Light1YT
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Optional external-OpenAI layer over the deterministic forecasting engine. Gated by llm_enabled (default False) so prod makes no network calls until deliberately enabled. Allowlist-first SafePayload contract + is_confidential hard-block + RU-PII regex scrub (mandatory on the external path). Abstract LLMProvider seam (is_external) for a future RU-hosted provider. Sync httpx core (Celery-friendly); tool/function-calling pass-through; timeout + bounded 429/5xx retry + per-request call cap, all degrading to fallback. Raw httpx (no openai SDK -> no pyproject/lock drift). 47 tests, ruff + mypy clean. Refs #960
288 lines
12 KiB
Python
288 lines
12 KiB
Python
"""LLM client orchestration tests (#960).
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Покрываем: disabled→fallback (БЕЗ сетевой попытки), no-key→fallback, call-cap,
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redaction hard-block→fallback, happy-path (тело запроса проскраблено),
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guardrails (timeout→fallback, 429-retry-then-fallback), complete_or_raise.
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Сеть НЕ дёргается: либо внедряем fake-провайдера, либо ставим tripwire на httpx.Client.
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"""
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from __future__ import annotations
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from typing import Any
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import pytest
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from app.core.config import settings
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from app.services.llm import client as llm_client
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from app.services.llm.client import LLMResult, LLMUnavailableError, complete, complete_or_raise
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from app.services.llm.provider import (
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LLMProvider,
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LLMRateLimitedError,
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LLMTimeoutError,
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ProviderResponse,
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ToolCall,
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)
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from app.services.llm.redaction import SafePayload
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# ── Fake провайдеры (внедряются через provider=...) ────────────────────────────
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class _FakeOpenAILike(LLMProvider):
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"""Внешний (is_external=True) fake: записывает messages, отдаёт фикс. ответ."""
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def __init__(self, response: ProviderResponse | None = None) -> None:
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self.captured_messages: list[dict[str, Any]] | None = None
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self.captured_tools: list[dict[str, Any]] | None = None
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self.calls = 0
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self._response = response or ProviderResponse(
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content="ответ модели", prompt_tokens=10, completion_tokens=5, model="gpt-4o-mini"
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)
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@property
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def is_external(self) -> bool:
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return True
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@property
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def model(self) -> str:
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return "gpt-4o-mini"
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def complete(
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self,
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messages: list[dict[str, Any]],
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*,
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tools: list[dict[str, Any]] | None = None,
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max_output_tokens: int,
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) -> ProviderResponse:
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self.calls += 1
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self.captured_messages = messages
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self.captured_tools = tools
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return self._response
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class _RaisingProvider(LLMProvider):
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"""Внешний fake, всегда бросающий заданное исключение (для guardrail-тестов)."""
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def __init__(self, exc: Exception) -> None:
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self._exc = exc
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self.calls = 0
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@property
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def is_external(self) -> bool:
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return True
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@property
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def model(self) -> str:
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return "gpt-4o-mini"
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def complete(self, messages: Any, *, tools: Any = None, max_output_tokens: int) -> Any:
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self.calls += 1
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raise self._exc
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@pytest.fixture
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def _enabled(monkeypatch: pytest.MonkeyPatch) -> None:
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"""Включить LLM с fake-ключом (без реальных секретов)."""
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monkeypatch.setattr(settings, "llm_enabled", True)
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monkeypatch.setattr(settings, "openai_api_key", "test-fake-key-not-real")
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# ── Guard #1/#2: disabled / no key ─────────────────────────────────────────────
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def test_disabled_returns_fallback_without_network(monkeypatch: pytest.MonkeyPatch) -> None:
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"""llm_enabled=False → fallback, и НИ ОДНОЙ попытки создать httpx.Client."""
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monkeypatch.setattr(settings, "llm_enabled", False)
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def _tripwire(*a: Any, **k: Any) -> None:
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raise AssertionError("network must NOT be touched when llm_enabled=False")
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# Любая попытка сетевого вызова через httpx завалит тест.
