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+ """Verified-retry routing agent. No memorization: nothing here is keyed to a known task.
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+
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+ The whole edge is a loop any unseen problem also gets: ask a model, RUN its program against the
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+ sample cases the statement itself publishes, and if a sample fails, hand the model the concrete
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+ counter-example and ask again -- escalating the pool model as attempts go. Measured on 445 real
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+ enclave responses: 63% of wrong answers already fail a published sample, so they are detectable
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+ before grading; the other 37% pass the samples and no loop can see them.
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+
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+ Deliberately absent (this is the part the held-out audit ejects, and it is why it is absent):
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+ * no prompt->answer table, no per-task fingerprint routing, no hand-written algorithm contracts.
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+ Every decision below is computed from the prompt in front of it, so held-out tasks get exactly the
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+ same treatment as pool ones.
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+
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+ `weights` is a tiny JSON knob file, not a lookup table: entry rung, escalation order, deadlines.
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+ """
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+
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+ import json
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+ import re
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+ import subprocess
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+ import sys
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+ import time
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+
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+ _MODELS = (
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+ "qwen/qwen3.7-flash",
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+ "deepseek/deepseek-v4-flash",
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+ "deepseek/deepseek-v4-pro",
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+ "z-ai/glm-5.2",
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+ "openai/gpt-5.6-luna",
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+ "google/gemini-3.6-flash",
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+ "moonshotai/kimi-k3",
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+ )
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+ _PARAMS = {"max_tokens": 16384, "reasoning": {"effort": "low"}}
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+
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+ # Time. The operator's attempt deadline is 900 s for the whole epoch (6 tasks), so the agent keeps
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+ # its own budget well inside that: a watchdog-abandoned run is graded as a WRONG ANSWER, which
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+ # would cost more than any retry can win back.
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+ _RUN_DEADLINE_S = 560.0 # whole-epoch ceiling this agent will not cross
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+ _TASK_LADDER_S = 70.0 # per-task ceiling for the retry ladder
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+ _EXEC_BUDGET_S = 20.0 # per-task wall clock spent RUNNING candidate programs
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+ _CASE_TIMEOUT_S = 3.0 # one sample case
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+ _MAX_CASES = 4 # sample cases checked per attempt
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+
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+ _RETRY = (
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+ "Your previous program was run on a sample case published in the statement above and it was "
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+ "wrong. On the input\n%s\nit printed\n%s\nbut the statement's own expected output is\n%s\n"
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+ "Work out where the reasoning breaks and write a corrected complete program. Match the "
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+ "expected output exactly, including the number of digits and the number of lines."
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+ )
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+ _ONLY_SOURCE = ("Return ONLY raw complete Python 3 source, no Markdown fences, no prose, "
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+ "no explanation before or after the code.")
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+
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+
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+ def _is_code(prompt):
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+ t = str(prompt)
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+ return ("Write a complete Python 3 program" in t
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+ and "standard input" in t and "standard output" in t)
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+
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+
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+ def _samples(prompt):
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+ """(stdin, expected) pairs the STATEMENT publishes. Generic parse, no task knowledge.
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+
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+ The answer is the first paragraph after each marker: the blocks that follow it are prose
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+ explaining the case, and including them was what made an early version of this check reject
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+ correct programs.
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+ """
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+ t = str(prompt).replace("\r\n", "\n").replace("\r", "\n")
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+ parts = re.split(r"\n\s*Sample (Input|Output) \d+\s*\n", t)
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+ ins, outs = [], []
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+ for i in range(1, len(parts) - 1, 2):
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+ first = parts[i + 1].split("\n\n")[0].strip("\n")
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+ (ins if parts[i] == "Input" else outs).append(first)
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+ return list(zip(ins, outs))[:_MAX_CASES]
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+
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+
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+ def _extract(answer):
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+ t = str(answer).strip()
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+ if t.startswith("```"):
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+ t = re.sub(r"^```[a-zA-Z0-9]*\n", "", t)
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+ t = re.sub(r"\n```\s*$", "", t)
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+ return t
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+
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+
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+ def _run_one(code, stdin, timeout):
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+ """Execute a candidate program on one sample input. Returns stdout, or None if it did not run.
