"""LLM client orchestration tests (#960).

Покрываем: disabled→fallback (БЕЗ сетевой попытки), no-key→fallback, call-cap,
redaction hard-block→fallback, happy-path (тело запроса проскраблено),
guardrails (timeout→fallback, 429-retry-then-fallback), complete_or_raise.

Сеть НЕ дёргается: либо внедряем fake-провайдера, либо ставим tripwire на httpx.Client.
"""

from __future__ import annotations

from typing import Any

import pytest

from app.core.config import settings
from app.services.llm import client as llm_client
from app.services.llm.client import LLMResult, LLMUnavailableError, complete, complete_or_raise
from app.services.llm.provider import (
    LLMProvider,
    LLMRateLimitedError,
    LLMTimeoutError,
    ProviderResponse,
    ToolCall,
)
from app.services.llm.redaction import SafePayload

# ── Fake провайдеры (внедряются через provider=...) ────────────────────────────


class _FakeOpenAILike(LLMProvider):
    """Внешний (is_external=True) fake: записывает messages, отдаёт фикс. ответ."""

    def __init__(self, response: ProviderResponse | None = None) -> None:
        self.captured_messages: list[dict[str, Any]] | None = None
        self.captured_tools: list[dict[str, Any]] | None = None
        self.calls = 0
        self._response = response or ProviderResponse(
            content="ответ модели", prompt_tokens=10, completion_tokens=5, model="gpt-4o-mini"
        )

    @property
    def is_external(self) -> bool:
        return True

    @property
    def model(self) -> str:
        return "gpt-4o-mini"

    def complete(
        self,
        messages: list[dict[str, Any]],
        *,
        tools: list[dict[str, Any]] | None = None,
        max_output_tokens: int,
    ) -> ProviderResponse:
        self.calls += 1
        self.captured_messages = messages
        self.captured_tools = tools
        return self._response


class _RaisingProvider(LLMProvider):
    """Внешний fake, всегда бросающий заданное исключение (для guardrail-тестов)."""

    def __init__(self, exc: Exception) -> None:
        self._exc = exc
        self.calls = 0

    @property
    def is_external(self) -> bool:
        return True

    @property
    def model(self) -> str:
        return "gpt-4o-mini"

    def complete(self, messages: Any, *, tools: Any = None, max_output_tokens: int) -> Any:
        self.calls += 1
        raise self._exc


@pytest.fixture
def _enabled(monkeypatch: pytest.MonkeyPatch) -> None:
    """Включить LLM с fake-ключом (без реальных секретов)."""
    monkeypatch.setattr(settings, "llm_enabled", True)
    monkeypatch.setattr(settings, "openai_api_key", "test-fake-key-not-real")


# ── Guard #1/#2: disabled / no key ─────────────────────────────────────────────


def test_disabled_returns_fallback_without_network(monkeypatch: pytest.MonkeyPatch) -> None:
    """llm_enabled=False → fallback, и НИ ОДНОЙ попытки создать httpx.Client."""
    monkeypatch.setattr(settings, "llm_enabled", False)

    def _tripwire(*a: Any, **k: Any) -> None:
        raise AssertionError("network must NOT be touched when llm_enabled=False")

    # Любая попытка сетевого вызова через httpx завалит тест.
    monkeypatch.setattr("app.services.llm.provider.httpx.Client", _tripwire)

    res = complete(system_prompt="sys", payload=SafePayload(text="hi"))
    assert res.ok is False
    assert res.fallback_used is True
    assert res.reason == "disabled"


def test_enabled_but_no_key_returns_fallback(monkeypatch: pytest.MonkeyPatch) -> None:
    """llm_enabled=True но ключ None → fallback (no_api_key), без сети."""
    monkeypatch.setattr(settings, "llm_enabled", True)
    monkeypatch.setattr(settings, "openai_api_key", None)

    def _tripwire(*a: Any, **k: Any) -> None:
        raise AssertionError("no network without a key")

    monkeypatch.setattr("app.services.llm.provider.httpx.Client", _tripwire)
    res = complete(system_prompt="sys", payload=SafePayload(text="hi"))
    assert res.reason == "no_api_key"
    assert res.fallback_used is True


