from collections.abc import Mapping
from typing import Any
from urllib.parse import urljoin

import httpx


class OpenAICompatibleGateway:
    """One adapter for OpenAI, lk666.ai and other OpenAI-compatible gateways."""

    def __init__(self, values: Mapping[str, Any]) -> None:
        self.values = values

    def _url(self, path_key: str, fallback: str) -> str:
        base_url = str(self.values.get("ai_base_url", "")).rstrip("/") + "/"
        path = str(self.values.get(path_key, fallback)).lstrip("/")
        return urljoin(base_url, path)

    @property
    def headers(self) -> dict[str, str]:
        return {
            "Authorization": f"Bearer {self.values.get('ai_api_key', '')}",
            "Content-Type": "application/json",
        }

    async def list_models(self) -> list[str]:
        async with httpx.AsyncClient(timeout=15) as client:
            response = await client.get(self._url("ai_models_path", "/models"), headers=self.headers)
            response.raise_for_status()
            payload = response.json()
        return [item["id"] for item in payload.get("data", []) if isinstance(item, dict) and item.get("id")]

    async def chat(self, messages: list[dict[str, Any]], *, vision: bool = False) -> dict[str, Any]:
        model_key = "vision_model" if vision else "orchestrator_model"
        async with httpx.AsyncClient(timeout=120) as client:
            response = await client.post(
                self._url("ai_chat_path", "/chat/completions"),
                headers=self.headers,
                json={"model": self.values[model_key], "messages": messages},
            )
            response.raise_for_status()
            return response.json()
    async def generate_image(self, prompt: str, **options: Any) -> dict[str, Any]:
        payload = {"model": self.values["image_model"], "prompt": prompt, **options}
        async with httpx.AsyncClient(timeout=180) as client:
            response = await client.post(
                self._url("ai_image_generation_path", "/images/generations"),
                headers=self.headers,
                json=payload,
            )
            response.raise_for_status()
            return response.json()

    async def edit_image(
        self,
        prompt: str,
        image: bytes,
        *,
        filename: str = "image.png",
        mask: bytes | None = None,
        **options: Any,
    ) -> dict[str, Any]:
        files: dict[str, tuple[str, bytes, str]] = {
            "image": (filename, image, "image/png"),
        }
        if mask is not None:
            files["mask"] = ("mask.png", mask, "image/png")
        data = {"model": self.values["image_model"], "prompt": prompt, **options}
        headers = {"Authorization": self.headers["Authorization"]}
        async with httpx.AsyncClient(timeout=180) as client:
            response = await client.post(
                self._url("ai_image_edit_path", "/images/edits"),
                headers=headers,
                data=data,
                files=files,
            )
            response.raise_for_status()
            return response.json()