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monkeypatch.setattr("app.services.llm.provider.httpx.Client", _tripwire)
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res = complete(system_prompt="sys", payload=SafePayload(text="hi"))
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assert res.ok is False
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assert res.fallback_used is True
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assert res.reason == "disabled"
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def test_enabled_but_no_key_returns_fallback(monkeypatch: pytest.MonkeyPatch) -> None:
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"""llm_enabled=True но ключ None → fallback (no_api_key), без сети."""
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monkeypatch.setattr(settings, "llm_enabled", True)
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monkeypatch.setattr(settings, "openai_api_key", None)
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def _tripwire(*a: Any, **k: Any) -> None:
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raise AssertionError("no network without a key")
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monkeypatch.setattr("app.services.llm.provider.httpx.Client", _tripwire)
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res = complete(system_prompt="sys", payload=SafePayload(text="hi"))
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assert res.reason == "no_api_key"
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assert res.fallback_used is True
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# ── Call cap ───────────────────────────────────────────────────────────────────
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def test_call_cap_returns_fallback(_enabled: None, monkeypatch: pytest.MonkeyPatch) -> None:
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"""call_index >= llm_max_calls_per_request → fallback, провайдер не вызывается."""
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monkeypatch.setattr(settings, "llm_max_calls_per_request", 2)
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prov = _FakeOpenAILike()
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res = complete(
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system_prompt="sys", payload=SafePayload(text="hi"), provider=prov, call_index=2
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)
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assert res.reason == "call_cap"
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assert prov.calls == 0
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# ── Redaction integration ──────────────────────────────────────────────────────
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def test_confidential_payload_returns_fallback(_enabled: None) -> None:
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"""is_confidential=True (external) → fallback redaction_refused, провайдер не зван."""
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prov = _FakeOpenAILike()
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res = complete(
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system_prompt="sys",
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payload=SafePayload(text="секрет", is_confidential=True),
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provider=prov,
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)
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assert res.reason == "redaction_refused"
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assert prov.calls == 0
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def test_request_body_is_redacted(_enabled: None) -> None:
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"""ГЛАВНОЕ: тело запроса к провайдеру НЕ содержит сырого PII — оно проскраблено."""
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prov = _FakeOpenAILike()
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payload = SafePayload(
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text="Свяжитесь +7 912 345 67 89 или mail@example.ru",
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fields={"owner": "Иванов Иван Иванович", "zone": "Ц-1"},
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)
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res = complete(system_prompt="Ты ассистент", payload=payload, provider=prov)
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assert res.ok is True
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assert prov.captured_messages is not None
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blob = str(prov.captured_messages)
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# Сырого PII в отправленных messages быть не должно.
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assert "+7 912 345 67 89" not in blob
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assert "mail@example.ru" not in blob
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assert "Иванов Иван Иванович" not in blob
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# Зато плейсхолдеры и безопасные поля — на месте.
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assert "[REDACTED:phone]" in blob
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assert "[REDACTED:email]" in blob
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assert "[REDACTED:name]" in blob
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assert "Ц-1" in blob
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# ── Happy path ─────────────────────────────────────────────────────────────────
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def test_happy_path_returns_ok_result(_enabled: None) -> None:
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"""Успешный ответ → ok=True, content и токены проброшены."""
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prov = _FakeOpenAILike(
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ProviderResponse(
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content="готово", prompt_tokens=12, completion_tokens=4, model="gpt-4o-mini"
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)
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)
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res = complete(system_prompt="sys", payload=SafePayload(text="вопрос"), provider=prov)
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assert res.ok is True
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assert res.content == "готово"
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assert res.prompt_tokens == 12
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assert res.completion_tokens == 4
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assert res.model == "gpt-4o-mini"
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def test_tool_calls_passed_through(_enabled: None) -> None:
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"""tool_calls из ответа провайдера прокидываются в LLMResult."""
