):
            cat, s, n, prompt, _ = it
            content, err = ask(mid, prompt, None, max_tokens=6000)
            got = last_int(content) if not err else None
            return {"kategorie": cat, "text": s, "soll": n, "antwort": content[:300], "zahl": got, "richtig": got == n, "fehler": err}
        t0 = time.time()
        with ThreadPoolExecutor(threads) as ex:
            for r in ex.map(one, items):
                rows.append(r)
                with lock:
                    results[mid] = {"name": name, "rows": rows}
                    json.dump(results, open(OUT, "w", encoding="utf-8"), ensure_ascii=False)
        print(f"[{name}] fertig: {sum(r['richtig'] for r in rows)}/{len(rows)} richtig, {sum(1 for r in rows if r['fehler'])} Fehler, {time.time() - t0:.0f}s", flush=True)

    ours_rows = [{"kategorie": c, "richtig": e == n, "soll": n} for c, s, n, p, e in items]
    results["unser"] = {"name": "UNSER Hardcore-Modell ('Das sind N')", "rows": ours_rows}
    # unser Modell zusaetzlich mit Zahl aus dem Think-Block
    think = {"kategorie": None}
    ours_think = [{"kategorie": r["kategorie"], "richtig": r["sicherheitszahl"] == len(r["text"])} for r in ours]
    results["unser_think"] = {"name": "UNSER Modell (Zahl im Think-Block)", "rows": ours_think}
    json.dump(results, open(OUT, "w", encoding="utf-8"), ensure_ascii=False)

    print("\n===== AUSWERTUNG (richtig je Kategorie) =====")
    print(f"{'Modell':44} " + " ".join(f"{c[:10]:>11}" for c in cats) + f" {'Gesamt':>8}")
    for key in ["unser", "unser_think"] + [m[0] for m in MODELS]:
        rows = results[key]["rows"]
        per = [(sum(r["richtig"] for r in rows if r["kategorie"] == c), len([r for r in rows if r["kategorie"] == c])) for c in cats]
        print(f"{results[key]['name'][:44]:44} " + " ".join(f"{a:>7}/{b:<3}" for a, b in per) + f" {sum(a for a, _ in per):>4}/{len(rows)}")
    print(f"\nErgebnisse: {OUT}")


if __name__ == "__main__":
    main()