from __future__ import annotations

from fastapi import APIRouter, File, Form, Header, HTTPException, Request, UploadFile
from fastapi.concurrency import run_in_threadpool
from pydantic import BaseModel, ConfigDict, Field

from api.support import require_identity, resolve_image_base_url
from services.content_filter import check_request, request_text
from services.log_service import LoggedCall
from services.protocol import (
    anthropic_v1_messages,
    openai_v1_chat_complete,
    openai_v1_image_edit,
    openai_v1_image_generations,
    openai_v1_models,
    openai_v1_response,
)


class ImageGenerationRequest(BaseModel):
    prompt: str = Field(..., min_length=1)
    model: str = "gpt-image-2"
    n: int = Field(default=1, ge=1, le=4)
    size: str | None = None
    response_format: str = "b64_json"
    history_disabled: bool = True
    stream: bool | None = None


class ChatCompletionRequest(BaseModel):
    model_config = ConfigDict(extra="allow")
    model: str | None = None
    prompt: str | None = None
    n: int | None = None
    stream: bool | None = None
    modalities: list[str] | None = None
    messages: list[dict[str, object]] | None = None


class ResponseCreateRequest(BaseModel):
    model_config = ConfigDict(extra="allow")
    model: str | None = None
    input: object | None = None
    tools: list[dict[str, object]] | None = None
    tool_choice: object | None = None
    stream: bool | None = None


class AnthropicMessageRequest(BaseModel):
    model_config = ConfigDict(extra="allow")
    model: str | None = None
    messages: list[dict[str, object]] | None = None
    system: object | None = None
    stream: bool | None = None


async def filter_or_log(call: LoggedCall, text: str) -> None:
    try:
        await run_in_threadpool(check_request, text)
    except HTTPException as exc:
        call.log("调用失败", status="failed", error=str(exc.detail))
        raise


def create_router() -> APIRouter:
    router = APIRouter()

    @router.get("/v1/models")
    async def list_models(authorization: str | None = Header(default=None)):
        require_identity(authorization)
        try:
            return await run_in_threadpool(openai_v1_models.list_models)
        except Exception as exc:
            raise HTTPException(status_code=502, detail={"error": str(exc)}) from exc

    @router.post("/v1/images/generations")
    async def generate_images(
            body: ImageGenerationRequest,
            request: Request,
            authorization: str | None = Header(default=None),
    ):
        identity = require_identity(authorization)
        payload = body.model_dump(mode="python")
        payload["base_url"] = resolve_image_base_url(request)
        call = LoggedCall(identity, "/v1/images/generations", body.model, "文生图", request_text=body.prompt)
        await filter_or_log(call, body.prompt)
        return await call.run(openai_v1_image_generations.handle, payload)

    @router.post("/v1/images/edits")
    async def edit_images(
            request: Request,
            authorization: str | None = Header(default=None),
            image: list[UploadFile] | None = File(default=None),
            image_list: list[UploadFile] | None = File(default=None, alias="image[]"),
            prompt: str = Form(...),
            model: str = Form(default="gpt-image-2"),
            n: int = Form(default=1),
            size: str | None = Form(default=None),
            response_format: str = Form(default="b64_json"),
            stream: bool | None = Form(default=None),
    ):
        identity = require_identity(authorization)
        call = LoggedCall(identity, "/v1/images/edits", model, "图生图", request_text=prompt)
        if n < 1 or n > 4:
            raise HTTPException(status_code=400, detail={"error": "n must be between 1 and 4"})
        await filter_or_log(call, prompt)
        uploads = [*(image or []), *(image_list or [])]
        if not uploads:
            raise HTTPException(status_code=400, detail={"error": "image file is required"})
        images: list[tuple[bytes, str, str]] = []
        for upload in uploads:
            image_data = await upload.read()
            if not image_data:
                raise HTTPException(status_code=400, detail={"error": "image file is empty"})
            images.append((image_data, upload.filename or "image.png", upload.content_type or "image/png"))
        payload = {
            "prompt": prompt,
            "images": images,
            "model": model,
            "n": n,
            "size": size,
            "response_format": response_format,
            "stream": stream,
            "base_url": resolve_image_base_url(request),
        }
        return await call.run(openai_v1_image_edit.handle, payload)

    @router.post("/v1/chat/completions")
    async def create_chat_completion(body: ChatCompletionRequest, authorization: str | None = Header(default=None)):
        identity = require_identity(authorization)
        payload = body.model_dump(mode="python")
        model = str(payload.get("model") or "auto")
        request_preview = request_text(payload.get("prompt"), payload.get("messages"))
        call = LoggedCall(identity, "/v1/chat/completions", model, "文本生成", request_text=request_preview)
        await filter_or_log(call, request_preview)
        return await call.run(openai_v1_chat_complete.handle, payload)

    @router.post("/v1/responses")
    async def create_response(body: ResponseCreateRequest, authorization: str | None = Header(default=None)):
        identity = require_identity(authorization)
        payload = body.model_dump(mode="python")
        model = str(payload.get("model") or "auto")
        request_preview = request_text(payload.get("input"), payload.get("instructions"))
        call = LoggedCall(identity, "/v1/responses", model, "Responses", request_text=request_preview)
        await filter_or_log(call, request_preview)
        return await call.run(openai_v1_response.handle, payload)

    @router.post("/v1/messages")
    async def create_message(
            body: AnthropicMessageRequest,
            authorization: str | None = Header(default=None),
            x_api_key: str | None = Header(default=None, alias="x-api-key"),
            anthropic_version: str | None = Header(default=None, alias="anthropic-version"),
    ):
        identity = require_identity(authorization or (f"Bearer {x_api_key}" if x_api_key else None))
        payload = body.model_dump(mode="python")
        model = str(payload.get("model") or "auto")
        request_preview = request_text(payload.get("system"), payload.get("messages"), payload.get("tools"))
        call = LoggedCall(identity, "/v1/messages", model, "Messages", request_text=request_preview)
        await filter_or_log(call, request_preview)
        return await call.run(anthropic_v1_messages.handle, payload, sse="anthropic")

    return router