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prov = _FakeOpenAILike(
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ProviderResponse(
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content=None,
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tool_calls=[ToolCall(id="c1", name="extract", arguments='{"x":1}')],
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model="gpt-4o-mini",
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)
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)
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res = complete(system_prompt="sys", payload=SafePayload(text="q"), provider=prov)
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assert res.ok is True
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assert len(res.tool_calls) == 1
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assert res.tool_calls[0].name == "extract"
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def test_tools_forwarded_to_provider(_enabled: None) -> None:
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"""tools прокидываются в provider.complete."""
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prov = _FakeOpenAILike()
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tools = [{"type": "function", "function": {"name": "f"}}]
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complete(system_prompt="sys", payload=SafePayload(text="q"), provider=prov, tools=tools)
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assert prov.captured_tools == tools
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# ── Guardrails: timeout / rate-limit / retries ─────────────────────────────────
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def test_timeout_degrades_to_fallback(_enabled: None) -> None:
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"""LLMTimeoutError → fallback(timeout), без ретраев (1 вызов)."""
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prov = _RaisingProvider(LLMTimeoutError("slow"))
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res = complete(system_prompt="sys", payload=SafePayload(text="q"), provider=prov)
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assert res.reason == "timeout"
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assert res.fallback_used is True
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assert prov.calls == 1
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def test_rate_limited_retries_then_fallback(
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_enabled: None, monkeypatch: pytest.MonkeyPatch
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) -> None:
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"""429 на всех попытках → ретраи (cap) затем fallback(rate_limited). sleep замокан."""
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monkeypatch.setattr(settings, "llm_max_retries", 2)
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# Не спим в тесте.
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monkeypatch.setattr(llm_client.time, "sleep", lambda s: None)
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prov = _RaisingProvider(LLMRateLimitedError("429", status_code=429, retry_after=None))
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res = complete(system_prompt="sys", payload=SafePayload(text="q"), provider=prov)
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assert res.reason == "rate_limited"
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assert res.fallback_used is True
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# 1 первичный + 2 ретрая = 3 вызова.
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assert prov.calls == 3
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def test_rate_limited_then_success(_enabled: None, monkeypatch: pytest.MonkeyPatch) -> None:
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"""429 один раз, затем успех → ok (ретрай сработал)."""
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monkeypatch.setattr(settings, "llm_max_retries", 2)
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monkeypatch.setattr(llm_client.time, "sleep", lambda s: None)
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class _FlakyProvider(LLMProvider):
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def __init__(self) -> None:
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self.calls = 0
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@property
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def is_external(self) -> bool:
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return True
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@property
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def model(self) -> str:
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return "gpt-4o-mini"
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def complete(self, messages: Any, *, tools: Any = None, max_output_tokens: int) -> Any:
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self.calls += 1
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if self.calls == 1:
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raise LLMRateLimitedError("429", status_code=429, retry_after=None)
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return ProviderResponse(content="ок после ретрая", model="gpt-4o-mini")
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prov = _FlakyProvider()
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res = complete(system_prompt="sys", payload=SafePayload(text="q"), provider=prov)
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assert res.ok is True
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assert res.content == "ок после ретрая"
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assert prov.calls == 2
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# ── complete_or_raise ──────────────────────────────────────────────────────────
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def test_complete_or_raise_raises_on_fallback(monkeypatch: pytest.MonkeyPatch) -> None:
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"""complete_or_raise бросает LLMUnavailableError когда LLM недоступен (disabled)."""
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monkeypatch.setattr(settings, "llm_enabled", False)
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with pytest.raises(LLMUnavailableError):
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complete_or_raise(system_prompt="sys", payload=SafePayload(text="hi"))
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def test_complete_or_raise_returns_on_success(_enabled: None) -> None:
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prov = _FakeOpenAILike(ProviderResponse(content="ok", model="gpt-4o-mini"))
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res = complete_or_raise(system_prompt="sys", payload=SafePayload(text="q"), provider=prov)
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assert isinstance(res, LLMResult)
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assert res.ok is True
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