from fastapi import APIRouter

from app.schemas.model import ModelDownloadRequest, ModelDownloadResponse, ModelInfo
from app.services import model_service

router = APIRouter()


@router.get("/", response_model=list[ModelInfo])
async def list_models():
    """列出所有本地缓存的模型。"""
    models = model_service.list_cached_models()
    return [
        ModelInfo(
            id=m["id"],
            name=m.get("name", m["id"]),
            model_type=m.get("model_type", "text"),
            path=m.get("path"),
            is_downloaded=m.get("is_downloaded", True),
            context_length=m.get("context_length"),
            supported_peft_methods=m.get("supported_peft_methods", []),
        )
        for m in models
    ]


@router.post("/download", response_model=ModelDownloadResponse)
async def download_model(req: ModelDownloadRequest):
    """从 HuggingFace 或 ModelScope 下载模型。"""
    result = await model_service.download_model(req.model_id, req.use_modelscope)
    return ModelDownloadResponse(
        model_id=result["model_id"],
        status=result["status"],
        path=result.get("path"),
        error=result.get("error"),
    )


@router.get("/{model_id}", response_model=ModelInfo)
async def get_model_info(model_id: str):
    """获取已缓存模型的详细信息。"""
    info = await model_service.get_model_info(model_id)
    if info:
        return ModelInfo(
            id=info["id"],
            name=info.get("name", model_id.split("/")[-1]),
            model_type=info.get("model_type", "text"),
            path=info.get("path"),
            is_downloaded=info.get("is_downloaded", True),
            context_length=info.get("context_length"),
            supported_peft_methods=info.get("supported_peft_methods", []),
        )
    return ModelInfo(
        id=model_id,
        name=model_id.split("/")[-1],
        model_type="text",
        is_downloaded=False,
    )