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"""Rescue-experiment prompt construction.
For each (model, variant, flip-case) we build prompts under three conditions:
- own_T2: model's own original-correct trajectory truncated at first
formal equation (with leakage filter), variables auto-renamed
to variant names via the dataset's rename map
- canonical_T2: the dataset's canonical variant solution truncated at first
formal equation (no rename needed; already in variant naming)
- null: generic content-free scaffold
Truncation rule (event-boundary):
1. Find the FIRST display-math block ($$...$$, \\[...\\], \\begin{equation/align/...})
2. If none, fall back to the first line containing a substantive math relation
(>=, <=, =, <, >, ≡, ∈) that is not merely a definition (e.g., 'let x:=...')
3. The T2 prefix INCLUDES that first formal relation
4. Apply leakage filter BEFORE returning: stop at the earliest of:
- any line containing \\boxed
- any line containing 'therefore', 'hence', 'we conclude', 'the answer',
'we obtain', 'thus', 'it suffices', 'we have proved', 'as a result'
- any line containing the dataset's recorded final_answer string
"""
from __future__ import annotations
import re
from typing import Optional, Dict
# ---------- Display-math detection ----------
# Order matters: try richest patterns first
_DISPLAY_MATH_PATTERNS = [
re.compile(r"\$\$.+?\$\$", re.DOTALL),
re.compile(r"\\\[.+?\\\]", re.DOTALL),
re.compile(r"\\begin\{equation\*?\}.+?\\end\{equation\*?\}", re.DOTALL),
re.compile(r"\\begin\{align\*?\}.+?\\end\{align\*?\}", re.DOTALL),
re.compile(r"\\begin\{gather\*?\}.+?\\end\{gather\*?\}", re.DOTALL),
re.compile(r"\\begin\{eqnarray\*?\}.+?\\end\{eqnarray\*?\}", re.DOTALL),
]
def _first_display_math_end(text: str) -> Optional[int]:
"""Return the end position of the first display-math block, or None."""
earliest = None
for pat in _DISPLAY_MATH_PATTERNS:
m = pat.search(text)
if m:
if earliest is None or m.end() < earliest:
earliest = m.end()
return earliest
# Inline relation fallback: first line with a "real" relation
_INLINE_REL_RE = re.compile(
r"[A-Za-z\)\]\}\d_]\s*(?:=|<|>|\\le[q]?|\\ge[q]?|\\equiv|\\in)\s*[A-Za-z\(\[\{\d\\\-]"
)
# Definition exclusion: lines that are 'let x = ...' or 'denote ...' are setup,
# not actual derivations. We allow them in the prefix but don't stop on them.
_DEFINITION_RE = re.compile(
r"^\s*(?:let|denote|define|set|put|call|consider|introduce|let us)\b",
re.IGNORECASE
)
def _first_inline_relation_line_end(text: str) -> Optional[int]:
"""Find the end of the first line containing a non-definition math relation.
Returns absolute character offset (one past the newline)."""
pos = 0
while pos < len(text):
nl = text.find("\n", pos)
line_end = nl if nl != -1 else len(text)
line = text[pos:line_end]
if _INLINE_REL_RE.search(line) and not _DEFINITION_RE.search(line):
return line_end + 1 if nl != -1 else line_end
pos = line_end + 1
if nl == -1:
break
return None
# ---------- Leakage detection ----------
LEAKAGE_PATTERNS = [
re.compile(r"\\boxed\b", re.IGNORECASE),
re.compile(r"\btherefore\b", re.IGNORECASE),
re.compile(r"\bhence\b", re.IGNORECASE),
re.compile(r"\bwe conclude\b", re.IGNORECASE),
re.compile(r"\bthe answer\b", re.IGNORECASE),
re.compile(r"\bwe obtain\b", re.IGNORECASE),
re.compile(r"\bthus\b", re.IGNORECASE),
re.compile(r"\bit suffices\b", re.IGNORECASE),
re.compile(r"\bwe have proved\b", re.IGNORECASE),
re.compile(r"\bwe have shown\b", re.IGNORECASE),
re.compile(r"\bas a result\b", re.IGNORECASE),
re.compile(r"\bin conclusion\b", re.IGNORECASE),
re.compile(r"\bthe final answer\b", re.IGNORECASE),
re.compile(r"\bso the answer\b", re.IGNORECASE),
]
def _first_leakage_pos(text: str, final_answer: Optional[str] = None) -> Optional[int]:
"""Return the starting char position of the earliest leakage marker."""
earliest = None
for pat in LEAKAGE_PATTERNS:
m = pat.search(text)
if m:
if earliest is None or m.start() < earliest:
earliest = m.start()
if final_answer:
# Final-answer leakage: only check if the answer string is non-trivial
fa = final_answer.strip()
if 8 <= len(fa) <= 200:
idx = text.find(fa)
if idx != -1:
if earliest is None or idx < earliest:
earliest = idx
return earliest
# ---------- T2 truncation ----------
MIN_PREFIX_CHARS = 50
MAX_PREFIX_CHARS = 2400 # roughly 600 tokens
def truncate_T2(text: str, final_answer: Optional[str] = None) -> Optional[str]:
"""Return the T2 (after-first-equation) prefix, or None if not detectable.
