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# from .vlm_model import VisionLanguageModel
from .beit3_model import Beit3Model
from fastapi import APIRouter, File, status
from fastapi.responses import JSONResponse
from pydantic import BaseModel
from .dtb_cursor import DatabaseCursor
class Item(BaseModel):
query_text: str
topk: int
router = APIRouter()
vectordb_cursor = None
vlm_model = None
def init_vectordb(**kargs):
# Singleton pattern
global vectordb_cursor
if vectordb_cursor is None:
vectordb_cursor = DatabaseCursor(**kargs)
def init_model(device: str):
# Singleton
global vlm_model
if vlm_model is None:
vlm_model = Beit3Model(device=device)
@router.post("/retrieval")
async def retrieve(item: Item) -> JSONResponse:
try:
query_vector = vlm_model.get_embedding(input=item.query_text)
search_results = vectordb_cursor.kNN_search(query_vector, item.topk)
except Exception:
return JSONResponse(
status_code=status.HTTP_500_INTERNAL_SERVER_ERROR,
content={"message": "Search error"},
)
return JSONResponse(
status_code=status.HTTP_200_OK,
content={"message": "success", "details": search_results},
)
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