"""Tests for the grading module and the unified post-answer pipeline. ``grade_answer`` is the pure correctness check. ``classify_error`` is the coarse wrong-answer tagger. ``LearningService.grade_and_record`` folds both of those through the full record -> mastery -> spaced-repetition pipeline and is fail-closed: with no stored expected answer the attempt is recorded wrong. """ from deeptutor.learning.grading import classify_error, grade_answer from deeptutor.learning.models import ( ErrorType, KnowledgePoint, KnowledgeType, LearningModule, LearningProgress, ) from deeptutor.learning.scheduler import SpacedRepetitionScheduler from deeptutor.learning.service import LearningService from deeptutor.learning.storage import LearningStore class TestChoiceGrading: def test_choice_exact_match(self): assert grade_answer("A", "A", "choice") is True def test_choice_case_insensitive(self): assert grade_answer("b", "B", "choice") is True def test_choice_with_spaces(self): assert grade_answer("A ", " A", "choice") is True def test_choice_wrong(self): assert grade_answer("C", "A", "choice") is False class TestShortGrading: def test_short_exact_match(self): assert grade_answer("photosynthesis", "photosynthesis", "short") is True def test_short_fuzzy_pass(self): # "photosynthesi" vs "photosynthesis" — high similarity assert grade_answer("photosynthesi", "photosynthesis", "short") is True def test_short_fuzzy_fail(self): assert grade_answer("completely different", "photosynthesis", "short") is False def test_short_long_expected_no_fuzzy(self): long_expected = "a" * 31 # >30 chars, no fuzzy assert grade_answer(long_expected, long_expected, "short") is True assert grade_answer("something else entirely", long_expected, "short") is False class TestOpenGrading: def test_open_keywords_pass(self): expected = "cell membrane, nucleus, mitochondria" user = "The cell has a cell membrane and nucleus, with mitochondria for energy" assert grade_answer(user, expected, "open") is True def test_open_keywords_fail(self): expected = "cell membrane, nucleus, mitochondria" user = "I don't know anything about cells" assert grade_answer(user, expected, "open") is False def test_open_chinese_separators(self): expected = "光合作用；叶绿体；二氧化碳" user = "光合作用发生在叶绿体中，需要二氧化碳" assert grade_answer(user, expected, "open") is True class TestEdgeCases: def test_empty_expected_returns_false(self): assert grade_answer("anything", "", "short") is False assert grade_answer("anything", " ", "short") is False def test_empty_user_answer(self): assert grade_answer("", "expected", "short") is False def test_substring_no_longer_matches(self): """Regression: 'expected in user' substring match must not cause false positive.""" user = "I do not know electromagnetic induction but maybe something else" expected = "electromagnetic induction" assert grade_answer(user, expected, "short") is False def test_unknown_type_returns_false(self): assert grade_answer("a", "a", "unknown") is False class TestClassifyError: """Coarse wrong-answer tagging used by the post-answer pipeline. Blank means "I didn't know" (metacognitive); anything else is treated as a wrong application. The richer taxonomy is assigned later by the LLM. """ def test_blank_answer_is_metacognitive(self): assert classify_error("") is ErrorType.METACOGNITIVE def test_whitespace_only_answer_is_metacognitive(self): assert classify_error(" \n\t ") is ErrorType.METACOGNITIVE def test_nonblank_answer_is_application_error(self): assert classify_error("the answer is 42") is ErrorType.APPLICATION_ERROR def _progress_with_kp(kp_type: KnowledgeType = KnowledgeType.CONCEPT) -> LearningProgress: progress = LearningProgress(book_id="book1") progress.modules = [ LearningModule( id="m1", name="Module 1", order=0, knowledge_points=[KnowledgePoint(id="kp1", name="KP1", type=kp_type, module_id="m1")], ) ] progress.knowledge_types["kp1"] = kp_type return progress class TestGradeAndRecordFailClosed: """``grade_and_record`` is the single post-answer pipeline. It must never grade an answer correct when there is no stored expected answer, and it must fold correctness through attempt history, mastery, and error records.""" def test_no_expected_answer_is_wrong_and_records_error(self, tmp_path): service = LearningService(LearningStore(root=tmp_path)) progress = _progress_with_kp() result = service.grade_and_record( progress, question_id="q1", knowledge_point_id="kp1", module_id="m1", user_answer="anything plausible", expected_answer="", # missing expected -> fail-closed ) assert result is False assert len(progress.quiz_attempts) == 1 attempt = progress.quiz_attempts[0] assert attempt.is_correct is False # Non-blank wrong answer is an application error and opens an error record. assert attempt.error_type is ErrorType.APPLICATION_ERROR assert len(progress.error_records) == 1 assert progress.error_records[0].status == "active" assert progress.error_records[0].error_type is ErrorType.APPLICATION_ERROR def test_blank_wrong_answer_is_metacognitive(self, tmp_path): service = LearningService(LearningStore(root=tmp_path)) progress = _progress_with_kp() result = service.grade_and_record( progress, question_id="q1", knowledge_point_id="kp1", module_id="m1", user_answer="", expected_answer="photosynthesis", ) assert result is False assert progress.quiz_attempts[0].error_type is ErrorType.METACOGNITIVE def test_correct_answer_records_and_caps_single_attempt_mastery(self, tmp_path): service = LearningService(LearningStore(root=tmp_path)) progress = _progress_with_kp() result = service.grade_and_record( progress, question_id="q1", knowledge_point_id="kp1", module_id="m1", user_answer="photosynthesis", expected_answer="photosynthesis", ) assert result is True assert progress.quiz_attempts[0].is_correct is True assert progress.quiz_attempts[0].error_type is None # A single correct attempt is capped at low confidence (0.5), never 1.0. assert progress.mastery_levels["kp1"] == 0.5 assert progress.error_records == [] def test_correct_answer_graduates_existing_error_record(self, tmp_path): service = LearningService(LearningStore(root=tmp_path)) progress = _progress_with_kp() # First a wrong answer opens an error record... service.grade_and_record( progress, question_id="q1", knowledge_point_id="kp1", module_id="m1", user_answer="wrong guess", expected_answer="photosynthesis", ) assert progress.error_records[0].status == "active" # ...then a correct retry graduates it. service.grade_and_record( progress, question_id="q1", knowledge_point_id="kp1", module_id="m1", user_answer="photosynthesis", expected_answer="photosynthesis", ) assert progress.error_records[0].status == "graduated" def test_persists_through_store(self, tmp_path): store = LearningStore(root=tmp_path) service = LearningService(store) progress = _progress_with_kp() service.grade_and_record( progress, question_id="q1", knowledge_point_id="kp1", module_id="m1", user_answer="photosynthesis", expected_answer="photosynthesis", ) loaded = store.load("book1") assert loaded is not None assert len(loaded.quiz_attempts) == 1 assert loaded.mastery_levels["kp1"] == 0.5 def test_scheduler_advances_repetition_and_builds_queue(self, tmp_path): store = LearningStore(root=tmp_path) service = LearningService(store) scheduler = SpacedRepetitionScheduler() progress = _progress_with_kp(KnowledgeType.CONCEPT) service.grade_and_record( progress, question_id="q1", knowledge_point_id="kp1", module_id="m1", user_answer="photosynthesis", expected_answer="photosynthesis", scheduler=scheduler, ) # A repetition state was created and the review queue rebuilt from it. assert "kp1" in progress.repetition_states assert len(progress.review_queue) == 1 assert progress.review_queue[0].knowledge_point_id == "kp1"