732642856
267 lines
11 KiB
Python
267 lines
11 KiB
Python
#!/usr/bin/env python3
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"""Regression tests for source-pack content contracts beyond visibility."""
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from __future__ import annotations
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import json
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import subprocess
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import sys
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from pathlib import Path
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from mcp_server import _collect_strict_evidence, _existing_interpretation_source_pack
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ROOT = Path(__file__).resolve().parents[1]
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CORE5 = [
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"references/prediction-boundary-protocol.md",
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"references/event_judgment_skeleton.md",
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"references/planetary-dignity-complete-reference.md",
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"references/retrograde-combustion-war-guide.md",
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"references/transit-multi-reference-guide.md",
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]
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PROMOTE_BATCH2 = [
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"references/vimshottari_dasha_guide.md",
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"references/pratyantar-calculation-guide.md",
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"references/divisional-chart-deep-reading.md",
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"references/shadbala-complete-methodology.md",
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"references/ashtakavarga-complete-system.md",
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"references/tajika-yoga-complete-guide.md",
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"references/jaimini-complete-system.md",
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"references/kp-astrology-complete-system.md",
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"references/argala-complete-guide.md",
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"references/badhaka-obstacle-planet-guide.md",
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"references/condition-dasha-complete.md",
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]
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REFERENCE_ONLY = [
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"references/dasa-convergence-methodology.md",
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"references/multi-dasha-convergence-protocol.md",
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"references/yoga-strength-scoring-system.md",
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]
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NON_RUNTIME = [
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"references/varga-system-quick-reference.md",
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"references/yoga-list-chinese.md",
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"references/analysis-full-reading-v4.0.md",
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"references/analysis-full-reading-v1.8-review.md",
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"references/audit-skill-full-test-2026-05-04.md",
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"references/feature-gap-matrix-2026.md",
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"references/kp-practical-event-timing.md",
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"references/consultation-case-library.md",
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]
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def _base_modules() -> dict:
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return {
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"modules": {
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"chart": {
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"ascendant": {"sign": "Leo"},
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"planets": {
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"Sun": {"status": "中性(Neutral)"},
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"Moon": {"status": "中性(Neutral)"},
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"Mercury": {"status": "中性(Neutral)"},
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"Venus": {"status": "中性(Neutral)"},
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"Jupiter": {"status": "中性(Neutral)"},
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"Saturn": {"status": "中性(Neutral)"},
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},
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},
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"varga_full": {
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"D10_Dasamsa": {"summary": "career varga present"},
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"D9_Navamsha": {"summary": "relationship varga present"},
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"D2_Hora": {"summary": "wealth varga present"},
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"D11_Rudramsha": {"summary": "gains varga present"},
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},
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"special_lagnas": {
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"A10_Karma_Pada": {"sign": "Capricorn", "lord": "Saturn"},
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"Upapada_Lagna": {"sign": "Libra", "lord": "Venus"},
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},
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"jaimini": {
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"karakas": {
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"Amatyakaraka": {"planet": "Mercury"},
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"Atmakaraka": {"planet": "Sun"},
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"Darakaraka": {"planet": "Venus"},
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},
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"karakamsha": {"karakamsha_sign": "Leo", "karakamsha_lord": "Sun"},
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},
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"dasha": {"current_dasha": {"mahadasha": "Mercury", "antardasha": "Sun"}},
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"narayana_dasha": {"current_dasha": {"sign": "Capricorn", "lord": "Saturn"}},
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"dasa_convergence": {
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"domain_activations": {
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"career_status": {"convergence_level": "L2", "probability": "35-50%"},
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"marriage_relationship": {"convergence_level": "L2", "probability": "35-50%"},
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"wealth_income": {"convergence_level": "L2", "probability": "35-50%"},
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}
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},
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}
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}
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def _run_engine(*args: str) -> dict:
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completed = subprocess.run(
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[sys.executable, "scripts/jyotish_engine.py", *args],
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cwd=ROOT,
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check=False,
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text=True,
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capture_output=True,
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timeout=180,
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)
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assert completed.returncode == 0, completed.stderr[-2000:] or completed.stdout[-2000:]
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return json.loads(completed.stdout)
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def test_core5_sources_drive_prediction_boundary_contract_for_all_strict_routes() -> None:
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for route in ["career", "relationship", "finance"]:
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strict = _collect_strict_evidence(route, _base_modules())
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contract = strict["prediction_boundary_contract"]
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assert contract["source_refs"] == CORE5
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assert contract["event_judgment_skeleton"]["required_sections"] == [
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"promise",
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"activation",
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"manifestation",
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"label",
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]
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assert contract["promise"]["status"] == strict["adjudication_stages"]["promise"]["status"]
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assert contract["activation"]["status"] == strict["adjudication_stages"]["activation"]["status"]
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assert contract["manifestation"]["status"] == strict["adjudication_stages"]["manifestation"]["status"]
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assert contract["confidence_boundary"]["mevg_status"] == "blocked"
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assert contract["confidence_boundary"]["real_case_calibration_status"] == "blocked"
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assert contract["confidence_boundary"]["unverified_claim_policy"] == "downgrade_or_block"
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def test_batch2_and_reference_only_layers_are_wired_without_polluting_truth_sources() -> None:
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source_pack = _existing_interpretation_source_pack()
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assert source_pack["promote_batch2_topic_layer"]["status"] == "available"
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assert source_pack["promote_batch2_topic_layer"]["source_refs"] == PROMOTE_BATCH2
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assert source_pack["reference_only_conflict_layer"]["status"] == "available"
