import threading import pytest from core import llm from core.llm import is_fatal_error, is_transient_error, model_for_step, provider_for from core.model_schema import LLMUsage class FakeCompletions: def __init__(self): self.kwargs = None def create_with_completion(self, **kwargs): self.kwargs = kwargs return "ok", object() def fake_session(model="deepseek/deepseek-v4.1-flash", step_models=None): """LLMSession ohne echten Client – der Konstruktor würde einen API-Key verlangen.""" session = llm.LLMSession.__new__(llm.LLMSession) session.model, session.provider = model, provider_for(model) session.step_models = step_models or {} session.usage = LLMUsage(model=model, provider=session.provider) session._lock = threading.Lock() session.session_id = "lauf-1" session.ignored_providers = [] completions = {} session._clients = {} for provider in {session.provider, *(provider_for(m) for m in session.step_models.values())}: completions[provider] = FakeCompletions() session._clients[provider] = type("C", (), {"chat": type("Chat", (), {"completions": completions[provider]})()})() session.client = session._clients[session.provider] return session, completions @pytest.mark.parametrize("message", [ "429 RESOURCE_EXHAUSTED. {'error': {'code': 429, 'message': 'You exceeded your current quota'}}", # Gemini-Kontingent "Error code: 402 - {'error': {'message': 'Insufficient credits'}}", # OpenRouter-Guthaben "Error code: 401 - {'error': {'message': 'No auth credentials found'}}", ]) def test_fatal_errors_are_not_retried(message): assert is_fatal_error(message) assert not is_transient_error(message) @pytest.mark.parametrize("message", [ "503 UNAVAILABLE. {'error': {'code': 503, 'message': 'model is currently experiencing high demand'}}", "Error code: 429 - {'error': {'message': 'Rate limit exceeded'}}", "Error code: 502 - Bad Gateway", "Connection error.", ]) def test_transient_errors_are_retried(message): assert is_transient_error(message) def test_validation_error_is_neither(): message = "1 validation error for OptimizationModelSpecification" assert not is_fatal_error(message) and not is_transient_error(message) def test_provider_detection(): assert provider_for("deepseek/deepseek-v4-flash-0731") == "openrouter" assert provider_for("gemini-2.5-flash") == "gemini" def test_reasoning_effort_is_sent_only_when_configured(monkeypatch): def make_session(effort): monkeypatch.setattr(llm, "REASONING_EFFORT", effort) session, completions = fake_session() session.create(str, [{"role": "user", "content": "x"}]) return completions["openrouter"].kwargs["extra_body"] assert "reasoning" not in make_session("") assert make_session("low")["reasoning"] == {"effort": "low"} def test_truncated_answer_is_retried(): # beobachtet: ein Anbieter schnitt die Modellspezifikation ab (max_tokens-Vorgabe des Anbieters) message = "IncompleteOutputException: The output is incomplete due to a max_tokens length limit." assert is_transient_error(message) and not is_fatal_error(message) def test_max_tokens_is_sent_to_openrouter(): session, completions = fake_session() session.create(str, [{"role": "user", "content": "x"}]) assert completions["openrouter"].kwargs["max_tokens"] == llm.LLM_MAX_TOKENS >= 16000 # --- Modell je Pipeline-Stufe (LLM_MODEL_EXTRACTION, LLM_MODEL_SOLVER, ...) --- def test_step_model_falls_back_to_session_model(monkeypatch): monkeypatch.delenv("LLM_MODEL_SOLVER", raising=False) assert model_for_step("Solver-Code", "a/b") == "a/b" assert model_for_step("unbenannt", "a/b") == "a/b" # Stufe ohne Umgebungsvariable def test_step_model_from_environment(monkeypatch): monkeypatch.setenv("LLM_MODEL_SOLVER", "schnell/modell") assert model_for_step("Solver-Code", "a/b") == "schnell/modell" assert model_for_step("Solver-Reparatur", "a/b") == "schnell/modell" # dieselbe Variable assert model_for_step("Extraktion", "a/b") == "a/b" def test_create_uses_step_model_and_records_it(): session, completions = fake_session(step_models={"Extraktion": "stark/modell", "Solver-Code": "gemini-2.5-flash"}) session.create(str, [{"role": "user", "content": "x"}], step="Extraktion") assert completions["openrouter"].kwargs["model"] == "stark/modell" # anderer Anbieter je Stufe: Gemini bekommt keine OpenRouter-Parameter session.create(str, [{"role": "user", "content": "x"}], step="Solver-Code") assert completions["gemini"].kwargs["model"] == "gemini-2.5-flash" assert "extra_body" not in completions["gemini"].kwargs assert [r.model for r in session.usage.call_records] == ["stark/modell", "gemini-2.5-flash"] def test_overrides_lists_only_deviating_steps(): session, _ = fake_session(model="a/b", step_models={"Extraktion": "a/b", "Solver-Code": "schnell/modell"}) assert session.overrides() == {"Solver-Code": "schnell/modell"} # --- Prompt-Caching: Kennung je Lauf (Sticky Routing) und erfasste Cache-Treffer --- def test_all_calls_of_a_run_share_one_openrouter_session_id(): session, completions = fake_session(step_models={"Solver-Code": "gemini-2.5-flash"}) session.create(str, [{"role": "user", "content": "x"}], step="Extraktion") assert completions["openrouter"].kwargs["extra_body"]["session_id"] == "lauf-1" session.create(str, [{"role": "user", "content": "x"}], step="Solver-Code") assert "extra_body" not in completions["gemini"].kwargs # Gemini kennt den Parameter nicht def test_new_session_gets_a_new_id(monkeypatch): monkeypatch.setattr(llm, "_make_client", lambda provider: object()) assert llm.LLMSession("a/b").session_id != llm.LLMSession("a/b").session_id def test_cached_tokens_are_recorded_per_call_and_step(): from types import SimpleNamespace as NS session, _ = fake_session() def antwort(prompt, cached): return NS(provider="Modal", usage=NS(prompt_tokens=prompt, completion_tokens=100, cost=0.001, completion_tokens_details=NS(reasoning_tokens=40), prompt_tokens_details=NS(cached_tokens=cached))) session._record(antwort(5000, 0), step="Prüfung") session._record(antwort(5200, 4800), step="Prüfung") # zweite Runde liest den gleichen Präfix session._record(NS(provider=None, usage=NS(prompt_tokens=900, completion_tokens=10, cost=None, completion_tokens_details=None, prompt_tokens_details=None)), step="Verstehen") # Anbieter ohne Cache-Angabe assert session.usage.cached_tokens == 4800 and session.usage.prompt_tokens == 11100 assert [(r.prompt_tokens, r.cached_tokens) for r in session.usage.call_records] == [(5000, 0), (5200, 4800), (900, 0)] stufen = session.usage.by_step() assert stufen["Prüfung"]["prompt_tokens"] == 10200 and stufen["Prüfung"]["cached_tokens"] == 4800 def test_old_results_without_cache_fields_still_load(): from core.model_schema import LLMUsage alt = {"model": "a/b", "provider": "openrouter", "calls": 1, "prompt_tokens": 10, "completion_tokens": 5, "reasoning_tokens": 0, "call_records": [{"step": "Verstehen", "seconds": 1.0, "completion_tokens": 5}]} usage = LLMUsage.model_validate(alt) assert usage.cached_tokens == 0 and usage.call_records[0].cached_tokens == 0 def test_understanding_and_figure_reading_share_their_own_model(monkeypatch): monkeypatch.setenv("LLM_MODEL_UNDERSTANDING", "bild/modell") assert model_for_step("Verstehen", "a/b") == "bild/modell" assert model_for_step("Abbildungen", "a/b") == "bild/modell" # --- Tatsächlich antwortendes Modell (wichtig bei Aliasen wie ~deepseek/deepseek-flash-latest) --- def test_responded_model_is_recorded_per_call_and_summed(): from types import SimpleNamespace as NS session, _ = fake_session(model="~deepseek/deepseek-flash-latest") def antwort(modell): return NS(provider="Together", model=modell, usage=NS(prompt_tokens=10, completion_tokens=5, cost=0.0001, completion_tokens_details=None, prompt_tokens_details=None)) session._record(antwort("deepseek/deepseek-v4.1-flash"), step="Verstehen", model="~deepseek/deepseek-flash-latest") session._record(antwort("deepseek/deepseek-v4.2-flash"), step="Extraktion", model="~deepseek/deepseek-flash-latest") assert [(r.model, r.responded_model) for r in session.usage.call_records] == [ ("~deepseek/deepseek-flash-latest", "deepseek/deepseek-v4.1-flash"), ("~deepseek/deepseek-flash-latest", "deepseek/deepseek-v4.2-flash")] assert session.usage.responded_models == {"deepseek/deepseek-v4.1-flash": 1, "deepseek/deepseek-v4.2-flash": 1} def test_missing_or_odd_model_field_is_ignored(): from types import SimpleNamespace as NS session, _ = fake_session() session._record(NS(provider=None, model=object(), usage=NS(prompt_tokens=1, completion_tokens=1, cost=None, completion_tokens_details=None, prompt_tokens_details=None))) assert session.usage.responded_models == {} and session.usage.call_records[0].responded_model is None def _antwort_mit_verbrauch(completion_tokens): from types import SimpleNamespace as NS return NS(provider="AtlasCloud", model="deepseek/deepseek-v4.1-flash", usage=NS(prompt_tokens=8000, completion_tokens=completion_tokens, cost=0.02, completion_tokens_details=NS(reasoning_tokens=completion_tokens - 500), prompt_tokens_details=NS(cached_tokens=0))) def test_truncated_answer_is_counted_before_the_retry(monkeypatch): # beobachtet an wagner_whitin_dijkstra: an LLM_MAX_TOKENS abgeschnitten, bezahlt, aber nirgends gezählt from instructor.core.exceptions import IncompleteOutputException monkeypatch.setattr(llm, "RETRY_WAITS", (0,)) session, completions = fake_session() versuche = iter([IncompleteOutputException(last_completion=_antwort_mit_verbrauch(32000)), ("ok", _antwort_mit_verbrauch(9000))]) def create_with_completion(**kwargs): naechster = next(versuche) if isinstance(naechster, Exception): raise naechster return naechster completions["openrouter"].create_with_completion = create_with_completion assert session.create(str, [{"role": "user", "content": "x"}], step="Solver-Code") == "ok" assert session.usage.calls == 2 and session.usage.completion_tokens == 41000 assert session.usage.cost_usd == pytest.approx(0.04) assert [r.step for r in session.usage.call_records] == ["Solver-Code (verworfen)", "Solver-Code"] def test_rejected_attempts_are_counted_even_when_the_call_fails(monkeypatch): from types import SimpleNamespace as NS from instructor.core.exceptions import InstructorRetryException session, completions = fake_session() fehler = InstructorRetryException("Schema verletzt", last_completion=_antwort_mit_verbrauch(3000), n_attempts=1, total_usage=0, failed_attempts=[NS(completion=_antwort_mit_verbrauch(3000))]) def create_with_completion(**kwargs): raise fehler completions["openrouter"].create_with_completion = create_with_completion with pytest.raises(InstructorRetryException): session.create(str, [{"role": "user", "content": "x"}], step="Prüfung") assert session.usage.calls == 2 and session.usage.completion_tokens == 6000 # zwei verschiedene Antworten def test_ordinary_errors_have_no_discarded_answers(): assert llm.discarded_completions(RuntimeError("Error code: 503")) == [] # --- Langsamen Anbieter nicht festhalten (OPENROUTER_SWITCH_BELOW) --- def _aufruf(session, anbieter, tokens, sekunden): from types import SimpleNamespace as NS session._record(NS(provider=anbieter, usage=NS(prompt_tokens=100, completion_tokens=tokens, cost=None, completion_tokens_details=None, prompt_tokens_details=None)), step="Verstehen", seconds=sekunden) session._avoid_if_slow() def test_slow_provider_is_avoided_for_the_rest_of_the_run(monkeypatch): # beobachtet: alle Aufrufe bei AtlasCloud mit ~65 Tokens/s, 1575 s statt ~150 s monkeypatch.setattr(llm, "OPENROUTER_SWITCH_BELOW", 75) session, completions = fake_session() _aufruf(session, "AtlasCloud", 15201, 232.0) assert session.ignored_providers == ["AtlasCloud"] and session.session_id != "lauf-1" session.create(str, [{"role": "user", "content": "x"}], step="Extraktion") body = completions["openrouter"].kwargs["extra_body"] assert body["provider"]["ignore"] == ["AtlasCloud"] and body["session_id"] == session.session_id @pytest.mark.parametrize("anbieter, tokens, sekunden", [ ("Together", 15000, 60.0), # schnell ("Fireworks", 400, 20.0), # zu kurz, um die Rate zu beurteilen (Wartezeit bis zum ersten Token) ]) def test_fast_or_short_calls_keep_the_provider(monkeypatch, anbieter, tokens, sekunden): monkeypatch.setattr(llm, "OPENROUTER_SWITCH_BELOW", 75) session, _ = fake_session() _aufruf(session, anbieter, tokens, sekunden) assert session.ignored_providers == [] and session.session_id == "lauf-1" def test_switching_can_be_disabled_and_is_capped(monkeypatch): monkeypatch.setattr(llm, "OPENROUTER_SWITCH_BELOW", 0) session, _ = fake_session() _aufruf(session, "AtlasCloud", 15000, 230.0) assert session.ignored_providers == [] monkeypatch.setattr(llm, "OPENROUTER_SWITCH_BELOW", 75) for anbieter in ("A", "B", "C", "D"): _aufruf(session, anbieter, 15000, 230.0) assert session.ignored_providers == ["A", "B", "C"] # höchstens MAX_IGNORED_PROVIDERS def test_no_endpoints_left_lifts_the_ignore_list(): session, completions = fake_session() session.ignored_providers = ["AtlasCloud", "Parasail"] gesendet = [] def create_with_completion(**kwargs): gesendet.append(kwargs["extra_body"]["provider"].get("ignore")) if len(gesendet) == 1: raise RuntimeError("Error code: 404 - {'error': {'message': 'No endpoints found for deepseek/x.'}}") return "ok", object() completions["openrouter"].create_with_completion = create_with_completion assert session.create(str, [{"role": "user", "content": "x"}], step="Prüfung") == "ok" assert gesendet == [["AtlasCloud", "Parasail"], None] and session.ignored_providers == [] # --- Abschneiden am Tokenlimit: anderer Anbieter statt Warten, am Ende LLMUnavailable statt Absturz --- def _abgeschnitten(anbieter): from instructor.core.exceptions import IncompleteOutputException antwort = _antwort_mit_verbrauch(32000) antwort.provider = anbieter return IncompleteOutputException(last_completion=antwort) def test_truncation_avoids_the_provider_and_retries_without_waiting(monkeypatch): # gemessen am 18.09.2026: Venice 4 von 28 Aufrufen abgeschnitten, alle übrigen Anbieter fast nie gewartet = [] monkeypatch.setattr(llm.time, "sleep", gewartet.append) session, completions = fake_session() gesendet, versuche = [], iter([_abgeschnitten("Venice"), ("ok", _antwort_mit_verbrauch(9000))]) def create_with_completion(**kwargs): gesendet.append((kwargs["extra_body"]["provider"].get("ignore"), kwargs["extra_body"]["session_id"])) naechster = next(versuche) if isinstance(naechster, Exception): raise naechster return naechster completions["openrouter"].create_with_completion = create_with_completion assert session.create(str, [{"role": "user", "content": "x"}], step="Solver-Code") == "ok" assert gewartet == [0] assert gesendet[0] == (None, "lauf-1") and gesendet[1][0] == ["Venice"] and gesendet[1][1] != "lauf-1" def test_exhausted_retries_raise_llm_unavailable(monkeypatch): monkeypatch.setattr(llm.time, "sleep", lambda s: None) session, completions = fake_session() anbieter = iter(["Venice", "Makora", "Parasail", "Together"]) def create_with_completion(**kwargs): raise _abgeschnitten(next(anbieter)) completions["openrouter"].create_with_completion = create_with_completion with pytest.raises(llm.LLMUnavailable) as exc: session.create(str, [{"role": "user", "content": "x"}], step="Extraktion") assert exc.value.step == "Extraktion" assert session.usage.calls == 4 # alle vier bezahlten Antworten gezählt assert session.ignored_providers == ["Venice", "Makora", "Parasail"] # höchstens MAX_IGNORED_PROVIDERS def test_fatal_errors_stay_unwrapped(): session, completions = fake_session() def create_with_completion(**kwargs): raise RuntimeError("Error code: 402 - {'error': {'message': 'Insufficient credits'}}") completions["openrouter"].create_with_completion = create_with_completion with pytest.raises(RuntimeError) as exc: session.create(str, [{"role": "user", "content": "x"}]) assert not isinstance(exc.value, llm.LLMUnavailable)