T2 = up to and including the first formal equation, then capped by leakage
filter and MAX_PREFIX_CHARS.
"""
if not text:
return None
end = _first_display_math_end(text)
if end is None:
end = _first_inline_relation_line_end(text)
if end is None:
return None
prefix = text[:end]
# Apply leakage filter BEFORE the equation if a leakage marker appears earlier
leak = _first_leakage_pos(prefix, final_answer)
if leak is not None and leak < end:
prefix = text[:leak].rstrip()
# Cap length
if len(prefix) > MAX_PREFIX_CHARS:
prefix = prefix[:MAX_PREFIX_CHARS]
# Trim at last newline to avoid cutting mid-sentence
last_nl = prefix.rfind("\n")
if last_nl > MIN_PREFIX_CHARS:
prefix = prefix[:last_nl]
if len(prefix) < MIN_PREFIX_CHARS:
return None
return prefix.rstrip()
# ---------- Variable rename for own prefix ----------
def rename_own_prefix(prefix: str, rename_map: Dict[str, str]) -> str:
"""Apply orig->variant rename mapping to the model's own prefix.
Sort longest-first to avoid prefix collisions (e.g., 'al' eating 'almondtree').
Use word-boundary regex. Pass replacement via lambda to avoid escape-sequence
interpretation when the variant name starts with '\\x', '\\g', etc.
"""
if not prefix or not rename_map:
return prefix
items = sorted(rename_map.items(), key=lambda kv: -len(kv[0]))
out = prefix
for src, dst in items:
if not src:
continue
pat = r"(?<![A-Za-z0-9_])" + re.escape(src) + r"(?![A-Za-z0-9_])"
# Use a lambda so dst is treated literally (no \1, \x, etc. escapes).
out = re.sub(pat, lambda _m, _dst=dst: _dst, out)
return out
# ---------- Null scaffold ----------
NULL_SCAFFOLD = (
"Let us proceed carefully. We will first identify the relevant variables "
"and their roles, then state the governing relations of the problem, and "
"finally develop the argument step by step."
)
# ---------- Prompt builders ----------
# We tell the model to PRODUCE the complete solution that begins with the
# provided prefix verbatim. This means the grader will see one continuous
# solution that starts with the injected setup. The instruction to begin
# verbatim avoids the model paraphrasing the prefix and removing the very
# representational anchor we are testing.
RESCUE_USER_TEMPLATE = """Please solve the following mathematical problem.
PROBLEM:
{problem_statement}
You must structure your solution as a continuation of the partial work below.
Begin your solution with the partial work copied verbatim, then continue
seamlessly to a complete answer.
PARTIAL WORK (to copy verbatim at the start of your solution):
{prefix}
Provide a complete, rigorous solution. Return your response in JSON format:
{{"solution": "your complete solution starting with the partial work above and continuing to the end",
"final_answer": "your final answer in clear, concise form"}}"""
NULL_USER_TEMPLATE = """Please solve the following mathematical problem.
PROBLEM:
{problem_statement}
{scaffold}
Provide a complete, rigorous solution. Return your response in JSON format:
{{"solution": "your complete step-by-step solution",
"final_answer": "your final answer in clear, concise form"}}"""
def build_rescue_prompt(problem_statement: str, prefix: str) -> str:
return RESCUE_USER_TEMPLATE.format(
problem_statement=problem_statement, prefix=prefix)
def build_null_prompt(problem_statement: str) -> str:
return NULL_USER_TEMPLATE.format(
problem_statement=problem_statement, scaffold=NULL_SCAFFOLD)
# ---------- Smoke test ----------
if __name__ == "__main__":
# Quick smoke test on a real flip case
import json
import sys
sys.path.insert(0, "/home/yurenh2/gap/analysis")
from structural_overlap import find_variant_file, load_problems
# Pick gpt-4.1-mini original on a known problem
op = find_variant_file(
__import__("pathlib").Path("/home/yurenh2/gap/results_new/gpt-4.1-mini"),
"original")
probs = {p["index"]: p for p in load_problems(op)}
sample = next(p for idx, p in probs.items()
if p.get("correct") is True and (p.get("solve") or {}).get("solution"))
text = sample["solve"]["solution"]
fa = sample["solve"].get("final_answer")
print(f"Sample index: {sample['index']}, type: {sample['problem_type']}")
print(f"Original solution length: {len(text)} chars")
print(f"Recorded final_answer: {fa[:200] if fa else None!r}")
pre = truncate_T2(text, fa)
print(f"\n--- T2 PREFIX ({len(pre or '')} chars) ---")
print(pre)
print("--- END ---")
# Test rename: load 1987-B-2 dataset to get a sample map
ds = json.load(open("/home/yurenh2/gap/putnam-bench-anon/dataset/1987-B-2.json"))
rmap_raw = ds["variants"]["garbled_string"]["map"]
rmap = (eval(rmap_raw, {"__builtins__": {}}, {})
if isinstance(rmap_raw, str) else rmap_raw)
print(f"\nRename map: {rmap}")
test_text = "Let n be a positive integer and let f be a continuous function. Then $f(n) = 0$."
print(f"\nOriginal: {test_text}")
print(f"Renamed: {rename_own_prefix(test_text, rmap)}")
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