# ── Call cap ───────────────────────────────────────────────────────────────────


def test_call_cap_returns_fallback(_enabled: None, monkeypatch: pytest.MonkeyPatch) -> None:
    """call_index >= llm_max_calls_per_request → fallback, провайдер не вызывается."""
    monkeypatch.setattr(settings, "llm_max_calls_per_request", 2)
    prov = _FakeOpenAILike()
    res = complete(
        system_prompt="sys", payload=SafePayload(text="hi"), provider=prov, call_index=2
    )
    assert res.reason == "call_cap"
    assert prov.calls == 0


# ── Redaction integration ──────────────────────────────────────────────────────


def test_confidential_payload_returns_fallback(_enabled: None) -> None:
    """is_confidential=True (external) → fallback redaction_refused, провайдер не зван."""
    prov = _FakeOpenAILike()
    res = complete(
        system_prompt="sys",
        payload=SafePayload(text="секрет", is_confidential=True),
        provider=prov,
    )
    assert res.reason == "redaction_refused"
    assert prov.calls == 0


def test_request_body_is_redacted(_enabled: None) -> None:
    """ГЛАВНОЕ: тело запроса к провайдеру НЕ содержит сырого PII — оно проскраблено."""
    prov = _FakeOpenAILike()
    payload = SafePayload(
        text="Свяжитесь +7 912 345 67 89 или mail@example.ru",
        fields={"owner": "Иванов Иван Иванович", "zone": "Ц-1"},
    )
    res = complete(system_prompt="Ты ассистент", payload=payload, provider=prov)

    assert res.ok is True
    assert prov.captured_messages is not None
    blob = str(prov.captured_messages)
    # Сырого PII в отправленных messages быть не должно.
    assert "+7 912 345 67 89" not in blob
    assert "mail@example.ru" not in blob
    assert "Иванов Иван Иванович" not in blob
    # Зато плейсхолдеры и безопасные поля — на месте.
    assert "[REDACTED:phone]" in blob
    assert "[REDACTED:email]" in blob
    assert "[REDACTED:name]" in blob
    assert "Ц-1" in blob


# ── Happy path ─────────────────────────────────────────────────────────────────


def test_happy_path_returns_ok_result(_enabled: None) -> None:
    """Успешный ответ → ok=True, content и токены проброшены."""
    prov = _FakeOpenAILike(
        ProviderResponse(
            content="готово", prompt_tokens=12, completion_tokens=4, model="gpt-4o-mini"
        )
    )
    res = complete(system_prompt="sys", payload=SafePayload(text="вопрос"), provider=prov)
    assert res.ok is True
    assert res.content == "готово"
    assert res.prompt_tokens == 12
    assert res.completion_tokens == 4
    assert res.model == "gpt-4o-mini"


def test_tool_calls_passed_through(_enabled: None) -> None:
    """tool_calls из ответа провайдера прокидываются в LLMResult."""
    prov = _FakeOpenAILike(
        ProviderResponse(
            content=None,
            tool_calls=[ToolCall(id="c1", name="extract", arguments='{"x":1}')],
            model="gpt-4o-mini",
        )
    )
    res = complete(system_prompt="sys", payload=SafePayload(text="q"), provider=prov)
    assert res.ok is True
    assert len(res.tool_calls) == 1
    assert res.tool_calls[0].name == "extract"


def test_tools_forwarded_to_provider(_enabled: None) -> None:
    """tools прокидываются в provider.complete."""
    prov = _FakeOpenAILike()
    tools = [{"type": "function", "function": {"name": "f"}}]
    complete(system_prompt="sys", payload=SafePayload(text="q"), provider=prov, tools=tools)
    assert prov.captured_tools == tools


