meeting-lab/tests/test_negative_act_form_experiment.py

import argparse
import json
import tempfile
import unittest
from copy import deepcopy
from pathlib import Path
from unittest.mock import patch

import src.meeting_lab.controlled_semantic_derivation.experiment_negative_act as module
from src.meeting_lab.controlled_semantic_derivation.experiment_negative_act import (
    DerivationValidationError,
    build_ollama_payload,
    build_prompt,
    evaluate_case,
    load_gold_cases,
    parse_model_json,
    run_experiment,
    validate_classification,
)


GOLD_PATH = Path("tests/gold/negative_act_form_v0/cases.json")


FORM_TEXT = {
    "NA-01": "Zusammenarbeit mit Dr. Schlummer fortsetzen",
    "NA-02": "externe Lösung weiterverfolgen",
    "NA-03": "reale Anlage für den Versuch nutzen",
    "NA-04": "reale Anlage verwenden",
    "NA-05": "Waschstufe einbauen",
}


def classification_for(case):
    expected = case["expected"]
    return {
        "observation_id": expected["observation_id"],
        "negative_act_form": expected["negative_act_form"],
        "normalized_action_text": FORM_TEXT.get(case["case_id"]),
    }


class NegativeActFormExperimentTests(unittest.TestCase):
    @classmethod
    def setUpClass(cls):
        cls.cases = load_gold_cases(GOLD_PATH)
        cls.by_id = {case["case_id"]: case for case in cls.cases}

    def test_fixture_contains_exactly_na_01_through_na_08(self):
        self.assertEqual(list(self.by_id), [f"NA-{number:02d}" for number in range(1, 9)])

    def test_exact_schema_is_accepted(self):
        case = self.by_id["NA-01"]
        self.assertEqual(validate_classification(classification_for(case), case["observations"]), classification_for(case))

    def test_unknown_field_is_rejected(self):
        case = self.by_id["NA-01"]
        classification = classification_for(case)
        classification["explanation"] = "extra"
        with self.assertRaisesRegex(DerivationValidationError, "unknown keys"):
            validate_classification(classification, case["observations"])

    def test_invalid_enum_is_rejected(self):
        case = self.by_id["NA-01"]
        classification = classification_for(case)
        classification["negative_act_form"] = "rejection"
        with self.assertRaisesRegex(DerivationValidationError, "unsupported value"):
            validate_classification(classification, case["observations"])

    def test_non_none_requires_normalized_action_text(self):
        case = self.by_id["NA-01"]
        for value in (None, ""):
            classification = classification_for(case)
            classification["normalized_action_text"] = value
            with self.subTest(value=value), self.assertRaises(DerivationValidationError):
                validate_classification(classification, case["observations"])

    def test_none_requires_null_normalized_action_text(self):
        case = self.by_id["NA-06"]
        classification = classification_for(case)
        self.assertIsNone(classification["normalized_action_text"])
        classification["normalized_action_text"] = "Material einsetzen"
        with self.assertRaisesRegex(DerivationValidationError, "requires null"):
            validate_classification(classification, case["observations"])

    def test_forbidden_normative_fields_are_rejected_recursively(self):
        case = self.by_id["NA-01"]
        fields = (
            "rejection_form", "explicitly_rejected", "status", "decision", "outcome",
            "topic_status", "responsible_person", "responsibility", "owner",
            "requested_actor", "action_item", "protocol_category", "confidence",
            "relation", "relations", "graph", "unresolved_issue",
        )
        for field in fields:
            classification = classification_for(case)
            classification["wrapper"] = {field: "forbidden"}
            with self.subTest(field=field), self.assertRaisesRegex(DerivationValidationError, "forbidden semantic keys"):
                validate_classification(classification, case["observations"])

    def test_unknown_observation_id_is_rejected(self):
        case = self.by_id["NA-01"]
        classification = classification_for(case)
        classification["observation_id"] = "obs_99"
        with self.assertRaisesRegex(DerivationValidationError, "unknown observation"):
            validate_classification(classification, case["observations"])

    def test_malformed_json_is_rejected(self):
        with self.assertRaises(json.JSONDecodeError):
            parse_model_json("{bad json")

    def test_all_expected_classifications_evaluate_as_pass(self):
        for case in self.cases:
            evaluation = evaluate_case(case, classification_for(case))
            with self.subTest(case=case["case_id"]):
                self.assertEqual(evaluation["classification"], "PASS")

    def test_fixed_prompt_contains_candidate_and_no_gold_expectation(self):
        prompt = build_prompt(self.by_id["NA-03"])
        self.assertIn("candidate observation is obs_2", prompt)
        self.assertNotIn("expected", prompt)
        self.assertNotIn("Who is responsible", prompt)

    def test_fixed_model_configuration(self):
        payload = build_ollama_payload("qwen3.5:9B", "prompt", 16384, 1024)
        self.assertFalse(payload["think"])
        self.assertFalse(payload["stream"])
        self.assertEqual(payload["options"]["temperature"], 0)

    def test_no_rejection_or_status_derivation_function_exists(self):
        public_names = {name for name in dir(module) if not name.startswith("_")}
        self.assertNotIn("derive_rejection", public_names)
        self.assertFalse(any(name.startswith("derive_") for name in public_names))

    def test_artifacts_preserve_semantic_classification_only(self):
        case = self.by_id["NA-01"]
        raw = json.dumps(classification_for(case), ensure_ascii=False)
        with tempfile.TemporaryDirectory() as temporary:
            output = Path(temporary) / "run"
            args = argparse.Namespace(
                cases=GOLD_PATH, output=output, model="qwen3.5:9B",
                endpoint="http://unused", timeout=1, num_ctx=16384, num_predict=1024,
            )
            with patch.object(module, "load_gold_cases", return_value=[deepcopy(case)]), patch.object(
                module, "call_ollama", return_value=(raw, {"model": "qwen3.5:9B"})
            ):
                summary = run_experiment(args)
            self.assertEqual(summary["successful_llm_call_count"], 1)
            case_dir = output / "na-01"
            for filename in (
                "v3_style_input_observations.json", "prompt.txt", "raw_model_response.txt",
                "parsed_semantic_classification.json", "structural_validation.json",
                "evaluation.json", "ollama_metadata.json",
            ):
                self.assertTrue((case_dir / filename).is_file(), filename)
            self.assertFalse((case_dir / "final_derived_result.json").exists())
            self.assertFalse((case_dir / "deterministic_gate_results.json").exists())
            parsed = json.loads((case_dir / "parsed_semantic_classification.json").read_text())
            self.assertEqual(set(parsed), {"observation_id", "negative_act_form", "normalized_action_text"})


if __name__ == "__main__":
    unittest.main()