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"""Shared helpers for LeanCat evaluation scripts."""
from __future__ import annotations
import argparse
import json
import os
import re
import subprocess
import tempfile
import time
import urllib.error
import urllib.request
from pathlib import Path
from typing import Any
ROOT = Path(__file__).resolve().parents[1]
DEFAULT_MODEL = os.getenv("LEANCAT_MODEL", os.getenv("OPENAI_MODEL", "gpt-5.2"))
DEFAULT_BASE_URL = os.getenv("OPENAI_BASE_URL", "https://api.openai.com/v1")
INVALID_TOKEN_RE = re.compile(r"\b(sorry|admit|axiom|unsafe)\b")
MAX_LOG_OUTPUT_CHARS = 4000
def log(message: str) -> None:
print(f"[LeanCat] {message}", flush=True)
def log_block(title: str, text: str, max_chars: int = MAX_LOG_OUTPUT_CHARS) -> None:
if not text:
return
display = text if len(text) <= max_chars else text[:max_chars] + "\n...[truncated]"
print(f"[LeanCat] {title}:\n{display}", flush=True)
def problem_ids(start: int, end: int) -> list[str]:
if start < 1 or end < start or end > 100:
raise ValueError("--start and --end must define a range within 1..100")
return [f"{i:04d}" for i in range(start, end + 1)]
def load_problem(problem_id: str) -> tuple[str, str]:
lean_path = ROOT / "CAT_statement" / f"S_{problem_id}.lean"
md_path = ROOT / "problems" / f"{problem_id}.md"
return (
md_path.read_text(encoding="utf-8"),
lean_path.read_text(encoding="utf-8"),
)
def load_prompt(relative_path: str) -> str:
return (ROOT / relative_path).read_text(encoding="utf-8").strip()
def render_prompt(template: str, **values: str) -> str:
return template.format(**values)
def extract_lean_code(text: str) -> str:
fenced = re.findall(r"```(?:lean4?|Lean4?)?\s*\n(.*?)```", text, flags=re.DOTALL)
if fenced:
return fenced[-1].strip()
return text.strip()
def strip_lean_comments_and_strings(code: str) -> str:
"""Replace Lean comments and string contents with spaces before token checks."""
output: list[str] = []
index = 0
block_depth = 0
in_string = False
while index < len(code):
char = code[index]
next_char = code[index + 1] if index + 1 < len(code) else ""
if block_depth > 0:
if char == "/" and next_char == "-":
block_depth += 1
output.extend(" ")
index += 2
elif char == "-" and next_char == "/":
block_depth -= 1
output.extend(" ")
index += 2
else:
output.append("\n" if char == "\n" else " ")
index += 1
continue
if in_string:
if char == "\\" and next_char:
output.extend(" ")
index += 2
elif char == "\"":
in_string = False
output.append(" ")
index += 1
else:
output.append("\n" if char == "\n" else " ")
index += 1
continue
if char == "-" and next_char == "-":
output.extend(" ")
index += 2
while index < len(code) and code[index] != "\n":
output.append(" ")
index += 1
continue
if char == "/" and next_char == "-":
block_depth = 1
output.extend(" ")
index += 2
continue
if char == "\"":
in_string = True
output.append(" ")
index += 1
continue
output.append(char)
index += 1
return "".join(output)
def has_invalid_tokens(code: str) -> bool:
return INVALID_TOKEN_RE.search(strip_lean_comments_and_strings(code)) is not None
def verify_lean(code: str, timeout: int) -> tuple[bool, str]:
if has_invalid_tokens(code):
log("Lean verification skipped: forbidden token found")
return False, "Candidate contains forbidden tokens: sorry/admit/axiom/unsafe."
temp_dir = ROOT / ".lake" / "leancat_eval"
temp_dir.mkdir(parents=True, exist_ok=True)
with tempfile.NamedTemporaryFile(
mode="w",
suffix=".lean",
prefix="attempt_",
dir=temp_dir,
delete=False,
encoding="utf-8",
) as handle:
handle.write(code)
temp_path = Path(handle.name)
try:
relative = temp_path.relative_to(ROOT)
log(f"running Lean verifier on {relative}")
result = subprocess.run(
["lake", "env", "lean", str(relative)],
cwd=ROOT,
text=True,
encoding="utf-8",
capture_output=True,
timeout=timeout,
)
output = (result.stdout or "") + (result.stderr or "")
log(f"Lean verifier finished with exit code {result.returncode}")
if result.returncode != 0:
log_block("Lean verifier output", output.strip())
return result.returncode == 0, output.strip()
except subprocess.TimeoutExpired:
log(f"Lean verifier timed out after {timeout} seconds")
return False, f"Lean verification timed out after {timeout} seconds."
finally:
try:
temp_path.unlink()
except OSError:
pass
def chat_completion(
prompt: str,
model: str,
temperature: float,
max_tokens: int,
base_url: str,
api_key: str | None,
) -> str:
if not api_key:
raise RuntimeError("Set OPENAI_API_KEY or pass --api-key.")
url = base_url.rstrip("/") + "/chat/completions"
log(f"calling LLM model={model} base_url={base_url.rstrip('/')} prompt_chars={len(prompt)}")
payload = {
"model": model,
"messages": [{"role": "user", "content": prompt}],
"temperature": temperature,
"max_tokens": max_tokens,
}
data = json.dumps(payload).encode("utf-8")
request = urllib.request.Request(
url,
data=data,
headers={
"Authorization": f"Bearer {api_key}",
"Content-Type": "application/json",
},
method="POST",
)
try:
with urllib.request.urlopen(request, timeout=600) as response:
body = response.read().decode("utf-8")
except urllib.error.HTTPError as exc:
detail = exc.read().decode("utf-8", errors="replace")
raise RuntimeError(f"LLM request failed: HTTP {exc.code}: {detail}") from exc
parsed: dict[str, Any] = json.loads(body)
content = parsed["choices"][0]["message"]["content"]
log(f"LLM response received chars={len(content)}")
return content
def write_json(path: Path, payload: dict[str, Any]) -> None:
path.parent.mkdir(parents=True, exist_ok=True)
path.write_text(json.dumps(payload, ensure_ascii=False, indent=2), encoding="utf-8")
def add_common_args(parser: argparse.ArgumentParser) -> None:
parser.add_argument("--start", type=int, default=1, help="First problem id, 1-indexed.")
parser.add_argument("--end", type=int, default=100, help="Last problem id, inclusive.")
parser.add_argument("--model", default=DEFAULT_MODEL)
parser.add_argument("--temperature", type=float, default=1.0)
parser.add_argument("--max-tokens", type=int, default=50000)
parser.add_argument("--timeout", type=int, default=300, help="Lean timeout per attempt.")
parser.add_argument("--base-url", default=DEFAULT_BASE_URL)
parser.add_argument("--api-key", default=os.getenv("OPENAI_API_KEY"))
parser.add_argument("--output-dir", type=Path, default=ROOT / "results")
parser.add_argument("--resume", action="store_true", help="Skip attempts already on disk.")
def now_seconds() -> float:
return time.time()
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