Zayden-Jung
d3555d9a52
Replaces the previous tree entirely. The pipeline is four separable pieces, each
testable on its own:
1. leanbench/llm.py provider-neutral OpenAI-compatible connector, stdlib only,
with retries, JSON coercion and a scripted client so the
rest of the code is testable without a network.
2. leanbench/detect.py per-page detection of formalizable mathematics. Case 1 is
mathematics asserted as fact (definition/theorem/lemma/...,
deliberately not sub-classified); case 2 is a problem left
open to the reader. Hits come back as spans -- start page
and index, end page and index -- so several per page is
normal. A hit cut off by the page end makes the detector
re-read that page together with the next, repeatedly, so an
item spread over three pages is found whole.
Offsets come from verbatim quotes resolved by
leanbench/anchors.py (exact -> whitespace-insensitive ->
fuzzy), because models quote well and count badly.
3. leanbench/formalize.py + leanbench/verify.py
each span becomes one Lean 4 declaration, judged by the real
compiler: full elaboration for case 1, statement legality
only for case 2, which has no proof to check. Lean's own
diagnostics feed back for a repair attempt. "verified" (Lean
accepted it) and "proved" (accepted with no sorry) are kept
strictly apart.
4. leanbench/db.py indexed SQLite plus JSONL export. Every item is indexed by
the types of its inputs, or by its own type when it is not a
proof, and records the source book (sha256) and the page it
starts on -- so `drop --source H --pages A-B` followed by a
re-ingest redoes exactly those pages and nothing else.
Also: lean/ Lake project pinned to Mathlib, docker/ image carrying Lean 4 and a
prebuilt Mathlib (the Mathlib revision and the toolchain are resolved against each
other at build time rather than both hardcoded), and .gitea/workflows for tests,
image build and push to the Gitea registry, and a manual "submit a book" run.
58 tests; they need neither network nor Lean.
91 lines
3.5 KiB
Python
91 lines
3.5 KiB
Python
from __future__ import annotations
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from leanbench.detect import KIND_PROBLEM, KIND_STATEMENT, Detection
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from leanbench.formalize import formalize, formalize_all, verification_mode
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from leanbench.llm import ScriptedClient
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from leanbench.verify import MODE_FULL, MODE_STATEMENT
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from .conftest import formalize_reply
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def make_detection(kind: str = KIND_STATEMENT) -> Detection:
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return Detection(
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kind=kind,
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label="Theorem 1.6.2",
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summary="divisibility is additive",
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start_page=12,
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start_index=100,
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end_page=12,
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end_index=260,
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text="Theorem 1.6.2. If a divides b and a divides c then a divides b + c.",
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)
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def test_open_problems_are_only_checked_as_statements() -> None:
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assert verification_mode(make_detection(KIND_PROBLEM)) == MODE_STATEMENT
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assert verification_mode(make_detection(KIND_STATEMENT)) == MODE_FULL
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def test_formalize_produces_verified_code_and_types(fake_checker) -> None:
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client = ScriptedClient([formalize_reply()])
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result = formalize(client, make_detection(), checker=fake_checker)
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assert result.lean_code.startswith("theorem test_decl")
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assert result.verified
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assert not result.proved, "a sorry in the code means it is not proved"
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assert ("Int", "input") in result.index_types
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def test_a_real_proof_counts_as_proved(fake_checker) -> None:
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client = ScriptedClient(
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[formalize_reply(lean_code="theorem t (n : Nat) : n = n := rfl", has_proof=True)]
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)
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result = formalize(client, make_detection(), checker=fake_checker)
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assert result.has_proof and result.proved
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def test_lean_diagnostics_drive_a_repair_attempt(fake_checker) -> None:
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client = ScriptedClient(
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[
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formalize_reply(lean_code="theorem t : BAD := by sorry"),
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formalize_reply(lean_code="theorem t (n : Nat) : n = n := rfl", has_proof=True),
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]
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)
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result = formalize(client, make_detection(), checker=fake_checker, repair_attempts=1)
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assert result.attempts == 2
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assert result.verified
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assert len(client.calls) == 2
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repair_prompt = client.calls[1][-1]["content"]
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assert "error: bad" in repair_prompt, "the compiler's own words go back to the model"
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def test_repair_gives_up_after_the_budget(fake_checker) -> None:
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client = ScriptedClient([formalize_reply(lean_code="theorem t : BAD := by sorry")] * 3)
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result = formalize(client, make_detection(), checker=fake_checker, repair_attempts=1)
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assert result.attempts == 2
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assert not result.verified
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def test_model_may_decline_an_unformalizable_passage(fake_checker) -> None:
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client = ScriptedClient(['{"skip": true, "reason": "prose only"}'])
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result = formalize(client, make_detection(), checker=fake_checker)
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assert result.skipped and result.skip_reason == "prose only"
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assert fake_checker.calls == []
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def test_imports_inside_the_body_are_stripped(fake_checker) -> None:
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client = ScriptedClient(
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[formalize_reply(lean_code="import Mathlib\ntheorem t (n : Nat) : n = n := rfl")]
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)
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result = formalize(client, make_detection(), checker=fake_checker)
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assert "import" not in result.lean_code
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def test_one_bad_item_does_not_stop_the_batch(fake_checker) -> None:
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client = ScriptedClient(["garbage, not json", formalize_reply()])
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results = formalize_all(
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client, [make_detection(), make_detection(KIND_PROBLEM)], checker=fake_checker
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)
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assert len(results) == 2
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assert results[0].skipped and "formalizer failed" in results[0].skip_reason
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assert results[1].verified
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