"""
POST /api/chat_callback — 自定义 LLM 回调（SSE 流式响应）
"""

import json

from fastapi import APIRouter, Request
from fastapi.responses import StreamingResponse

from services.local_llm_service import local_llm_service
from services.scene_service import ensure_custom_llm_authorized, get_custom_llm_callback_settings
from utils.responses import custom_llm_error_response

router = APIRouter()


@router.post("/api/chat_callback")
async def chat_callback(request: Request):
    try:
        settings = get_custom_llm_callback_settings()
        ensure_custom_llm_authorized(request, settings["api_key"])
        payload = await request.json()
    except PermissionError as exc:
        return custom_llm_error_response(
            str(exc),
            code="AuthenticationError",
            status_code=401,
        )
    except json.JSONDecodeError:
        return custom_llm_error_response(
            "请求体必须是合法的 JSON",
            code="BadRequest",
            status_code=400,
        )
    except ValueError as exc:
        return custom_llm_error_response(str(exc))
    except Exception as exc:
        return custom_llm_error_response(
            f"解析请求失败: {exc}",
            code="InternalError",
            status_code=500,
        )

    messages = payload.get("messages")
    if not isinstance(messages, list) or not messages:
        return custom_llm_error_response(
            "messages 不能为空",
            code="BadRequest",
            status_code=400,
        )

    last_message = messages[-1]
    if last_message.get("role") != "user":
        return custom_llm_error_response(
            "最后一条消息必须是用户消息",
            code="BadRequest",
            status_code=400,
        )

    try:
        stream_iterator = local_llm_service.chat_stream(
            history_messages=messages,
            request_options={
                "temperature": payload.get("temperature"),
                "max_tokens": payload.get("max_tokens"),
                "top_p": payload.get("top_p"),
            },
        )
    except Exception as exc:
        return custom_llm_error_response(
            f"初始化本地 LLM 流式调用失败: {exc}",
            code="InternalError",
            status_code=500,
        )

    def generate_sse():
        has_error = False
        try:
            for chunk in stream_iterator:
                if chunk is None:
                    continue

                if hasattr(chunk, "model_dump_json"):
                    chunk_json = chunk.model_dump_json()
                else:
                    chunk_json = json.dumps(chunk, ensure_ascii=False)
                yield f"data: {chunk_json}\n\n"
        except GeneratorExit:
            raise
        except Exception as exc:
            has_error = True
            print(f"❌ /api/chat_callback 流式输出失败: {exc}")

        if has_error:
            print("⚠️ 已提前结束当前 SSE 流")

        yield "data: [DONE]\n\n"

    return StreamingResponse(
        generate_sse(),
        status_code=200,
        media_type="text/event-stream",
        headers={
            "Cache-Control": "no-cache",
            "Connection": "keep-alive",
            "Access-Control-Allow-Origin": "*",
        },
    )