#!/usr/bin/env python3
"""T01 v2 · слой текста через OpenRouter (protocol.md § «Слой текста»): 5 моделей × P1–P10, 1 попытка + ≤ 1 повтор.
Запуск: python3 run_text.py → text/<модель>/P<N>.json|.md, text/runs.jsonl. Уже готовые (status ok) пропускает.
"""
import base64, json, subprocess, tempfile, time
from concurrent.futures import ThreadPoolExecutor
from pathlib import Path

HERE = Path(__file__).resolve().parent
ROOT = HERE.parent
WRAP = str(Path("обёртка OpenRouter редакции").expanduser())
MODELS = {"gpt54mini": "openai/gpt-5.4-mini", "gemini31pro": "google/gemini-3.1-pro-preview",
          "sonnet5": "anthropic/claude-sonnet-5", "deepseekv4": "deepseek/deepseek-v4-flash-vision-exp",
          "qwen38max": "qwen/qwen3.8-max-0902"}
TAIL = "\nГлавное фото не генерируй — дай только название и описание."
OUT = HERE / "text"


def items():
    for f in ("inputs.json", "inputs-c2.json"):
        for it in json.loads((ROOT / f).read_text(encoding="utf-8"))["items"]:
            n = it["id"].split("-")[1]
            img = (ROOT / it["image"]).resolve()
            prompt = (ROOT / "runs" / f"prompt-{it['id']}.txt").read_text(encoding="utf-8").rstrip()
            yield n, img, prompt


def small(img):
    t = Path(tempfile.mkdtemp()) / "in.jpg"
    subprocess.run(["sips", "-Z", "1024", "-s", "format", "jpeg", str(img), "--out", str(t)], check=True,
                   capture_output=True)
    return "data:image/jpeg;base64," + base64.b64encode(t.read_bytes()).decode()


def call(short, model, n, url, prompt):
    d = OUT / short
    d.mkdir(parents=True, exist_ok=True)
    body = {"model": model, "max_tokens": 2000, "messages": [{"role": "user", "content": [
        {"type": "text", "text": prompt + TAIL}, {"type": "image_url", "image_url": {"url": url}}]}]}
    rec = {"model": model, "input": n}
    for attempt in (1, 2):
        t0 = time.time()
        p = subprocess.run([WRAP, "chat", json.dumps(body, ensure_ascii=False)], capture_output=True, text=True,
                           timeout=300)
        rec.update(attempt=attempt, sec=round(time.time() - t0, 1))
        try:
            r = json.loads(p.stdout)
        except json.JSONDecodeError:
            r = {"error": (p.stdout or p.stderr)[:300]}
        txt = None
        if not r.get("error") and r.get("choices"):
            txt = r["choices"][0]["message"].get("content")
        u = r.get("usage") or {}
        rec.update(cost=u.get("cost"), prompt_tokens=u.get("prompt_tokens"),
                   completion_tokens=u.get("completion_tokens"),
                   finish=(r.get("choices") or [{}])[0].get("finish_reason"))
        if txt:
            (d / f"{n}.json").write_text(json.dumps(r, ensure_ascii=False, indent=1), encoding="utf-8")
            (d / f"{n}.md").write_text(txt.strip() + "\n", encoding="utf-8")
            rec["status"] = "ok"
            return rec
        rec.update(status="fail", error=str(r.get("error"))[:300])
        (d / f"{n}-fail-{attempt}.json").write_text(json.dumps(r, ensure_ascii=False)[:5000], encoding="utf-8")
    return rec


def main():
    OUT.mkdir(exist_ok=True)
    log = OUT / "runs.jsonl"
    done = set()
    if log.exists():
        for line in log.read_text().splitlines():
            j = json.loads(line)
            if j["status"] == "ok":
                done.add((j["model"], j["input"]))
    jobs = []
    for n, img, prompt in items():
        url = small(img)
        for short, model in MODELS.items():
            if (model, n) not in done:
                jobs.append((short, model, n, url, prompt))
    with ThreadPoolExecutor(5) as ex, log.open("a") as fh:
        for rec in ex.map(lambda a: call(*a), jobs):
            fh.write(json.dumps(rec, ensure_ascii=False) + "\n"); fh.flush()
            print(rec["model"], rec["input"], rec["status"], rec.get("cost"), rec.get("finish"), flush=True)


if __name__ == "__main__":
    main()