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"""
Model management endpoints.
This module provides routes for listing and inspecting
available embedding models.
"""
from typing import Dict, Any
from fastapi import APIRouter, Depends, HTTPException, Path, status
from loguru import logger
from src.models.schemas import ModelsListResponse, ModelInfo
from src.core.manager import ModelManager
from src.core.exceptions import ModelNotFoundError
from src.api.dependencies import get_model_manager
router = APIRouter(prefix="/models", tags=["models"])
@router.get(
"",
response_model=ModelsListResponse,
summary="List all models",
description="Get a list of all available embedding models",
)
async def list_models(manager: ModelManager = Depends(get_model_manager)):
"""
List all available embedding models.
Returns information about all configured models including:
- Model ID
- Model name (Hugging Face path)
- Model type (dense or sparse)
- Load status
- Repository URL
Args:
manager: Model manager dependency
Returns:
ModelsListResponse with list of models and total count
"""
try:
models_info = manager.list_models()
return ModelsListResponse(
models=[ModelInfo(**info) for info in models_info], total=len(models_info)
)
except Exception:
logger.exception("Failed to list models")
raise HTTPException(
status_code=status.HTTP_500_INTERNAL_SERVER_ERROR,
detail="Failed to list models",
)
@router.get(
"/{model_id}",
response_model=ModelInfo,
summary="Get model info",
description="Get detailed information about a specific model",
)
async def get_model_info(
model_id: str = Path(..., description="Model identifier"),
manager: ModelManager = Depends(get_model_manager),
):
"""
Get detailed information about a specific model.
Args:
model_id: The model identifier
manager: Model manager dependency
Returns:
ModelInfo with model details
Raises:
HTTPException: If model not found
"""
try:
info = manager.get_model_info(model_id)
if not info:
raise ModelNotFoundError(model_id)
return ModelInfo(**info)
except ModelNotFoundError as e:
raise HTTPException(status_code=e.status_code, detail=e.message)
except Exception as e:
logger.exception(f"Failed to get info for model {model_id}")
raise HTTPException(
status_code=status.HTTP_500_INTERNAL_SERVER_ERROR,
detail=f"Failed to get model info: {str(e)}",
)
@router.get(
"/{model_id}/load",
summary="Load a model",
description="Manually trigger loading of a specific model",
)
async def load_model(
model_id: str = Path(..., description="Model identifier"),
manager: ModelManager = Depends(get_model_manager),
) -> Dict[str, Any]:
"""
Manually load a specific model into memory.
This endpoint is useful for preloading models on-demand
without waiting for the first request.
Args:
model_id: The model identifier
manager: Model manager dependency
Returns:
Dictionary with load status
Raises:
HTTPException: If model not found or fails to load
"""
try:
# This will load the model if not already loaded
model = manager.get_model(model_id)
return {
"status": "success",
"message": f"Model '{model_id}' loaded successfully",
"model_id": model_id,
"loaded": model.is_loaded,
}
except ModelNotFoundError as e:
raise HTTPException(status_code=e.status_code, detail=e.message)
except Exception as e:
logger.exception(f"Failed to load model {model_id}")
raise HTTPException(
status_code=status.HTTP_500_INTERNAL_SERVER_ERROR,
detail=f"Failed to load model: {str(e)}",
)
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