# ── Guardrails: timeout / rate-limit / retries ─────────────────────────────────


def test_timeout_degrades_to_fallback(_enabled: None) -> None:
    """LLMTimeoutError → fallback(timeout), без ретраев (1 вызов)."""
    prov = _RaisingProvider(LLMTimeoutError("slow"))
    res = complete(system_prompt="sys", payload=SafePayload(text="q"), provider=prov)
    assert res.reason == "timeout"
    assert res.fallback_used is True
    assert prov.calls == 1


def test_rate_limited_retries_then_fallback(
    _enabled: None, monkeypatch: pytest.MonkeyPatch
) -> None:
    """429 на всех попытках → ретраи (cap) затем fallback(rate_limited). sleep замокан."""
    monkeypatch.setattr(settings, "llm_max_retries", 2)
    # Не спим в тесте.
    monkeypatch.setattr(llm_client.time, "sleep", lambda s: None)
    prov = _RaisingProvider(LLMRateLimitedError("429", status_code=429, retry_after=None))

    res = complete(system_prompt="sys", payload=SafePayload(text="q"), provider=prov)
    assert res.reason == "rate_limited"
    assert res.fallback_used is True
    # 1 первичный + 2 ретрая = 3 вызова.
    assert prov.calls == 3


def test_rate_limited_retry_after_capped(
    _enabled: None, monkeypatch: pytest.MonkeyPatch
) -> None:
    """#1209: серверный Retry-After (86400с при quota-exhaustion) должен капаться
    _MAX_BACKOFF_S — иначе time.sleep блокирует anyio-threadpool на часы.
    """
    monkeypatch.setattr(settings, "llm_max_retries", 1)
    sleeps: list[float] = []
    monkeypatch.setattr(llm_client.time, "sleep", lambda s: sleeps.append(s))

    class _BigRetryAfterProvider(LLMProvider):
        @property
        def is_external(self) -> bool:
            return True

        @property
        def model(self) -> str:
            return "gpt-4o-mini"

        def complete(self, messages: Any, *, tools: Any = None, max_output_tokens: int) -> Any:
            raise LLMRateLimitedError("429", status_code=429, retry_after=86400.0)

    prov = _BigRetryAfterProvider()
    res = complete(system_prompt="sys", payload=SafePayload(text="q"), provider=prov)
    assert res.ok is False
    assert res.reason == "rate_limited"
    # ровно один backoff (1 ретрай); значение должно быть капано _MAX_BACKOFF_S (30с).
    assert len(sleeps) == 1
    assert sleeps[0] == llm_client._MAX_BACKOFF_S


def test_rate_limited_then_success(_enabled: None, monkeypatch: pytest.MonkeyPatch) -> None:
    """429 один раз, затем успех → ok (ретрай сработал)."""
    monkeypatch.setattr(settings, "llm_max_retries", 2)
    monkeypatch.setattr(llm_client.time, "sleep", lambda s: None)

    class _FlakyProvider(LLMProvider):
        def __init__(self) -> None:
            self.calls = 0

        @property
        def is_external(self) -> bool:
            return True

        @property
        def model(self) -> str:
            return "gpt-4o-mini"

        def complete(self, messages: Any, *, tools: Any = None, max_output_tokens: int) -> Any:
            self.calls += 1
            if self.calls == 1:
                raise LLMRateLimitedError("429", status_code=429, retry_after=None)
            return ProviderResponse(content="ок после ретрая", model="gpt-4o-mini")

    prov = _FlakyProvider()
    res = complete(system_prompt="sys", payload=SafePayload(text="q"), provider=prov)
    assert res.ok is True
    assert res.content == "ок после ретрая"
    assert prov.calls == 2


# ── complete_or_raise ──────────────────────────────────────────────────────────


def test_complete_or_raise_raises_on_fallback(monkeypatch: pytest.MonkeyPatch) -> None:
    """complete_or_raise бросает LLMUnavailableError когда LLM недоступен (disabled)."""
    monkeypatch.setattr(settings, "llm_enabled", False)
    with pytest.raises(LLMUnavailableError):
        complete_or_raise(system_prompt="sys", payload=SafePayload(text="hi"))


def test_complete_or_raise_returns_on_success(_enabled: None) -> None:
    prov = _FakeOpenAILike(ProviderResponse(content="ok", model="gpt-4o-mini"))
    res = complete_or_raise(system_prompt="sys", payload=SafePayload(text="q"), provider=prov)
    assert isinstance(res, LLMResult)
    assert res.ok is True