| """Imprint measurement — before/after recall scoring (lexical fallback path).""" |
|
|
| from __future__ import annotations |
|
|
| from mindxtrain.eval import imprint as I |
|
|
|
|
| def test_default_inquiries_nonempty(): |
| qs = I.default_inquiries("Codephreak") |
| assert len(qs) >= 3 |
| assert any("Codephreak" in q for q in qs) |
|
|
|
|
| def test_lexical_similarity_bounds(): |
| assert I._lexical_similarity("hello world", "hello world") == 1.0 |
| assert I._lexical_similarity("abc", "xyz") == 0.0 |
| mid = I._lexical_similarity("the quick fox", "the slow fox") |
| assert 0.0 < mid < 1.0 |
|
|
|
|
| def test_score_imprint_detects_movement_toward_persona(): |
| inquiries = ["Who are you?", "What do you do?"] |
| baseline = ["i am codephreak, augmentic intelligence orchestrator.", |
| "i orchestrate autonomous agents."] |
| |
| before = ["I am an AI assistant.", "I help with tasks."] |
| after = ["i am codephreak, augmentic intelligence.", "i orchestrate autonomous agents."] |
|
|
| rep = I.score_imprint(inquiries, before, after, baseline) |
| assert rep.after_voice > rep.before_voice |
| assert rep.imprint_delta > 0.0 |
| assert rep.shift > 0.0 |
| assert rep.imprinted is True |
| assert rep.method in ("lexical", "sentence-transformers") |
|
|
|
|
| def test_score_imprint_no_movement_not_imprinted(): |
| inquiries = ["Who are you?"] |
| baseline = ["i am codephreak."] |
| same = ["I am an AI assistant."] |
| rep = I.score_imprint(inquiries, same, same, baseline) |
| |
| assert rep.shift == 0.0 |
| assert rep.imprinted is False |
|
|
|
|
| def test_score_imprint_report_is_frozen_and_jsonable(): |
| import pytest |
| from pydantic import ValidationError |
|
|
| rep = I.score_imprint(["q"], ["a"], ["b"], ["c"]) |
| blob = rep.model_dump_json() |
| assert '"imprint_delta"' in blob |
| with pytest.raises(ValidationError): |
| rep.imprint_delta = 1.0 |
|
|