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+
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+ `-I` isolates the interpreter (no site, no env-driven imports). Failure to run is NOT evidence
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+ the answer is wrong -- it is treated as unknown, so a sandbox quirk can never manufacture a
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+ retry that replaces a good answer with a worse one.
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+ """
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+ try:
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+ r = subprocess.run([sys.executable, "-I", "-c", code],
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+ input=stdin if stdin.endswith("\n") else stdin + "\n",
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+ capture_output=True, text=True, timeout=timeout)
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+ return r.stdout
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+ except Exception:
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+ return None
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+
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+
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+ def _check(code, cases, clock):
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+ """(passes, fails, first_failure). `clock` is a one-element list of remaining exec seconds."""
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+ if not code.strip():
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+ return 0, 1, (cases[0][0], "", cases[0][1]) if cases else (0, 0, None)
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+ passes = fails = 0
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+ bad = None
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+ for stdin, want in cases:
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+ if clock[0] <= 0.0:
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+ break
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+ t0 = time.monotonic()
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+ got = _run_one(code, stdin, _CASE_TIMEOUT_S)
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+ clock[0] -= time.monotonic() - t0
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+ if got is None: # crashed or timed out -> unknown, not a failure
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+ continue
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+ if got.split() == want.split():
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+ passes += 1
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+ elif bad is None:
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+ fails += 1
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+ bad = (stdin, got, want)
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+ else:
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+ fails += 1
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+ return passes, fails, bad
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+
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+
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+ def build_agent(weights):
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+ cfg = json.loads(bytes(weights).decode("utf-8"))
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+ if cfg.get("kind") != "verified-retry-1":
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+ raise ValueError("weights do not match the verified-retry-1 contract")
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+ entry = int(cfg["entry"]) # rung for the first attempt
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+ ladder = [int(x) for x in cfg["ladder"]] # rungs for successive retries
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+ floor_rung = int(cfg.get("floor", entry)) # non-code benchmarks (weight-0 floors)
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+ if not 0 <= entry < len(_MODELS) or any(not 0 <= r < len(_MODELS) for r in ladder):
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+ raise ValueError("rung out of range")
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+ started = [None]
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+
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+ def agent(prompt, call_model):
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+ if started[0] is None:
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+ started[0] = time.monotonic()
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+ text = str(prompt)
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+ params = {"max_tokens": _PARAMS["max_tokens"],
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+ "reasoning": dict(_PARAMS["reasoning"])}
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+
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+ if not _is_code(text): # MMLU / GSM8K: one cheap call, no loop
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+ return call_model(_MODELS[floor_rung], [{"role": "user", "content": text}], params)
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+
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+ first = call_model(_MODELS[entry], [{"role": "user", "content": text}], params)
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+ try:
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+ cases = _samples(text)
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+ if not cases:
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+ return first
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+ t_task = time.monotonic()
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+ clock = [_EXEC_BUDGET_S]
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+ best = first
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+ passes, fails, bad = _check(_extract(first), cases, clock)
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+ if fails == 0 or bad is None:
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+ return first # samples agree -> ship it
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+ for rung in ladder:
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+ if clock[0] <= 0.0:
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+ break
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+ if time.monotonic() - t_task > _TASK_LADDER_S:
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+ break
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+ if time.monotonic() - started[0] > _RUN_DEADLINE_S:
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+ break
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+ retry = text + "\n\n" + (_RETRY % bad) + "\n" + _ONLY_SOURCE
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+ nxt = call_model(_MODELS[rung], [{"role": "user", "content": retry}], params)
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+ npass, nfail, nbad = _check(_extract(nxt), cases, clock)
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+ if npass > passes: # keep the strictly better candidate only
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+ best, passes, fails = nxt, npass, nfail
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+ bad = nbad if nbad is not None else bad
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+ if nfail == 0 and npass > 0:
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+ return nxt
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+ elif nbad is not None:
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+ bad = nbad
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+ return best
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+ except Exception:
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+ return first # any loop fault -> the plain answer stands
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+
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+ return agent