"""Exp 0 KL probe: get top-20 prompt logprobs for a few long SWE prefixes.

Sends token-id prompts to /v1/completions (max_tokens=1, prompt_logprobs=20) and
stores the top-20 (id, logprob) per position for positions in [START, END).
compare_kl.py then computes KL between configs on identical token sequences.
"""
import argparse
import json
import time
import urllib.request
from pathlib import Path

from transformers import AutoTokenizer

ap = argparse.ArgumentParser()
ap.add_argument("--out", required=True)
ap.add_argument("--n", type=int, default=3)            # trajectories
ap.add_argument("--prefix_tokens", type=int, default=24000)
ap.add_argument("--start", type=int, default=4000)     # measured window
ap.add_argument("--url", default="http://localhost:8000/v1/completions")
a = ap.parse_args()

tok = AutoTokenizer.from_pretrained(Path.home() / "models" / "Qwen3.8-27B")
rows = [json.loads(l) for l in open(Path.home() / "bench" / "data" / "swe_kl_50.jsonl")][: a.n]
out = []
for r in rows:
    ids = tok.apply_chat_template(r["messages"], tools=r["tools"], tokenize=True)
    if not isinstance(ids, list):
        ids = ids["input_ids"]
    ids = ids[: a.prefix_tokens]
    body = {"model": "Qwen/Qwen3.8-27B", "prompt": ids, "max_tokens": 1, "temperature": 0,
            "prompt_logprobs": 20}
    t0 = time.time()
    req = urllib.request.Request(a.url, data=json.dumps(body).encode(), headers={"Content-Type": "application/json"})
    resp = json.loads(urllib.request.urlopen(req, timeout=1800).read())
    pl = resp["choices"][0]["prompt_logprobs"]
    pos = []
    for i in range(a.start, len(ids)):
        d = pl[i] or {}
        top = sorted(((int(k), v["logprob"]) for k, v in d.items()), key=lambda x: -x[1])[:21]
        pos.append({"t": ids[i], "top": top})
    out.append({"id": r["id"], "n_tokens": len(ids), "start": a.start, "positions": pos})
    print(f"{r['id']}: {len(ids)} tokens, {time.time() - t0:.1f}s", flush=True)
Path(a.out).write_text(json.dumps(out))
print("KL_PROBE_OK", a.out)