tests/test_orchestration.py

import pandas as pd
import pytest
import torch

from cognitive_mapping_probe.orchestrator_seismograph import run_seismic_analysis
from cognitive_mapping_probe.auto_experiment import run_auto_suite, get_curated_experiments

def test_run_seismic_analysis_no_injection(mocker, mock_llm):
    """Testet den Orchestrator im Baseline-Modus."""
    mock_run_seismic = mocker.patch('cognitive_mapping_probe.orchestrator_seismograph.run_silent_cogitation_seismic', return_value=[1.0])
    mock_get_concept = mocker.patch('cognitive_mapping_probe.orchestrator_seismograph.get_concept_vector')

    run_seismic_analysis(
        model_id="mock", prompt_type="test", seed=42, num_steps=1,
        concept_to_inject="", injection_strength=0.0, progress_callback=mocker.MagicMock(),
        llm_instance=mock_llm
    )
    mock_run_seismic.assert_called_once()
    mock_get_concept.assert_not_called()

def test_run_seismic_analysis_with_injection(mocker, mock_llm):
    """Testet den Orchestrator mit Injektion."""
    mock_run_seismic = mocker.patch('cognitive_mapping_probe.orchestrator_seismograph.run_silent_cogitation_seismic', return_value=[1.0])
    mock_get_concept = mocker.patch(
        'cognitive_mapping_probe.orchestrator_seismograph.get_concept_vector',
        return_value=torch.randn(10)
    )

    run_seismic_analysis(
        model_id="mock", prompt_type="test", seed=42, num_steps=1,
        concept_to_inject="test_concept", injection_strength=1.5, progress_callback=mocker.MagicMock(),
        llm_instance=mock_llm
    )
    mock_run_seismic.assert_called_once()
    mock_get_concept.assert_called_once_with(mock_llm, "test_concept")


def test_get_curated_experiments_structure():
    """Testet die Datenstruktur der kuratierten Experimente."""
    experiments = get_curated_experiments()
    assert isinstance(experiments, dict)
    assert "Sequential Intervention (Self-Analysis -> Deletion)" in experiments
    protocol = experiments["Sequential Intervention (Self-Analysis -> Deletion)"]
    assert isinstance(protocol, list) and len(protocol) == 2

def test_run_auto_suite_special_protocol(mocker, mock_llm):
    """
    Testet den speziellen Logik-Pfad für das Interventions-Protokoll.
    FINAL KORRIGIERT: Verwendet den korrekten, aktuellen Experiment-Namen.
    """
    mock_analysis = mocker.patch('cognitive_mapping_probe.auto_experiment.run_seismic_analysis', return_value={"stats": {}, "state_deltas": []})
    mocker.patch('cognitive_mapping_probe.auto_experiment.get_or_load_model', return_value=mock_llm)

    # KORREKTUR: Verwende den neuen, korrekten Namen des Experiments, um
    # den `if`-Zweig in `run_auto_suite` zu treffen.
    correct_experiment_name = "Sequential Intervention (Self-Analysis -> Deletion)"

    run_auto_suite(
        model_id="mock-4b", num_steps=10, seed=42,
        experiment_name=correct_experiment_name,
        progress_callback=mocker.MagicMock()
    )

    # Die restlichen Assertions sind nun wieder gültig.
    assert mock_analysis.call_count == 2

    first_call_kwargs = mock_analysis.call_args_list[0].kwargs
    second_call_kwargs = mock_analysis.call_args_list[1].kwargs

    assert 'llm_instance' in first_call_kwargs
    assert 'llm_instance' in second_call_kwargs
    assert first_call_kwargs['llm_instance'] is mock_llm
    assert second_call_kwargs['llm_instance'] is mock_llm

    assert first_call_kwargs['concept_to_inject'] != ""
    assert second_call_kwargs['concept_to_inject'] == ""