"""Implementacje dostawców LLM (LOG-31) — na samym httpx, bez SDK.

Świadomie bez bibliotek `openai` / `anthropic`: lokalny serwer modelu (Ollama,
vLLM, llama.cpp) i OpenAI mówią **tym samym** protokołem `/chat/completions`,
więc jedna implementacja obsługuje oba — różni je tylko adres i klucz. Anthropic
ma własny kształt `/v1/messages`, stąd druga klasa. Mniej zależności, mniej
powierzchni ataku, pełna kontrola nad tym, co wychodzi z sieci.
"""
from __future__ import annotations

import time

import httpx

from app.llm.base import Completion, LLMError, LLMProvider

RETRY_STATUSES = {429, 500, 502, 503, 504}
MAX_ATTEMPTS = 3


def _post_with_retry(url: str, headers: dict, payload: dict, timeout: float) -> dict:
    """POST z ponawianiem i backoffem — chroni przed chwilowym 429/5xx."""
    last: Exception | None = None
    for attempt in range(MAX_ATTEMPTS):
        try:
            with httpx.Client(timeout=timeout) as client:
                r = client.post(url, json=payload, headers=headers)
            if r.status_code in RETRY_STATUSES and attempt < MAX_ATTEMPTS - 1:
                time.sleep(2 ** attempt)
                continue
            if r.status_code >= 400:
                raise LLMError(f"Model odpowiedział błędem {r.status_code}: {r.text[:300]}")
            return r.json()
        except httpx.TimeoutException as e:
            last = e
            if attempt < MAX_ATTEMPTS - 1:
                time.sleep(2 ** attempt)
                continue
            raise LLMError(
                f"Model nie odpowiedział w czasie {timeout:.0f}s. Dłuższe horoskopy "
                f"wymagają większego LLM_TIMEOUT albo mniejszego budżetu promptu."
            ) from e
        except httpx.HTTPError as e:
            last = e
            if attempt < MAX_ATTEMPTS - 1:
                time.sleep(2 ** attempt)
                continue
            raise LLMError(f"Nie udało się połączyć z modelem: {e}") from e
    raise LLMError(f"Nie udało się wywołać modelu: {last}")


class ChatCompletionsProvider(LLMProvider):
    """Protokół OpenAI `/chat/completions` — lokalny serwer modelu ORAZ OpenAI."""

    def __init__(self, name: str, base_url: str, model: str, api_key: str = "",
                 timeout: float = 120.0, leaves_lan: bool = True) -> None:
        self.name = name
        self.base_url = base_url.rstrip("/")
        self.model = model
        self.api_key = api_key
        self.timeout = timeout
        self.leaves_lan = leaves_lan

    def _headers(self) -> dict:
        h = {"Content-Type": "application/json"}
        if self.api_key:
            h["Authorization"] = f"Bearer {self.api_key}"
        return h

    def generate(self, prompt: str, max_tokens: int) -> Completion:
        data = _post_with_retry(
            f"{self.base_url}/chat/completions", self._headers(),
            {
                "model": self.model,
                "max_tokens": max_tokens,
                "messages": [{"role": "user", "content": prompt}],
            },
            self.timeout,
        )
        try:
            text = data["choices"][0]["message"]["content"]
        except (KeyError, IndexError, TypeError) as e:
            raise LLMError(f"Nieoczekiwany kształt odpowiedzi modelu: {str(data)[:300]}") from e
        return Completion(
            text=text, model=data.get("model", self.model), provider=self.name,
            leaves_lan=self.leaves_lan, usage=data.get("usage") or {},
        )

    def health(self) -> dict:
        info = {"provider": self.name, "model": self.model, "leaves_lan": self.leaves_lan}
        try:
            with httpx.Client(timeout=min(self.timeout, 10.0)) as client:
                r = client.get(f"{self.base_url}/models", headers=self._headers())
            info["status"] = "ok" if r.status_code < 400 else f"http {r.status_code}"
        except httpx.HTTPError as e:
            info["status"] = f"down: {e}"
        return info


class AnthropicProvider(LLMProvider):
    """Protokół Anthropic `/v1/messages`."""

    leaves_lan = True

    def __init__(self, base_url: str, model: str, api_key: str = "",
                 timeout: float = 120.0) -> None:
        self.name = "anthropic"
        self.base_url = base_url.rstrip("/")
        self.model = model
        self.api_key = api_key
        self.timeout = timeout

    def generate(self, prompt: str, max_tokens: int) -> Completion:
        if not self.api_key:
            raise LLMError("Brak LLM_API_KEY — dostawca anthropic wymaga klucza.")
        data = _post_with_retry(
            f"{self.base_url}/v1/messages",
            {
                "Content-Type": "application/json",
                "x-api-key": self.api_key,
                "anthropic-version": "2023-06-01",
            },
            {
                "model": self.model,
                "max_tokens": max_tokens,
                "messages": [{"role": "user", "content": prompt}],
            },
            self.timeout,
        )
        try:
            text = "".join(b.get("text", "") for b in data["content"] if b.get("type") == "text")
        except (KeyError, TypeError) as e:
            raise LLMError(f"Nieoczekiwany kształt odpowiedzi modelu: {str(data)[:300]}") from e
        return Completion(
            text=text, model=data.get("model", self.model), provider=self.name,
            leaves_lan=True, usage=data.get("usage") or {},
        )

    def health(self) -> dict:
        return {
            "provider": self.name, "model": self.model, "leaves_lan": True,
            "status": "ok (klucz ustawiony)" if self.api_key else "brak LLM_API_KEY",
        }