"""CLI `TextToModel.main`: Optionen, Defaults, Ausgabe und Exit-Codes – ohne LLM.""" import json import pytest import TextToModel from core import llm from core.model_schema import PipelineResult from solving import solver_stage from test_resolve import gespeichertes_ergebnis @pytest.fixture(autouse=True) def einstellungen_zuruecksetzen(monkeypatch): # main() setzt Modulkonstanten; monkeypatch stellt sie nach jedem Test wieder her for modul, name in ((TextToModel, "UNDERSTAND_RETRIES"), (TextToModel, "INFEASIBLE_RECHECK"), (llm, "REASONING_EFFORT"), (llm, "LLM_MAX_TOKENS"), (llm, "LLM_TIMEOUT"), (solver_stage, "SOLVER_TIMEOUT"), (solver_stage, "SANDBOX")): monkeypatch.setattr(modul, name, getattr(modul, name)) def aufruffehler(argv, capsys) -> str: with pytest.raises(SystemExit) as exc: TextToModel.main(argv) assert exc.value.code == TextToModel.EXIT_USAGE # nicht 2 – das hieße „unzuverlässig“ return capsys.readouterr().err def test_resolve_writes_json_report_and_code_with_prefix(tmp_path): ergebnis = gespeichertes_ergebnis(tmp_path) praefix = tmp_path / "neu" / "lauf" # Ordner existiert noch nicht assert TextToModel.main(["--resolve", str(ergebnis), "-a", str(praefix)]) == TextToModel.EXIT_OK neu = PipelineResult.model_validate_json((tmp_path / "neu" / "lauf.json").read_text(encoding="utf-8")) assert neu.solver_run.objective_value == pytest.approx(9) assert (tmp_path / "neu" / "lauf.html").exists() and (tmp_path / "neu" / "lauf.py").exists() def test_explicit_output_wins_over_prefix(tmp_path): ergebnis = gespeichertes_ergebnis(tmp_path) TextToModel.main(["--resolve", str(ergebnis), "-a", str(tmp_path / "p"), "--report", str(tmp_path / "r.md")]) assert (tmp_path / "r.md").exists() and not (tmp_path / "p.html").exists() def test_json_goes_to_redirected_stdout(tmp_path, capsys): ergebnis = gespeichertes_ergebnis(tmp_path) daten = tmp_path / "daten.json" daten.write_text(json.dumps({"bedarf": 5}), encoding="utf-8") assert TextToModel.main(["--resolve", str(ergebnis), "--data", str(daten)]) == TextToModel.EXIT_OK assert json.loads(capsys.readouterr().out)["solver_run"]["objective_value"] == pytest.approx(12) def test_terminal_gets_a_summary_instead_of_json(tmp_path, capsys, monkeypatch): monkeypatch.setattr("sys.stdout.isatty", lambda: True) TextToModel.main(["--resolve", str(gespeichertes_ergebnis(tmp_path))]) out = capsys.readouterr().out assert "Zielwert: 9" in out and "Zuverlässig." in out and not out.lstrip().startswith("{") def test_unreliable_result_exits_with_2(tmp_path): daten = tmp_path / "daten.json" daten.write_text(json.dumps({"kosten": "keine Zahl"}), encoding="utf-8") code = TextToModel.main(["--resolve", str(gespeichertes_ergebnis(tmp_path)), "--data", str(daten), "-o", str(tmp_path / "x.json")]) assert code == TextToModel.EXIT_UNRELIABLE def test_broken_result_file_is_an_error_not_a_traceback(tmp_path): kaputt = tmp_path / "kaputt.json" kaputt.write_text("{}", encoding="utf-8") assert TextToModel.main(["--resolve", str(kaputt)]) == TextToModel.EXIT_ERROR @pytest.mark.parametrize("argv, meldung", [ (["--data", "d.json"], "--data wirkt nur"), (["a.txt", "--report", "r.pdf"], "Endung"), (["a.txt", "--no-solve", "--code", "c.py"], "--no-solve"), (["--von", "extraktion", "e.json"], "Stufe"), (["--von", "solver", "e.json", "--no-solve"], "not allowed"), (["--max-revisions", "-1"], "negativ"), (["--solver-timeout", "0"], "positiv"), (["fehlt.txt"], "Datei nicht gefunden"), ]) def test_wrong_calls_are_usage_errors(argv, meldung, capsys): assert meldung in aufruffehler(argv, capsys) def test_task_file_with_resolve_is_rejected(tmp_path, capsys): ergebnis = gespeichertes_ergebnis(tmp_path) assert "keine Aufgabendatei" in aufruffehler([str(ergebnis), "--resolve", str(ergebnis)], capsys) def test_options_reach_pipeline_and_modules(tmp_path, monkeypatch): aufgabe = tmp_path / "aufgabe.md" aufgabe.write_text("Maximiere x unter x ≤ 3.", encoding="utf-8") gesehen = {} def fake_pipeline(task, **kwargs): gesehen.update(kwargs, task=task) return PipelineResult(task=task, rejected=True, reliable=False, reliability_issues=["keine Aufgabe"]) monkeypatch.setattr(TextToModel, "run_pipeline", fake_pipeline) code = TextToModel.main([str(aufgabe), "-m", "x/y", "--max-revisions", "0", "--solver-retries", "4", "--max-restarts", "0", "--understand-retries", "-1", "--infeasible-recheck", "0", "--reasoning", "low", "--max-tokens", "1000", "--llm-timeout", "30", "--solver-timeout", "90", "--sandbox", "bwrap", "-o", str(tmp_path / "e.json")]) assert code == TextToModel.EXIT_REJECTED assert gesehen["task"].startswith("Maximiere") and gesehen["task_dir"] == tmp_path assert (gesehen["model"], gesehen["max_revisions"], gesehen["solver_retries"], gesehen["max_restarts"]) \ == ("x/y", 0, 4, 0) assert gesehen["solve_model"] is True assert (TextToModel.UNDERSTAND_RETRIES, TextToModel.INFEASIBLE_RECHECK) == (-1, 0) assert (llm.REASONING_EFFORT, llm.LLM_MAX_TOKENS, llm.LLM_TIMEOUT) == ("low", 1000, 30) assert (solver_stage.SOLVER_TIMEOUT, solver_stage.SANDBOX) == (90, "bwrap") assert "90" in solver_stage.solver_prompt() # Zeitbudget im Prompt folgt der Option def test_without_options_the_defaults_stay(tmp_path, monkeypatch): vorher = (llm.LLM_MAX_TOKENS, solver_stage.SOLVER_TIMEOUT, solver_stage.SANDBOX, TextToModel.UNDERSTAND_RETRIES) monkeypatch.setattr(TextToModel, "run_pipeline", lambda task, **kw: PipelineResult(task=task, reliable=True)) aufgabe = tmp_path / "a.txt" aufgabe.write_text("Minimiere x.", encoding="utf-8") TextToModel.main([str(aufgabe), "-o", str(tmp_path / "e.json")]) assert (llm.LLM_MAX_TOKENS, solver_stage.SOLVER_TIMEOUT, solver_stage.SANDBOX, TextToModel.UNDERSTAND_RETRIES) == vorher