Didactopus/tests/test_pack_emitter.py

85 lines
3.5 KiB
Python

from pathlib import Path
import yaml
from didactopus.course_ingest import parse_markdown_course, extract_concept_candidates
from didactopus.knowledge_graph import write_knowledge_graph
from didactopus.rule_policy import RuleContext, build_default_rules, run_rules
from didactopus.pack_emitter import build_draft_pack, write_draft_pack, write_source_corpus
SAMPLE = '''
# Sample Course
## Module 1
### Lesson A
- Objective: Explain Topic A.
- Exercise: Do task A.
Topic A body.
'''
def test_emit_pack(tmp_path: Path) -> None:
course = parse_markdown_course(SAMPLE, "Sample Course")
concepts = extract_concept_candidates(course)
ctx = RuleContext(course=course, concepts=concepts)
run_rules(ctx, build_default_rules())
draft = build_draft_pack(course, ctx.concepts, "Tester", "REVIEW", ctx.review_flags)
write_draft_pack(draft, tmp_path)
write_source_corpus(course, tmp_path)
write_knowledge_graph(course, ctx.concepts, tmp_path)
assert (tmp_path / "pack.yaml").exists()
assert (tmp_path / "review_report.md").exists()
assert (tmp_path / "source_corpus.json").exists()
assert (tmp_path / "knowledge_graph.json").exists()
def test_emit_pack_can_write_groundrecall_query_bundle(tmp_path: Path) -> None:
course = parse_markdown_course(SAMPLE, "Sample Course")
concepts = extract_concept_candidates(course)
ctx = RuleContext(course=course, concepts=concepts)
run_rules(ctx, build_default_rules())
groundrecall_bundle = {
"bundle_kind": "groundrecall_query_bundle",
"concept": {"concept_id": "concept::topic-a", "title": "Topic A"},
"review_candidates": [{"candidate_id": "concept::topic-a", "rationale": "Topic A | lane=knowledge_capture | priority=20"}],
}
draft = build_draft_pack(
course,
ctx.concepts,
"Tester",
"REVIEW",
ctx.review_flags,
groundrecall_query_bundle=groundrecall_bundle,
)
write_draft_pack(draft, tmp_path)
pack_yaml = (tmp_path / "pack.yaml").read_text(encoding="utf-8")
bundle_payload = (tmp_path / "groundrecall_query_bundle.json").read_text(encoding="utf-8")
notebook_payload = (tmp_path / "notebook_page.json").read_text(encoding="utf-8")
assert "groundrecall_query_bundle.json" in pack_yaml
assert "notebook_page.json" in pack_yaml
assert '"bundle_kind": "groundrecall_query_bundle"' in bundle_payload
assert '"page_kind": "didactopus_notebook_page"' in notebook_payload
def test_emit_pack_preserves_richer_concept_fields(tmp_path: Path) -> None:
sample = """
# OCW Slice
## Broader Applications
### Thermodynamics and Entropy
- Objective: Explain how thermodynamic entropy relates to, and differs from, Shannon entropy.
- Exercise: Compare the two entropy notions and identify what is preserved across the analogy.
Entropy is a measure of uncertainty in the source model. The analogy is useful but dangerous when used loosely.
"""
course = parse_markdown_course(sample, "OCW Slice")
concepts = extract_concept_candidates(course)
ctx = RuleContext(course=course, concepts=concepts)
run_rules(ctx, build_default_rules())
draft = build_draft_pack(course, ctx.concepts, "Tester", "REVIEW", ctx.review_flags)
write_draft_pack(draft, tmp_path)
concepts_yaml = yaml.safe_load((tmp_path / "concepts.yaml").read_text(encoding="utf-8"))
concept = concepts_yaml["concepts"][0]
assert concept["source_role"] == "nuance"
assert concept["distinctions"]
assert concept["definition_candidates"]
assert concept["qualification_candidates"]