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])
    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 # Übergebe den Mock direkt
    )
    mock_run_seismic.assert_called_once()

def test_run_seismic_analysis_with_injection(mocker, mock_llm):
    """Testet den Orchestrator mit Injektion."""
    mocker.patch('cognitive_mapping_probe.orchestrator_seismograph.run_silent_cogitation_seismic', return_value=[1.0])
    mocker.patch('cognitive_mapping_probe.concepts.get_concept_vector', return_value=torch.randn(10)) # Patch im concepts-Modul
    run_seismic_analysis(
        model_id="mock", prompt_type="test", seed=42, num_steps=1,
        concept_to_inject="test", injection_strength=1.5, progress_callback=mocker.MagicMock(),
        llm_instance=mock_llm # Übergebe den Mock direkt
    )

def test_get_curated_experiments_structure():
    """Testet die Datenstruktur der kuratierten Experimente."""
    experiments = get_curated_experiments()
    assert isinstance(experiments, dict)
    assert "Therapeutic Intervention (4B-Model)" in experiments
    protocol = experiments["Therapeutic Intervention (4B-Model)"]
    assert isinstance(protocol, list) and len(protocol) > 0

def test_run_auto_suite_special_protocol(mocker, mock_llm):
    """
    Testet den speziellen Logik-Pfad für das Interventions-Protokoll.
    KORRIGIERT: Verwendet nun die `mock_llm`-Fixture und patcht `get_or_load_model`
    im `auto_experiment`-Modul, um den Netzwerkaufruf zu verhindern.
    """
    # Patch `get_or_load_model` im `auto_experiment` Modul, da dort der erste Aufruf stattfindet
    mocker.patch('cognitive_mapping_probe.auto_experiment.get_or_load_model', return_value=mock_llm)
    mock_analysis = mocker.patch('cognitive_mapping_probe.auto_experiment.run_seismic_analysis', return_value={"stats": {}, "state_deltas": []})

    run_auto_suite(
        model_id="mock-4b", num_steps=1, seed=42,
        experiment_name="Therapeutic Intervention (4B-Model)",
        progress_callback=mocker.MagicMock()
    )

    assert mock_analysis.call_count == 2

    first_call_llm = mock_analysis.call_args_list[0].kwargs['llm_instance']
    second_call_llm = mock_analysis.call_args_list[1].kwargs['llm_instance']
    assert first_call_llm is mock_llm
    assert second_call_llm is mock_llm