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assert source_pack["reference_only_conflict_layer"]["source_refs"] == REFERENCE_ONLY
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assert source_pack["reference_only_conflict_layer"]["promotion_status"] == "reference_only"
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runtime_refs = set(source_pack["source_refs"])
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for path in PROMOTE_BATCH2 + REFERENCE_ONLY:
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assert path in runtime_refs
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for path in NON_RUNTIME:
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assert path not in runtime_refs
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inventory = source_pack["interpretation_source_inventory"]
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assert inventory["layers"]["promote_batch2_topic_sources"]["source_refs"] == PROMOTE_BATCH2
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assert inventory["layers"]["reference_only_conflict_sources"]["source_refs"] == REFERENCE_ONLY
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assert inventory["summary"]["blocked_non_runtime_count"] >= len(NON_RUNTIME)
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def test_prompt_pack_and_real_reading_regression_expose_content_contracts() -> None:
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result = _run_engine(
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"full-reading",
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"--year",
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"1955",
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"--month",
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"2",
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"--day",
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"24",
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"--hour",
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"19",
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"--minute",
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"15",
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"--lat",
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"37.7749",
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"--lon",
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"-122.4194",
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"--tz",
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"8",
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"--today",
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"2026-07-02",
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"--transit-date",
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"2026-07-02",
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)
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prompt_pack = result["ai_prompt_pack"]
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snapshot = prompt_pack["evidence_snapshot"]
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assert snapshot["prediction_boundary_contract"]["source_refs"] == CORE5
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assert snapshot["interpretation_source_pack"]["core_rule_source_refs"] == CORE5
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assert snapshot["interpretation_source_pack"]["promote_batch2_source_refs"] == PROMOTE_BATCH2
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assert snapshot["interpretation_source_pack"]["reference_only_source_refs"] == REFERENCE_ONLY
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assert "必须按 promise → activation → manifestation → label 输出" in prompt_pack["prompt_zh"]
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assert "未完成 MEVG / Real Case Calibration 时必须降级或标 blocked" in prompt_pack["prompt_zh"]
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docs = prompt_pack["retrieval_plan"]["local_reference_docs"]
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for path in CORE5 + PROMOTE_BATCH2 + REFERENCE_ONLY:
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assert path in docs
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for path in NON_RUNTIME:
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assert path not in docs
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for route in ["career", "relationship", "finance"]:
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contract = snapshot["strict_workflow_contracts"][route]
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assert contract["prediction_boundary_contract"]["source_refs"] == CORE5
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audit = contract["technique_audit_summary"]
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assert audit["mevg_global_web_evidence"]["status"] == "blocked"
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assert audit["real_case_calibration"]["status"] == "blocked"
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assert audit["interpretation_source_pack"]["core_rule_source_refs"] == CORE5
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def test_real_case_studies_batch1_is_exposed_as_local_retrieval_layer() -> None:
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source_pack = _existing_interpretation_source_pack()
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case_layer = source_pack["real_case_calibration_layer"]
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assert case_layer["batch_id"] == "real_case_studies_batch1"
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assert case_layer["index_status"] == "available"
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assert case_layer["status"] == "queued"
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assert "career" in case_layer["case_index_by_domain"]
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assert "finance" in case_layer["case_index_by_domain"]
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assert "relationship" in case_layer["case_index_by_domain"]
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assert (
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"references/real_case_studies/vedicka/career-success-poverty-prosperity.md"
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in case_layer["case_index_by_domain"]["career"]
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)
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assert (
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"docs/benchmark/legacy-marriage-v6.1/verify-results-v6.1.json"
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in case_layer["case_index_by_domain"]["relationship"]
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)
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assert (
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"references/real_case_studies/vedicka/career-success-poverty-prosperity.md"
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in source_pack["source_refs"]
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)
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assert source_pack["real_case_calibration"]["local_index_status"] == "available"
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assert source_pack["real_case_calibration"]["status"] == "blocked"
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def test_open_source_batches_and_external_gaps_are_visible_without_polluting_truth() -> None:
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source_pack = _existing_interpretation_source_pack()
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rishi_layer = source_pack["rishi_ai_mcp_batch1_layer"]
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assert rishi_layer["status"] == "available"
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assert rishi_layer["promotion_status"] == "open_source_reference_layer"
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assert rishi_layer["runtime_truth_status"] == "not_primary_truth"
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assert "career" in rishi_layer["domain_map"]
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assert "relationship" in rishi_layer["domain_map"]
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assert "references/open_source_sources/rishi-ai-mcp/.agents/rules/rishi-ai.md" in rishi_layer["source_refs"]
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assert (
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"references/open_source_sources/rishi-ai-mcp/.agents/workflows/career-analysis.md"
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in rishi_layer["domain_map"]["career"]
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)
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vedic_layer = source_pack["vedic_astro_skills_batch1_layer"]
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assert vedic_layer["status"] == "available"
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assert vedic_layer["promotion_status"] == "external_skill_reference_layer"
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assert vedic_layer["runtime_truth_status"] == "not_primary_truth"
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assert "calculator" in vedic_layer["domain_map"]
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assert "references/open_source_sources/vedic-astro-skills/codex/skills/vedic-core/SKILL.md" in vedic_layer["source_refs"]
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assert (
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"references/open_source_sources/vedic-astro-skills/codex/skills/vedic-reader/resources/data_contract.md"
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in vedic_layer["domain_map"]["reader_validation"]
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)
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external_gaps = source_pack["external_closure_gap_layer"]
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assert external_gaps["vedastro_official"]["status"] == "blocked"
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assert external_gaps["oracle_parity"]["status"] == "blocked"
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assert external_gaps["install_usage_path"]["status"] == "needs_slimming"
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queue = source_pack["remaining_priority1_batch_queue"]
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assert queue["next_batches"] == [
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"references_batch2",
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"vedastro_official_default_closure",
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"external_oracle_parity_batch",
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"install_usage_path_slimming",
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]
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