Fine-tuning/backend/app/api/models.py

from fastapi import APIRouter, HTTPException

from app.schemas.model import ModelDownloadRequest, ModelDownloadResponse, ModelInfo
from app.schemas.model_test import ModelTestRequest, ModelTestResponse
from app.services import model_service, model_test_service

router = APIRouter()


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


@router.post("/download", response_model=ModelDownloadResponse, status_code=200)
async def download_model(req: ModelDownloadRequest):
    """从 HuggingFace 或 ModelScope 下载模型。"""
    from app.core.logging import logger
    logger.info(f"[DEBUG] download request: model_id={req.model_id}, use_modelscope={req.use_modelscope}, type={type(req.use_modelscope)}")
    result = await model_service.download_model(req.model_id, req.use_modelscope)
    logger.info(f"[DEBUG] download result: {result}")

    if result["status"] == "failed":
        raise HTTPException(status_code=400, detail=result.get("error", "Download failed"))

    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["name"],
            model_type=info["model_type"],
            path=info["path"],
            is_downloaded=info["is_downloaded"],
            context_length=info["context_length"],
            supported_peft_methods=info["supported_peft_methods"],
        )
    raise HTTPException(status_code=404, detail=f"Model not found: {model_id}")


@router.delete("/{model_id}")
async def delete_model(model_id: str):
    """删除已缓存的模型（数据库记录 + 本地文件）。"""
    result = await model_service.delete_model(model_id)
    return result


@router.post("/test", response_model=ModelTestResponse)
async def test_model(req: ModelTestRequest):
    """快速测试已缓存模型的生成能力。"""
    result = await model_test_service.test_model(
        req.model_id, req.prompt, req.max_new_tokens, req.temperature, req.top_p,
    )
    if "error" in result:
        raise HTTPException(status_code=400, detail=result["error"])
    return ModelTestResponse(**result)