Merge pull request #1223 from MemPalace/chore/corpus-origin-merge-followup
chore(corpus-origin): tag merged evidence by tier + pin confidence-source contract
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+15
-2
@@ -149,8 +149,21 @@ def _run_pass_zero(project_dir, palace_dir, llm_provider) -> dict:
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result.user_name = llm_result.user_name
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if llm_result.agent_persona_names:
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result.agent_persona_names = list(llm_result.agent_persona_names)
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# Combine evidence — keep both signal trails for the audit record.
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result.evidence = list(result.evidence) + list(llm_result.evidence)
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# Combine evidence — keep both signal trails for the audit record,
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# prefixed so the on-disk origin.json says which tier produced
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# each entry. Idempotent: re-prefixing an already-tagged entry
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# is a no-op.
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tier1_prefix = "Tier-1 heuristic: "
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tier2_prefix = "Tier-2 LLM: "
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heuristic_evidence = [
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s if s.startswith(tier1_prefix) else f"{tier1_prefix}{s}"
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for s in (str(e) for e in result.evidence)
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]
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llm_evidence = [
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s if s.startswith(tier2_prefix) else f"{tier2_prefix}{s}"
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for s in (str(e) for e in llm_result.evidence)
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]
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result.evidence = heuristic_evidence + llm_evidence
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except Exception as exc: # noqa: BLE001 — never block init on LLM failure
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print(f" LLM corpus-origin tier failed ({exc}); using heuristic only.")
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@@ -1483,6 +1483,19 @@ def test_merge_tier_fields_heuristic_yes_llm_no_keeps_heuristic_bool():
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f"Merged result must KEEP heuristic's True, not flip to False. "
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f"Got: {res}"
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)
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# The bool and the confidence are paired — both must come from the
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# heuristic. Compare to detect_origin_heuristic on the same samples
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# so this stays correct regardless of what the heuristic computes
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# for these samples (avoids brittleness vs. a hardcoded sentinel).
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from mempalace.corpus_origin import detect_origin_heuristic
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expected_confidence = detect_origin_heuristic(_ai_dialogue_samples()).confidence
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assert res["confidence"] == expected_confidence, (
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f"Merged confidence {res['confidence']} did not match the heuristic's "
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f"{expected_confidence} for these samples. The mocked LLM returned "
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f"0.90; if the merge accidentally took the LLM's confidence, the "
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f"merged value would not equal the heuristic's. Got: {res}"
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)
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# Persona/user/platform from LLM should still be merged in.
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assert res["agent_persona_names"] == [
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"Echo",
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@@ -1539,6 +1552,13 @@ def test_merge_tier_fields_heuristic_no_no_personas_leak():
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assert (
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res["agent_persona_names"] == []
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), f"No personas should leak when both tiers report none. Got: {res}"
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# Heuristic owns confidence. Mocked LLM returned 0.95; heuristic's
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# narrative-branch confidence is 0.9. Verifying we kept 0.9 catches
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# any future regression that lets LLM confidence override heuristic.
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assert res["confidence"] == 0.9, (
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f"Heuristic confidently classified narrative at 0.9; mocked LLM "
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f"returned 0.95. Merge must keep heuristic's 0.9. Got: {res}"
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)
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def test_merge_tier_fields_heuristic_yes_llm_yes_combines_evidence():
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@@ -1597,6 +1617,75 @@ def test_merge_tier_fields_heuristic_yes_llm_yes_combines_evidence():
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assert len(res["evidence"]) >= 2, (
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f"Combined evidence should include both heuristic + LLM lines. " f"Got: {res['evidence']}"
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)
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# Each entry must carry its tier prefix so on-disk origin.json is
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# auditable — readers can tell which tier produced which signal line.
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tier1_lines = [e for e in res["evidence"] if e.startswith("Tier-1 heuristic: ")]
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tier2_lines = [e for e in res["evidence"] if e.startswith("Tier-2 LLM: ")]
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assert tier1_lines, (
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f"Expected at least one 'Tier-1 heuristic: ' prefixed evidence line. "
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f"Got: {res['evidence']}"
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)
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assert tier2_lines, (
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f"Expected at least one 'Tier-2 LLM: ' prefixed evidence line. " f"Got: {res['evidence']}"
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)
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# Every entry should be tier-prefixed (no untagged passthrough).
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untagged = [
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e
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for e in res["evidence"]
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if not (e.startswith("Tier-1 heuristic: ") or e.startswith("Tier-2 LLM: "))
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]
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assert not untagged, f"Untagged evidence entries leaked into merge: {untagged}"
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def test_merge_tier_fields_confidence_matches_heuristic_call():
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"""Pin the contract: merged confidence equals what `detect_origin_heuristic`
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returns for the same samples — independent of what the LLM produced.
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Catches a regression class where some future refactor lets Tier 2's
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confidence creep back into the merged result.
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"""
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from unittest.mock import MagicMock, patch
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from mempalace.cli import _run_pass_zero
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from mempalace.corpus_origin import CorpusOriginResult, detect_origin_heuristic
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samples = _ai_dialogue_samples()
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expected_confidence = detect_origin_heuristic(samples).confidence
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fake_provider = MagicMock()
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# LLM picks a deliberately distinct confidence so any leak is visible.
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llm_distinct_result = CorpusOriginResult(
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likely_ai_dialogue=True,
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confidence=0.123456,
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primary_platform="Claude (Anthropic)",
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user_name=None,
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agent_persona_names=[],
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evidence=["LLM said yes with an unusual confidence"],
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)
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import tempfile
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with tempfile.TemporaryDirectory() as tmp_dir:
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project_dir = Path(tmp_dir) / "project"
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project_dir.mkdir()
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for i, sample in enumerate(samples):
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(project_dir / f"log{i}.md").write_text(sample)
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palace_dir = Path(tmp_dir) / "palace"
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with patch("mempalace.cli.detect_origin_llm", return_value=llm_distinct_result):
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wrapped = _run_pass_zero(
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project_dir=str(project_dir),
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palace_dir=str(palace_dir),
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llm_provider=fake_provider,
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)
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assert wrapped is not None
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res = wrapped["result"]
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assert res["confidence"] == expected_confidence, (
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f"Merged confidence {res['confidence']} did not match "
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f"detect_origin_heuristic's {expected_confidence}. Looks like "
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f"LLM's 0.123456 (or another source) leaked through the merge."
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)
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def test_merge_tier_fields_no_llm_provider_returns_heuristic_only():
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